title: The scaling laws of human travel

text: The dynamic spatial redistribution of individuals is a key driving force of various spatiotemporal phenomena on geographical scales. It can synchronize populations of interacting species, stabilize them, and diversify gene pools. Human travel, for example, is responsible for the geographical spread of human infectious disease. In the light of increasing international trade, intensified human mobility and the imminent threat of an influenza A epidemic, the knowledge of dynamical and statistical properties of human travel is of fundamental importance. Despite its crucial role, a quantitative assessment of these properties on geographical scales remains elusive, and the assumption that humans disperse diffusively still prevails in models. Here we report on a solid and quantitative assessment of human travelling statistics by analysing the circulation of bank notes in the United States. Using a comprehensive data set of over a million individual displacements, we find that dispersal is anomalous in two ways. First, the distribution of travelling distances decays as a power law, indicating that trajectories of bank notes are reminiscent of scale-free random walks known as Lévy flights. Second, the probability of remaining in a small, spatially confined region for a time T is dominated by algebraically long tails that attenuate the superdiffusive spread. We show that human travelling behaviour can be described mathematically on many spatiotemporal scales by a two-parameter continuous-time random walk model to a surprising accuracy, and conclude that human travel on geographical scales is an ambivalent and effectively superdiffusive process.


title: Estimating surface normals in noisy point cloud data

text: In this paper we describe and analyze a method based on local least square fitting for estimating the normals at all sample points of a point cloud data (PCD) set, in the presence of noise. We study the effects of neighborhood size, curvature, sampling density, and noise on the normal estimation when the PCD is sampled from a smooth curve in R2 or a smooth surface in R3 and noise is added. The analysis allows us to find the optimal neighborhood size using other local information from the PCD. Experimental results are also provided.


title: Big data: the next frontier for innovation in therapeutics and healthcare.

text: Advancements in genomics and personalized medicine not only effect healthcare delivery from patient and provider standpoints, but also reshape biomedical discovery. We are in the era of the '-omics', wherein an individual's genome, transcriptome, proteome and metabolome can be scrutinized to the finest resolution to paint a personalized biochemical fingerprint that enables tailored treatments, prognoses, risk factors, etc. Digitization of this information parlays into 'big data' informatics-driven evidence-based medical practice. While individualized patient management is a key beneficiary of next-generation medical informatics, this data also harbors a wealth of novel therapeutic discoveries waiting to be uncovered. 'Big data' informatics allows for networks-driven systems pharmacodynamics whereby drug information can be coupled to cellular- and organ-level physiology for determining whole-body outcomes. Patient '-omics' data can be integrated for ontology-based data-mining for the discovery of new biological associations and drug targets. Here we highlight the potential of 'big data' informatics for clinical pharmacology.


title: Forecasting Real Estate Prices ∗

text: This chapter reviews the evidence of predictability in US residential and commercial real estate markets. First, we highlight the main methodologies used in the construction of real estate indices, their underlying assumptions and their impact on the stochastic properties of the resultant series. We then survey the key empirical findings in the academic literature, including short-run persistence and long-run reversals in the log changes of real estate prices. Next, we summarize the ability of local as well as aggregate variables to forecast real estate returns. We illustrate a number of these results by relying on six aggregate indexes of the prices of unsecuritized (residential and commercial) real estate and REITs. The effect of leverage and monetary policy is also discussed.


title: The Beta Generalized Exponential Distribution

text: We introduce the beta generalized exponential distribution that includes the beta exponential and generalized exponential distributions as special cases. We provide a comprehensive mathematical treatment of this distribution. We derive the moment generating function and the rth moment thus generalizing some results in the literature. Expressions for the density, moment generating function and rth moment of the order statistics also are obtained. We discuss estimation of the parameters by maximum likelihood and provide the information matrix. We observe in one application to real data set that this model is quite flexible and can be used quite effectively in analyzing positive data in place of the beta exponential and generalized exponential distributions. keywords: Beta exponential distribution, Information matrix, Generalized exponential distribution, Maximum likelihood estimation.


title: Motivation and job satisfaction

text: The movement of workers to act in a desired manner has always consumed the thoughts of managers. In many ways, this goal has been reached through incentive programs, corporate pep talks, and other types of conditional administrative policy. However, as the workers adjust their behaviour in response to one of the aforementioned stimuli, is job satisfaction actualized? The instilling of satisfaction within workers is a crucial task of management. Satisfaction creates confidence, loyalty and ultimately improved quality in the output of the employed. Satisfaction, though, is not the simple result of an incentive program. Employees will most likely not take any more pride in their work even if they win the weekend getaway for having the highest sales. This paper reviews the literature of motivational theorists and draws from their approaches to job satisfaction and the role of motivation within job satisfaction. The theories of Frederick Herzberg and Edwin Locke are presented chronologically to show how Locke’s theory was a response to Herzberg’s theory. By understanding these theories, managers can focus on strategies of creating job satisfaction. This is followed by a brief examination of Kenneth Blanchard and Paul Hersey’s theory on leadership within management and how this art is changing through time. Herzberg and job satisfaction


title: Recognizing Objects in Range Data Using Regional Point Descriptors

text: Recognition of three dimensional (3D) objects in noisy and cluttered scenes is a challenging problem in 3D computer vision. One approach that has been successful in past research is the regional shape descriptor. In this paper, we introduce two new regional shape descriptors: 3D shape contexts and harmonic shape contexts. We evaluate the performance of these descriptors on the task of recognizing vehicles in range scans of scenes using a database of 56 cars. We compare the two novel descriptors to an existing descriptor, the spin image, showing that the shape context based descriptors have a higher recognition rate on noisy scenes and that 3D shape contexts outperform the others on cluttered scenes.


title: How Smart is Smart Money ? An Empirical Two-Sided Matching Model of Venture Capital

text: In capital markets, top-tier investors may have better abilities to monitor and manage their investments. In addition, there may be sorting in these markets, with top-tier investors investing in the best deals, second-tier investors investing in the second-best deals, and so forth. To separate and quantify these two effects, a structural model of the market for venture capital is developed and estimated. The model is a two-sided matching model that allows for sorting in equilibrium. It is found that more experienced venture capitalists make more successful investments. This is explained both by their value-adding influence on their investments, and by their access to late stage and biotechnology companies, companies that are more successful on average. Sorting is found to be prevalent and has general implications for the interpretation of empirical evidence of the impact of investors on their investments.


title: Supervised Topic Models

text: We introduce supervised latent Dirichlet allocation (sLDA), a statistical model of labelled documents. The model accommodates a variety of response types. We derive a maximum-likelihood procedure for parameter estimation, which relies on variational approximations to handle intractable posterior expectations. Prediction problems motivate this research: we use the fitted model to predict response values for new documents. We test sLDA on two real-world problems: movie ratings predicted from reviews, and web page popularity predicted from text descriptions. We illustrate the benefits of sLDA versus modern regularized regression, as well as versus an unsupervised LDA analysis followed by a separate regression.


title: A Circuit-Compatible SPICE model for Enhancement Mode Carbon Nanotube Field Effect Transistors

text: This paper presents a circuit-compatible compact model for short channel length (5 nm~100 nm), quasi-ballistic single wall carbon nanotube field-effect transistors (CNFETs). For the first time, a universal circuit-compatible CNFET model was implemented with HSPICE. This model includes practical device non-idealities, e.g. the quantum confinement effects in both circumferential and channel length direction, the acoustical/optical phonon scattering in channel region and the resistive source/drain, as well as the real time dynamic response with a transcapacitance array. This model is valid for CNFET for a wide diameter range and various chiralities as long as the carbon nanotube (CNT) is semiconducting


title: Fear bradycardia and activation of the human periaqueductal grey

text: Animal models of predator defense distinguish qualitatively different behavioral modes that are activated at increasing levels of predation threat. A defense mode observed at intermediate threat levels is freezing: a cessation of locomotion that is characterized by a parasympathetically dominated autonomic nervous system response that causes heart rate deceleration, or fear bradycardia. Studies in rodents have shown that freezing depends on amygdalar projections to the periaqueductal grey (PAG). In humans, freezing-like behaviors are implicated in development and maintenance of psychopathology, but neural mechanisms underlying freezing or its characteristic autonomic response profile have not been identified. Here, we combined event-related blood oxygenation level-dependent functional MRI (BOLD-fMRI) with autonomic response measures in a picture viewing paradigm to probe activity and interconnectivity within the amygdala-PAG pathway and test for an association with parasympathetic as opposed to sympathetic activation. In response to negatively arousing pictures, we observed parasympathetic (bradycardia) and sympathetic (pupil dilation) autonomic responses, BOLD responses in the amygdala and PAG, and effective connectivity between these regions. Critically, BOLD responses in the PAG to negative pictures correlated on a trial-by-trial basis with bradycardia but not pupil dilation. This correlation with bradycardia remained significant when partialling out pupil dilation. Additionally, activity in regions associated with motor planning and inhibition mirrored the PAG response. Thus, our findings implicate the human PAG in a parasympathetically dominated defense mode that subserves a state of attentive immobility. Mechanistic insight into this qualitatively distinct defense mode may importantly advance translational models of anxiety disorders.


title: RSSI informed phase method for distance calculations

text: In an attempt to find an accurate, environmentally robust, and fast process for RFID distance estimations, a method was developed called RSSI Informed Phase. This method uses both phase and RSSI measurements to estimate the distance, and potentially location, of a moving RFID tag. RSSI is initially used to find an approximate reader to tag separation distance. This distance value is applied to find an approximate slope of the phase angle vs. frequency curve. The estimated slope can inform the phase distance calculation, meaning fewer reads are required to find the actual phase angle vs. frequency slope. The reduction in the number of necessary reads accelerates the localization process and makes this method more robust for dynamic environments.


title: Teleoperated robot writing using EMG signals

text: In this paper, we have developed a method to tele-control a robot arm to imitate human writing skills using electromyography (EMG) signals. The control method is implemented on the Baxter® robot with a brush attached on the endpoint of its arm to imitate human writing skills, and a MYO sensor is used to measure the surface electromyographic (sEMG) signals generated by contractions of human muscles involved in writing tasks. A haptic device Sensable® Omni is used to control the motion of the Baxter® robot arm, and V-Rep® is employed to simulate the movement of the arm and to calculate the inverse kinematic of Baxter® robot arm. All the communications for Baxter® robot, V-Rep simulator, Omni device and MYO are integrated in MATLAB®/Simulink®. The main test is to make the Baxter® arm following the movement of a human subject when writing with Omni stylus, and the EMG signals are processed using low pass filter and moving average technique to extract the smoothed envelope which is utilised to control the variation of position instead of variation of force along the vertical Z axis, so when the operator writes with force variations, the Baxter® can draw lines with variable thickness. This imitation system is successfully tested to make the Baxter® arm to follow the writing movement of the operator's hand and would have potential applications in more complicated human robot teleoperation tasks such as tele-rehabilitation and tele-surgery.


title: Parallel computations for controlling an arm.

text: In order to control a reaching movement of the arm and body, several different computational problems must be solved. Some parallel methods that could be implemented in networks of neuron-like processors are described. Each method solves a different part of the overall task. First, a method is described for finding the torques necessary to follow a desired trajectory. The methods is more economical and more versatile than table look-up and requires very few sequential steps. Then a way of generating an internal representation of a desired trajectory is described. This method shows the trajectory one piece at a time by applying a large set of heuristic rules to a "motion blackboard" that represents the static and dynamic parameters of the state of the body at the current point in the trajectory. The computations are simplified by expressing the positions, orientations, and motions of parts of the body in terms of a single, non-accelerating, world-based frame of reference, rather than in terms of the joint-angles or an egocentric frame based on the body itself.


title: TimeMachine: Timeline Generation for Knowledge-Base Entities

text: We present a method called TIMEMACHINE to generate a timeline of events and relations for entities in a knowledge base. For example for an actor, such a timeline should show the most important professional and personal milestones and relationships such as works, awards, collaborations, and family relationships. We develop three orthogonal timeline quality criteria that an ideal timeline should satisfy: (1) it shows events that are relevant to the entity; (2) it shows events that are temporally diverse, so they distribute along the time axis, avoiding visual crowding and allowing for easy user interaction, such as zooming in and out; and (3) it shows events that are content diverse, so they contain many different types of events (e.g., for an actor, it should show movies and marriages and awards, not just movies). We present an algorithm to generate such timelines for a given time period and screen size, based on submodular optimization and web-co-occurrence statistics with provable performance guarantees. A series of user studies using Mechanical Turk shows that all three quality criteria are crucial to produce quality timelines and that our algorithm significantly outperforms various baseline and state-of-the-art methods.


title: Sustainable construction: construction and demolition waste reconsidered.

text: Construction activity in Europe has increased substantially in the past decade. Likewise, there has also been a commensurate rise in the generation of construction and demolition waste (C&DW). This, together with the fact that in many European countries the rate of recycling and reuse of C&DW is still quite low has engendered a serious environmental problem and a motivation to develop strategies and management plans to solve it. Due to its composition, there is a significant potential to reuse and/or recycle C&DW, and thereby, contribute to improving the sustainability of construction and development, but practical procedures are not yet widely known or practiced in the construction industry. This article (a) summarizes the different applications that are presently practiced to optimize the recovery and/or application of C&DW for reuse, and (b) proposes various measures and strategies to improve the processing of this waste. The authors suggest that to enhance environmental effectiveness, a conscious and comprehensive C&DW management plan should be implemented in each jurisdiction. More precisely, this study presents a holistic approach towards C&DW management, through which environmental benefits can be achieved through the application of new construction methods that can contribute to sustainable growth.


title: Wireless image communication system for fire-fighting robots

text: Recently, it has sometimes been impossible for fire-fighting personnel to access the site of a fire, even as the fire causes tremendous property damage and loss of human life, due to high temperatures or the presence of explosive materials. In such environments, fire-fighting robots can be useful for extinguishing a fire, and they should be controlled by remote operators. In order to help a remote operator who is located far away from the fire-fighting robot, wireless image communication systems have been investigated in this study. The developed system uses a High-Speed Downlink Packet Access (HSDPA) network to transmit images, showing the view from a fire-fighting robot. The fire-fighting robots and remote controllers are equipped with industrial computers, and image-transmitting and image-receiving programs function according to various protocols to allow communication between the robots and controllers


title: Low voltage low power analog circuit design OTA using signal attenuation technique in universal filter application

text: This paper presents a new configuration for a linear operational transconductance amplifier (OTA) using a signal attenuation technique. The OTA is designed to operate with a ±0.8V supply voltage and consumes 0.45mW power. All simulations are performed by ELDO model BSIM3v3 technology CMOS TSMC 0.18μm. The simulation results of this circuit showed a high DC gain of 73.6dB with a unity frequency of 50.19MHz and a total harmonic distortion of -60.81dB at 100 kHz for an input voltage of 1Vpp. Based on this circuit, a voltage mode universal filter has been implemented. The simulation results are in a good agreement with the theoretical calculations.


title: Competitive intelligence: construct exploration, validation and equivalence

text: Purpose – Little empirical research has been conducted on competitive intelligence (CI). This paper aims to contribute to the quantitative strand of the CI literature by exploring and validating the theoretical constructs of the CI process. Design/methodology/approach – Data from 601 questionnaires filled out by South African and Flemish exporters were subjected to exploratory factor analysis and construct equivalence analysis between the sub-samples. Findings – The results showed that the CI process consists of three constructs, while the context in which CI takes place consists of four constructs. This agrees to some extent with the literature. When verifying the constructs for both cultures it was found that all but one CI context construct can be viewed as equivalent in both groups. Bias analysis identified one item in the questionnaire that was biased. Via regression analysis it was also indicated that the context in which CI takes place influences the CI process to a large extent. The research identified size as an important influencing factor in a business’ CI process. Practical implications – Businesses involved in CI should take note that an improvement in their formal infrastructure, employee involvement and internal information processes could enhance their CI capability. Originality/value – This paper contributes towards the formalising of the constructs of competitive intelligence.


title: Empirical studies of software engineering: a roadmap

text: In this article we summarize the strengths and weaknesses of empirical research in software engineering. We argue that in order to improve the current situation we must create better studies and draw more credible interpretations from them. We finally present a roadmap for this improvement, which includes a general structure for software empirical studies and concrete steps for achieving these goals: designing better studies, collecting data more effectively, and involving others in our empirical enterprises.


title: Hidost: a static machine-learning-based detector of malicious files

text: Malicious software, i.e., malware, has been a persistent threat in the information security landscape since the early days of personal computing. The recent targeted attacks extensively use non-executable malware as a stealthy attack vector. There exists a substantial body of previous work on the detection of non-executable malware, including static, dynamic, and combined methods. While static methods perform orders of magnitude faster, their applicability has been hitherto limited to specific file formats. This paper introduces Hidost, the first static machine-learning-based malware detection system designed to operate onmultiple file formats. Extending a previously published, highly effective method, it combines the logical structure of files with their content for even better detection accuracy. Our system has been implemented and evaluated on two formats, PDF and SWF (Flash). Thanks to its modular design and general feature set, it is extensible to other formats whose logical structure is organized as a hierarchy. Evaluated in realistic experiments on timestamped datasets comprising 440,000 PDF and 40,000 SWF files collected during several months, Hidost outperformed all antivirus engines deployed by the website VirusTotal to detect the highest number of malicious PDF files and ranked among the best on SWF malware.


title: Thinking in circuits: toward neurobiological explanation in cognitive neuroscience

text: Cognitive theory has decomposed human mental abilities into cognitive (sub) systems, and cognitive neuroscience succeeded in disclosing a host of relationships between cognitive systems and specific structures of the human brain. However, an explanation of why specific functions are located in specific brain loci had still been missing, along with a neurobiological model that makes concrete the neuronal circuits that carry thoughts and meaning. Brain theory, in particular the Hebb-inspired neurocybernetic proposals by Braitenberg, now offers an avenue toward explaining brain–mind relationships and to spell out cognition in terms of neuron circuits in a neuromechanistic sense. Central to this endeavor is the theoretical construct of an elementary functional neuronal unit above the level of individual neurons and below that of whole brain areas and systems: the distributed neuronal assembly (DNA) or thought circuit (TC). It is shown that DNA/TC theory of cognition offers an integrated explanatory perspective on brain mechanisms of perception, action, language, attention, memory, decision and conceptual thought. We argue that DNAs carry all of these functions and that their inner structure (e.g., core and halo subcomponents), and their functional activation dynamics (e.g., ignition and reverberation processes) answer crucial localist questions, such as why memory and decisions draw on prefrontal areas although memory formation is normally driven by information in the senses and in the motor system. We suggest that the ability of building DNAs/TCs spread out over different cortical areas is the key mechanism for a range of specifically human sensorimotor, linguistic and conceptual capacities and that the cell assembly mechanism of overlap reduction is crucial for differentiating a vocabulary of actions, symbols and concepts.


title: Face, Age and Gender Recognition using Local Descriptors

text: This thesis focuses on the area of face processing and aims at designing a reliable framework to facilitate face, age, and gender recognition. A Bag-of-Words framework has been optimized for the task of face recognition by evaluating different feature descriptors and different bag-of-words configurations. More specifically, we choose a compact set of features (e.g., descriptors, window locations, window sizes, dictionary sizes, etc.) in order to produce the highest possible rate of accuracy. Experiments on a challenging dataset shows that our framework achieves a better level of accuracy when compared to other popular approaches such as dimension reduction techniques, edge detection operators, and texture and shape feature extractors. The second contribution of this thesis is the proposition of a general framework for age and gender classification. Although the vast majority of the existing solutions focus on a single visual descriptor that often only encodes a certain characteristic of the image regions, this thesis aims at integrating multiple feature types. For this purpose, feature selection is employed to obtain more accurate and robust facial descriptors. Once descriptors have been computed, a compact set of features is chosen, which facilitates facial image processing for age and gender analysis. In addition to this, a new color descriptor (CLR-LBP) is proposed and the results obtained is shown to be comparable to those of other pre-existing color descriptors. The experimental results indicates that our age and gender framework outperforms other proposed methods when examined on two challenging databases, where face objects are present with different expressions and levels of illumination. This achievement demonstrates the effectiveness of our proposed solution and allows us to achieve a higher accuracy over the existing state-of-the-art methods.


title: Mate choice decisions: the role of facial beauty

text: For most people, facial beauty appears to play a prominent role in choosing a mate. Evidence from research on facial attractiveness indicates that physical beauty is a sexually selected trait mediated, in part, by pubertal facial hormone markers that signal important biological information about the displayer. Such signals would be ineffective if they did not elicit appropriate cognitive and/or emotional responses in members of the opposite sex. In this article, I argue that the effectiveness of these hormonal displays varies with perceivers' brains, which have been organized by the degree of steroid hormone exposure in the uterus, and activated by varying levels of circulating steroids following puberty. I further propose that the methodology used for examining mate choice decisions has general applicability for determining how cognitive and emotional evaluations enter into decision processes.


title: Learning from the past: answering new questions with past answers

text:
Community-based Question Answering sites, such as Yahoo! Answers or Baidu Zhidao, allow users to get answers to complex, detailed and personal questions from other users. However, since answering a question depends on the ability and willingness of users to address the asker's needs, a significant fraction of the questions remain unanswered. We measured that in Yahoo! Answers, this fraction represents 15% of all incoming English questions. At the same time, we discovered that around 25% of questions in certain categories are recurrent, at least at the question-title level, over a period of one year.
 We attempt to reduce the rate of unanswered questions in Yahoo! Answers by reusing the large repository of past resolved questions, openly available on the site. More specifically, we estimate the probability whether certain new questions can be satisfactorily answered by a best answer from the past, using a statistical model specifically trained for this task. We leverage concepts and methods from query-performance prediction and natural language processing in order to extract a wide range of features for our model. The key challenge here is to achieve a level of quality similar to the one provided by the best human answerers.
 We evaluated our algorithm on offline data extracted from Yahoo! Answers, but more interestingly, also on online data by using three "live" answering robots that automatically provide past answers to new questions when a certain degree of confidence is reached. We report the success rate of these robots in three active Yahoo! Answers categories in terms of both accuracy, coverage and askers' satisfaction. This work presents a first attempt, to the best of our knowledge, of automatic question answering to questions of social nature, by reusing past answers of high quality.


title: Netprobe: a fast and scalable system for fraud detection in online auction networks

text: Given a large online network of online auction users and their histories of transactions, how can we spot anomalies and auction fraud? This paper describes the design and implementation of NetProbe, a system that we propose for solving this problem. NetProbe models auction users and transactions as a Markov Random Field tuned to detect the suspicious patterns that fraudsters create, and employs a Belief Propagation mechanism to detect likely fraudsters. Our experiments show that NetProbe is both efficient and effective for fraud detection. We report experiments on synthetic graphs with as many as 7,000 nodes and 30,000 edges, where NetProbe was able to spot fraudulent nodes with over 90% precision and recall, within a matter of seconds. We also report experiments on a real dataset crawled from eBay, with nearly 700,000 transactions between more than 66,000users, where NetProbe was highly effective at unearthing hidden networks of fraudsters, within a realistic response time of about 6 minutes. For scenarios where the underlying data is dynamic in nature, we propose IncrementalNetProbe, which is an approximate, but fast, variant of NetProbe. Our experiments prove that Incremental NetProbe executes nearly doubly fast as compared to NetProbe, while retaining over 99% of its accuracy.


title: Multicommodity max-flow min-cut theorems and their use in designing approximation algorithms

text: In this paper, we establish max-flow min-cut theorems for several important classes of multicommodity flow problems. In particular, we show that for any n-node multicommodity flow problem with uniform demands, the max-flow for the problem is within an O(log n) factor of the upper bound implied by the min-cut. The result (which is existentially optimal) establishes an important analogue of the famous 1-commodity max-flow min-cut theorem for problems with multiple commodities. The result also has substantial applications to the field of approximation algorithms. For example, we use the flow result to design the first polynomial-time (polylog n-times-optimal) approximation algorithms for well-known NP-hard optimization problems such as graph partitioning, min-cut linear arrangement, crossing number, VLSI layout, and minimum feedback arc set. Applications of the flow results to path routing problems, network reconfiguration, communication in distributed networks, scientific computing and rapidly mixing Markov chains are also described in the paper.


title: Requirements Traceability: a Systematic Review and Industry Case Study

text: Requirements traceability enables software engineers to trace a requirement from its emergence to its ful ̄llment. In this paper we examine requirements traceability de ̄nitions, challenges, tools and techniques, by the use of a systematic review performing an exhaustive search through the years 1997 2007. We present a number of common de ̄nitions, challenges, available tools and techniques (presenting empirical evidence when found), while complementing the results and analysis with a static validation in industry through a series of interviews.


title: StudentLife: assessing mental health, academic performance and behavioral trends of college students using smartphones

text: Much of the stress and strain of student life remains hidden. The StudentLife continuous sensing app assesses the day-to-day and week-by-week impact of workload on stress, sleep, activity, mood, sociability, mental well-being and academic performance of a single class of 48 students across a 10 week term at Dartmouth College using Android phones. Results from the StudentLife study show a number of significant correlations between the automatic objective sensor data from smartphones and mental health and educational outcomes of the student body. We also identify a Dartmouth term lifecycle in the data that shows students start the term with high positive affect and conversation levels, low stress, and healthy sleep and daily activity patterns. As the term progresses and the workload increases, stress appreciably rises while positive affect, sleep, conversation and activity drops off. The StudentLife dataset is publicly available on the web.


title: Finite Element Analysis Based Design of Mobile Robot for Removing Plug Oil Well

text: In order to develop the mobile robot for removing the plug oil well, the robot was designed based on the wheeltype and leg-type robot mechanism. A well functioning prototype has been manufactured. To demonstrate the validity and the benefit of the mobile robot, supporting mechanism and guiding rod were chosen to design based on the FEM. The mathematical model of the supporting mechanism is established and the mechanical property is analyzed using the FEM. The deformation and stress of some components of the supporting mechanism and the guiding rod is investigated. The results show that the supporting mechanism and the guiding rod have excellent performance with little displacement and small stress under working condition. The strength and rigidity of supporting mechanism and the guiding rod are good enough to ensure the reliability of the whole robot mechanism.


title: Cognitive load and detection thresholds in car following situations: safety implications for using mobile (cellular) telephones while driving.

text: This study was aimed at investigating drivers' ability to detect a car ahead decelerating, while doing mobile phone related tasks. Nineteen participants aged between 20 and 29 years, (2000-125000 km driving experience) drove at 80 km/h, 50 m behind a lead car, on a 30 km section of motorway in normal traffic. During each trial the lead car started to decelerate at an average of 0.47 m/s2 while the participant either looked at the car in front (control), continuously dialed series of three random integers on a numeric keypad (divided visual attention), or performed a memory and addition task (non-visual attention). The results indicated that drivers' detection ability was impaired by about 0.5 s in terms of brake reaction time and almost 1 s in terms of time-to-collision, when they were doing the non-visual task whilst driving. This impairment was similar to when the drivers were dividing their visual attention between the road ahead and dialing numbers on the keypad. It was concluded that neither a hands-free option nor a voice controlled interface removes the safety problems associated with the use of mobile phones in a car.


title: Telerobotics, automation, and human supervisory control [Review]

text: In Telerobotics, Automation, and Human Supervisory Control, Thomas B. Sheridan shows that progress in robotics depends not only on change in technology, but also on advances in humans’ relationships to machines. Sheridan, Professor of Engineering and Applied Psychology at M.I.T., has spent decades studying human-machine relations. His idea of “human supervisory control” (just “supervisory control” for short) has the potential to bring robotics out of the laboratory and into the difficult and messy world. Traditionally, the public and researchers alike have focused on automation which seeks to build into a machine all necessary capabilities for achieving a particular task, including sensors, actuators, servos, and algorithms. In contrast to automatic control, supervisory control puts a human back “in the loop,” usually at the highest levels of abstraction, while maintaining lower-level functions within the machine. In a supervisory control system human and machine work together. The operator may intervene and operate manually in a particular situation, or she (Sheridan refers to the generic operator as female) might turn over control to an automatic controller for a time, acting as monitor of the task at hand. Typically the “system” (including the human) will operate somewhere on the spectrum between manual and automatic, dividing the task in different degrees depending on the situation. When the operator and the machine are not collocated but are connected by some communication channel, the system is said to be telerobotic. Determining the proper balance of man and machine, manual and automatic control, or providing tools to do so, is the goal of Sheridan’s book. An important modern example of a supervisory control system (although not a telerobotic one) is a modem aircraft. The pilot can command the flight surfaces directly and fly manually, or she can program an autopilot to fly a complete route, including nearly complete takeoff and landing. Typically, the pilot performs some


title: Internet Traffic Classification by Aggregating Correlated Naive Bayes Predictions

text: This paper presents a novel traffic classification scheme to improve classification performance when few training data are available. In the proposed scheme, traffic flows are described using the discretized statistical features and flow correlation information is modeled by bag-of-flow (BoF). We solve the BoF-based traffic classification in a classifier combination framework and theoretically analyze the performance benefit. Furthermore, a new BoF-based traffic classification method is proposed to aggregate the naive Bayes (NB) predictions of the correlated flows. We also present an analysis on prediction error sensitivity of the aggregation strategies. Finally, a large number of experiments are carried out on two large-scale real-world traffic datasets to evaluate the proposed scheme. The experimental results show that the proposed scheme can achieve much better classification performance than existing state-of-the-art traffic classification methods.


title: New relationships between breast microcalcifications and cancer

text: Background:Breast microcalcifications are key diagnostically significant radiological features for localisation of malignancy. This study explores the hypothesis that breast calcification composition is directly related to the local tissue pathological state.Methods:A total of 236 human breast calcifications from 110 patients were analysed by mid-Fouries transform infrared (FTIR) spectroscopy from three different pathology types (112 invasive carcinoma (IC), 64 in-situ carcinomas and 60 benign). The biochemical composition and the incorporation of carbonate into the hydroxyapatite lattice of the microcalcifications were studied by infrared microspectroscopy. This allowed the spectrally identified composition to be directly correlated with the histopathology grading of the surrounding tissue.Results:The carbonate content of breast microcalcifications was shown to significantly decrease when progressing from benign to malignant disease. In this study, we report significant correlations (P<0.001) between microcalcification chemical composition (carbonate content and protein matrix : mineral ratios) and distinct pathology grades (benign, in-situ carcinoma and ICs). Furthermore, a significant correlation (P<0.001) was observed between carbonate concentrations and carcinoma in-situ sub-grades. Using the two measures of pathology-specific calcification composition (carbonate content and protein matrix : mineral ratios) as the inputs to a two-metric discriminant model sensitivities of 79, 84 and 90% and specificities of 98, 82 and 96% were achieved for benign, ductal carcinoma in situ and invasive malignancies, respectively.Conclusions:We present the first demonstration of a direct link between the chemical nature of microcalcifications and the grade of the pathological breast disease. This suggests that microcalcifications have a significant association with cancer progression, and could be used for future objective analytical classification of breast pathology. A simple two-metric model has been demonstrated, more complex spectral analysis may yeild greater discrimination performance. Furthermore there appears to be a sequential progression of calcification composition.


title: Link prediction in complex networks: a local naïve Bayes model

text: Common-neighbor-based method is simple yet effective to predict missing links, which assume that two nodes are more likely to be connected if they have more common neighbors. In such method, each common neighbor of two nodes contributes equally to the connection likelihood. In this Letter, we argue that different common neighbors may play different roles and thus lead to different contributions, and propose a local näıve Bayes model accordingly. Extensive experiments were carried out on eight real networks. Compared with the common-neighbor-based methods, the present method can provide more accurate predictions. Finally, we gave a detailed case study on the US air transportation network. Introduction. – The problem of link prediction aims at estimating the likelihood of the existence of a link between two nodes in a given network, based on the observed links [1]. Recently, the study of link prediction has attracted much attention from disparate scientific communities. In the theoretical aspect, accurate prediction indeed gives evidence to some underlying mechanisms that drives the network evolution [2]. Moveover, it is very possible to build a fair evaluation platform for network modeling under the framework of link prediction, which might be interested by network scientists [1, 3]. In the practical aspect, for biological networks such as protein-protein interaction networks and metabolic networks [4–6], the experiments of uncovering the new links or interactions are costly, and thus to predict in advance and focus on the links most likely to exist can sharply reduce the experimental costs [7]. In addition, some of the representative methods of link prediction have been successfully applied to address the classification problem in partially labeled networks [8, 9], as well as identified the spurious links resulted from the inaccurate information in the data [10]. Motivated by the theoretical interests and practical significance, many methods for link predication have been proposed. Therein some algorithms are based on Markov chains [11–13] and machine learning [14, 15]. Another group of algorithms are based on node similarity [1, 16]. (a)Corresponding author:linyuan.lue@unifr.ch Common Neighbors (CN) is one of the simplest similarity indices. Empirically, Kossinets and Watts [17] analyzed a large-scale social network, suggesting that two students having many mutual friends are very probable to be friend in the future. Also in online society like Facebook, the users tend to be friend if they have common friends and therefore form a community. Extensive analysis on disparate networks suggests that CN index is of good performance on predicting the missing links [16, 18]. Lü et al. [19] suggested that in a network with large clustering coefficient, CN can provide competitively accurate predictions compared with the indices making use of global information. Very recently, Cui et al. [20] revealed that the nodes with more common neighbors are more likely to form new links in a growing network. The basic assumption of CN is that two nodes are more likely to be connected if they have more common neighbors. Simply counting the number of common neighbors indicates that each common neighbor gives equal contribution to the connection likelihood. However, sometimes different common neighbors may play different roles. For instance, the common close friends of two people who don’t know each other may contribute more to their possibly future friendship than their common nodding acquaintances. In this Letter, we propose a probabilistic model based on the Bayesian theory, called Local Näıve Bayes (LNB) model, to predict the missing links in complex networks. Based on the LNB model,


title: A Rank-Switching, Open-Row DRAM Controller for Time-Predictable Systems

text: We introduce ROC, a Rank-switching, Open-row Controller for Double Data Rate Dynamic RAM (DDR DRAM). ROC is optimized for mixed-criticality multicore systems using modern DDR devices: compared to existing real-time memory controllers, it provides significantly lower worst case latency bounds for hard real-time tasks and supports throughput-oriented optimizations for soft real-time applications. The key to improved performance is an innovative rank-switching mechanism which hides the latency of write-read transitions in DRAM devices without requiring unpredictable request reordering. We further employ open row policy to take advantage of the data caching mechanism (row buffering) in each device. ROC provides complete timing isolation between hard and soft tasks and allows for compositional timing analysis over the number of cores and memory ranks in the system. We implemented and synthesized the ROC back end in Verilog RTL, and evaluated its performance on both synthetic tasks and a set of representative benchmarks.


title: Interprofessional education: effects on professional practice and health care outcomes.

text:
BACKGROUND
As patient care becomes more complex, effective collaboration between health and social care professionals is required. However, evidence suggests that these professionals do not collaborate well together. Interprofessional education (IPE) offers a possible way forward in this area.

OBJECTIVES
To assess the usefulness of IPE interventions compared to education in which the same professions were learning separately from one another.

SEARCH STRATEGY
We searched the Cochrane Effective Practice and Organisation of Care Group specialised register, MEDLINE (1968 to 1998) and Cinahl (1982 to 1998). We also hand searched the Journal of Interprofessional Care (1992 to 1998), the Centre for the Advancement of Interprofessional Education Bulletin (1987 to 1998), conference proceedings, the 'grey literature' held by relevant organisations, and reference lists of articles.

SELECTION CRITERIA
Randomised trials, controlled before and after studies and interrupted time series studies of IPE interventions designed to improve collaborative practice between health/social care practitioners and/or the health/well being of patients/clients. The participants included chiropodists/podiatrists, complementary therapists, dentists, dietitians, doctors/physicians, hygienists, psychologists, psychotherapists, midwives, nurses, pharmacists, physiotherapists, occupational therapists, radiographers, speech therapists and/or social workers. The outcomes included objectively measured or self reported (validated instrument) patient/client outcomes and reliable (objective or validated subjective) health care process measures.

DATA COLLECTION AND ANALYSIS
Two reviewers independently assessed the eligibility of potentially relevant studies.

MAIN RESULTS
The total yield from the search strategy was 1042, of which 89 were retained for further consideration. However none of these studies met the inclusion criteria.

REVIEWER'S CONCLUSIONS
Despite finding a large body of literature on the evaluation of IPE, these studies lacked the methodological rigour needed to begin to convincingly understand the impact of IPE on professional practice and/or health care outcomes.


title: Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking

text: Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a difficult problem in complex scenes, because of the large ambiguity in associating multiple objects in consecutive frames and the low discriminability between objects appearances. In this paper, we propose a robust online multi-object tracking method that can handle these difficulties effectively. We first define the tracklet confidence using the detectability and continuity of a tracklet, and decompose a multi-object tracking problem into small subproblems based on the tracklet confidence. We then solve the online multi-object tracking problem by associating tracklets and detections in different ways according to their confidence values. Based on this strategy, tracklets sequentially grow with online-provided detections, and fragmented tracklets are linked up with others without any iterative and expensive association steps. For more reliable association between tracklets and detections, we also propose a deep appearance learning method to learn a discriminative appearance model from large training datasets, since the conventional appearance learning methods do not provide rich representation that can distinguish multiple objects with large appearance variations. In addition, we combine online transfer learning for improving appearance discriminability by adapting the pre-trained deep model during online tracking. Experiments with challenging public datasets show distinct performance improvement over other state-of-the-arts batch and online tracking methods, and prove the effect and usefulness of the proposed methods for online multi-object tracking.


title: The Mini Nutritional Assessment (MNA) review of the literature--What does it tell us?

text:
UNLABELLED
To review the literature on the MNA to Spring 2006, we searched MEDLINE, Web of Science and Scopus, and did a manual search in J Nutr Health Aging, Clin Nutr, Eur J Clin Nutr and free online available publications.

VALIDATION AND VALIDITY
The MNA was validated against two principal criteria, clinical status and comprehensive nutrition assessment using principal component and discriminant analysis. The MNA shortform (MNA-SF) was developed and validated to allow a 2-step screening process. The MNA and MNA-SF are sensitive, specific, and accurate in identifying nutrition risk.

NUTRITIONAL SCREENING
The prevalence of malnutrition in community-dwelling elderly (21 studies, n = 14149 elderly) is 2 +/- 0.1% (mean +/- SE, range 0- 8%) and risk of malnutrition is 24 +/- 0.4% (range 8-76%). A similar pattern is seen in out-patient and home care elderly (25 studies, n = 3119 elderly) with prevalence of undernutrition 9 +/- 0.5% (mean +/- SE, range 0-30%) and risk of malnutrition 45 +/- 0.9% (range 8-65%). A high prevalence of undernutrition has been reported in hospitalized and institutionalized elderly patients: prevalence of malnutrition is 23 +/- 0.5% (mean +/- SE, range 1- 74%) in hospitals (35 studies, n = 8596) and 21 +/- 0.5% (mean +/- SE, range 5-71%) in institutions (32 studies, n = 6821 elderly). An even higher prevalence of risk of malnutrition was observed in the same populations, with 46 +/- 0.5% (range 8-63%) and 51 +/- 0.6% (range 27-70%), respectively. In cognitively impaired elderly subjects (10 studies, n = 2051 elderly subjects), detection using the MNA, prevalence of malnutrition was 15 +/- 0.8% (mean +/- SE, range 0-62%), and 44 +/- 1.1% (range 19-87%) of risk of malnutrition.

CHARACTERISTICS
The large variability is due to differences in level of dependence and health status among the elderly. In hospital settings, a low MNA score is associated with an increase in mortality, prolonged length of stay and greater likelihood of discharge to nursing homes. Malnutrition is associated with functional and cognitive impairment and difficulties eating. The MNA(R) detects risk of malnutrition before severe change in weight or serum proteins occurs.

NUTRITIONAL INTERVENTION
Intervention studies demonstrate that timely intervention can stop weight loss in elderly at risk of malnutrition or undernourished and is associated with improvements in MNA scores. The MNA can also be used as a follow up assessment tool.

CONCLUSION
The MNA is a screening and assessment tool with a reliable scale and clearly defined thresholds, usable by health care professionals. It should be included in the geriatric assessment and is proposed in the minimum data set for nutritional interventions.


title: Examining students' online interaction in a live video streaming environment using data mining and text mining

text: 0747-5632/$ see front matter 2012 Elsevier Ltd. A http://dx.doi.org/10.1016/j.chb.2012.07.020 ⇑ Tel.: +1 757 683 5008; fax: +1 757 683 5639. E-mail address: whe@odu.edu This study analyses the online questions and chat messages automatically recorded by a live video streaming (LVS) system using data mining and text mining techniques. We apply data mining and text mining techniques to analyze two different datasets and then conducted an in-depth correlation analysis for two educational courses with the most online questions and chat messages respectively. The study found the discrepancies as well as similarities in the students’ patterns and themes of participation between online questions (student–instructor interaction) and online chat messages (student–students interaction or peer interaction). The results also identify disciplinary differences in students’ online participation. A correlation is found between the number of online questions students asked and students’ final grades. The data suggests that a combination of using data mining and text mining techniques for a large amount of online learning data can yield considerable insights and reveal valuable patterns in students’ learning behaviors. Limitations with data and text mining were also revealed and discussed in the paper. 2012 Elsevier Ltd. All rights reserved.


title: Learning to Detect Human-Object Interactions

text: We study the problem of detecting human-object interactions (HOI) in static images, defined as predicting a human and an object bounding box with an interaction class label that connects them. HOI detection is a fundamental problem in computer vision as it provides semantic information about the interactions among the detected objects. We introduce HICO-DET, a new large benchmark for HOI detection, by augmenting the current HICO classification benchmark with instance annotations. To solve the task, we propose Human-Object Region-based Convolutional Neural Networks (HO-RCNN). At the core of our HO-RCNN is the Interaction Pattern, a novel DNN input that characterizes the spatial relations between two bounding boxes. Experiments on HICO-DET demonstrate that our HO-RCNN, by exploiting human-object spatial relations through Interaction Patterns, significantly improves the performance of HOI detection over baseline approaches.


title: Biohashing: two factor authentication featuring fingerprint data and tokenised random number

text: Human authentication is the security task whose job is to limit access to physical locations or computer network only to those with authorisation. This is done by equipped authorised users with passwords, tokens or using their biometrics. Unfortunately, the first two suffer a lack of security as they are easy being forgotten and stolen; even biometrics also suffers from some inherent limitation and specific security threats. A more practical approach is to combine two or more factor authenticator to reap benefits in security or convenient or both. This paper proposed a novel two factor authenticator based on iterated inner products between tokenised pseudo-random number and the user specific fingerprint feature, which generated from the integrated wavelet and Fourier–Mellin transform, and hence produce a set of user specific compact code that coined as BioHashing. BioHashing highly tolerant of data capture offsets, with same user fingerprint data resulting in highly correlated bitstrings. Moreover, there is no deterministic way to get the user specific code without having both token with random data and user fingerprint feature. This would protect us for instance against biometric fabrication by changing the user specific credential, is as simple as changing the token containing the random data. The BioHashing has significant functional advantages over solely biometrics i.e. zero equal error rate point and clean separation of the genuine and imposter populations, thereby allowing elimination of false accept rates without suffering from increased occurrence of false reject rates. 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.


title: A weighted additive fuzzy programming approach for multi-criteria supplier selection

text: In supply chain management, to build strategic and strong relationships, firms should select best suppliers by applying appropriate method and selection criteria. In this paper, to handle ambiguity and fuzziness in supplier selection problem effectively, a new weighted additive fuzzy programming approach is developed. Firstly, linguistic values expressed as trapezoidal fuzzy numbers are used to assess the weights of the factors. By applying the distances of each factor between Fuzzy Positive Ideal Rating and Fuzzy Negative Ideal Rating, weights are obtained. Then applying suppliers’ constraints, goals and weights of the factors, a fuzzy multi-objective linear model is developed to overcome the selection problem and assign optimum order quantities to each supplier. The proposed model is explained by a numerical example. 2010 Elsevier Ltd. All rights reserved.


title: Artificial Neural Networks architectures for stock price prediction: comparisons and applications

text: We present an Artificial Neural Network (ANN) approach to predict stock market indices, particularly with respect to the forecast of their trend movements up or down. Exploiting different Neural Networks architectures, we provide numerical analysis of concrete financial time series. In particular, after a brief résumé of the existing literature on the subject, we consider the Multi-layer Perceptron (MLP), the Convolutional Neural Networks (CNN), and the Long Short-Term Memory (LSTM) recurrent neural networks techniques. We focus on the importance of choosing the correct input features, along with their preprocessing, for the specific learning algorithm one wants to use. Eventually, we consider the S&P500 historical time series, predicting trend on the basis of data from the past days, and proposing a novel approach based on combination of wavelets and CNN, which outperforms the basic neural networks ones. We show, that neural networks are able to predict financial time series movements even trained only on plain time series data and propose more ways to improve results. Key–Words: Artificial neural networks, Multi-layer neural network, Convolutional neural network, Long shortterm memory, Recurrent neural network, Deep Learning, Stock markets analysis, Time series analysis, financial forecasting


title: MIR_EVAL: A Transparent Implementation of Common MIR Metrics

text: Central to the field of MIR research is the evaluation of algorithms used to extract information from music data. We present mir_eval, an open source software library which provides a transparent and easy-to-use implementation of the most common metrics used to measure the performance of MIR algorithms. In this paper, we enumerate the metrics implemented by mir_eval and quantitatively compare each to existing implementations. When the scores reported by mir_eval differ substantially from the reference, we detail the differences in implementation. We also provide a brief overview of mir_eval’s architecture, design, and intended use. 1. EVALUATING MIR ALGORITHMS Much of the research in Music Information Retrieval (MIR) involves the development of systems that process raw music data to produce semantic information. The goal of these systems is frequently defined as attempting to duplicate the performance of a human listener given the same task [5]. A natural way to determine a system’s effectiveness might be for a human to study the output produced by the system and judge its correctness. However, this would yield only subjective ratings, and would also be extremely timeconsuming when evaluating a system’s output over a large corpus of music. Instead, objective metrics are developed to provide a well-defined way of computing a score which indicates each system’s output’s correctness. These metrics typically involve a heuristically-motivated comparison of the system’s output to a reference which is known to be correct. Over time, certain metrics have become standard for each ∗Please direct correspondence to craffel@gmail.com c © Colin Raffel, Brian McFee, Eric J. Humphrey, Justin Salamon, Oriol Nieto, Dawen Liang, Daniel P. W. Ellis. Licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Attribution: Colin Raffel, Brian McFee, Eric J. Humphrey, Justin Salamon, Oriol Nieto, Dawen Liang, Daniel P. W. Ellis.


title: Fuzzy Cognitive Map software

text: Fuzzy Cognitive Map (FCM) is a soft computing modelling methodology for complex systems. Beyond the mathematical formulation of the FCM theory, there was a need of developing a software tool to facilitate the implementation of FCMs. This paper describes the use of a software tool that was developed to construct FCM models. Some theoretical elements of Fuzzy Cognitive Maps are presented. Then, it is discussed how the software tool is used to develop a model and simulate the use of Fuzzy Cognitive Maps. The user interface of the software tool is described and how the FCM-Analyst is used to facilitate the implementation and simulation of Fuzzy Cognitive Maps.


title: In the mood: engaging teenagers in psychotherapy using mobile phones

text: Mental illness is a significant and growing problem throughout the world. Many mental health problems have their root in childhood, and early intervention is recommended. Engaging young people in psychotherapeutic activities is challenging, and treatment adherence is often poor. This paper presents a series of studies carried out as part of the development of a mobile and online symptom tracking tool for adolescents with mental health problems. Teenagers use the system to record symptoms on their mobile phones and can view this information in a clinical setting with a therapist. We focus on a clinical pilot of the system with ten users in public mental health clinics. As well as indicating that the mobile diary tool can increase client adherence to therapeutic activities, the study yields insight into the factors influencing the success of the design and informs the design of other systems to be used as adjuncts to therapy.


title: Perspectives on Live Streaming: Apps, Users, and Research

text: The emergence of mobile live streaming as a popular app over the past couple years provides a new platform for socio-technical interaction in the world. This panel brings together several different perspectives on live streaming: companies who are producing commercial apps, researchers studying how people are using live streaming, and users. We hope the discussion identifies design and research implications for the future.


title: Lightweight Management of Resource-Constrained Sensor Devices in Internet of Things

text: It is predicted that billions of intelligent devices and networks, such as wireless sensor networks (WSNs), will not be isolated but connected and integrated with computer networks in future Internet of Things (IoT). In order to well maintain those sensor devices, it is often necessary to evolve devices to function correctly by allowing device management (DM) entities to remotely monitor and control devices without consuming significant resources. In this paper, we propose a lightweight RESTful Web service (WS) approach to enable device management of wireless sensor devices. Specifically, motivated by the recent development of IPv6-based open standards for accessing wireless resource-constrained networks, we consider to implement IPv6 over low-power wireless personal area network (6LoWPAN)/routing protocol for low power and lossy network (RPL)/constrained application protocol (CoAP) protocols on sensor devices and propose a CoAP-based DM solution to allow easy access and management of IPv6 sensor devices. By developing a prototype cloud system, we successfully demonstrate the proposed solution in efficient and effective management of wireless sensor devices.


title: 2011 terminology of the vulva of the International Federation for Cervical Pathology and Colposcopy.

text:
OBJECTIVE
This study aimed to present the clinical and colposcopic terminology of the vulva (including the anus) of the International Federation of Cervical Pathology and Colposcopy.

MATERIALS AND METHODS
The terminology has been developed by the International Federation of Cervical Pathology and Colposcopy Nomenclature Committee during 2009-2011.

RESULTS
The terminology is part of a comprehensive terminology of the lower genital tract, allowing for standardization of nomenclature by colposcopists, clinicians, and researchers taking care of women with lesions in these areas. The terminology includes basic definitions and normal findings that are important for the clinician lacking experience with management of vulvar disease. This terminology introduces definitions for abnormal findings recently accepted by the International Society for the Study of Vulvovaginal Disease and includes patterns to identify malignancy.

CONCLUSIONS
The terminology differs from past terminologies in that it includes colposcopic patterns and anal colposcopy. Nevertheless, the role of the colposcope in the management of vulvar disease is limited.


title: Single-Fed Broadband Circularly Polarized Stacked Patch Antenna With Horizontally Meandered Strip for Universal UHF RFID Applications

text: In this paper, a horizontally meandered strip (HMS) feed technique is proposed to achieve good impedance matching and symmetrical broadside radiation patterns for a single-fed broadband circularly polarized stacked patch antenna, which is suitable for universal ultrahigh frequency (UHF) RF identification (RFID) applications. The antenna is composed of two corner truncated patches and an HMS, all of which are printed on the upper side of the FR4 substrates. One end of the HMS is connected to the main patch by a probe, while the other end is connected to an SMA connector. Simulation results are compared with the measurements, and a good agreement is obtained. The measurements show that the antenna has an impedance bandwidth (VSWR <; 1.5) of about 25.8% (758-983 MHz), a 3-dB axial ratio (AR) bandwidth of about 13.5% (838-959 MHz), and a gain level of about 8.6 dBic or larger within the 3-dB AR bandwidth. Therefore, the proposed antenna can be a good candidate for universal UHF RFID readers operating at the UHF band of 840-955 MHz. In addition, a parametric study and a design guideline of the proposed antenna are presented to provide the engineers with information for designing, modifying, and optimizing such an antenna. At last, the proposed antenna is validated in RFID system applications.


title: Asymmetric-Circular Shaped Slotted Microstrip Antennas for Circular Polarization and RFID Applications

text: Novel asymmetric-circular shaped slotted microstrip patch antennas with slits are proposed for circularly polarized (CP) radiation and radio frequency identification (RFID) reader applications. A single-feed configuration based asymmetric-circular shaped slotted square microstrip patches are adopted to realize the compact circularly polarized microstrip antennas. The asymmetric-circular shaped slot(s) along the diagonal directions are embedded symmetrically onto a square microstrip patch for CP radiation and small antenna size. The CP radiation can be achieved by slightly asymmetric (unbalanced) patch along the diagonal directions by slot areas. Four symmetric-slits are also embedded symmetrically along the orthogonal directions of the asymmetric-circular shaped slotted patch to further reduce antenna size. The operating frequency of the antenna can be tuned by varying the slit length while keeping the CP radiation unchanged. The measured 3-dB axial-ratio (AR) bandwidth of around 6.0 MHz with 17.0 MHz impedance bandwidth is achieved for the antenna on a RO4003C substrate. The overall antenna size is 0.27λo × 0.27λo × 0.0137λo at 900 MHz.


title: A circularly polarized short backfire antenna excited by an unbalance-fed cross aperture

text: An unbalance-fed cross aperture is developed to excite a short backfire antenna (SBA) for circular polarization. The cross aperture consists of two orthogonal H-shaped slots with a pair of capacitive stubs and is fed by a single probe that forms an unbalanced feed with a shorting pin. It is demonstrated that the cross-aperture-excited SBA can achieve an axial ratio (les 3 dB) bandwidth of 4.2% with a voltage standing wave ratio (VSWR) bandwidth of 6.5% (VSWR<1.2) and a gain of 14 dBi. The antenna structure is described and the simulation and experimental results are presented. The mechanisms for impedance matching and circular-polarization production are analyzed


title: A Dual-Band Circularly Polarized Aperture-Coupled Stacked Microstrip Antenna for Global Positioning Satellite

text: This paper describes the design and testing of an aperture-coupled circularly polarized antenna for global positioning satellite (GPS) applications. The antenna operates at both the L1 and L2 frequencies of 1575 and 1227 MHz, which is required for differential GPS systems in order to provide maximum positioning accuracy. Electrical performance, lowprofile, and cost were equally important requirements for this antenna. The design procedure is discussed, and measured results are presented. Results from a manufacturing sensitivity analysis are also included.


title: Wideband Circularly Polarized Patch Antenna Using Broadband Baluns

text: A novel 90deg broadband balun comprising a broadband 90deg Schiffman phase shifter is introduced as a means of enhancing the wideband circular polarization performance of dual-fed type microstrip antennas. The proposed 90deg broadband balun delivers good impedance matching, balanced power splitting and consistent 90deg (plusmn5deg) phase shifting, across a wide bandwidth (~57.5%). A circular patch antenna utilizing the proposed 90deg broadband balun is shown to attain measured impedance(S11< -10 dB) and axial ratio (AR < 3 dB) bandwidths of 60.24% and 37.7%, respectively, for the dual L-probe case; and 71.28% and 81.6% respectively, for the quadruple L-probe case.


title: vFPGAmanager: A Virtualization Framework for Orchestrated FPGA Accelerator Sharing in 5G Cloud Environments

text: Network operators are actively pushing towards the new 5G era and a crucial part to accomplish this is the Network Functions Virtualization (NFV). FPGAs and their hardware accelerators are a promising solution for NFV and 5G cloud environments because of their fast turnaround time and great speedup potential through application parallelism mapping on the reconfigurable fabric. Recently, consolidation reached a plateau in this field with lightweight virtualization techniques, that require a high overcommitment of FPGA accelerator resources to cope with numerous demands of guests. Although FPGAs can play an important role for the future 5G networks their capability to manage and control them from the upper layers of the software stack is inadequate. The lack of such support coupled with cloud integration and programmability issues can repel potential providers from utilizing FPGAs at their data centers. This paper presents the communication mechanism of the vFPGAmanager, an FPGA virtualization framework which can be orchestrated, monitored and enables accelerators overcommitment with direct guest access. These are key features to allow potential adopters of FPGA technology to include them in the next generation of NFV systems. The communication mechanism architecture is detailed and then benchmarked to show that even under heavy load on the system it demonstrates a minimal overhead to orchestrate and monitor the FPGA as a resource.


title: Refining Duplicate Detection for Improved Data Quality

text: Detecting duplicates is a pervasive data quality challenge that hinders organizations from extracting value from their data sooner. The increased complexity and heterogeneity of modern datasets has lead to the presence of varying record formats, missing values, and evolving data semantics. As data is integrated, duplicates inevitably occur in the integrated instance. One of the challenges in deduplication is determining whether two values are sufficiently close to be considered equal. Existing similarity functions often rely on counting the number of required edits to transform one value to the other. This is insufficient in attribute domains, such as time, where small syntactic differences do not always translate to ’closeness’. In this paper, we propose a duplication detection framework, which adapts metric functional dependencies (MFDs) to improve the detection accuracy by relaxing the matching condition on numeric values to allow a permitted tolerance. We evaluate our techniques against two existing approaches using three real data collections, and show that we achieve an average 25% and 34% improvement in precision and recall, respectively, over non-MFD versions.


title: Automatic music transcription: challenges and future directions

text: Automatic music transcription is considered by many to be a key enabling technology in music signal processing. However, the performance of transcription systems is still significantly below that of a human expert, and accuracies reported in recent years seem to have reached a limit, although the field is still very active. In this paper we analyse limitations of current methods and identify promising directions for future research. Current transcription methods use general purpose models which are unable to capture the rich diversity found in music signals. One way to overcome the limited performance of transcription systems is to tailor algorithms to specific use-cases. Semi-automatic approaches are another way of achieving a more reliable transcription. Also, the wealth of musical scores and corresponding audio data now available are a rich potential source of training data, via forced alignment of audio to scores, but large scale utilisation of such data has yet to be attempted. Other promising approaches include the integration of information from multiple algorithms and different musical aspects.


title: Improving Interaction in HMD-Based Vehicle Simulators through Real Time Object Reconstruction

text: Bringing real objects into the virtual world has been shown to increase usability and presence in virtual reality applications. This paper presents a system to generate a real time virtual reconstruction of real world user interface elements for use in a head mounted display based driving simulator. Our system uses sensor fusion algorithms to combine data from depth and color cameras to generate an accurate, detailed, and fast rendering of the user's hands while using the simulator. We tested our system and show in our results that the inclusion of the participants real hands, the wheel, and the shifter in the virtual environment increases the immersion, presence, and usability of the simulation. Our system can also be used to bring other real objects into the virtual world, especially when accuracy, detail, and real time updates are desired.


title: Business process management - lessons from European business

text: This paper reports on the findings of a survey and case study research into the understanding and application of business process management (BPM) in European companies. The process perspective is increasingly being seen as a mechanism for achieving competitive advantage through performance improvement and in response to market pressures, customer expectations for better and more reliable service and increasing competition. We reveal the level of importance European companies attach to BPM, what it means to them and what they have done in practice. The paper draws on a postal survey conducted with quality directors and business process managers in organisations which are members of the European Foundation for Quality Management (EFQM) and case studies in a number of organisations regarded as being leaders in the adoption of BPM. The study has helped to highlight some interesting approaches and reveal features which are important for BPM to be successful. Introduction One of the difficulties with business process management (BPM) is that of terminology. The term process can be found in many disciplines which contribute to our understanding of organisations in the management literature. An operational view is seen in quality improvement (Deming, 1986), total quality management (Oakland, 1989) and the concept of just-in-time (Harrison, 1992). Systems thinking (Jenkins, 1971; Checkland, 1981), cybernetics (Beer, 1966) and systems dynamics (Senge, 1990) give a richer meaning to the term. Organisational theorists have also talked in terms of social and organisational processes (Burrell and Morgan, 1979; Monge, 1990). A useful review of these antecedents has been provided by Peppard and Preece (1995). The domain in which the current study is centred develops out of recent approaches which seek to improve organisational effectiveness through the attachment of managerial thinking to Total Quality or Business Excellence models. These have been essentially practitioner driven and not grounded in academic theory. Examples include the European Foundation for Quality Management model (EFQM) (Hakes, 1995) and the Malcom Baldrige National Quality Award model (MBNQA) (George, 1992). While these models espouse multi-factorial and multi-constituency models of organisational effectiveness they remain essentially goal-based (Cameron, 1986). They have also developed from a strong operational framework and often have absorbed the approaches of We would like to thank Bob Dart, Simon Machin and Tony Grant from Royal Mail. We also gratefully appreciate the assistance of the EFQM, Rank Xerox, British Telecom, TNT and Nortel during the various stages of our research. D ow nl oa de d by S E L C U K U N IV E R SI T Y A t 0 2: 52 0 8 Fe br ua ry 2 01 5 (P T ) Lessons from European business 11 business process re-engineering (Hammer, 1990). They have also been influenced by strategic thinking in the strong process orientation of the value chain analysis (Porter, 1985) and they accommodate the resources based view of the firm (Grant, 1991). Use of the models may lead to questioning the design of an organisation at a strategic level by reassessing the value of functions in favour of processes which transcend functionality (Ghoshal and Bartlett, 1995; Galbraith, 1995). However, neither the EFQM nor the MBNQA provide direct guidance on how to deploy BPM. Approaches often incorporate attempts to identify business processes and to classify them as being operational, supporting or direction setting. This activity is often facilitated by consultants using a range of methods but commonly including aspects of process mapping at least at the top level of the organisation. There is evidence that adopting the process paradigm is favoured at least by senior managers (Garvin, 1995), although it is by no means clear that this is a widely held opinion throughout organisations. While it is possible to point to aspects of good practice in BPM, at least at an operational level (Armistead, 1996), we do not know how organisations apply the notion in practice and what they have found to be the key components of a BPM approach. Method The aim of the research has been to develop a better understanding of BPM and how it can be applied as a route to achieving organisational effectiveness. We have been especially interested to find out how companies have used a business process perspective as a way of managing their whole organisation, rather than just the application of process improvement techniques. In particular we have sought to explore the following questions: . How important is BPM for European managers? . Is there a common understanding of BPM among European organisations? . How are European organisations implementing BPM in practice? In addressing these questions we hope to shed light on how organisations conceptualise BPM and draw on their experiences in order to enlighten others both in terms of strategy formulation and deployment. This paper discusses the findings of the research and proposes lessons which can be learnt. During our research we have built up a rich databank of case study material. The case studies have been compiled using an open-ended interview format where senior executives (usually the quality director or business process manager) have been invited to elaborate on their organisation's approach to BPM. The interviews were recorded and transcribed and a cognitive map was developed to identify concepts. In some cases data from the interviews were supplemented by material used for internal self assessments against the EFQM model. Organisations were typically chosen because they were known to have adopted BPM approaches. This paper refers specifically to case studies with Rank Xerox, Nortel, British Telecom and TNT, all of whom have been winners in some form (either directly of through subsidiaries) of European Quality Awards. D ow nl oa de d by S E L C U K U N IV E R SI T Y A t 0 2: 52 0 8 Fe br ua ry 2 01 5 (P T )


title: Reconfigurable antennas in cognitive radio that can think for themselves?

text: This paper discusses the use of reconfigurable antennas in cognitive radio. Most of the emphasis on cognitive radio so far has been in the area of spectral estimation and signal classification. In this paper we show that once a cognitive device manages to learn the RF environment (cognition part), from past observations and decisions using machine learning techniques, we can use the collected data to train reconfigurable antennas to adapt to any change in the RF environment.


title: Self-regulation strategies improve self-discipline in adolescents : benefits of mental contrasting and implementation intentions

text: Self-regulation strategies improve self-discipline in adolescents: benefits of mental contrasting and implementation intentions Angela Lee Duckwortha; Heidi Grantb; Benjamin Loewa; Gabriele Oettingenac; Peter M. Gollwitzerad a Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA b Department of Psychology, Lehigh University, Bethlehem, PA, USA c Department of Psychology, University of Hamburg, Hamburg, Germany d Department of Psychology, University of Konstanz, Konstanz, Germany


title: The FaceSketchID System: Matching Facial Composites to Mugshots

text: Facial composites are widely used by law enforcement agencies to assist in the identification and apprehension of suspects involved in criminal activities. These composites, generated from witness descriptions, are posted in public places and media with the hope that some viewers will provide tips about the identity of the suspect. This method of identifying suspects is slow, tedious, and may not lead to the timely apprehension of a suspect. Hence, there is a need for a method that can automatically and efficiently match facial composites to large police mugshot databases. Because of this requirement, facial composite recognition is an important topic for biometrics researchers. While substantial progress has been made in nonforensic facial composite (or viewed composite) recognition over the past decade, very little work has been done using operational composites relevant to law enforcement agencies. Furthermore, no facial composite to mugshot matching systems have been documented that are readily deployable as standalone software. Thus, the contributions of this paper include: 1) an exploration of composite recognition use cases involving multiple forms of facial composites; 2) the FaceSketchID System, a scalable, and operationally deployable software system that achieves state-of-the-art matching accuracy on facial composites using two algorithms (holistic and component based); and 3) a study of the effects of training data on algorithm performance. We present experimental results using a large mugshot gallery that is representative of a law enforcement agency's mugshot database. All results are compared against three state-of-the-art commercial-off-the-shelf face recognition systems.


title: Office Procedure as Practical Action: Models of Work and System Design

text: The design of office technology relies upon underlying conceptions of human organization and action. The goal of building office information systems requires a representation of office work and its relevant objects. The concern of this paper is that although system designers recognize the centrality of procedural tasks in the office, they tend to ignore the actual work involved in accomplishing those tasks. A perspicuous instance of work in an accounting office is used to recommend a new line of research into the practical problems of office work, and to suggest preliminary implications of that research for office systems design.


title: Multilabel classification via calibrated label ranking

text: Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operate on an underlying (utility) scale which is not calibrated in the sense that it lacks a natural zero point. We propose a suitable extension of label ranking that incorporates the calibrated scenario and substantially extends the expressive power of these approaches. In particular, our extension suggests a conceptually novel technique for extending the common learning by pairwise comparison approach to the multilabel scenario, a setting previously not being amenable to the pairwise decomposition technique. The key idea of the approach is to introduce an artificial calibration label that, in each example, separates the relevant from the irrelevant labels. We show that this technique can be viewed as a combination of pairwise preference learning and the conventional relevance classification technique, where a separate classifier is trained to predict whether a label is relevant or not. Empirical results in the area of text categorization, image classification and gene analysis underscore the merits of the calibrated model in comparison to state-of-the-art multilabel learning methods.


title: Graph-based term weighting for information retrieval

text: A standard approach to Information Retrieval (IR) is to model text as a bag of words. Alternatively, text can be modelled as a graph, whose vertices represent words, and whose edges represent relations between the words, defined on the basis of any meaningful statistical or linguistic relation. Given such a text graph, graph theoretic computations can be applied to measure various properties of the graph, and hence of the text. This work explores the usefulness of such graph-based text representations for IR. Specifically, we propose a principled graph-theoretic approach of (1) computing term weights and (2) integrating discourse aspects into retrieval. Given a text graph, whose vertices denote terms linked by co-occurrence and grammatical modification, we use graph ranking computations (e.g. PageRank Page et al. in The pagerank citation ranking: Bringing order to the Web. Technical report, Stanford Digital Library Technologies Project, 1998) to derive weights for each vertex, i.e. term weights, which we use to rank documents against queries. We reason that our graph-based term weights do not necessarily need to be normalised by document length (unlike existing term weights) because they are already scaled by their graph-ranking computation. This is a departure from existing IR ranking functions, and we experimentally show that it performs comparably to a tuned ranking baseline, such as BM25 (Robertson et al. in NIST Special Publication 500-236: TREC-4, 1995). In addition, we integrate into ranking graph properties, such as the average path length, or clustering coefficient, which represent different aspects of the topology of the graph, and by extension of the document represented as a graph. Integrating such properties into ranking allows us to consider issues such as discourse coherence, flow and density during retrieval. We experimentally show that this type of ranking performs comparably to BM25, and can even outperform it, across different TREC (Voorhees and Harman in TREC: Experiment and evaluation in information retrieval, MIT Press, 2005) datasets and evaluation measures.


title: Confronting the Challenge of Quality Diversity

text: In contrast to the conventional role of evolution in evolutionary computation (EC) as an optimization algorithm, a new class of evolutionary algorithms has emerged in recent years that instead aim to accumulate as diverse a collection of discoveries as possible, yet where each variant in the collection is as fit as it can be. Often applied in both neuroevolution and morphological evolution, these new quality diversity (QD) algorithms are particularly well-suited to evolution's inherent strengths, thereby offering a promising niche for EC within the broader field of machine learning. However, because QD algorithms are so new, until now no comprehensive study has yet attempted to systematically elucidate their relative strengths and weaknesses under different conditions. Taking a first step in this direction, this paper introduces a new benchmark domain designed specifically to compare and contrast QD algorithms. It then shows how the degree of alignment between the measure of quality and the behavior characterization (which is an essential component of all QD algorithms to date) impacts the ultimate performance of different such algorithms. The hope is that this initial study will help to stimulate interest in QD and begin to unify the disparate ideas in the area.


title: A Finger-Vein Based Cancellable Bio-cryptosystem

text: Irrevocability is one major issue in existing bio-cryptosystems. In this paper, we proposed a cancellable bio-cryptosystem by taking the full advantage of cancellable and non-invertible properties of bio-hashing biometrics. Specifically, two transformed templates are generated by using the bio-hashing algorithm and applied into two different secure sketches, fuzzy commitment sketch and fuzzy vault sketch, respectively. These two secure sketches can be fused in two different ways: AND fusion and OR fusion, so as to emphasis either on the recognition accuracy or the security level of the system. Experimental results and security analysis show the validity of the proposed scheme.


title: Protocol considerations for a prefix-caching proxy for multimedia streams

text: The increasing popularity of multimedia streaming applications introduces new challenges in content distribution. Web-initiated multimedia streams typically experience high start-up delay, due to large protocol overheads and the poor delay, throughput, and loss properties of the Internet. Internet service providers can improve performance by caching the initial segment (the pre x) of popular streams at proxies near the requesting clients. The proxy can initiate transmission to the client while simultaneously requesting the remainder of the stream from the server. This paper analyzes the challenges of realizing a pre x-caching service in the context of the IETF's Real-Time Streaming Protocol (RTSP), a multimedia streaming protocol that derives from HTTP. We describe how to exploit existing RTSP features, such as the Range header, and how to avoid several round-trip delays by caching protocol information at the proxy. Based on our experiences, we propose extensions to RTSP that would ease the development of new multimedia proxy services. In addition, we discuss how caching the partial contents of multimedia streams introduces new challenges in cache coherency and feedback control. Then, we brie y present our preliminary implementation of pre x caching on a Linux-based PC, and describe how the proxy interoperates with the RealNetworks server and client.


title: Planning for decentralized control of multiple robots under uncertainty

text: This paper presents a probabilistic framework for synthesizing control policies for general multi-robot systems that is based on decentralized partially observable Markov decision processes (Dec-POMDPs). Dec-POMDPs are a general model of decision-making where a team of agents must cooperate to optimize a shared objective in the presence of uncertainty. Dec-POMDPs also consider communication limitations, so execution is decentralized. While Dec-POMDPs are typically intractable to solve for real-world problems, recent research on the use of macro-actions in Dec-POMDPs has significantly increased the size of problem that can be practically solved. We show that, in contrast to most existing methods that are specialized to a particular problem class, our approach can synthesize control policies that exploit any opportunities for coordination that are present in the problem, while balancing uncertainty, sensor information, and information about other agents. We use three variants of a warehouse task to show that a single planner of this type can generate cooperative behavior using task allocation, direct communication, and signaling, as appropriate. This demonstrates that our algorithmic framework can automatically optimize control and communication policies for complex multi-robot systems.


title: SCL: Simplifying Distributed SDN Control Planes

text: We consider the following question: what consistency model is appropriate for coordinating the actions of a replicated set of SDN controllers? We first argue that the conventional requirement of strong consistency, typically achieved through the use of Paxos or other consensus algorithms, is conceptually unnecessary to handle unplanned network updates. We present an alternate approach, based on the weaker notion of eventual correctness, and describe the design of a simple coordination layer (SCL) that can seamlessly turn a set of single-image SDN controllers (that obey certain properties) into a distributed SDN system that achieves this goal (whereas traditional consensus mechanisms do not). We then show through analysis and simulation that our approach provides faster responses to network events. While our primary focus is on handling unplanned network updates, our coordination layer also handles policy updates and other situations where consistency is warranted. Thus, contrary to the prevailing wisdom, we argue that distributed SDN control planes need only be slightly more complicated than single-image controllers.


title: A compact 2.45 GHz, low power wireless energy harvester with a reflector-backed folded dipole rectenna

text: This paper paper describes the design procedure as well as the experimental performance of a 2.45GHz 10 μW wireless energy harvester (WEH) with a maximum total efficiency of ≈ 30% at 1 μW/cm2 incident power density. The WEH integrates a shunt high-speed rectifying diode with a folded dipole. A metal reflector increases the gain of the rectenna and a quarter wavelength differential line is used as a choke. Both a VDI WVD and a Skyworks GaAs Schottky diode are integrated with the antenna and their performance is compared.


title: A Comparison of Evolutionary Algorithms and Gradient-based Methods for the Optimal Control Problem

text: An experimental comparison of evolutionary algorithms and gradient-based methods for the optimal control problem is carried out. The problem is solved separately by Particle swarm optimization, Grey wolf optimizer, Fast gradient descent method, Marquardt method and Adam method. The simulation is performed on a jet aircraft model. The results of each algorithm performance are compared according to the best found value of the fitness function, the mean value and the standard deviation.


title: Improving speech recognition by revising gated recurrent units

text: Speech recognition is largely taking advantage of deep learning, showing that substantial benefits can be obtained by modern Recurrent Neural Networks (RNNs). The most popular RNNs are Long Short-Term Memory (LSTMs), which typically reach state-of-the-art performance in many tasks thanks to their ability to learn long-term dependencies and robustness to vanishing gradients. Nevertheless, LSTMs have a rather complex design with three multiplicative gates, that might impair their efficient implementation. An attempt to simplify LSTMs has recently led to Gated Recurrent Units (GRUs), which are based on just two multiplicative gates. This paper builds on these efforts by further revising GRUs and proposing a simplified architecture potentially more suitable for speech recognition. The contribution of this work is two-fold. First, we suggest to remove the reset gate in the GRU design, resulting in a more efficient single-gate architecture. Second, we propose to replace tanh with ReLU activations in the state update equations. Results show that, in our implementation, the revised architecture reduces the per-epoch training time with more than 30% and consistently improves recognition performance across different tasks, input features, and noisy conditions when compared to a standard GRU.