title: Mapping science through bibliometric triangulation: An experimental approach applied to water research

text: The idea of constructing science maps based on bibliographic data has intrigued researchers for decades, and various techniques have been developed to map the structure of research disciplines. Most science mapping studies use a single method. However, as research fields have various properties, a valid map of a field should actually be composed of a set of maps derived from a series of investigations using different methods. That leads to the question what can be learned from a combination – triangulation – of these different science maps. In this paper, we propose a method for triangulation, using the example of water science. We combine three different mapping approaches: journal-journal citation relations (JJCR), shared author keywords (SAK), and title word-cited reference co-occurrence (TWRC). Our results demonstrate that triangulation of JJCR, SAK, and TWRC produces a more comprehensive picture than each method does individually. The outcomes from the three different approaches are associated with each other and can be systematically interpreted, and provide insights into the complex multidisciplinary structure of the field of water


title: Iterative Document Representation Learning Towards Summarization with Polishing

text: In this paper, we introduce Iterative Text Summarization (ITS), an iteration-based model for supervised extractive text summarization, inspired by the observation that it is often necessary for a human to read an article multiple times in order to fully understand and summarize its contents. Current summarization approaches read through a document only once to generate a document representation, resulting in a sub-optimal representation. To address this issue we introduce a model which iteratively polishes the document representation on many passes through the document. As part of our model, we also introduce a selective reading mechanism that decides more accurately the extent to which each sentence in the model should be updated. Experimental results on the CNN/DailyMail and DUC2002 datasets demonstrate that our model significantly outperforms state-of-the-art extractive systems when evaluated by machines and by humans.


title: TouchIn: Sightless two-factor authentication on multi-touch mobile devices

text: Mobile authentication is indispensable for preventing unauthorized access to multi-touch mobile devices. Existing mobile authentication techniques are often cumbersome to use and also vulnerable to shoulder-surfing and smudge attacks. This paper focuses on designing, implementing, and evaluating TouchIn, a two-factor authentication system on multi-touch mobile devices. TouchIn works by letting a user draw on the touchscreen with one or multiple fingers to unlock his mobile device, and the user is authenticated based on the geometric properties of his drawn curves as well as his behavioral and physiological characteristics. TouchIn allows the user to draw on arbitrary regions on the touchscreen without looking at it. This nice sightless feature makes TouchIn very easy to use and also robust to shoulder-surfing and smudge attacks. Comprehensive experiments on Android devices confirm the high security and usability of TouchIn.


title: Understanding and Using Patterns in Software Development

text: Patterns have shown to be an effective means of capturing and communicating software design experience. However, there is more to patterns than software design patterns: We believe that patterns work for software development on several levels. In this paper we explore what we have come to understand as crucial aspects of the pattern concept, relate patterns to the different models built during software design, discuss pattern forms and how we think that patterns can form larger wholes like pattern handbooks.


title: Korean pop takes off! Social media strategy of Korean entertainment industry

text: The Korean Wave (K-wave), or Hallyu, referred as “the phenomenon of Korean pop culture, such as TV dramas, films, pop music, fashion, and online games being widely embraced and shared among the people of Japan, China, Hong Kong, Taiwan, and other Asian countries”. After the drama-oriented craze of the first K-wave, Korean pop music (shortly K-pop) took the integral part of the second K-wave. In addition, with the rapid spread of social media like YouTube and Twitter, K-pop has expanded its fandom outside of Asia to the West. The world-wide success of K-pop contributes to improve the `Korea' image and make a positive impact on Korean economy. It is reported that around 1,000 entertainment agencies are active in Korea, while there exist the “big three” record labels and entertainment agencies: SM Entertainment, YG Entertainment and JYP Entertainment. In this case, we address the world-wide phenomenon of K-pop popularity and the role of social media on recent boom of K-pop. Focusing the major agencies above, we present lessons on how to manage social media strategically: align strategic business model with social media; maximize various social media channels; engage customers with on-and offline promotions; and stimulate audience with exclusive contents.


title: Performance Evaluation of Channel Decoding with Deep Neural Networks

text: With the demand of high data rate and low latency in fifth generation (5G), deep neural network decoder (NND) has become a promising candidate due to its capability of one-shot decoding and parallel computing. In this paper, three types of NND, i.e., multi-layer perceptron (MLP), convolution neural network (CNN) and recurrent neural network (RNN), are proposed with the same parameter magnitude. The performance of these deep neural networks are evaluated through extensive simulation. Numerical results show that RNN has the best decoding performance, yet at the price of the highest computational overhead. Moreover, we find there exists a saturation length for each type of neural network, which is caused by their restricted learning abilities.


title: Impact Analysis of Flow Shaping in Ethernet-AVB/TSN and AFDX from Network Calculus and Simulation Perspective

text: Ethernet-AVB/TSN (Audio Video Bridging/Time-Sensitive Networking) and AFDX (Avionics Full DupleX switched Ethernet) are switched Ethernet technologies, which are both candidates for real-time communication in the context of transportation systems. AFDX implements a fixed priority scheduling strategy with two priority levels. Ethernet-AVB/TSN supports a similar fixed priority scheduling with an additional Credit-Based Shaper (CBS) mechanism. Besides, TSN can support time-triggered scheduling strategy. One direct effect of CBS mechanism is to increase the delay of its flows while decreasing the delay of other priority ones. The former effect can be seen as the shaping restriction and the latter effect can be seen as the shaping benefit from CBS. The goal of this paper is to investigate the impact of CBS on different priority flows, especially on the intermediate priority ones, as well as the effect of CBS bandwidth allocation. It is based on a performance comparison of AVB/TSN and AFDX by simulation in an automotive case study. Furthermore, the shaping benefit is modeled based on integral operation from network calculus perspective. Combing with the analysis of shaping restriction and shaping benefit, some configuration suggestions on the setting of CBS bandwidth are given. Results show that the effect of CBS depends on flow loads and CBS configurations. A larger load of high priority flows in AVB tends to a better performance for the intermediate priority flows when compared with AFDX. Shaping benefit can be explained and calculated according to the changing from the permitted maximum burst.


title: The empathic brain: how, when and why?

text: Recent imaging results suggest that individuals automatically share the emotions of others when exposed to their emotions. We question the assumption of the automaticity and propose a contextual approach, suggesting several modulatory factors that might influence empathic brain responses. Contextual appraisal could occur early in emotional cue evaluation, which then might or might not lead to an empathic brain response, or not until after an empathic brain response is automatically elicited. We propose two major roles for empathy; its epistemological role is to provide information about the future actions of other people, and important environmental properties. Its social role is to serve as the origin of the motivation for cooperative and prosocial behavior, as well as help for effective social communication.


title: Marine animal classification using UMSLI in HBOI optical test facility

text: Environmental monitoring is a critical aspect of marine renewable energy project success. A new system called Unobtrusive Multistatic Serial LiDAR Imager (UMSLI) has been prepared to capture and classify marine life interaction with electrical generation equipment. We present both hardware and software innovations of the UMSLI system. Underwater marine animal imagery has been captured for the first time using red laser diode serial LiDAR, which has advantages over conventional optical cameras in many areas. Moreover, given the scarcity of existing underwater LiDAR data, a shape matching based classification algorithm is proposed which requires few training data. On top of applying shape descriptors, the algorithm also adopts information theoretical learning based affine shape registration, improving point correspondences found by shape descriptors as well as the final similarity measure. Within Florida Atlantic University’s Harbor Branch Oceanographic Institute optical test facility, experimental LiDAR data are collected through the front end of the UMSLI prototype, on which the classification algorithm is validated.


title: “The Internet is a Mask”: High School Students' Suggestions for Preventing Cyberbullying

text:
INTRODUCTION
Interactions through technology have an important impact on today's youth. While some of these interactions are positive, there are concerns regarding students engaging in negative interactions like cyberbullying behaviors and the negative impact these behaviors have on others. The purpose of the current study was to explore participant suggestions for both students and adults for preventing cyberbullying incidents.

METHODS
Forty high school students participated in individual, semi-structured interviews. Participant experiences and perceptions were coded using constant comparative methods to illustrate ways in which students and adults may prevent cyberbullying from occurring within their school and community.

RESULTS
Students reported that peers would benefit from increasing online security, as well as becoming more aware of their cyber-surroundings. Regarding adult-provided prevention services, participants often discussed that there is little adults can do to reduce cyberbullying. Reasons included the difficulties in restricting online behaviors or providing effective consequences. However, some students did discuss the use of in-school curricula while suggesting that adults blame people rather than technology as potential ways to prevent cyberbullying.

CONCLUSION
Findings from the current study indicate some potential ways to improve adult efforts to prevent cyberbullying. These strategies include parent/teacher training in technology and cyberbullying, interventions focused more on student behavior than technology restriction, and helping students increase their online safety and awareness.


title: Brain regions with mirror properties: A meta-analysis of 125 human fMRI studies

text: Mirror neurons in macaque area F5 fire when an animal performs an action, such as a mouth or limb movement, and also when the animal passively observes an identical or similar action performed by another individual. Brain-imaging studies in humans conducted over the last 20 years have repeatedly attempted to reveal analogous brain regions with mirror properties in humans, with broad and often speculative claims about their functional significance across a range of cognitive domains, from language to social cognition. Despite such concerted efforts, the likely neural substrates of these mirror regions have remained controversial, and indeed the very existence of a distinct subcategory of human neurons with mirroring properties has been questioned. Here we used activation likelihood estimation (ALE), to provide a quantitative index of the consistency of patterns of fMRI activity measured in human studies of action observation and action execution. From an initial sample of more than 300 published works, data from 125 papers met our strict inclusion and exclusion criteria. The analysis revealed 14 separate clusters in which activation has been consistently attributed to brain regions with mirror properties, encompassing 9 different Brodmann areas. These clusters were located in areas purported to show mirroring properties in the macaque, such as the inferior parietal lobule, inferior frontal gyrus and the adjacent ventral premotor cortex, but surprisingly also in regions such as the primary visual cortex, cerebellum and parts of the limbic system. Our findings suggest a core network of human brain regions that possess mirror properties associated with action observation and execution, with additional areas recruited during tasks that engage non-motor functions, such as auditory, somatosensory and affective components.


title: Immersion and Emotion: Their Impact on the Sense of Presence

text: The present study is designed to test the role of immersion and media content in the sense of presence. Specifically, we are interested in the affective valence of the virtual environments. This paper describes an experiment that compares three immersive systems (a PC monitor, a rear projected video wall, and a head-mounted display) and two virtual environments, one involving emotional content and the other not. The purpose of the experiment was to test the interactive role of these two media characteristics (form and content). Scores on two self-report presence measurements were compared among six groups of 10 people each. The results suggest that both immersion and affective content have an impact on presence. However, immersion was more relevant for non-emotional environments than for emotional ones.


title: Understanding emotions in others: mirror neuron dysfunction in children with autism spectrum disorders

text: To examine mirror neuron abnormalities in autism, high-functioning children with autism and matched controls underwent fMRI while imitating and observing emotional expressions. Although both groups performed the tasks equally well, children with autism showed no mirror neuron activity in the inferior frontal gyrus (pars opercularis). Notably, activity in this area was inversely related to symptom severity in the social domain, suggesting that a dysfunctional 'mirror neuron system' may underlie the social deficits observed in autism.


title: The successive mean quantization transform

text: This paper presents the successive mean quantization transform (SMQT). The transform reveals the organization or structure of the data and removes properties such as gain and bias. The transform is described and applied in speech processing and image processing. The SMQT is considered as an extra processing step for the mel frequency cepstral coefficients commonly used in speech recognition. In image processing the transform is applied in automatic image enhancement and dynamic range compression.


title: Global asymptotic and robust stability of recurrent neural networks with time delays

text: In this paper, two related problems, global asymptotic stability (GAS) and global robust stability (GRS) of neural networks with time delays, are studied. First, GAS of delayed neural networks is discussed based on Lyapunov method and linear matrix inequality. New criteria are given to ascertain the GAS of delayed neural networks. In the designs and applications of neural networks, it is necessary to consider the deviation effects of bounded perturbations of network parameters. In this case, a delayed neural network must be formulated as a interval neural network model. Several sufficient conditions are derived for the existence, uniqueness, and GRS of equilibria for interval neural networks with time delays by use of a new Lyapunov function and matrix inequality. These results are less restrictive than those given in the earlier references.


title: Evaluating iterative optimization across 1000 datasets

text:
While iterative optimization has become a popular compiler optimization approach, it is based on a premise which has never been truly evaluated: that it is possible to learn the best compiler optimizations across data sets. Up to now, most iterative optimization studies find the best optimizations through repeated runs on the same data set. Only a handful of studies have attempted to exercise iterative optimization on a few tens of data sets.
 In this paper, we truly put iterative compilation to the test for the first time by evaluating its effectiveness across a large number of data sets. We therefore compose KDataSets, a data set suite with 1000 data sets for 32 programs, which we release to the public. We characterize the diversity of KDataSets, and subsequently use it to evaluate iterative optimization.We demonstrate that it is possible to derive a robust iterative optimization strategy across data sets: for all 32 programs, we find that there exists at least one combination of compiler optimizations that achieves 86% or more of the best possible speedup across all data sets using Intel's ICC (83% for GNU's GCC). This optimal combination is program-specific and yields speedups up to 1.71 on ICC and 2.23 on GCC over the highest optimization level (-fast and -O3, respectively). This finding makes the task of optimizing programs across data sets much easier than previously anticipated, and it paves the way for the practical and reliable usage of iterative optimization. Finally, we derive pre-shipping and post-shipping optimization strategies for software vendors.


title: SDN-Guard: DoS Attacks Mitigation in SDN Networks

text: Software Defined Networking (SDN) has recently emerged as a new networking technology offering an unprecedented programmability that allows network operators to dynamically configure and manage their infrastructures. The main idea of SDN is to move the control plane into a central controller that is in charge of taking all routing decisions in the network. However, despite all the advantages offered by this technology, Deny-of-Service (DoS) attacks are considered a major threat to such networks as they can easily overload the controller processing and communication capacity and flood switch CAM tables, resulting in a critical degradation of the overall network performance. To address this issue, we propose in this paper SDN-Guard, a novel scheme able to efficiently protect SDN networks against DoS attacks by dynamically (1) rerouting potential malicious traffic, (2) adjusting flow timeouts and (3) aggregating flow rules. Realistic experiments using Mininet show that the proposed solution succeeds in minimizing by up to 32% the impact of DoS attacks on~the controller performance, switch memory usage and control plane bandwidth and thereby maintaining acceptable network performance during such attacks.


title: Twitter Geolocation Prediction Shared Task of the 2016 Workshop on Noisy User-generated Text

text: This paper describes the shared task for the English Twitter geolocation prediction associated with WNUT 2016. We discuss details of the task settings, data preparation and participant systems. The derived dataset and performance figures from each system provide baselines for future research in this realm.


title: Feasibility of a DC network for commercial facilities

text: This paper analyzes the feasibility of direct current for the supply of offices and commercial facilities. This is done by analyzing a case study, i.e. the supply to a university department. Voltage drop calculations have been carried out for different voltage levels. A back-up system for reliable power supply is designed based on commercially available batteries. Finally, an economic evaluation of AC vs. DC is performed.


title: Sexual arousal: The correspondence of eyes and genitals

text: Men's, more than women's, sexual responses may include a coordination of several physiological indices in order to build their sexual arousal to relevant targets. Here, for the first time, genital arousal and pupil dilation to sexual stimuli were simultaneously assessed. These measures corresponded more strongly with each other, subjective sexual arousal, and self-reported sexual orientation in men than women. Bisexual arousal is more prevalent in women than men. We therefore predicted that if bisexual-identified men show bisexual arousal, the correspondence of their arousal indices would be more female-typical, thus weaker, than for other men. Homosexual women show more male-typical arousal than other women; hence, their correspondence of arousal indices should be stronger than for other women. Findings, albeit weak in effect, supported these predictions. Thus, if sex-specific patterns are reversed within one sex, they might affect more than one aspect of sexual arousal. Because pupillary responses reflected sexual orientation similar to genital responses, they offer a less invasive alternative for the measurement of sexual arousal.


title: Personal Safety is More Important Than Cost of Damage During Robot Failure

text: As robots become more common in everyday life it will be increasingly important to understand how non-experts will view robot failure. In this study, we found that severity of failure seems to be tightly coupled with perceived risk to self rather than risk to the robot's task and object. We initially thought perceived severity would be tied to the cost of damage. Instead, participants placed falling drinking glasses above a laptop when rating the severity of the failure. Related results reinforce the primacy of personal safety over the financial cost of damage and suggest the results were tied to proximity to breaking glass.


title: MusicMixer: computer-aided DJ system based on an automatic song mixing

text: In this paper, we present MusicMixer, a computer-aided DJ system that helps DJs, specifically with song mixing. MusicMixer continuously mixes and plays songs using an automatic music mixing method that employs audio similarity calculations. By calculating similarities between song sections that can be naturally mixed, MusicMixer enables seamless song transitions. Though song mixing is the most fundamental and important factor in DJ performance, it is difficult for untrained people to seamlessly connect songs. MusicMixer realizes automatic song mixing using an audio signal processing approach; therefore, users can perform DJ mixing simply by selecting a song from a list of songs suggested by the system, enabling effective DJ song mixing and lowering entry barriers for the inexperienced. We also propose personalization for song suggestions using a preference memorization function of MusicMixer.


Fast Discovery of Association Rules


title: The SEMAINE Database: Annotated Multimodal Records of Emotionally Colored Conversations between a Person and a Limited Agent

text: SEMAINE has created a large audiovisual database as a part of an iterative approach to building Sensitive Artificial Listener (SAL) agents that can engage a person in a sustained, emotionally colored conversation. Data used to build the agents came from interactions between users and an "operator” simulating a SAL agent, in different configurations: Solid SAL (designed so that operators displayed an appropriate nonverbal behavior) and Semi-automatic SAL (designed so that users' experience approximated interacting with a machine). We then recorded user interactions with the developed system, Automatic SAL, comparing the most communicatively competent version to versions with reduced nonverbal skills. High quality recording was provided by five high-resolution, high-framerate cameras, and four microphones, recorded synchronously. Recordings total 150 participants, for a total of 959 conversations with individual SAL characters, lasting approximately 5 minutes each. Solid SAL recordings are transcribed and extensively annotated: 6-8 raters per clip traced five affective dimensions and 27 associated categories. Other scenarios are labeled on the same pattern, but less fully. Additional information includes FACS annotation on selected extracts, identification of laughs, nods, and shakes, and measures of user engagement with the automatic system. The material is available through a web-accessible database.


title: Analysis and Simulation of Theme Park Queuing System

text: It has been an important issue to improve customers' satisfaction in theme parks for which become a major role of recreation in our daily life. Waiting for rides has been identified as a factor decreasing satisfaction. A previous study indicated that a virtual queuing system can reduce the total waiting time so the customer's satisfaction is improved. The results from a simulation tool Arena show that an index Satisfaction Value (SV) increases when the queuing system is introduced. In this study, a more complex scenario of theme park queuing system (TPQS) is first designed, followed by comparison of a number of combinations of the rides with various waiting time and distribution factors. Analysis is also carried out.


title: Reverse Engineering Flash EEPROM Memories Using Scanning Electron Microscopy

text: In this article, a methodology to extract Flash EEPROM memory contents is presented. Samples are first backside prepared to expose the tunnel oxide of floating gate transistors. Then, a Scanning Electron Microscope (SEM) in the so called Passive Voltage Contrast (PVC) mode allows distinguishing ‘0’ and ‘1’ bit values stored in individual memory cell. Using SEM operator-free acquisition and standard image processing technique we demonstrate the possible automating of such technique over a full memory. The presented fast, efficient and low cost technique is successfully implemented on 0.35μm technology node microcontrollers and on a 0.21μm smart card type integrated circuit. The technique is at least two orders of magnitude faster than state-of-the-art Scanning Probe Microscopy (SPM) methods. Without adequate protection an adversary could obtain the full memory array content within minutes. The technique is a first step for reverse engineering secure embedded systems.


title: Multi-stage beamforming codebook for 60GHz WPAN

text: Beamforming(BF) based on codebook is regarded as an attractive solution to resolve the poor link budget of millimeter-wave 60GHz wireless communication. Because the number of the elements of antenna array in 60GHz increases, the beam patterns generated are more than common BF, and it causes long set-up time during beam patterns searching. In order to reduce the set-up time, three stages protocol, namely the device (DEV) to DEV linking, sector-level searching and beam-level searching has been adopted by the IEEE 802.15.3c as an optional functionality to realize Gbps communication systems. However, it is still a challenge to create codebook of different patterns to support three stages protocol from common codebook of beam pattern. In this paper, we proposes a multi-stage codebook design and the realization architecture to support three stages BF. The multi-stage codebook can create different granularity of beam patterns and realize progressive searching. Simulation results for eight elements uniform linear array (ULA) show that this design can divide the beam searching to three stages searching without increasing the system complexity.


title: Explanation of Two Anomalous Results in Statistical Mediation Analysis.

text: Previous studies of different methods of testing mediation models have consistently found two anomalous results. The first result is elevated Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap tests not found in nonresampling tests or in resampling tests that did not include a bias correction. This is of special concern as the bias-corrected bootstrap is often recommended and used due to its higher statistical power compared with other tests. The second result is statistical power reaching an asymptote far below 1.0 and in some conditions even declining slightly as the size of the relationship between X and M, a, increased. Two computer simulations were conducted to examine these findings in greater detail. Results from the first simulation found that the increased Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap are a function of an interaction between the size of the individual paths making up the mediated effect and the sample size, such that elevated Type I error rates occur when the sample size is small and the effect size of the nonzero path is medium or larger. Results from the second simulation found that stagnation and decreases in statistical power as a function of the effect size of the a path occurred primarily when the path between M and Y, b, was small. Two empirical mediation examples are provided using data from a steroid prevention and health promotion program aimed at high school football players (Athletes Training and Learning to Avoid Steroids; Goldberg et al., 1996), one to illustrate a possible Type I error for the bias-corrected bootstrap test and a second to illustrate a loss in power related to the size of a. Implications of these findings are discussed.


title: The Use Of Edmodo In Creating An Online Learning Community Of Practice For Learning To Teach Science

text: This study aimed to create an online community of practice by creating a virtual classroom in the Edmodo application and ascertain the opinions of pre-service primary teachers about the effects of Edmodo on their learning to teach science and availability of Edmodo. The research used a case study, which is one method of descriptive research. During the implementation process, pre-service primary teachers used Edmodo to share activities they had designed that centred on the scientific concepts taught in primary science education programmes. They also shared their diary entries that outlined their experiences and views after they had practised their activities in a real classroom. 58 pre-service primary teachers participated in the study. The author developed a questionnaire and it included one closed-ended and six open-ended questions; the questionnaire was used as the data collection tool. The pre-service primary teachers used Edmodo for 12 weeks. Descriptive and content analysis methods were used to analyse the data obtained from the study. The results obtained from the data analysis showed that pre-service primary teachers generally had positive views about the use of Edmodo in teacher education programmes. Most pre-service primary teachers stated that Edmodo provides the possibility of sharing knowledge, experiences and views. However, some pre-service teachers stated that Edmodo has some limitations; for example, the fact that it requires the user to have internet access. As a result, it can be said that Edmodo can be used to create an online community of practice in teacher education programmes.


title: QUANTUM COMPUTING : AN INTRODUCTION

text: After some remarks on the fundamental physical nature of information, Bennett and Fredkin's ideas of reversible computation are introduced. This leads on to the suggestions of Benioff and Feynman as to the possibilit y of a new type of essentially ‘quantum computers’ . If we can build such devices, Deutsch showed that ‘quantum paralleli sm’ leads to new algorithms and new complexity classes. This is dramatically ill ustrated by Shor's quantum algorithm for factorization which is polynomial in time in contrast to algorithms for factorization on a classical Turing computer. This discovery has potentiall y important implications for the security of many modern cryptographic systems. The fundamentals of quantum computing are then introduced reversible logic gates, qubits and quantum registers. The key quantum property of ‘ entanglement’ is described, with due homage to Einstein and Bell . As an ill ustration of a quantum program, Grover's database search algorithm is described in some detail . After all this theory, the status of experimental attempts to build a quantum computer is reviewed: it will become evident that we have a long way to go before we can factorize even small numbers. Finally, we end with some thoughts about the process of ‘quantum compilation’ translating a quantum algorithm into actual physical operations on a quantum system and some comments on prospects for future progress.


title: Classification methods for activity recognition

text: Activity recognition is an important subject in different areas of research, like e-health and ubiquitous computing. In this paper we give an overview of recent work in the field of activity recognition from both body mounted sensors and ambient sensors. We discuss some of the differences among approaches and present guidelines for choosing a suitable approach under various circumstances.


title: Biocybernetic system evaluates indices of operator engagement in automated task

text: A biocybernetic system has been developed as a method to evaluate automated flight deck concepts for compatibility with human capabilities. A biocybernetic loop is formed by adjusting the mode of operation of a task set (e.g., manual/automated mix) based on electroencephalographic (EEG) signals reflecting an operator's engagement in the task set. A critical issue for the loop operation is the selection of features of the EEG to provide an index of engagement upon which to base decisions to adjust task mode. Subjects were run in the closed-loop feedback configuration under four candidate and three experimental control definitions of an engagement index. The temporal patterning of system mode switching was observed for both positive and negative feedback of the index. The indices were judged on the basis of their relative strength in exhibiting expected feedback control system phenomena (stable operation under negative feedback and unstable operation under positive feedback). Of the candidate indices evaluated in this study, an index constructed according to the formula, beta power/(alpha power + theta power), reflected task engagement best.


title: AmphiBot I: an amphibious snake-like robot

text: This article presents a project that aims at constructing a biologically inspired amphibious snake-like robot. The robot is designed to be capable of anguilliform swimming like sea-snakes and lampreys in water and lateral undulatory locomotion like a snake on ground. Both the structure and the controller of the robot are inspired by elongate vertebrates. In particular, the locomotion of the robot is controlled by a central pattern generator (a system of coupled oscillators) that produces travelling waves of oscillations as limit cycle behavior. We present the design considerations behind the robot and its controller. Experiments are carried out to identify the types of travelling waves that optimize speed during lateral undulatory locomotion on ground. In particular, the optimal frequency, amplitude and wavelength are thus identified when the robot is crawling on a particular surface.


title: Breakthrough in improving the skin sagging with focusing on the subcutaneous tissue structure , retinacula cutis

text: Skin sagging is one of the most prominent aging signs and a concerning issue for people over middle age. Although many cosmetic products are challenging the reduction of the skin sagging by improving the dermal elasticity, which decreases with age, the effects are insufficient for giving drastic changes to the facial morphology. This study focused on subcutaneous tissue for investigating a skin sagging mechanism. Subcutaneous tissue consists of predominantly adipose tissue with fibrous network structures, called retinacula cutis (RC), which is reported to have a possibility to maintain the soft tissue structure and morphology. This study investigated the effect of subcutaneous tissue physical-property alteration due to RC-deterioration on the skin sagging. For evaluating RC structure noninvasively, the tomographic images of faces were obtained by magnetic resonance (MR) imaging. Subcutaneous tissue network structures observed by MR imaging were indicated to be RC by comparing MR images and the histological specimens of human skin. The density of RC was measured by image analysis. For evaluating sagging degree and physical properties of the skin, sagging scoring and the measurement of elasticity of deeper skin layers were performed. The density of RC was correlated with the elasticity data of deeper skin layers, and the sagging scores tended to increase with decreasing the density. These results suggested that the sparse RC structure gave a decrease in the elasticity of subcutaneous tissue layer, which consequently would be the cause of facial sagging. This study would be a pathfinder for the complete elimination of skin sagging.


title: Predicting defects using network analysis on dependency graphs

text: In software development, resources for quality assurance are limited by time and by cost. In order to allocate resources effectively, managers need to rely on their experience backed by code complexity metrics. But often dependencies exist between various pieces of code over which managers may have little knowledge. These dependencies can be construed as a low level graph of the entire system. In this paper, we propose to use network analysis on these dependency graphs. This allows managers to identify central program units that are more likely to face defects. In our evaluation on Windows Server 2003, we found that the recall for models built from network measures is by 10% points higher than for models built from complexity metrics. In addition, network measures could identify 60% of the binaries that the Windows developers considered as critical-twice as many as identified by complexity metrics.


title: Conditional Generation and Snapshot Learning in Neural Dialogue Systems

text: Recently a variety of LSTM-based conditional language models (LM) have been applied across a range of language generation tasks. In this work we study various model architectures and different ways to represent and aggregate the source information in an endto-end neural dialogue system framework. A method called snapshot learning is also proposed to facilitate learning from supervised sequential signals by applying a companion cross-entropy objective function to the conditioning vector. The experimental and analytical results demonstrate firstly that competition occurs between the conditioning vector and the LM, and the differing architectures provide different trade-offs between the two. Secondly, the discriminative power and transparency of the conditioning vector is key to providing both model interpretability and better performance. Thirdly, snapshot learning leads to consistent performance improvements independent of which architecture is used.


title: Solving optimization problems using black hole algorithm

text: Various meta-heuristic optimization approaches have been recently created and applied in different areas. Many of these approaches are inspired by swarm behaviors in the nature. This paper studies the solving optimization problems using Black Hole Algorithm (BHA) which is a population-based algorithm. Since the performance of this algorithm was not tested in mathematical functions, we have studied this issue using some standard functions. The results of the BHA are compared with the results of GA and PSO algorithms which indicate that the performance of BHA is better than the other two mentioned algorithms.


title: A Wideband Dual-Polarized L-Probe Stacked Patch Antenna Array

text: A 2 times 1 dual-polarized L-probe stacked patch antenna array is presented. It has employed a novel technique to achieve high isolation between the two input ports. The proposed antenna has a 14-dB return loss bandwidth of 19.8%, which is ranged from 0.808 to 0.986 GHz, for both ports. Also, it has an input port isolation of more than 30 dB and an average gain of 10.5 dBi over this bandwidth. Moreover, its radiation patterns in the two principal planes have cross-polarization level of less than -15 dB within the 3-dB beamwidths across the passband. Due to these features, this antenna array is highly suitable for the outdoor base station that is required to cover the operating bandwidths of both CDMA800 and GSM900 mobile communication systems.


title: High-Isolation XX-Polar Antenna

text: A new configuration of the dual-band and dual-polarized antenna is presented, which is fed by aperture coupling for the existing mobile communication systems working over 870-960 MHz (GSM) and 1710-2180 MHz (DCS/UMTS) frequency band. XX-Polar antenna stands for an antenna with dual-band and dual linear slant polarization. In this paper DU band stands for DCS/UMTS band. Measurement results show that the proposed antenna yields good broadside radiation characteristics including symmetric radiation patterns, low cross-polarization level ( <; -14 dB), low backlobe level (F/B >; 20 dB) and high isolation (>; 30 dB) at both bands. The designed antenna has an impedance bandwidth of 20.4% (790-970 MHz) for VSWR <; 1.5 in the lower band and 29.3% for VSWR <; 1.6 (1630-2190 MHz) in the upper band. The measured average gains are about 9.3-10.2 and 8.6-10 dBi in the lower and upper band, respectively. It is also promising for array antenna in various wireless systems.


title: A Compact Dual-Polarized Printed Dipole Antenna With High Isolation for Wideband Base Station Applications

text: A compact dual-polarized printed dipole antenna for wideband base station applications is presented in this communication. The proposed dipole antenna is etched on three assembled substrates. Four horizontal triangular patches are introduced to form two dipoles in two orthogonal polarizations. Two integrated baluns connected with 50 Ω SMA launchers are used to excite the dipole antenna. The proposed dipole antenna achieves a more compact size than many reported wideband printed dipole and magneto-electric dipole antennas. Both simulated and measured results show that the proposed antenna has a port isolation higher than 35 dB over 52% impendence bandwidth (VSWR <; 1.5). Moreover, stable radiation pattern with a peak gain of 7 dBi - 8.6 dBi is obtained within the operating band. The proposed dipole antenna is suitable as an array element and can be used for wideband base station antennas in the next generation IMT-advanced communications.


title: Wideband Dual-Polarized Patch Antenna With Broadband Baluns

text: A pair of novel 180deg broadband microstrip baluns are used to feed a dual-polarized patch antenna. The 180deg broadband balun delivers equal amplitude power division and consistent 180deg (plusmn5deg) phase shifting over a wide bandwidth (>50%). We demonstrate that for a dual-polarized quadruple L-probe square patch antenna, the use of the proposed 180deg broadband balun pair, in place of a conventional 180deg narrowband balun pair, provides improved input port isolation and reduced H-plane cross-polarization levels over a wider frequency range, while maintaining low E-plane cross-polarization levels and stable E- and H-plane co-polarization patterns throughout the impedance passband


title: Design of dual-polarized L-probe patch antenna arrays with high isolation

text: An experimental study of a dual-polarized L-probe patch antenna is presented. The antenna is designed to operate at around 1.8 GHz. A "dual-feed" technique is introduced to achieve high isolation between two input ports. The proposed antenna has an impedance bandwidth of 23.8% (SWR/spl les/2), 15% (SWR/spl les/1.5) and an isolation over 30 dB. In array designs, techniques for improving the isolation between two adjacent elements of an antenna array are also investigated. A two-element array with more than 30 dB isolation is designed and tested.


title: Mining process models with non-free-choice constructs

text: Process mining aims at extracting information from event logs to capture the business process as it is being executed. Process mining is particularly useful in situations where events are recorded but there is no system enforcing people to work in a particular way. Consider for example a hospital where the diagnosis and treatment activities are recorded in the hospital information system, but where health-care professionals determine the “careflow.” Many process mining approaches have been proposed in recent years. However, in spite of many researchers’ persistent efforts, there are still several challenging problems to be solved. In this paper, we focus on mining non-free-choice constructs, i.e., situations where there is a mixture of choice and synchronization. Although most real-life processes exhibit non-free-choice behavior, existing algorithms are unable to adequately deal with such constructs. Using a Petri-net-based representation, we will show that there are two kinds of causal dependencies between tasks, i.e., explicit and implicit ones. We propose an algorithm that is able to deal with both kinds of dependencies. The algorithm has been implemented in the ProM framework and experimental results shows that the algorithm indeed significantly improves existing process mining techniques.


title: EigenTrustp++: Attack resilient trust management

text: This paper argues that trust and reputation models should take into account not only direct experiences (local trust) and experiences from the circle of “friends”, but also be attack resilient by design in the presence of dishonest feedbacks and sparse network connectivity. We first revisit EigenTrust, one of the most popular reputation systems to date, and identify the inherent vulnerabilities of EigenTrust in terms of its local trust vector, its global aggregation of local trust values, and its eigenvector based reputation propagating model. Then we present EigenTrust++, an attack resilient trust management scheme. EigenTrust++ extends the eigenvector based reputation propagating model, the core of EigenTrust, and counters each of vulnerabilities identified with alternative methods that are by design more resilient to dishonest feedbacks and sparse network connectivity under four known attack models. We conduct extensive experimental evaluation on EigenTrust++, and show that EigenTrust++ can significantly outperform EigenTrust in terms of both performance and attack resilience in the presence of dishonest feedbacks and sparse network connectivity against four representative attack models.


title: Expression and regulation of lincRNAs during T cell development and differentiation

text: Although intergenic long noncoding RNAs (lincRNAs) have been linked to gene regulation in various tissues, little is known about lincRNA transcriptomes in the T cell lineages. Here we identified 1,524 lincRNA clusters in 42 T cell samples, from early T cell progenitors to terminally differentiated helper T cell subsets. Our analysis revealed highly dynamic and cell-specific expression patterns for lincRNAs during T cell differentiation. These lincRNAs were located in genomic regions enriched for genes that encode proteins with immunoregulatory functions. Many were bound and regulated by the key transcription factors T-bet, GATA-3, STAT4 and STAT6. We found that the lincRNA LincR-Ccr2-5′AS, together with GATA-3, was an essential component of a regulatory circuit in gene expression specific to the TH2 subset of helper T cells and was important for the migration of TH2 cells.


title: Hierarchical Complex Activity Representation and Recognition Using Topic Model and Classifier Level Fusion

text: Human activity recognition is an important area of ubiquitous computing. Most current researches in activity recognition mainly focus on simple activities, e.g., sitting, running, walking, and standing. Compared with simple activities, complex activities are more complicated with high-level semantics, e.g., working, commuting, and having a meal. This paper presents a hierarchical model to recognize complex activities as mixtures of simple activities and multiple actions. We generate the components of complex activities using a clustering algorithm, represent and recognize complex activities by applying a topic model on these components. It is a data-driven method that can retain effective information for representing and recognizing complex activities. In addition, acceleration and physiological signals are fused in classifier level to ensure the overall performance of complex activity recognition. The results of experiments show that our method has ability to represent and recognize complex activities effectively.


title: 5G security architecture and light weight security authentication

text: The concept of future 5G (the 5th generation of mobile networks) widely spreads in industry, but the related standards are still unclear. The definition of 5G is to provide adequate RF coverage, more bits/Hz and to interconnect all wireless heterogeneous networks to provide seamless, consistent telecom experience to the user. In this paper we have surveyed 5G network architecture and proposed a multi-tier security architecture and a lightweight authentication measure for 5G. The proposed scheme aims at achieving fast authentication and minimizing the packet transmission overhead without compromising the security requirements.


title: Higher-Order Inference for Multi-class Log-Supermodular Models

text: Higher-order models have been shown to be very useful for a plethora of computer vision tasks. However, existing techniques have focused mainly on MAP inference. In this paper, we present the first efficient approach towards approximate Bayesian marginal inference in a general class of high-order, multi-label attractive models, where previous techniques slow down exponentially with the order (clique size). We formalize this task as performing inference in log-supermodular models under partition constraints, and present an efficient variational inference technique. The resulting optimization problems are convex and yield bounds on the partition function. We also obtain a fully factorized approximation to the posterior, which can be used in lieu of the true complicated distribution. We empirically demonstrate the performance of our approach by comparing it to traditional inference methods on a challenging high-fidelity multi-label image segmentation dataset. We obtain state-of-the-art classification accuracy for MAP inference, and substantially improved ROC curves using the approximate marginals.


title: EOMM: An Engagement Optimized Matchmaking Framework

text: Matchmaking connects multiple players to participate in online player-versus-player games. Current matchmaking systems depend on a single core strategy: create fair games at all times. These systems pair similarly skilled players on the assumption that a fair game is best player experience. We will demonstrate, however, that this intuitive assumption sometimes fails and that matchmaking based on fairness is not optimal for engagement. In this paper, we propose an Engagement Optimized Matchmaking (EOMM) framework that maximizes overall player engagement. We prove that equal-skill based matchmaking is a special case of EOMM on a highly simplified assumption that rarely holds in reality. Our simulation on real data from a popular game made by Electronic Arts,Inc. (EA) supports our theoretical results, showing significant improvement in enhancing player engagement compared to existing matchmaking methods.


title: Local information statistics of LBP and HOG for pedestrian detection

text: We present several methods of pedestrian detection in intensity images using different local statistical measures applied to two classes of features extensively used in pedestrian detection: uniform local binary patterns - LBP and a modified version of histogram of oriented gradients - HOG. Our work extracts local binary patterns and magnitude and orientation of the gradient image. Then we divide the image into blocks. Within each block we extract different statistics like: histogram (weighted by the gradient magnitude in the case of HOG), information, entropy and energy of the local binary code. We use Adaboost for training four classifiers and we analyze the classification error of each method on the Daimler benchmark pedestrian dataset.


title: Event Detection in Social Media Detecting

text: The proliferation of social media and user-generated content in the Web has opened new opportunities for detecting and disseminating information quickly. The Twitter stream is one large source of information, but the magnitude of tweets posted and the noisy nature of its content makes the harvesting of knowledge from Twitter very hard. Aiming at overcoming some of the challenges and extract some of the hidden information, this thesis proposes a system for real-time detection of news events from the Twitter stream. The first step of our approach is to let a classifier, based on an Artificial Neural Network and deep learning, detect news relevant tweets from the stream. Next, a novel streaming data clustering algorithm is applied to the detected news tweets to form news events. Finally, the events of highest interest is retrieved based on events’ sizes and rapid growth in tweet frequencies, before the news events are presented and visualized in a web user interface. We evaluate the proposed system on a large, publicly available corpus of annotated news events from Twitter. As part of the evaluation, we compare our approach with a related state-of-the-art solution. Overall, our experiments and user-based evaluation show that our approach on detecting current (real) news events delivers state-of-the-art performance.


title: Predicting statistics of asynchronous SGD parameters for a large-scale distributed deep learning system on GPU supercomputers

text: Many studies have shown that Deep Convolutional Neural Networks (DCNNs) exhibit great accuracies given large training datasets in image recognition tasks. Optimization technique known as asynchronous mini-batch Stochastic Gradient Descent (SGD) is widely used for deep learning because it gives fast training speed and good recognition accuracies, while it may increases generalization error if training parameters are in inappropriate ranges. We propose a performance model of a distributed DCNN training system called SPRINT that uses asynchronous GPU processing based on mini-batch SGD. The model considers the probability distribution of mini-batch size and gradient staleness that are the core parameters of asynchronous SGD training. Our performance model takes DCNN architecture and machine specifications as input parameters, and predicts time to sweep entire dataset, mini-batch size and staleness with 5%, 9% and 19% error in average respectively on several supercomputers with up to thousands of GPUs. Experimental results on two different supercomputers show that our model can steadily choose the fastest machine configuration that nearly meets a target mini-batch size.


title: Analysis on robust H∞ performance and stability for linear systems with interval time-varying state delays via some new augmented Lyapunov-Krasovskii functional

text: In this paper, the problem ofH1 performance and stability analysis for linear systems with interval time-varying delays is considered. First, by constructing a newly augmented Lyapunov–Krasovskii functional which has not been proposed yet, an improvedH1 performance criterion with the framework of linear matrix inequalities (LMIs) is introduced. Next, the result and method are extended to the problem of a delay-dependent stability criterion. Finally, numerical examples are given to show the superiority of proposed method. 2013 Elsevier Inc. All rights reserved.


title: Existence and Stability of Equilibrium of DC Microgrid With Constant Power Loads

text: Constant power loads (CPLs) are often the cause of instability and no equilibrium of dc microgrids. In this study, we analyze the existence and stability of equilibrium of dc microgirds with CPLs and the sufficient conditions for them are provided. To derive the existence of system equilibrium, we transform the problem of quadratic equation solvability into the existence of a fixed point for an increasing fractional mapping. Then, the sufficient condition based on the Tarski fixed-point theorem is derived. It is less conservative compared with the existing results. Moreover, we adopt the small-signal model to predict the system qualitative behavior around equilibrium. The analytic conditions of robust stability are determined by analyzing quadratic eigenvalue. Overall, the obtained conditions provide the references for building reliable dc microgrids. The simulation results verify the correctness of the proposed conditions.


title: A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

text: Particle swarmoptimization (PSO) is a heuristic global optimizationmethod, proposed originally byKennedy and Eberhart in 1995. It is now one of themost commonly used optimization techniques.This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (tomultiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research,mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms.


title: Multi-Scale Patch-Based Image Restoration

text: Many image restoration algorithms in recent years are based on patch processing. The core idea is to decompose the target image into fully overlapping patches, restore each of them separately, and then merge the results by a plain averaging. This concept has been demonstrated to be highly effective, leading often times to the state-of-the-art results in denoising, inpainting, deblurring, segmentation, and other applications. While the above is indeed effective, this approach has one major flaw: the prior is imposed on intermediate (patch) results, rather than on the final outcome, and this is typically manifested by visual artifacts. The expected patch log likelihood (EPLL) method by Zoran and Weiss was conceived for addressing this very problem. Their algorithm imposes the prior on the patches of the final image, which in turn leads to an iterative restoration of diminishing effect. In this paper, we propose to further extend and improve the EPLL by considering a multi-scale prior. Our algorithm imposes the very same prior on different scale patches extracted from the target image. While all the treated patches are of the same size, their footprint in the destination image varies due to subsampling. Our scheme comes to alleviate another shortcoming existing in patch-based restoration algorithms-the fact that a local (patch-based) prior is serving as a model for a global stochastic phenomenon. We motivate the use of the multi-scale EPLL by restricting ourselves to the simple Gaussian case, comparing the aforementioned algorithms and showing a clear advantage to the proposed method. We then demonstrate our algorithm in the context of image denoising, deblurring, and super-resolution, showing an improvement in performance both visually and quantitatively.


title: Virtual machine placement strategies in cloud computing

text: The prominent technology that drives the industry now-a-days is cloud computing. The growth of cloud computing has resulted in the setup of large number of data centers around the world. The data centers consume more power making it source for the carbon dioxide emission and a major contributor to greenhouse effect. This led to the deployment of virtualization. Infrastructure as a Service is one of the important services offered by cloud computing that allows virtualization and hardware to get virtualized by creating many instances of Virtual Machine (VM) on a single Physical Machine (PM) and helps in improving utilization of resources. VM consolidation includes method of choosing the more appropriate algorithm for migration of VM's and placement of VMs to the most suitable host. VM placement is a part of VM migration. The effective placement of VM is aimed to improve performance, resource utilization and reduce the energy consumption in data centers without SLA violation. This paper aims to focus on various VM placement schemes.


title: Boosting Response Aware Model-Based Collaborative Filtering

text: Recommender systems are promising for providing personalized favorite services. Collaborative filtering (CF) technologies, making prediction of users' preference based on users' previous behaviors, have become one of the most successful techniques to build modern recommender systems. Several challenging issues occur in previously proposed CF methods: (1) most CF methods ignore users' response patterns and may yield biased parameter estimation and suboptimal performance; (2) some CF methods adopt heuristic weight settings, which lacks a systematical implementation; and (3) the multinomial mixture models may weaken the computational ability of matrix factorization for generating the data matrix, thus increasing the computational cost of training. To resolve these issues, we incorporate users' response models into the probabilistic matrix factorization (PMF), a popular matrix factorization CF model, to establish the response aware probabilistic matrix factorization (RAPMF) framework. More specifically, we make the assumption on the user response as a Bernoulli distribution which is parameterized by the rating scores for the observed ratings while as a step function for the unobserved ratings. Moreover, we speed up the algorithm by a mini-batch implementation and a crafting scheduling policy. Finally, we design different experimental protocols and conduct systematical empirical evaluation on both synthetic and real-world datasets to demonstrate the merits of the proposed RAPMF and its mini-batch implementation.


title: Interactive painterly stylization of images, videos and 3D animations

text: We introduce a real-time system that converts images, video, or 3D animation sequences to artistic renderings in various painterly styles. The algorithm, which is entirely executed on the GPU, can efficiently process 512 resolution frames containing 60,000 individual strokes at over 30 fps. In order to exploit the parallel nature of GPUs, our algorithm determines the placement of strokes entirely from local pixel neighborhood information. The strokes are rendered as point sprites with textures. Temporal coherence is achieved by treating the brush strokes as particles and moving them based on optical flow. Our system renders high quality results while allowing the user interactive control over many stylistic parameters such as stroke size, texture and density.


title: Energy-traffic tradeoff cooperative offloading for mobile cloud computing

text: This paper presents a quantitative study on the energy-traffic tradeoff problem from the perspective of entire Wireless Local Area Network (WLAN). We propose a novel Energy-Efficient Cooperative Offloading Model (E2COM) for energy-traffic tradeoff, which can ensure the fairness of energy consumption of mobile devices and reduce the computation repetition and eliminate the Internet data traffic redundancy through cooperative execution and sharing computation results. We design an Online Task Scheduling Algorithm (OTS) based on a pricing mechanism and Lyapunov optimization to address the problem without predicting future information on task arrivals, transmission rates and so on. OTS can achieve a desirable tradeoff between the energy consumption and Internet data traffic by appropriately setting the tradeoff coefficient. Simulation results demonstrate that E2COM is more efficient than no offloading and cloud offloading for a variety of typical mobile devices, applications and link qualities in WLAN.


title: Global Hypothesis Generation for 6D Object Pose Estimation

text: This paper addresses the task of estimating the 6D-pose of a known 3D object from a single RGB-D image. Most modern approaches solve this task in three steps: i) compute local features, ii) generate a pool of pose-hypotheses, iii) select and refine a pose from the pool. This work focuses on the second step. While all existing approaches generate the hypotheses pool via local reasoning, e.g. RANSAC or Hough-Voting, we are the first to show that global reasoning is beneficial at this stage. In particular, we formulate a novel fully-connected Conditional Random Field (CRF) that outputs a very small number of pose-hypotheses. Despite the potential functions of the CRF being non-Gaussian, we give a new, efficient two-step optimization procedure, with some guarantees for optimality. We utilize our global hypotheses generation procedure to produce results that exceed state-of-the-art for the challenging Occluded Object Dataset.


title: Decision-Making in a Robotic Architecture for Autonomy

text: This paper presents an overview of the intelligent decision-making capabilities of the CLARAty robotic architecture for autonomy. CLARAty is a two layered architecture where the top Decision Layer contains techniques for autonomously creating a plan of robot commands and the bottom Functional Layer provides standard robot capabilities that interface to system hardware. This paper focuses on the Decision Layer organization and capabilities. Specifically, the Decision Layer provides a framework for utilizing AI planning and executive techniques, which provide onboard, autonomous command generation and replanning for planetary rovers. The Decision Layer also provides a flexible interface to the Functional Layer, which can be tailored based on user preferences and domain features. This architecture is currently being tested on several JPL rovers.


title: Optimal estimation of the mean function based on discretely sampled functional data: Phase transition

text: The problem of estimating the mean of random functions based on discretely sampled data arises naturally in functional data analysis. In this paper, we study optimal estimation of the mean function under both common and independent designs. Minimax rates of convergence are established and easily implementable rateoptimal estimators are introduced. The analysis reveals interesting and different phase transition phenomena in the two cases. Under the common design, the sampling frequency solely determines the optimal rate of convergence when it is relatively small and the sampling frequency has no effect on the optimal rate when it is large. On the other hand, under the independent design, the optimal rate of convergence is determined jointly by the sampling frequency and the number of curves when the sampling frequency is relatively small. When it is large, the sampling frequency has no effect on the optimal rate. Another interesting contrast between the two settings is that smoothing is necessary under the independent design, while, somewhat surprisingly, it is not essential under the common design.


title: CTrigger: exposing atomicity violation bugs from their hiding places

text:
Multicore hardware is making concurrent programs pervasive. Unfortunately, concurrent programs are prone to bugs. Among different types of concurrency bugs, atomicity violation bugs are common and important. Existing techniques to detect atomicity violation bugs suffer from one limitation: requiring bugs to manifest during monitored runs, which is an open problem in concurrent program testing.
 This paper makes two contributions. First, it studies the interleaving characteristics of the common practice in concurrent program testing (i.e., running a program over and over) to understand why atomicity violation bugs are hard to expose. Second, it proposes CTrigger to effectively and efficiently expose atomicity violation bugs in large programs. CTrigger focuses on a special type of interleavings (i.e., unserializable interleavings) that are inherently correlated to atomicity violation bugs, and uses trace analysis to systematically identify (likely) feasible unserializable interleavings with low occurrence-probability. CTrigger then uses minimum execution perturbation to exercise low-probability interleavings and expose difficult-to-catch atomicity violation.
 We evaluate CTrigger with real-world atomicity violation bugs from four sever/desktop applications (Apache, MySQL, Mozilla, and PBZIP2) and three SPLASH2 applications on 8-core machines. CTrigger efficiently exposes the tested bugs within 1--235 seconds, two to four orders of magnitude faster than stress testing. Without CTrigger, some of these bugs do not manifest even after 7 full days of stress testing. In addition, without deterministic replay support, once a bug is exposed, CTrigger can help programmers reliably reproduce it for diagnosis. Our tested bugs are reproduced by CTrigger mostly within 5 seconds, 300 to over 60000 times faster than stress testing.


title: Cross-Domain Visual Matching via Generalized Similarity Measure and Feature Learning

text: Cross-domain visual data matching is one of the fundamental problems in many real-world vision tasks, e.g., matching persons across ID photos and surveillance videos. Conventional approaches to this problem usually involves two steps: i) projecting samples from different domains into a common space, and ii) computing (dis-)similarity in this space based on a certain distance. In this paper, we present a novel pairwise similarity measure that advances existing models by i) expanding traditional linear projections into affine transformations and ii) fusing affine Mahalanobis distance and Cosine similarity by a data-driven combination. Moreover, we unify our similarity measure with feature representation learning via deep convolutional neural networks. Specifically, we incorporate the similarity measure matrix into the deep architecture, enabling an end-to-end way of model optimization. We extensively evaluate our generalized similarity model in several challenging cross-domain matching tasks: person re-identification under different views and face verification over different modalities (i.e., faces from still images and videos, older and younger faces, and sketch and photo portraits). The experimental results demonstrate superior performance of our model over other state-of-the-art methods.


title: Design of Bidirectional DC–DC Resonant Converter for Vehicle-to-Grid (V2G) Applications

text: In this paper, a detailed design procedure is presented for a bidirectional CLLLC-type resonant converter for a battery charging application. This converter is similar to an LLC-type resonant converter with an extra inductor and capacitor in the secondary side. Soft-switching can be ensured in all switches without additional snubber or clamp circuitry. Because of soft-switching in all switches, very high-frequency operation is possible; thus, the size of the magnetics and the filter capacitors can be made small. To reduce the size and cost of the converter, a CLLC-type resonant network is derived from the original CLLLC-type resonant network. First, in this paper, an equivalent model for the bidirectional converter is derived for the steady-state analysis. Then, the design methodology is presented for the CLLLC-type resonant converter. Design of this converter includes determining the transformer turns ratio, design of the magnetizing inductance based on zero-voltage switching condition, design of the resonant inductances and capacitances. Then, the CLLCtype resonant network is derived from the CLLLC-type resonant network. To validate the design procedure, a 3.5-kW converter was designed following the guidelines in the proposed methodology. A prototype was built and tested in the laboratory. Experimental results verified the design procedure presented.


title: Evolutionary Computation Meets Machine Learning: A Survey

text: Evolutionary computation (EC) is a kind of optimization methodology inspired by the mechanisms of biological evolution and behaviors of living organisms. In the literature, the terminology evolutionary algorithms is frequently treated the same as EC. This article focuses on making a survey of researches based on using ML techniques to enhance EC algorithms. In the framework of an ML-technique enhanced-EC algorithm (MLEC), the main idea is that the EC algorithm has stored ample data about the search space, problem features, and population information during the iterative search process, thus the ML technique is helpful in analyzing these data for enhancing the search performance. The paper presents a survey of five categories: ML for population initialization, ML for fitness evaluation and selection, ML for population reproduction and variation, ML for algorithm adaptation, and ML for local search.


title: Obstruction-Free Synchronization: Double-Ended Queues as an Example

text: We introduce obstruction-freedom, a new nonblocking property for shared data structure implementations. This property is strong enough to avoid the problems associated with locks, but it is weaker than previous nonblocking properties—specifically lock-freedom and wait-freedom— allowing greater flexibility in the design of efficient implementations. Obstruction-freedom admits substantially simpler implementations, and we believe that in practice it provides the benefits of wait-free and lock-free implementations. To illustrate the benefits of obstruction-freedom, we present two obstruction-free CAS-based implementations of double-ended queues (deques); the first is implemented on a linear array, the second on a circular array. To our knowledge, all previous nonblocking deque implementations are based on unrealistic assumptions about hardware support for synchronization, have restricted functionality, or have operations that interfere with operations at the opposite end of the deque even when the deque has many elements in it. Our obstruction-free implementations have none of these drawbacks, and thus suggest that it is much easier to design obstruction-free implementations than lock-free and waitfree ones. We also briefly discuss other obstruction-free data structures and operations that we have implemented.


title: Scheduling Multithreaded Computations by Work Stealing

text:
This paper studies the problem of efficiently schedulling fully strict (i.e., well-structured) multithreaded computations on parallel computers. A popular and practical method of scheduling this kind of dynamic MIMD-style computation is “work stealing,” in which processors needing work steal computational threads from other processors. In this paper, we give the first provably good work-stealing scheduler for multithreaded computations with dependencies.
Specifically, our analysis shows that the expected time to execute a fully strict computation on <italic>P</italic> processors using our work-stealing scheduler is <italic>T</italic><subscrpt>1</subscrpt>/<italic>P</italic> + <italic>O</italic>(<italic>T</italic><subscrpt><inline-equation> <f> ∞ </f></inline-equation></subscrpt>, where  <italic>T</italic><subscrpt>1</subscrpt> is the minimum serial execution time of the multithreaded computation and (<italic>T</italic><subscrpt><inline-equation> <f> ∞</f></inline-equation></subscrpt> is the minimum execution time with an infinite number of processors. Moreover, the space required by the execution is at most <italic>S</italic><subscrpt>1</subscrpt><italic>P</italic>, where  <italic>S</italic><subscrpt>1</subscrpt> is the minimum serial space requirement. We also show that the expected total communication of the algorithm is at most <italic>O</italic>(<italic>PT</italic><subscrpt><inline-equation> <f> ∞</f> </inline-equation></subscrpt>( 1 +  <italic>n<subscrpt>d</subscrpt></italic>)<italic>S</italic><subscrpt>max</subscrpt>), where <italic>S</italic><subscrpt>max</subscrpt> is the size of the largest activation record of any thread and  <italic>n<subscrpt>d</subscrpt></italic> is the maximum number of times that any thread synchronizes with its parent. This communication bound justifies the folk wisdom that work-stealing schedulers are more communication efficient than their work-sharing counterparts. All three of these bounds are existentially optimal to within a constant factor.


title: Linearizability: A Correctness Condition for Concurrent Objects

text: A concurrent object is a data object shared by concurrent processes. Linearizability is a correctness condition for concurrent objects that exploits the semantics of abstract data types. It permits a high degree of concurrency, yet it permits programmers to specify and reason about concurrent objects using known techniques from the sequential domain. Linearizability provides the illusion that each operation applied by concurrent processes takes effect instantaneously at some point between its invocation and its response, implying that the meaning of a concurrent object's operations can be given by pre- and post-conditions. This paper defines linearizability, compares it to other correctness conditions, presents and demonstrates a method for proving the correctness of implementations, and shows how to reason about concurrent objects, given they are linearizable.


title: Introduction to Algorithms

text: problems To understand the class of polynomial-time solvable proble ms, we must first have a formal notion of what a “problem” is. We define anbstract problemQ to be a binary relation on a set I of probleminstancesand a setS of problemsolutions. For example, an instance for SHORTEST-PATH is a triple consi sting of a graph and two vertices. A solution is a sequence of vertices in the g raph, with perhaps the empty sequence denoting that no path exists. The problem SHORTEST-PATH itself is the relation that associates each instance of a gra ph and two vertices with a shortest path in the graph that connects the two vertices. S ince shortest paths are not necessarily unique, a given problem instance may have mo r than one solution. This formulation of an abstract problem is more general than is required for our purposes. As we saw above, the theory of NP-completeness res tricts attention to decision problems : those having a yes/no solution. In this case, we can view an abstract decision problem as a function that maps the instan ce setI to the solution set {0, 1}. For example, a decision problem related to SHORTEST-PATH i s the problem PATH that we saw earlier. If i = 〈G,u, v,k〉 is an instance of the decision problem PATH, then PATH(i ) = 1 (yes) if a shortest path fromu to v has at mostk edges, and PATH (i ) = 0 (no) otherwise. Many abstract problems are not decision problems, but rather optimization problems , in which some value must be minimized or maximized. As we saw above, however, it is usual ly a simple matter to recast an optimization problem as a decision problem that is no harder. 1See Hopcroft and Ullman [156] or Lewis and Papadimitriou [20 4] for a thorough treatment of the Turing-machine model. 34.1 Polynomial time 973


title: An Axiomatic Basis for Computer Programming

text: In this paper an attempt is made to explore the logical foundations of computer programming by use of techniques which were first applied in the study of geometry and have later been extended to other branches of mathematics. This involves the elucidation of sets of axioms and rules of inference which can be used in proofs of the properties of computer programs. Examples are given of such axioms and rules, and a formal proof of a simple theorem is displayed. Finally, it is argued that important advantage, both theoretical and practical, may follow from a pursuance of these topics.


title: Production of first and second generation biofuels : A comprehensive review

text: Sustainable economic and industrial growth requires safe, sustainable resources of energy. For the future re-arrangement of a sustainable economy to biological raw materials, completely new approaches in research and development, production, and economy are necessary. The ‘first-generation’ biofuels appear unsustainable because of the potential stress that their production places on food commodities. For organic chemicals and materials these needs to follow a biorefinery model under environmentally sustainable conditions. Where these operate at present, their product range is largely limited to simple materials (i.e. cellulose, ethanol, and biofuels). Second generation biorefineries need to build on the need for sustainable chemical products through modern and proven green chemical technologies such as bioprocessing including pyrolysis, Fisher Tropsch, and other catalytic processes in order to make more complex molecules and materials on which a future sustainable society will be based. This review focus on cost effective technologies and the processes to convert biomass into useful liquid biofuels and bioproducts, with particular focus on some biorefinery concepts based on different feedstocks aiming at the integral utilization of these feedstocks for the production of value added chemicals. 2009 Elsevier Ltd. All rights reserved.


title: Dissolvable films of silk fibroin for ultrathin conformal bio-integrated electronics.

text: Electronics that are capable of intimate, non-invasive integration with the soft, curvilinear surfaces of biological tissues offer important opportunities for diagnosing and treating disease and for improving brain/machine interfaces. This article describes a material strategy for a type of bio-interfaced system that relies on ultrathin electronics supported by bioresorbable substrates of silk fibroin. Mounting such devices on tissue and then allowing the silk to dissolve and resorb initiates a spontaneous, conformal wrapping process driven by capillary forces at the biotic/abiotic interface. Specialized mesh designs and ultrathin forms for the electronics ensure minimal stresses on the tissue and highly conformal coverage, even for complex curvilinear surfaces, as confirmed by experimental and theoretical studies. In vivo, neural mapping experiments on feline animal models illustrate one mode of use for this class of technology. These concepts provide new capabilities for implantable and surgical devices.


title: FURTHER ANALYSIS OF THE HIPPOCAMPAL AMNESIC SYNDROME : 14-YEAR FOLLOW-UP STUDY OF H . M . *

text: -The report attempts to delineatecertain residual learning capacities of H.M., a young man who became amnesic in 1953 following a bilateral removal in the hippocampal zone. In addition to being able to acquire new motor skills (CoRKIN [2]), this patient shows some evidence of perceptual learning. He also achieves some retention of very simple visual and tactual mazes in which the sequence of required turns is short enough to fit into his immediate memory span; even then, the rate of acquisition is extremely slow. These vestigial abilities, which have their occasional parallels in the patient's everyday life, are assessed against the background of his continuing profound amnesia for most on-going events, an amnesia that persists in spite of above-average intelligence and superior performance on many perceptual tasks. THE PRESENT repor t has three aims. In the first place, it describes the persis tent features of a severe amnesic syndrome acquired 14 years ago, fol lowing bi la tera l mesial t empora l lobec tomy (ScoVILLE [28]). Secondly, the repor t a t tempts to give further substance to our previous ly held belief tha t the pa t ien t ' s perceptua l and intel lectual capacit ies remain intact , as mani fes ted by no rma l or super ior pe r tb rmance on a fair ly wide range o f exper imental tasks. Thirdly , we are explor ing the na ture o f the m e m o r y detect in some detai l by trying to discover which learning tasks the pat ient can master , as c o m p a r e d with those on which he always fails. I N T E R V A L H I S T O R Y Since the onset of his amnes ia in 1953, we have twice had the oppor tun i ty o f br inging this pa t ien t under intensive observat ion. In 1962, he spent one week at the Mont rea l Neuro log ica l Inst i tute, and most results o f these and earl ier examinat ions have a l ready been repor ted (CoRK~N [1]; MILNER [16, 18, 19]). Extensive testing was again carr ied out in 1966, dur ing a two-week admiss ion to the Clinical Research Center at M.I .T. Findings ob ta ined dur ing that per iod, supplemented later by visits to the pa t ien t ' s home, form the basis of the present report . * From the Montreal Neurological Institute and from the Psychophysiological Laboratory and Clinical Research Center, M.I.T. "Ilais work was supported in part by the Medical Research Council of Canada, and in part by grants to H.-L. TEtmER from the John A. Hartford Foundation, NASA, and the National Institutes of Health (under MH-05673, and a Clinical Center Grant, FR88). The follow-up study of K.M. was supported by United States Public Health Small Grant M5774A to BRENDA MILNER.


title: Animation of dynamic legged locomotion

text: This paper is about the use of control algorithms to animate dynamic legged locomotion. Control could free the animator from specifying the details of joint and limb motion while producing both physically realistic and natural looking results. We implemented computer animations of a biped robot, a quadruped robot, and a kangaroo. Each creature was modeled as a linked set of rigid bodies with compliant actuators at its joints. Control algorithms regulated the running speed, organized use of the legs, and maintained balance. All motions were generated by numerically integrating equations of motion derived from the physical models. The resulting behavior included running at various speeds, traveling with several gaits (run, trot, bound, gallop, and hop), jumping, and traversing simple paths. Whereas the use of control permitted a variety of physically realistic animated behavior to be generated with limited human intervention, the process of designing the control algorithms was not automated: the algorithms were "tweaked" and adjusted for each new creature.


title: A Wideband Dual Circularly Polarized Full-Corporate Waveguide Array Antenna Fed by Triple-Resonant Cavities

text: A dual circularly polarized (CP) waveguide array antenna is presented for Ka-band wireless communication. A novel triple-resonant cavity is proposed to implement mode conversion and impedance matching in the <inline-formula> <tex-math notation="LaTeX">$2 \times 2$ </tex-math></inline-formula>-element subarray. A ridge waveguide polarizer is integrated to form the left-hand circular polarization (LHCP) and the right-hand circular polarization (RHCP). A flyover-shaped full-corporate feeding network is designed to accommodate the dual polarizations and keep the wideband characteristic for a large-scale array. Subarray spacing is used to optimize the port-to-port isolation and decrease the sidelobe level at some definite angles. Computer numerically controlled machining technology is applied to fabricating a <inline-formula> <tex-math notation="LaTeX">$16 \times 16$ </tex-math></inline-formula>-element prototype. Measured results demonstrate a bandwidth of 16% from 27.6 to 32.4 GHz for the dual polarizations, in terms of good reflection coefficient and axial ratio. A maximum gain of 32.8 dBic is achieved at 28.8 GHz. A total efficiency over 60% is obtained throughout the above band for both LHCP and RHCP ports.


title: Microfinance and Poverty : Evidence Using Panel Data from Bangladesh

text: Microfinance supports mainly informal activities that often have a low return and low market demand. It may therefore be hypothesized that the aggregate poverty impact of microfinance is modest or even nonexistent. If true, the poverty impact of microfinance observed at the participant level represents either income redistribution or short-run income generation from the microfinance intervention. This article examines the effects of microfinance on poverty reduction at both the participant and the aggregate levels using panel data from Bangladesh. The results suggest that access to microfinance contributes to poverty reduction, especially for female participants, and to overall poverty reduction at the village level. Microfinance thus helps not only poor participants but also the local economy.


title: Millimeter-Wave Microstrip Array Antenna with High Efficiency for Automotive Radar Systems

text: Automotive radar systems utilizing the millimeterwave band have been developed 2) since they can detect targets even in bad weather. In the automotive radar systems, linear polarization inclined 45 degrees is utilized in order to avoid mutual radio interference between them. The antenna for the automotive radar systems is required to have high efficiency, which means high gain against for an aperture area determined by the size of a radar sensor, in order to detect the targets at a long distance. In addition, low profile is required not to spoil the appearance of a car. Ease of manufacturing is also one of the significant factors in order to install the automotive radar systems in popular cars. As candidate antennas for the automotive radar systems, a slotted waveguide array antenna and a triplate-type array antenna have been studied. These antennas have low profile and high efficiency 7


title: A Calibration Technique for Bang-Bang ADPLLs Using Jitter Distribution Monitoring

text: This brief presents a built-in self-calibration (BISC) technique for minimization of the total jitter in bang-bang all-digital phase-locked loops (ADPLLs). It is based on the addition of a monitoring phase-frequency detector (PFD) with tunable delay cells for the reference clock and the divider clock and a counter for this PFD output signal. This allows for on-chip binary comparison of the jitter distribution widths at the ADPLL PFD input, when ADPLL filter parameters are altered. Since only a relative comparison is performed, no accurate delay calibration is required. The statistical properties of this comparison of two random distributions are analyzed theoretically, and guidelines for circuit dimensioning are derived. The proposed method is used for BISC by adaption of the ADPLL filter coefficients. This allows for jitter minimization under process, voltage and temperature variations as well as gain and period jitter of the digitally controlled oscillator. The proposed calibration technique is verified by system simulations and measurements of a silicon prototype implementation in 28-nm CMOS technology.


title: Towards Future THz Communications Systems

text: Carrier frequencies beyond 300 GHz, belonging to the so-called THz range, have received attention for considering this frequency band for future multi-gigabit short-range communication systems. This review paper gives an overview of current issues in the emerging field of THz communications targeting to deliver wireless 100 Gbps over short distances. The paper will start by introducing scenarios and applications requiring such high data rates followed by a discussion on the radio channel characteristics. In the 300 GHz frequency band, the path loss is even more significant than at 60 GHz and appropriate measures to mitigate effects in none-line-of-sight (NLOS) cases, caused e. g. by the influence of moving people, are required. Advanced antenna techniques like beam forming or beam switching are a pre-requisite to guarantee seamless service. In order to consider such techniques in the standards development, the propagation channel operating at these mmand sub-mm wave bands in realistic environments must be well understood. Therefore, intensive channel measurement and modeling activities have been done at 300 GHz, which started a couple of years ago at Terahertz Communications Lab (TCL). Due to the short wave length, the influence of surface roughness of typical building materials plays an important role. Hence, the modeling of rough surface scattering has been one of the main areas in these investigations. In this contribution, the main results of the propagation research activities at TCL are summarized. In the last part of the paper, an overview of the state-of-the-art in technology development and successful demonstrations of data transmission will be given together with a report on the status quo of ongoing activities in standardization at IEEE 802.15 IG THz and the regulation of the spectrum beyond 300 GHz.


Election Analysis and Prediction of Election Results with Twitter


title: A soft hand model for physically-based manipulation of virtual objects

text: We developed a new hand model for increasing the robustness of finger-based manipulations of virtual objects. Each phalanx of our hand model consists of a number of deformable soft bodies, which dynamically adapt to the shape of grasped objects based on the applied forces. Stronger forces directly result in larger contact areas, which increase the friction between hand and object as would occur in reality. For a robust collision-based soft body simulation, we extended the lattice-shape matching algorithm to work with adaptive stiffness values, which are dynamically derived from force and velocity thresholds. Our implementation demonstrates that this approach allows very precise and robust grasping, manipulation and releasing of virtual objects and performs in real-time for a variety of complex scenarios. Additionally, laborious tuning of object and friction parameters is not necessary for the wide range of objects that we typically grasp with our hands.


title: Stitching Web Tables for Improving Matching Quality

text: HTML tables on web pages (“web tables”) cover a wide variety of topics. Data from web tables can thus be useful for tasks such as knowledge base completion or ad hoc table extension. Before table data can be used for these tasks, the tables must be matched to the respective knowledge base or base table. The challenges of web table matching are the high heterogeneity and the small size of the tables. Though it is known that the majority of web tables are very small, the gold standards that are used to compare web table matching systems mostly consist of larger tables. In this experimental paper, we evaluate T2K Match, a web table to knowledge base matching system, and COMA, a standard schema matching tool, using a sample of web tables that is more realistic than the gold standards that were previously used. We find that both systems fail to produce correct results for many of the very small tables in the sample. As a remedy, we propose to stitch (combine) the tables from each web site into larger ones and match these enlarged tables to the knowledge base or base table afterwards. For this stitching process, we evaluate different schema matching methods in combination with holistic correspondence refinement. Limiting the stitching procedure to web tables from the same web site decreases the heterogeneity and allows us to stitch tables with very high precision. Our experiments show that applying table stitching before running the actual matching method improves the matching results by 0.38 in F1-measure for T2K Match and by 0.14 for COMA. Also, stitching the tables allows us to reduce the amount of tables in our corpus from 5 million original web tables to as few as 100,000 stitched tables.


title: Efficient adaptive density estimation per image pixel for the task of background subtraction

text: We analyze the computer vision task of pixel-level background subtraction. We present recursive equations that are used to constantly update the parameters of a Gaussian mixture model and to simultaneously select the appropriate number of components for each pixel. We also present a simple non-parametric adaptive density estimation method. The two methods are compared with each other and with some previously proposed algorithms. 2005 Elsevier B.V. All rights reserved.