Query: A Microfluidically Reconfigurable Dual-Band Slot Antenna With a Frequency Coverage Ratio of 3:1

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Continuous Electrowetting of Non-toxic Liquid Metal for RF Applications <=SEP=> Continuous electrowetting (CEW) is demonstrated to be an effective actuation mechanism for reconfigurable radio frequency (RF) devices that use non-toxic liquid-metal tuning elements. Previous research has shown CEW is an efficient means of electrically inducing motion in a liquid-metal slug, but precise control of the slug's position within fluidic channels has not been demonstrated. Here, the precise positioning of liquid-metal slugs is achieved using CEW actuation in conjunction with channels designed to minimize the liquid-metal surface energy at discrete locations. This approach leverages the high surface tension of liquid metal to control its resting position with submillimeter accuracy. The CEW actuation and fluidic channel design were optimized to create reconfigurable RF devices. In addition, solutions for the reliable actuation of a gallium-based, non-toxic liquid-metal alloy (Galinstan) are presented that mitigate the tendency of the alloy to form a surface oxide layer capable of wetting to the channel walls, inhibiting motion. A reconfigurable slot antenna utilizing these techniques to achieve a 15.2% tunable frequency bandwidth is demonstrated.

A Low-Profile Third-Order Bandpass Frequency Selective Surface <=SEP=> We demonstrate a new class of low-profile frequency selective surfaces (FSS) with an overall thickness of lambda/24 and a third-order bandpass frequency response. The proposed FSS is a three layer structure composed of three metal layers, separated by two electrically thin dielectric substrates. Each layer is a two-dimensional periodic structure with sub-wavelength unit cell dimensions and periodicity. The unit cell of the proposed FSS is composed of a combination of resonant and non-resonant elements. It is shown that this arrangement acts as a spatial bandpass filter with a third-order bandpass response. However, unlike traditional third-order bandpass FSSs, which are usually obtained by cascading three identical first-order bandpass FSSs a quarter wavelength apart from one another and have thicknesses in the order of lambda/2 , the proposed structure has an extremely low profile and an overall thickness of about lambda/24 , making it an attractive choice for conformal FSS applications. As a result of the miniaturized unit cells and the extremely small overall thickness of the structure, the proposed FSS has a reduced sensitivity to the angle of incidence of the EM wave compared to traditional third-order frequency selective surfaces. The principles of operation along with guidelines for the design of the proposed FSS are presented in this paper. A prototype of the proposed third-order bandpass FSS is also fabricated and tested using a free space measurement system at C band.

A Coplanar Reconfigurable Folded Slot Antenna Without Bias Network for WLAN Applications <=SEP=> The design of a reconfigurable single folded slot antenna is shown. Metal strips are used in the slot to manipulate the ground size around the slot, which yields to changing the slot's perimeter and thus changing the resonant frequency of the antenna. The design of a single folded slot antenna is first illustrated. Later, the design is modified to be reconfigurable. The resonant frequencies for the reconfigurable design are chosen to be applicable with the WLAN applications. The antenna design, simulation, and measurements are described. The simulated results both for the return loss and maximum gain agree with the measurements. The antenna has similar radiation patterns in both bands. The advantage of this design is that the length of the bias lines does not affect the antenna performance, thus making its design, feeding, and matching an extremely simple and low-cost procedure for antenna designers.

An electromechanical interpretation of electrowetting <=SEP=> Electrowetting on dielectric-coated electrodes involves two independently observable phenomena: (i) the well-known voltage dependence of the apparent contact angle and (ii) a central electromechanical force that can be exploited to move and manipulate small liquid volumes on a substrate. The electromechanical force does not depend upon field-mediated changes of the contact angle; it is operative even if the liquid surface is constrained. Forces on liquid volumes may be determined using capacitance or the Maxwell stress tensor with no reference made to liquid surface profiles. According to this interpretation, a nonlinear mechanism manifesting a voltage threshold is responsible for both contact angle saturation and the observed clamping of the electromechanical force.

Java-based graphical user interface for MRUI, a software package for quantitation of in vivo/medical magnetic resonance spectroscopy signals <=SEP=> This article describes a Java-based graphical user interface for the magnetic resonance user interface (MRUI) quantitation package. This package allows MR spectroscopists to easily perform time-domain analysis of in vivo/medical MR spectroscopy data. We have found that the Java programming language is very well suited for developing highly interactive graphical software applications such as the MRUI system. We also have established that MR quantitation algorithms, programmed in the past in other languages, can easily be embedded into the Java-based MRUI by using the Java native interface (JNI).

Improving Gait Cryptosystem Security Using Gray Code Quantization and Linear Discriminant Analysis <=SEP=> Gait has been considered as an efficient biometric trait for user authentication. Although there are some studies that address the task of securing gait templates/models in gait-based authentication systems, they do not take into account the low discriminability and high variation of gait data which significantly affects the security and practicality of the proposed systems. In this paper, we focus on addressing the aforementioned deficiencies in inertial-sensor based gait cryptosystem. Specifically, we leverage Linear Discrimination Analysis to enhance the discrimination of gait templates, and Gray code quantization to extract high discriminative and stable binary template. The experimental results on 38 different users showed that our proposed method significantly improve the performance and security of the gait cryptosystem. In particular, we achieved the False Acceptant Rate of 6×10−5% (i.e., 1 fail in 16983 trials) and False Rejection Rate of 9.2% with 148-bit security.

Optimal Reconstruction with a Small Number of Views <=SEP=> Estimating positions of world points from features observed in images is a key problem in 3D reconstruction, image mosaicking, simultaneous localization and mapping and structure from motion. We consider a special instance in which there is a dominant ground plane G viewed from a parallel viewing plane S above it. Such instances commonly arise, for example, in aerial photography. Consider a world point g ∈ G and its worst case reconstruction uncertainty ε(g,S) obtained by merging all possible views of g chosen from S. We first show that one can pick two views sp and sq such that the uncertainty ε(g, {sp, sq}) obtained using only these two views is almost as good as (i.e. within a small constant factor of) ε(g,S). Next, we extend the result to the entire ground plane G and show that one can pick a small subset of S ′ ⊆ S (which grows only linearly with the area of G) and still obtain a constant factor approximation, for every point g ∈ G, to the minimum worst case estimate obtained by merging all views in S. Our results provide a view selection mechanism with provable performance guarantees which can drastically increase the speed of scene reconstruction algorithms. In addition to theoretical results, we demonstrate their effectiveness in an application where aerial imagery is used for monitoring farms and orchards.

Viewpoint - Why "open source" misses the point of free software <=SEP=> Decoding the important differences in terminology, underlying philosophy, and value systems between two similar categories of software.

Fast Ego-motion Estimation with Multi-rate Fusion of Inertial and Vision <=SEP=> This paper presents a tracking system for ego-motion estimation which fuses vision and inertial measurements using EKF and UKF (Extended and Unscented Kalman Filters), where a comparison of their performance has been done. It also considers the multi-rate nature of the sensors: inertial sensing is sampled at a fast sampling frequency while the sampling frequency of vision is lower. the proposed approach uses a constant linear acceleration model and constant angular velocity model based on quaternions, which yields a non-linear model for states and a linear model in measurement equations. Results show that a significant improvement is obtained on the estimation when fusing both measurements with respect to just vision or just inertial measurements. It is also shown that the proposed system can estimate fast-motions even when vision system fails. Moreover, a study of the influence of the noise covariance is also performed, which aims to select their appropriate values at the tuning process. The setup is an end-effector mounted camera, which allow us to pre-define basic rotational and translational motions for validating results. KEY WORDS—vision and inertial, multi-rate systems, sensor fusion, tracking

Weaknesses in the Key Scheduling Algorithm of RC4 <=SEP=> In this paper we present several weaknesses in the key scheduling algorithm of RC4, and describe their cryptanalytic signi cance. We identify a large number of weak keys, in which knowledge of a small number of key bits su ces to determine many state and output bits with non-negligible probability. We use these weak keys to construct new distinguishers for RC4, and to mount related key attacks with practical complexities. Finally, we show that RC4 is completely insecure in a common mode of operation which is used in the widely deployed Wired Equivalent Privacy protocol (WEP, which is part of the 802.11 standard), in which a xed secret key is concatenated with known IV modi ers in order to encrypt di erent messages. Our new passive ciphertext-only attack on this mode can recover an arbitrarily long key in a negligible amount of time which grows only linearly with its size, both for 24 and 128 bit IV modi ers.

A gene-coexpression network for global discovery of conserved genetic modules. <=SEP=> To elucidate gene function on a global scale, we identified pairs of genes that are coexpressed over 3182 DNA microarrays from humans, flies, worms, and yeast. We found 22,163 such coexpression relationships, each of which has been conserved across evolution. This conservation implies that the coexpression of these gene pairs confers a selective advantage and therefore that these genes are functionally related. Many of these relationships provide strong evidence for the involvement of new genes in core biological functions such as the cell cycle, secretion, and protein expression. We experimentally confirmed the predictions implied by some of these links and identified cell proliferation functions for several genes. By assembling these links into a gene-coexpression network, we found several components that were animal-specific as well as interrelationships between newly evolved and ancient modules.

Conceptual modeling and development of an intelligent agent-assisted decision support system for anti-money laundering <=SEP=> Criminal elements in today’s technology-driven society are using every means available at their disposal to launder the proceeds from their illegal activities. In response, international anti-money laundering (AML) efforts are being made. The events of September 11, 2001, highlighted the need for more sophisticated AML and anti-terrorist financing programs across the industry and nation. In the wake of this, regulators are focusing on the role that technology can play in compliance with laws and ultimately in law enforcement. Banks will have to employ or enhance AML tools and technology to satisfy rising regulatory expectations. While many AML solutions have been in place for some time within the banks, they are faced with the challenge of adapting to the ever-changing risks and methods related to money laundering. In order to provide support for AML decisions, we have formulated an AML conceptual model by following Simon [Simon, H. A. (1977). The new science of management decision. Englewood Cliffs, NJ: Prentice-Hall] decision-making process model. Based on this model, a novel and open multi-agent AML system prototype has been designed and developed. Intelligent agents with their properties of autonomy, reactivity, and proactivity are well suited for dynamic, ill-structured, and complex ML prevention controls. The advanced architecture is able to provide more adaptive, intelligent, and flexible solution for AML. This paper is the first attempt at intelligent agent financial application in the AML domain, with a decision-making/problem-solving process model, an innovative agent-based architecture, and a prototype system. 2007 Elsevier Ltd. All rights reserved.

Latent Skill Embedding for Personalized Lesson Sequence Recommendation <=SEP=> Students in online courses generate large amounts of data that can be used to personalize the learning process and improve quality of education. In this paper, we present the Latent Skill Embedding (LSE), a probabilistic model of students and educational content that can be used to recommend personalized sequences of lessons with the goal of helping students prepare for specific assessments. Akin to collaborative filtering for recommender systems, the algorithm does not require students or content to be described by features, but it learns a representation using access traces. We formulate this problem as a regularized maximum-likelihood embedding of students, lessons, and assessments from historical student-content interactions. An empirical evaluation on large-scale data from Knewton, an adaptive learning technology company, shows that this approach predicts assessment results competitively with benchmark models and is able to discriminate between lesson sequences that lead to mastery and failure.

A deep CNN based multi-class classification of Alzheimer's disease using MRI <=SEP=> In the recent years, deep learning has gained huge fame in solving problems from various fields including medical image analysis. This work proposes a deep convolutional neural network based pipeline for the diagnosis of Alzheimer's disease and its stages using magnetic resonance imaging (MRI) scans. Alzheimer's disease causes permanent damage to the brain cells associated with memory and thinking skills. The diagnosis of Alzheimer's in elderly people is quite difficult and requires a highly discriminative feature representation for classification due to similar brain patterns and pixel intensities. Deep learning techniques are capable of learning such representations from data. In this paper, a 4-way classifier is implemented to classify Alzheimer's (AD), mild cognitive impairment (MCI), late mild cognitive impairment (LMCI) and healthy persons. Experiments are performed using ADNI dataset on a high performance graphical processing unit based system and new state-of-the-art results are obtained for multiclass classification of the disease. The proposed technique results in a prediction accuracy of 98.8%, which is a noticeable increase in accuracy as compared to the previous studies and clearly reveals the effectiveness of the proposed method.

Handwriting development, competency, and intervention. <=SEP=> Failure to attain handwriting competency during the school-age years often has far-reaching negative effects on both academic success and self-esteem. This complex occupational task has many underlying component skills that may interfere with handwriting performance. Fine motor control, bilateral and visual-motor integration, motor planning, in-hand manipulation, proprioception, visual perception, sustained attention, and sensory awareness of the fingers are some of the component skills identified. Poor handwriting may be related to intrinsic factors, which refer to the child's actual handwriting capabilities, or extrinsic factors which are related to environmental or biomechanical components, or both. It is important that handwriting performance be evaluated using a valid, reliable, standardized tool combined with informal classroom observation and teacher consultation. Studies of handwriting remediation suggest that intervention is effective. There is evidence to indicate that handwriting difficulties do not resolve without intervention and affect between 10 and 30% of school-aged children. Despite the widespread use of computers, legible handwriting remains an important life skill that deserves greater attention from educators and health practitioners.

Bluetooth based home automation system <=SEP=> The past decade has seen significant advancement in the field of consumer electronics. Various ‘intelligent’ appliances such as cellular phones, air-conditioners, home security devices, home theatres, etc. are set to realize the concept of a smart home. They have given rise to a Personal Area Network in home environment, where all these appliances can be interconnected and monitored using a single controller. Busy families and individuals with physical limitation represent an attractive market for home automation and networking. A wireless home network that does not incur additional costs of wiring would be desirable. Bluetooth technology, which has emerged in late 1990s, is an ideal solution for this purpose. This paper describes an application of Bluetooth technology in home automation and networking environment. It proposes a network, which contains a remote, mobile host controller and several client modules (home appliances). The client modules communicate with the host controller through Bluetooth devices. q 2002 Elsevier Science B.V. All rights reserved.

The formation and function of plant cuticles. <=SEP=> The plant cuticle is an extracellular hydrophobic layer that covers the aerial epidermis of all land plants, providing protection against desiccation and external environmental stresses. The past decade has seen considerable progress in assembling models for the biosynthesis of its two major components, the polymer cutin and cuticular waxes. Most recently, two breakthroughs in the long-sought molecular bases of alkane formation and polyester synthesis have allowed construction of nearly complete biosynthetic pathways for both waxes and cutin. Concurrently, a complex regulatory network controlling the synthesis of the cuticle is emerging. It has also become clear that the physiological role of the cuticle extends well beyond its primary function as a transpiration barrier, playing important roles in processes ranging from development to interaction with microbes. Here, we review recent progress in the biochemistry and molecular biology of cuticle synthesis and function and highlight some of the major questions that will drive future research in this field.

Towards a psychographic user model from mobile phone usage <=SEP=> Knowing the users' personality can be a strategic advantage for the design of adaptive and personalized user interfaces. In this paper, we present the results of a first trial conducted with the aim of inferring people's personality traits based on their mobile phone call behavior. Initial findings corroborate the efficacy of using call detail records (CDR) and Social Network Analysis (SNA) of the call graph to infer the Big Five personality factors. On-going work includes a large-scale study that shall refine the accuracy of the models with a reduced margin of error.

Integration of Modular Process Units Into Process Control Systems <=SEP=> The modularization of process plants is regarded as a promising approach to cope with upcoming requirements in the process industry regarding flexibility. Within the Decentralized Intelligence for Modular Assets Project, a concept has been developed to overcome current deficiencies in implementing modular plants and especially their automation. On one hand, the approach considers a clear separation of engineering efforts into plant-independent module engineering and plant-specific integration engineering. On the other hand, the concept provides a method for the fast integration of a module's automation system into a higher level process control system. To do so, each module provides its process functionality in encapsulated services. The core of the integration method is a file-based description of the module including its services, operating screens, and communication variables. The so-called “module-type package” is currently under standardization by different organizations. This paper presents the general approach as well as current results of the standardization efforts. Furthermore, the results are executed on an application demonstrator to allow a practical assessment. Thus, module engineering and integration engineering, as well as corresponding software tools can be demonstrated.

Cryptanalytic Attacks on MIFARE Classic Protocol <=SEP=> MIFARE Classic is the most widely used contactless smart card in the world. It implements a proprietary symmetric-key mutual authentication protocol with a dedicated reader and a proprietary stream cipher algorithm known as CRYPTO1, both of which have been reverse engineered. The existing attacks in various scenarios proposed in the literature demonstrate that MIFARE Classic does not offer the desired 48-bit security level. The most practical scenario is the card-only scenario where a fake, emulated reader has a wireless access to a genuine card in the on-line stage of the attack. The most effective known attack in the card-only scenario is a differential attack, which is claimed to require about 10 seconds of average on-line time in order to reconstruct the secret key from the card. This paper presents a critical comprehensive survey of currently known attacks on MIFARE Classic, puts them into the right perspective in light of the prior art in cryptanalysis, and proposes a number of improvements. It is shown that the differential attack is incorrectly analyzed and is optimized accordingly. A new attack of a similar, differential type is also introduced. In comparison with the optimized differential attack, it has a higher success probability of about 0.906 and a more than halved on-line time of about 1.8 seconds.

Using ultra-low parasitic hybrid packaging method to reduce high frequency EMI noise for SiC power module <=SEP=> In order to reduce high frequency electromagnetic interference (EMI) noise for SiC devices, this paper presents a hybrid structure SiC power module with low parasitic inductance and low ground capacitance that can suppress EMI efficiently. To certify the improvement on EMI, two buck converters, using the same power loop and gate drive, are built for experiment. Two converters use the proposed power module and TO-247 packaged commercial devices respectively. The experimental results show that low parasitic inductance can increase switching speed considerably while have only slight impact on EMI. And low parasitic ground capacitance can decrease the ground current effectively. Considering soft switching can also reduce EMI, this paper further compares EMI noise of two converters under two conditions: continuous current modulation (CCM) and triangle current modulation (TCM). The result shows that the proposed power module can suppress the common mode (CM) noise effectively at both situations. Furthermore, this paper verifies the noise mode transformation from differential mode (DM) EMI to CM EMI.

NEXMark – A Benchmark for Queries over Data Streams DRAFT <=SEP=> A lot of research has focused recently on executing queries over data streams. This recent attention is due to the large number of data streams available, and the desire to get answers to queries on these streams in real time. There are many sources of data streams: environmental sensor networks, network routing traces, financial transactions and cell phone call records. Many systems are currently under development to execute queries over data streams [BW01, CCC02, MF02, NDM00, SH98]. Further, many ideas have been presented to improve the execution of queries over data streams [ABB02, MSHR02, TMSF02]. It is important to be able to measure the effectiveness of this work. To this end, we present the Niagara Extension to XMark benchmark (NEXMark). This is a work in progress. We are circulating it now for feedback. We have three goals: To define a benchmark, to provide stream generators, and to define metrics for measuring queries over continuous data streams. The XMark benchmark [SWK01] is designed to measure the performance of XML repositories. The benchmark provides a data generator that models the state of an auction in XML format, and various queries over the generated data. An abbreviated schema for XMark is shown in Figure 1.

Exploration and apprenticeship learning in reinforcement learning <=SEP=> We consider reinforcement learning in systems with unknown dynamics. Algorithms such as E3 (Kearns and Singh, 2002) learn near-optimal policies by using "exploration policies" to drive the system towards poorly modeled states, so as to encourage exploration. But this makes these algorithms impractical for many systems; for example, on an autonomous helicopter, overly aggressive exploration may well result in a crash. In this paper, we consider the apprenticeship learning setting in which a teacher demonstration of the task is available. We show that, given the initial demonstration, no explicit exploration is necessary, and we can attain near-optimal performance (compared to the teacher) simply by repeatedly executing "exploitation policies" that try to maximize rewards. In finite-state MDPs, our algorithm scales polynomially in the number of states; in continuous-state linear dynamical systems, it scales polynomially in the dimension of the state. These results are proved using a martingale construction over relative losses.

A wearable 12-lead ECG acquisition system with fabric electrodes <=SEP=> Continuous electrocardiogram (ECG) monitoring is significant for prevention of heart disease and is becoming an important part of personal and family health care. In most of the existing wearable solutions, conventional metal sensors and corresponding chips are simply integrated into clothes and usually could only collect few leads of ECG signals that could not provide enough information for diagnosis of cardiac diseases such as arrhythmia and myocardial ischemia. In this study, a wearable 12-lead ECG acquisition system with fabric electrodes was developed and could simultaneously process 12 leads of ECG signals. By integrating the fabric electrodes into a T-shirt, the wearable system would provide a comfortable and convenient user interface for ECG recording. For comparison, the proposed fabric electrode and the gelled traditional metal electrodes were used to collect ECG signals on a subject, respectively. The approximate entropy (ApEn) of ECG signals from both types of electrodes were calculated. The experimental results show that the fabric electrodes could achieve similar performance as the gelled metal electrodes. This preliminary work has demonstrated that the developed ECG system with fabric electrodes could be utilized for wearable health management and telemedicine applications.

Local Rademacher Complexity Bounds based on Covering Numbers <=SEP=> This paper provides a general result on controlling local Rademacher complexities, which captures in an elegant form to relate the complexities with constraint on the expected norm to the corresponding ones with constraint on the empirical norm. This result is convenient to apply in real applications and could yield refined local Rademacher complexity bounds for function classes satisfying general entropy conditions. We demonstrate the power of our complexity bounds by applying them to derive effective generalization error bounds.

Social constructivist perspectives on teaching and learning. <=SEP=> Social constructivist perspectives focus on the interdependence of social and individual processes in the co-construction of knowledge. After the impetus for understanding the influence of social and cultural factors on cognition is reviewed, mechanisms hypothesized to account for learning from this perspective are identified, drawing from Piagetian and Vygotskian accounts. The empirical research reviewed illustrates (a) the application of institutional analyses to investigate schooling as a cultural process, (b) the application of interpersonal analyses to examine how interactions promote cognition and learning, and (c) discursive analyses examining and manipulating the patterns and opportunities in instructional conversation. The review concludes with a discussion of the application of this perspective to selected contemporary issues, including: acquiring expertise across domains, assessment, educational equity, and educational reform.

Movie recommendation system using clustering and pattern recognition network <=SEP=> As the world is going global, people have a lot to choose from when it comes to movies. There are different genres, cultures and languages to choose from in the world of movies. This arises the issue of recommending movies to users in automated systems. So far, a decent number of works has been done in this field. But there is always room for renovation. This paper proposed a machine learning approach to recommend movies to users using K-means clustering algorithm to separate similar users and creating a neural network for each cluster.

Role and users' approach to social networking sites (SNSs): a study of universities of North India <=SEP=> Purpose – The purpose of this paper is to evaluate and assess the awareness and extent of the use of social networking sites (SNSs) by the students and research scholars of universities of North India. Design/methodology/approach – The study is a questionnaire-based survey on the usage of SNSs among the students and research scholars of the universities of North India. The data of the study were collected through questionnaires, which were personally distributed to the identified population, i.e. undergraduate students, postgraduate students and research scholars, by the authors. The survey was based on a sample of 610 questionnaires; of which, 486 questionnaires were received, having a response rate of 79.67 per cent. Findings – The study showed that all the respondents were found to be aware of and making use of such applications in their academic affairs. It was revealed from the study that Facebook is the most popular SNS by all categories of respondents. To determine the purpose of SNSs, it emerged that SNSs are mostly used for entertainment and communication. The study also found that the majority of respondents were aware about the security aspects of SNSs. It signifies that excessive time consumption and fear of misusing personal information were the major hurdles in the way of accessing SNSs. Research limitations/implications – The study covers the students and research scholars of select universities of North India. It also signifies the use of SNSs in their research and academic environment. Originality/value – The paper provides reliable and authentic data. The study is worth, justifiable and enlightens the salient findings on the topic, which will be very useful for researchers in this area.

A Tour of Reinforcement Learning: The View from Continuous Control <=SEP=> This manuscript surveys reinforcement learning from the perspective of optimization and control with a focus on continuous control applications. It surveys the general formulation, terminology, and typical experimental implementations of reinforcement learning and reviews competing solution paradigms. In order to compare the relative merits of various techniques, this survey presents a case study of the Linear Quadratic Regulator (LQR) with unknown dynamics, perhaps the simplest and best-studied problem in optimal control. The manuscript describes how merging techniques from learning theory and control can provide non-asymptotic characterizations of LQR performance and shows that these characterizations tend to match experimental behavior. In turn, when revisiting more complex applications, many of the observed phenomena in LQR persist. In particular, theory and experiment demonstrate the role and importance of models and the cost of generality in reinforcement learning algorithms. This survey concludes with a discussion of some of the challenges in designing learning systems that safely and reliably interact with complex and uncertain environments and how tools from reinforcement learning and control might be combined to approach these challenges.