title: Bayesian Modeling with Gaussian Processes using the GPstuff Toolbox

abstract: Gaussian processes (GP) are powerful tools for probabilistic modeling purposes. They can be used to define prior distributions over latent functions in hierarchical Bayesian models. The prior over functions is defined implicitly by the mean and covariance function, which determine the smoothness and variability of the function. The inference can then be conducted directly in the function space by evaluating or approximating the posterior process. Despite their attractive theoretical properties GPs provide practical challenges in their implementation. GPstuff is a versatile collection of computational tools for GP models compatible with Linux and Windows MATLAB and Octave. It includes, among others, various inference methods, sparse approximations and tools for model assessment. In this work, we review these tools and demonstrate the use of GPstuff in several models.


title: Sarcastic or Not: Word Embeddings to Predict the Literal or Sarcastic Meaning of Words

abstract: Sarcasm is generally characterized as a figure of speech that involves the substitution of a literal by a figurative meaning, which is usually the opposite of the original literal meaning. We re-frame the sarcasm detection task as a type of word sense disambiguation problem, where the sense of a word is either literal or sarcastic. We call this the Literal/Sarcastic Sense Disambiguation (LSSD) task. We address two issues: 1) how to collect a set of target words that can have either literal or sarcastic meanings depending on context; and 2) given an utterance and a target word, how to automatically detect whether the target word is used in the literal or the sarcastic sense. For the latter, we investigate several distributional semantics methods and show that a Support Vector Machines (SVM) classifier with a modified kernel using word embeddings achieves a 7-10% F1 improvement over a strong lexical baseline.


title: Instance Weighting for Domain Adaptation in NLP

abstract: Domain adaptation is an important problem in natural language processing (NLP) due to the lack of labeled data in novel domains. In this paper, we study the domain adaptation problem from the instance weighting perspective. We formally analyze and characterize the domain adaptation problem from a distributional view, and show that there are two distinct needs for adaptation, corresponding to the different distributions of instances and classification functions in the source and the target domains. We then propose a general instance weighting framework for domain adaptation. Our empirical results on three NLP tasks show that incorporating and exploiting more information from the target domain through instance weighting is effective.


title: Traffic Coordination at Road Intersections: Autonomous Decision-Making Algorithms Using Model-Based Heuristics

abstract: This article focuses on the traffic coordination problem at traffic intersections. We present a decentralized coordination approach, combining optimal control with model-based heuristics. We show how model-based heuristics can lead to low-complexity solutions that are suitable for a fast online implementation, and analyze its properties in terms of efficiency, feasibility and optimality. Finally, simulation results for different scenarios are also presented.


title: EvalVid - A Framework for Video Transmission and Quality Evaluation

abstract: With EvalVid we present a complete framework and tool-set for evaluation of the quality of video transmitted over a real or simulated communication network. Besides measuring QoS parameters of the underlying network, like loss rates, delays, and jitter, we support also a subjective video quality evaluation of the received video based on the frame-by-frame PSNR calculation. The tool-set has a modular construction, making it possible to exchange both the network and the codec. We present here its application for MPEG-4 as example. EvalVid is targeted for researchers who want to evaluate their network designs or setups in terms of user perceived video quality. The tool-set is publicly available [11].


title: The Effect of Movie Subtitling on Incidental Vocabulary Learning among EFL Learners

abstract: This study investigated the effect of subtitling modality on incidental vocabulary learning among Iranian EFL learners. To this end, 90 freshmen students studying English Translation at BA level in Abadan Azad University were selected after taking a proficiency test to ensure their homogeneity. Participants were randomly assigned to three experimental groups, namely: Bimodal group (A), Standard group (B) and Reversed group(C). They watched eight video clips selected from three animated movies with different modes of subtitles: A) Bimodal subtitles, B) Standard subtitles and C) Reversed subtitles. Research instrumentation included a pre-test and a post-test following an experimental design. Participants took a pre-test containing new words selected from the clips. After eight treatment sessions, the post-test was administered. Data were analyzed descriptively and inferentially. To arrive at any difference between the three different modes of subtitles, the researcher conducted one-way ANOVA. The results obtained from the tests showed that participants in reversed subtitling group performed significantly different and learned more new vocabulary items. Standard subtitling was the second type of subtitling which revealed to be more effective than bimodal subtitling.


title: Facial Wrinkles Detection Techniques and its Application

abstract: Face recognition is process of identifying or verifying individual person by their face. One of the most important sources of the information is human face which can be intended for personal verification and identification of individual person. Wrinkles play an essential role in age estimation. They have been commonly used in applications, such as face age estimation, facial retouching and facial expression recognition. Facial wrinkles present 3D form of skin and appear as skillful discontinuities or cracks in surrounding skin texture. There are different techniques present for facial wrinkles detection. This paper presents the study and review of various techniques used in wrinkle detection. This paper is motivated by need of fast and robust algorithm for detection and classification of human age and


title: Real-Time Ray Tracing with CUDA

abstract: The graphics processors (GPUs) have recently emerged as a low-cost alternative for parallel programming. Since modern GPUs have great computational power as well as high memory bandwidth, running ray tracing on them has been an active field of research in computer graphics in recent years. Furthermore, the introduction of CUDA, a novel GPGPU architecture, has removed several limitations that the traditional GPU-based ray tracing suffered. In this paper, an implementation of high per formance CUDA ray tracing is demonstrated. We focus on the perfor mance and show how our design choices in various optimization lead to an implementation that outperforms the previous works. For reasonably complex scenes with simple shading, our implementation achieves the performance of 30 to 43 million traced rays per second. Our implementation also includes the effects of recursive specular reflection and refraction, which were less discussed in previous GPU-based ray tracing works.


Daily Physical Activity Improves Vascular Function and Motor Skills in Children


title: STUDY OF BACTERIAL CONTAMINANTS IN LOCAL AS WELL AS BRANDED LIPSTICKS BEFORE AND AFTER CONSUMER USE

abstract: Lipstick, is a face - care cosmetic that commands a unique market as it is one of the most affordable cosmetic products available with as many as 80% of women using it regularly. Lipsticks need not be sterile and may contain low l evels of microbial load during or prior to use. Lipsticks are often inadvertently consumed by the users and hence it is imperative that the health regulators have a microscopic look at the ingredients as well as the microbial flora (if any) in the lipstick s. This study was performed to determine the bacterial load in terms of colony forming units in addition to the type and concentration of a paraben preservatives used in lipsticks. Twelve brands of lipsticks were selected for the study of which , four were taken from the Indian market (unused samples), four (Multinational brands) used for over a year and four (multinational brands) used for over two years. The bacteria in these samples were isolated and identified by 16s rDNA sequencing and the amount of pre servative s quantified by HPLC (High Performance Liquid Chromatography). Our results indicated that all the products were contaminated to varying degrees depending on their usage. Besides the skin normal flora Staphylococci, gram negative organisms of Pseud omonas, Proteus , Morganella , Providencia species also featured prominent among the isolates. The HPLC data obtained indicated the presence of parabens at a concentration of 2740 ppm and 6960 ppm which is higher than 100 - 3000 ppm of parabens as stated by the US - FDA. The work cautions the end user about the qua lity of lipsticks a widely used cosmetic product.


University of Stirling The Late Acceptance Hill-Climbing Heuristic


title: Establishing a classification system and criteria for veneer preparations.

abstract: The concept of no- or minimal-preparation veneers is more than 25 years old, yet there is no classification system categorizing the extent of preparation for different veneer treatments. The lack of veneer preparation classifications creates misunderstanding and miscommunication with patients and within the dental profession. Such a system could be indicated in various clinical scenarios and would benefit dentists and patients, providing a guide for conservatively preparing and placing veneers. A classification system is proposed to divide preparation and veneering into reduction--referred to as space requirement, working thickness, or material room--volume of enamel remaining, and percentage of dentin exposed. Using this type of metric provides an accurate measurement system to quantify tooth structure removal, with preferably no reduction, on a case-by-case basis, dissolve uncertainty, and aid with multiple aspects of treatment planning and communication.


title: Behavioral activation and inhibition systems and the severity and course of depression

abstract: Theorists have proposed that depression is associated with abnormalities in the behavioral activation (BAS) and behavioral inhibition (BIS) systems. In particular, depressed individuals are hypothesized to exhibit deficient BAS and overactive BIS functioning. Self-reported levels of BAS and BIS were examined in 62 depressed participants and 27 nondepressed controls. Clinical functioning was assessed at intake and at 8-month follow-up. Relative to nondepressed controls, depressed participants reported lower BAS levels and higher BIS levels. Within the depressed group, lower BAS levels were associated with greater concurrent depression severity and predicted worse 8-month outcome. Levels of both BIS and BAS showed considerable stability over time and clinical state. Overall, results suggest that BAS dysregulation exacerbates the presentation and course of depressive illness. In recent years there has been converging evidence from biological, neurological, and psychosocial investigations that several forms of psychopathology are characterized by specific patterns of deficits in approach- and withdrawal-related behavior (e.g., Arnett, Smith, & Newman, 1997; Rosenbaum et al., 2000). In general, research in this area has focused on the relation of Gray’s (1973) behavioral activation system (BAS) and behavioral inhibition system (BIS) to different types of psychopathology. Whereas the BAS is an approach-related, positive-incentive motivation system, the BIS, in contrast, regulates sensitivity to threat and nonreward cues. Gray drew from the animal literature, as well as from work examining the mechanism of action of anxiolytic medications, to form his theory of the BIS. Although Gray’s model was originally applied to anxiety, Depue and Iacono (1989) have postulated more recently that systems similar to those proposed by Gray are implicated in depressive illness. More specifically, Depue and Iacono proposed that major depression is characterized by deficits or dysfunctions in the behavioral activation system (which they labeled the behavioral facilitation system) and the behavioral inhibition system. In support of this formulation, a wide range of empirical evidence indicates that depressed individuals are characterized by low


title: A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation

abstract: Over the years, datasets and benchmarks have proven their fundamental importance in computer vision research, enabling targeted progress and objective comparisons in many fields. At the same time, legacy datasets may impend the evolution of a field due to saturated algorithm performance and the lack of contemporary, high quality data. In this work we present a new benchmark dataset and evaluation methodology for the area of video object segmentation. The dataset, named DAVIS (Densely Annotated VIdeo Segmentation), consists of fifty high quality, Full HD video sequences, spanning multiple occurrences of common video object segmentation challenges such as occlusions, motionblur and appearance changes. Each video is accompanied by densely annotated, pixel-accurate and per-frame ground truth segmentation. In addition, we provide a comprehensive analysis of several state-of-the-art segmentation approaches using three complementary metrics that measure the spatial extent of the segmentation, the accuracy of the silhouette contours and the temporal coherence. The results uncover strengths and weaknesses of current approaches, opening up promising directions for future works.


Predicting Amazon review helpfulness [ CSE 255 Assignment 1 ]


title: Monad transformers and modular interpreters

abstract: We show how a set of building blocks can be used to construct programming language interpreters, and present implementations of such building blocks capable of supporting many commonly known features, including simple expressions, three different function call mechanisms (call-by-name, call-by-value and lazy evaluation), references and assignment, nondeterminism, first-class continuations, and program tracing. The underlying mechanism of our system is monad transformers , a simple form of abstraction for introducing a wide range of computational behaviors, such as state, I/O, continuations, and exceptions. Our work is significant in the following respects. First, we have succeeded in designing a fully modular interpreter based on monad transformers that incudes features missing from Steele's, Espinosa's, and Wadler's earlier efforts. Second, we have found new ways to lift monad operations through monad transformers, in particular difficult cases not achieved in Moggi's original work. Third, we have demonstrated that interactions between features are reflected in liftings and that semantics can be changed by reordering monad transformers. Finally, we have implemented our interpreter in Gofer, whose constructor classes provide just the added power over Haskell's type classes to allow precise and convenient expression of our ideas. This implementation includes a method for constructing extensible unions and a form of subtyping that is interesting in its own right.


title: Personal Information in Passwords and Its Security Implications

abstract: While it is not recommended, Internet users tend to include personal information in their passwords for easy memorization. However, the use of personal information in passwords and its security implications have yet to be studied. In this paper, we dissect user passwords from several leaked data sets to investigate the extent to which a user’s personal information resides in a password. Then, we introduce a new metric called coverage to quantify the correlation between passwords and personal information. Afterward, based on our analysis, we extend the probabilistic context-free grammars (PCFGs) method to be semantics-rich and propose personal-PCFG to crack passwords by generating personalized guesses. Through offline and online attack scenarios, we demonstrate that personal-PCFG cracks passwords much faster than PCFG and makes online attacks much more likely to succeed. To defend against such semantics-aware attacks, we examine the use of simple distortion functions that are chosen by users to mitigate unwanted correlation between personal information and passwords.


title: Adaptive Computing Optimization in Software-Defined Network-Based Industrial Internet of Things with Fog Computing

abstract: In recent years, cloud computing and fog computing have appeared one after the other, as promising technologies for augmenting the computing capability of devices locally. By offloading computational tasks to fog servers or cloud servers, the time for task processing decreases greatly. Thus, to guarantee the Quality of Service (QoS) of smart manufacturing systems, fog servers are deployed at network edge to provide fog computing services. In this paper, we study the following problems in a mixed computing system: (1) which computing mode should be chosen for a task in local computing, fog computing or cloud computing? (2) In the fog computing mode, what is the execution sequence for the tasks cached in a task queue? Thus, to solve the problems above, we design a Software-Defined Network (SDN) framework in a smart factory based on an Industrial Internet of Things (IIoT) system. A method based on Computing Mode Selection (CMS) and execution sequences based on the task priority (ASTP) is proposed in this paper. First, a CMS module is designed in the SDN controller and then, after operating the CMS algorithm, each task obtains an optimal computing mode. Second, the task priorities can be calculated according to their real-time performance and calculated amount. According to the task priority, the SDN controller sends a flow table to the SDN switch to complete the task transmission. In other words, the higher the task priority is, the earlier the fog computing service is obtained. Finally, a series of experiments and simulations are performed to evaluate the performance of the proposed method. The results show that our method can achieve real-time performance and high reliability in IIoT.


title: EHCTool: Managing Emotional Hotspots for Conversational Agents

abstract: Building conversational agents is becoming easier thanks to the profusion of designated platforms. Integrating emotional intelligence in such agents contributes to positive user satisfaction. Currently, this integration is implemented using calls to an emotion analysis service. In this demonstration we present EHCTool that aims to detect and notify the conversation designer about problematic conversation states where emotions are likely to be expressed by the user. Using its exploration view, the tool assists the designer to manage and define appropriate responses in these cases.


title: Augmented reality-based exergames for rehabilitation

abstract: Rehabilitation for stroke afflicted patients, through exercises tailored for individual needs, aims at relearning basic motor skills, especially in the extremities. Rehabilitation through Augmented Reality (AR) based games engage and motivate patients to perform exercises which, otherwise, maybe boring and monotonic. Also, mirror therapy allows users to observe one's own movements in the game providing them with good visual feedback. This paper presents an augmented reality based system for rehabilitation by playing four interactive, cognitive and fun Exergames (exercise and gaming). The system uses low-cost RGB-D cameras such as Microsoft Kinect V2 to capture and generate 3D model of the person by extracting him/her from the entire captured data and immersing it in different interactive virtual environments. Animation based limb movement enhancement along with cognitive aspects incorporated in the game can help in positive reinforcement, progressive challenges and motion improvement. Recording module of the toolkit allows future reference and facilitates feedback from the physician. 10 able-bodied users, 2 psychological experts and 2 Physical Medicine and Rehabilitation physicians evaluated the user experience and usability aspects of the exergames. Results obtained shows the games to be fun and realistic, and at the same time engaging and motivating for performing exercises.


title: Functional test generation using design and property decomposition techniques

abstract: Functional verification of microprocessors is one of the most complex and expensive tasks in the current system-on-chip design methodology. Simulation using functional test vectors is the most widely used form of processor validation. A significant bottleneck in the validation of such systems is the lack of automated techniques for directed test generation. While existing model checking--based approaches have proposed several promising ideas for automated test generation, many challenges remain in applying them to industrial microprocessors. The time and resources required for test generation using existing model checking--based techniques can be prohibitively large. This article presents an efficient test generation technique using decompositional model checking. The contribution of the article is the development of both property and design decomposition procedures for efficient test generation of pipelined processors. Our experimental results using a multi-issue MIPS processor and an industrial processor based on Power Architecture™ Technology demonstrate several orders-of-magnitude reduction in validation effort by drastically reducing both test generation time and test program length.


title: Nicotine potentiates proatherogenic effects of oxLDL by stimulating and upregulating macrophage CD36 signaling

abstract: Cigarette smoking is a major risk factor for atherosclerosis and cardiovascular disease. CD36 mediates oxidized LDL (oxLDL) uptake and contributes to macrophage foam cell formation. We investigated a role for the CD36 pathway in nicotine-induced activation of macrophages and foam cell formation in vitro and in vivo. Nicotine in the same plasma concentration range found in smokers increased the CD36(+)/CD14(+) cell population in human peripheral blood mononuclear cells, increased CD36 expression of human THP1 macrophages, and increased macrophage production of reactive oxygen species, PKCδ phosphorylation, and peroxisome proliferator-activated receptor-γ (PPARγ) expression. Nicotine-induced CD36 expression was suppressed by antioxidants and by specific PKCδ and PPARγ inhibitors, implicating mechanistic roles for these intermediates. Nicotine synergized with oxLDL to increase macrophage expression of CD36 and cytokines TNF-α, monocyte chemoattractant protein-1, IL-6, and CXCL9, all of which were prevented by CD36 small interfering (si)RNA. Incubation with oxLDL (50 μg/ml) for 72 h resulted in lipid deposition in macrophages and foam cell formation. Preincubation with nicotine further increased oxLDL-induced lipid accumulation and foam cell formation, which was also prevented by CD36 siRNA. Treatment of apoE-/- mice with nicotine markedly exacerbated inflammatory monocyte levels and atherosclerotic plaque accumulation, effects that were not seen in CD36-/- apoE-/- mice. Our results show that physiological levels of nicotine increase CD36 expression in macrophages, a pathway that may account at least in part for the known proinflammatory and proatherogenic properties of nicotine. These results identify such enhanced CD36 expression as a novel nicotine-mediated pathway that may constitute an independent risk factor for atherosclerosis in smokers. The results also suggest that exacerbated atherogenesis by this pathway may be an adverse side effect of extended use of high concentrations of nicotine independent of their mode of administration.


title: Managing Overloaded Hosts for Dynamic Consolidation of Virtual Machines in Cloud Data Centers under Quality of Service Constraints

abstract: Dynamic consolidation of virtual machines (VMs) is an effective way to improve the utilization of resources and energy efficiency in cloud data centers. Determining when it is best to reallocate VMs from an overloaded host is an aspect of dynamic VM consolidation that directly influences the resource utilization and quality of service (QoS) delivered by the system. The influence on the QoS is explained by the fact that server overloads cause resource shortages and performance degradation of applications. Current solutions to the problem of host overload detection are generally heuristic based, or rely on statistical analysis of historical data. The limitations of these approaches are that they lead to suboptimal results and do not allow explicit specification of a QoS goal. We propose a novel approach that for any known stationary workload and a given state configuration optimally solves the problem of host overload detection by maximizing the mean intermigration time under the specified QoS goal based on a Markov chain model. We heuristically adapt the algorithm to handle unknown nonstationary workloads using the Multisize Sliding Window workload estimation technique. Through simulations with workload traces from more than a thousand PlanetLab VMs, we show that our approach outperforms the best benchmark algorithm and provides approximately 88 percent of the performance of the optimal offline algorithm.


title: Involvement of the cerebellar cortex and nuclei in verbal and visuospatial working memory: A 7T fMRI study

abstract: Abstract The first aim of the present study was to extend previous findings of similar cerebellar cortical areas being involved in verbal and spatial n-back working memory to the level of the cerebellar nuclei. The second aim was to investigate whether different areas of the cerebellar cortex and nuclei contribute to different working memory tasks (n-back vs. Sternberg tasks). Young and healthy subjects participated in two functional magnetic resonance imaging (fMRI) studies using a 7 T MR scanner with its increased signal-to-noise ratio. One group of subjects (n = 21) performed an abstract and a verbal version of an n-back task contrasting a 2-back and 0-back condition. Another group of subjects (n = 23) performed an abstract and a verbal version of a Sternberg task contrasting a high load and a low load condition. A block design was used. For image processing of the dentate nuclei, a recently developed region of interest (ROI) driven normalization method of the dentate nuclei was applied (Diedrichsen et al., 2011). Whereas activated areas of the cerebellar cortex and dentate nuclei were not significantly different comparing the abstract and verbal versions of the n-back task, activation in the abstract and verbal Sternberg tasks was significantly different. In both n-back tasks activation was most prominent at the border of lobules VI and Crus I, within lobule VII, and within the more caudal parts of the dentate nucleus bilaterally. In Sternberg tasks the most prominent activations were found in lobule VI extending into Crus I on the right. In the verbal Sternberg task activation was significantly larger within right lobule VI compared to the abstract Sternberg task and compared to the verbal n-back task. Activations of rostral parts of the dentate were most prominent in the verbal Sternberg task, whereas activation of caudal parts predominated in the abstract Sternberg task. On the one hand, the lack of difference between abstract and verbal n-back tasks and the lack of significant lateralization suggest a more general contribution of the cerebellum to working memory regardless of the modality. On the other hand, the focus of activation in right lobule VI in the verbal Sternberg task suggests specific cerebellar contributions to verbal working memory. The verbal Sternberg task emphasizes maintenance of stimuli via phonological rehearsal, whereas central executive demands prevail in n-back tasks. Based on the model of working memory by Baddeley and Hitch (1974), the present results show that different regions of the cerebellum support functions of the central executive system and one of the subsidiary systems, the phonological loop.


title: Admittance control of an upper limb exoskeleton - Reduction of energy exchange

abstract: The synergy of human arms and wearable robot systems (e.g. exoskeletons) is enabled by a control algorithm that maximizes the transparency between the two subsystems. The transparency can be improved by integrating the admittance control along with an arm redundancy resolution algorithm. Recent research effort resulted in a new criterion for the human arm redundancy resolution for unconstrained arm motions estimating the swivel angle with prediction errors of less than 5°. The proposed criterion for the arm redundancy resolution defines the mouth as the primary target of the the human hand during unconstrained arm motions in free space. It was postulated based on experimental data analysis that this criterion is based on a neural mechanism directing the hand towards the head for self-feeding. In conjunction with the proposed redundancy resolution criteria a task space admittance control algorithm is introduced based on multiple force sensor inputs obtained at the interface between the human arm and the exoskeleton system. The system performance was evaluated by five healthy subjects performing a peg-in-hole task for three different target locations. The velocities and interaction forces at the upper arm, lower arm, handle and tip were recorded and further used to power exchange between the subject and the device. Results indicated that the proposed control scheme outperforms the purely reactive task space admittance control with energy exchange reduced to 11.22%. Improving the quality of the human control of a wearable robot system may allow the robot to be a natural and transparent extension of the operator's body.


Cancer stem cell markers in oral squamous cell carcinoma – Revisited


title: Movement imitation with nonlinear dynamical systems in humanoid robots

abstract: Presents an approach to movement planning, on-line trajectory modification, and imitation learning by representing movement plans based on a set of nonlinear differential equations with well-defined attractor dynamics. The resultant movement plan remains an autonomous set of nonlinear differential equations that forms a control policy (CP) which is robust to strong external perturbations and that can be modified on-line by additional perceptual variables. We evaluate the system with a humanoid robot simulation and an actual humanoid robot. Experiments are presented for the imitation of three types of movements: reaching movements with one arm, drawing movements of 2-D patterns, and tennis swings. Our results demonstrate (a) that multi-joint human movements can be encoded successfully by the CPs, (b) that a learned movement policy can readily be reused to produce robust trajectories towards different targets, (c) that a policy fitted for one particular target provides a good predictor of human reaching movements towards neighboring targets, and (d) that the parameter space which encodes a policy is suitable for measuring to which extent two trajectories are qualitatively similar.


title: Microstructures to control elasticity in 3D printing

abstract: We propose a method for fabricating deformable objects with spatially varying elasticity using 3D printing. Using a single, relatively stiff printer material, our method designs an assembly of small-scale microstructures that have the effect of a softer material at the object scale, with properties depending on the microstructure used in each part of the object. We build on work in the area of metamaterials, using numerical optimization to design tiled microstructures with desired properties, but with the key difference that our method designs families of related structures that can be interpolated to smoothly vary the material properties over a wide range. To create an object with spatially varying elastic properties, we tile the object's interior with microstructures drawn from these families, generating a different microstructure for each cell using an efficient algorithm to select compatible structures for neighboring cells. We show results computed for both 2D and 3D objects, validating several 2D and 3D printed structures using standard material tests as well as demonstrating various example applications.


title: Rescheduling manufacturing systems: A framework of strategies, policies, and methods

abstract: Many manufacturing facilities generate and update production schedules, which are plans that state when certain controllable activities (e.g., processing of jobs by resources) should take place. Production schedules help managers and supervisors coordinate activities to increase productivity and reduce operating costs. Because a manufacturing system is dynamic and unexpected events occur, rescheduling is necessary to update a production schedule when the state of the manufacturing system makes it infeasible. Rescheduling updates an existing production schedule in response to disruptions or other changes. Though many studies discuss rescheduling, there are no standard definitions or classification of the strategies, policies, and methods presented in the rescheduling literature. This paper presents definitions appropriate for most applications of rescheduling manufacturing systems and describes a framework for understanding rescheduling strategies, policies, and methods. This framework is based on a wide variety of experimental and practical approaches that have been described in the rescheduling literature. The paper also discusses studies that show how rescheduling affects the performance of a manufacturing system, and it concludes with a discussion of how understanding rescheduling can bring closer some aspects of scheduling theory and practice.


title: ECP technique based capacitor-less LDO with high PSRR at low frequencies, −89dB PSRR at 1MHz and enhanced transient response

abstract: An external capacitor-less low dropout (LDO) voltage regulator with high PSRR and enhanced transient response is presented. The novel idea is applying a replica circuit which can pull excessive current. Excessive Current Pulling (ECP) technique decreases the equivalent output impedance to enhance transient response. The proposed LDO has been simulated in 0.18 μm CMOS Technology. Its regulated output voltage is 1.6 V with the power supply of 1.8 V. The proposed technique has the advantages of simulated PSRR of −88.7 dB at 1 MHz and −67 dB at 100 KHz. Overshoots and undershoots are less than 45.2 mV and 30 mV under the load varies from 50 mA to 0 mA with rise/fall time of 100ns, respectively. Simulation results show that the achieved line regulation is 28.3 mV/V and the load regulation is 0.33 %/mA.


title: Interactive Tree Of Life v2: online annotation and display of phylogenetic trees made easy

abstract: Interactive Tree Of Life (http://itol.embl.de) is a web-based tool for the display, manipulation and annotation of phylogenetic trees. It is freely available and open to everyone. In addition to classical tree viewer functions, iTOL offers many novel ways of annotating trees with various additional data. Current version introduces numerous new features and greatly expands the number of supported data set types. Trees can be interactively manipulated and edited. A free personal account system is available, providing management and sharing of trees in user defined workspaces and projects. Export to various bitmap and vector graphics formats is supported. Batch access interface is available for programmatic access or inclusion of interactive trees into other web services.


title: Context matters: Towards extracting a citation's context using linguistic features

abstract: Keyword-based search engines are becoming increasingly sophisticated, and yet navigating the ever-increasing collection of academic knowledge remains an arduous task. Keeping abreast of relevant scientific literature is often a fragmented process that breaks the workflow of academic writing.


title: What is wrong with style transfer for texts?

abstract: A number of recent machine learning papers work with an automated style transfer for texts and, counter to intuition, demonstrate that there is no consensus formulation of this NLP task. Different researchers propose different algorithms, datasets and target metrics to address it. This short opinion paper aims to discuss possible formalization of this NLP task in anticipation of a further growing interest to it.


title: Privacy-Preserving Data Aggregation against False Data Injection Attacks in Fog Computing

abstract: As an extension of cloud computing, fog computing has received more attention in recent years. It can solve problems such as high latency, lack of support for mobility and location awareness in cloud computing. In the Internet of Things (IoT), a series of IoT devices can be connected to the fog nodes that assist a cloud service center to store and process a part of data in advance. Not only can it reduce the pressure of processing data, but also improve the real-time and service quality. However, data processing at fog nodes suffers from many challenging issues, such as false data injection attacks, data modification attacks, and IoT devices' privacy violation. In this paper, based on the Paillier homomorphic encryption scheme, we use blinding factors to design a privacy-preserving data aggregation scheme in fog computing. No matter whether the fog node and the cloud control center are honest or not, the proposed scheme ensures that the injection data is from legal IoT devices and is not modified and leaked. The proposed scheme also has fault tolerance, which means that the collection of data from other devices will not be affected even if certain fog devices fail to work. In addition, security analysis and performance evaluation indicate the proposed scheme is secure and efficient.


title: Fuzzy Running Average and Fuzzy Background Subtraction: Concepts and Application

abstract: Summary Running average method and its modified version are two simple and fast methods for background modeling. In this paper, some weaknesses of running average method and standard background subtraction are mentioned. Then, a fuzzy approach for background modeling and background subtraction is proposed. For fuzzy background modeling, fuzzy running average is suggested. Background modeling and background subtraction algorithms are very commonly used in vehicle detection systems. To demonstrate the advantages of fuzzy running average and fuzzy background subtraction, these methods and their standard versions are compared in vehicle detection application. Experimental results show that fuzzy approach is relatively more accurate than classical approach.


title: Dual and triple diagnoses: Addictions, mental illness, and HIV infection guidelines for outpatient therapists

abstract: Abstract The outpatient psychotherapist is faced with the challenge of being alert to the presence of other significant diagnoses in addition to the patient's presenting complaint. Failure to treat the unidentified diagnosis or diagnoses increases the risk of treatment failure or relapse in the identified diagnosis. Addictions (substance and behavioral), mental illness, and life-threatening medical illness (HIV infection) are all interactive. This article presents general guidelines to facilitate an integrated and organized approach to the assessment, treatment planning, and monitoring progress in dual, triple, and multiple diagnoses. Numerous tables are presented to promote clarity and familiarity with medical issues.


title: Associations Between ADHD and Psychoactive Substance Use Disorders

abstract: This article investigates the relationship between attention-deficit/hyperactivity disorder (ADHD) and psychoactive substance use disorders (PSUD) in siblings of ADHD and normal-control probands and addresses issues of psychiatric comorbidity and gender. Using DSM-III-R structured diagnostic interviews and blind raters, the authors conducted a 4-year follow-up of siblings. ADHD and male gender predicted higher rates and an earlier onset of PSUD after adjusting for high-risk status, other psychiatric disorders, and age. Risk was particularly high if the siblings had ADHD plus conduct disorder. This study's findings confirms the authors' prior report highlighting the importance of drug and alcohol prevention and cessation programs aimed at ADHD youth and their siblings, particularly those with comorbid conduct disorder.


title: A Study of Face Recognition as People Age

abstract: In this paper we study face recognition across ages within a real passport photo verification task. First, we propose using the gradient orientation pyramid for this task. Discarding the gradient magnitude and utilizing hierarchical techniques, we found that the new descriptor yields a robust and discriminative representation. With the proposed descriptor, we model face verification as a two-class problem and use a support vector machine as a classifier. The approach is applied to two passport data sets containing more than 1,800 image pairs from each person with large age differences. Although simple, our approach outperforms previously tested Bayesian technique and other descriptors, including the intensity difference and gradient with magnitude. In addition, it works as well as two commercial systems. Second, for the first time, we empirically study how age differences affect recognition performance. Our experiments show that, although the aging process adds difficulty to the recognition task, it does not surpass illumination or expression as a confounding factor.


title: Neural Network Language Modeling with Letter-Based Features and Importance Sampling

abstract: In this paper we describe an extension of the Kaldi software toolkit to support neural-based language modeling, intended for use in automatic speech recognition (ASR) and related tasks. We combine the use of subword features (letter n-grams) and one-hot encoding of frequent words so that the models can handle large vocabularies containing infrequent words. We propose a new objective function that allows for training of unnormalized probabilities. An importance sampling based method is supported to speed up training when the vocabulary is large. Experimental results on five corpora show that Kaldi-RNNLM rivals other recurrent neural network language model toolkits both on performance and training speed.


title: Impact of Photovoltaic-Oriented DC Stray Current Corrosion on Large-Scale Solar Farms' Grounding and Third-Party Infrastructure: Modeling and Assessment

abstract: This paper discusses the impact of photovoltaic (PV)-oriented dc stray current corrosion on large-scale solar farms' grounding and third-party infrastructure. The dc stray current may result from a fault or may be facilitated by buried cables' condition that allows dc leakage to flow into the earth. In particular, such abnormal conditions can impact the grounding electrodes of the PV plants as well as third-party metallic infrastructures (e.g., natural gas pipelines) that are laid in the nearby vicinity of a solar plant. This paper unfolds by thoroughly addressing three specific objectives: 1) defining the origin of the problem; 2) modeling the problem in commercially available software; and 3) discussing the arising implications.


A Novel Commutation Strategy to Suppress the Common Mode Voltage for the Matrix Converter


title: Islands in the Stream: A Study of Item Recommendation within an Enterprise Social Stream

abstract: Social streams allow users to receive updates from their network by syndicating social media activity. These streams have become a popular way to share and consume information both on the web and in the enterprise. With so much activity going on, filtering and personalizing the stream for individual users is a key challenge. In this work, we study the recommendation of enterprise social stream items through a user survey with 510 participants, conducted within a globally distributed organization. In the survey, participants rated their level of interest and surprise for different items from the stream and could also indicate whether they were already familiar with the item. Thus, our evaluation goes beyond the common accuracy measure and examines aspects of serendipity and novelty. We also inspect how various features of the recommended item, its author, and reader, influence its ratings. Our results shed light on the key factors that make a stream item valuable to its reader within the enterprise.


title: A Nano-Watt MOS-Only Voltage Reference With High-Slope PTAT Voltage Generators

abstract: This brief presents an MOS-only voltage reference circuit with high-slope proportional-to-absolute-temperature (PTAT) voltage generators for ultra-low-power applications. Biased by a nano-ampere current reference circuit, the PTAT voltage generator is realized by an asymmetrical differential cell with two additional cross-coupled nMOS/pMOS pairs, which enhance the slope of the PTAT voltage remarkably. As a result, only two cascaded PTAT stages are used to compensate the complementary-to-absolute-temperature voltage generated directly by a diode-connected nMOS in the current reference circuit. Therefore, much power and chip area can be saved. A trimming circuit is also adopted to compensate the process-related reference voltage variations. The experimental results of the proposed reference circuit fabricated in a 0.18- $ {\mu }$ m standard CMOS process demonstrate that the circuit could operate under a minimum supply voltage of 1 V, and generate a reference voltage of 756 mV with temperature coefficient of 74 and 49.6 ppm/°C under 1-V and 1.8-V power supply, respectively. The proposed circuit consumes only 23 nA under a 1-V power supply, and the active area is only 95 $ {\mu }\text{m}\,\, {\times } \,\, 170 ~{\mu }\text{m}$ .


title: Design and Modeling of a Series Elastic Element for Snake Robots

abstract: In this work, we detail the design, fabrication, and initial modeling of a compact, high-strength series elastic element designed for use in snake robots. The spring achieves its elasticity by torsionally shearing a rubber elastomer that is bonded to two rigid plates, and it is able to achieve mechanical compliance and energy storage that is an order of magnitude greater than traditional springs. Its novel design features a tapered conical cross-section that creates uniform shear stress in the rubber, improving the ultimate strength. Tests show that the torque-displacement profile of these springs is approximately linear, and initial results are reported on creating more accurate models that account for the element’s hysteresis and viscoelastic properties. Low-bandwidth force control is demonstrated by measuring the element’s torsional deflection to estimate the torque output of one of our snake robot modules.Copyright © 2013 by ASME


title: Barriers to Electronic Commerce Adoption in Small and Medium Enterprises: A Critical Literature Review

abstract: This study is attempting to determine if the barriers reported in early e-commerce researches differ from those found in recent e-commerce studies as well as exploring if the resultant barrier groupings created from e-commerce barriers are dissimilar. To achieve our research’s aim, an extensive literature review was conducted based on what we believe to be representative sample of some of the most cited pieces of research on this topic. The study concludes that though the issues inhibiting SMEs in their uptake of e-commerce are seemingly endless, the reality is that these issues have largely remained the same since the advent of e-commerce in the early 1990’s. The implication of our study is that researchers should stop reinventing the list of e-commerce adoption barriers but instead focus their efforts on how SMEs can overcome these barriers so as to reap the full benefits of the technology.


title: Evolutionary computation: Comments on the history and current state

abstract: Evolutionary computation has started to receive significant attention during the last decade, although the origins can be traced back to the late 1950's. This article surveys the history as well as the current state of this rapidly growing field. We describe the purpose, the general structure, and the working principles of different approaches, including genetic algorithms (GA) (with links to genetic programming (GP) and classifier systems (CS)), evolution strategies (ES), and evolutionary programming (EP) by analysis and comparison of their most important constituents (i.e. representations, variation operators, reproduction, and selection mechanism). Finally, we give a brief overview on the manifold of application domains, although this necessarily must remain incomplete.


title: Building Citizen Trust towards E-Government Services: Do High Quality Websites Matter?

abstract: E-governments are increasingly becoming a familiar fixture in virtual landscapes. Yet, the lack of citizen trust brought on by the novelty and uncertainty of online transactions has inhibited the widespread acceptance for public e-services. Ascribing to the perspective of technology as a social actor with whom the customer interacts and transacts, we put forward a research model that accentuates the pivotal role of e-government service quality as a salient driver of citizens' trustworthiness beliefs towards e-government Web sites, which in turn promotes the corresponding adoption of public e-services. E-government service quality, as conceptualized in this study, borrows from the popularized SERVQUAL constructs in deriving prescriptive design principles to guide the development of e-government Web sites. Data collected from a sample of 647 e-government service participants substantiates all 14 hypothesized relationships, thereby suggesting that high quality e- government Web sites do matter in building citizen trust towards public e-services.


title: A Security approach for Data Migration in Cloud Computing

abstract: Cloud computing is a new paradigm that combines several computing concepts and technologies of the Internet creating a platform for more agile and cost-effective business applications and IT infrastructure. The adoption of Cloud computing has been increasing for some time and the maturity of the market is steadily growing. Security is the question most consistently raised as consumers look to move their data and applications to the cloud. I justify the importance and motivation of security in the migration of legacy systems and I carry out an approach related to security in migration processes to cloud with the aim of finding the needs, concerns, requirements, aspects, opportunities and benefits of security in the migration process of legacy systems.


1 The Corporate Social Performance-- Financial Performance Link


title: Fully Secure Functional Encryption: Attribute-Based Encryption and (Hierarchical) Inner Product Encryption

abstract: We present two fully secure functional encryption schemes: a fully secure attribute-based encryption (ABE) scheme and a fully secure (attribute-hiding) predicate encryption (PE) scheme for inner-product predicates. In both cases, previous constructions were only proven to be selectively secure. Both results use novel strategies to adapt the dual system encryption methodology introduced by Waters. We construct our ABE scheme in composite order bilinear groups, and prove its security from three static assumptions. Our ABE scheme supports arbitrary monotone access formulas. Our predicate encryption scheme is constructed via a new approach on bilinear pairings using the notion of dual pairing vector spaces proposed by Okamoto and Takashima.


title: A linear damping scheme for higher order dc-dc converters supplying constant-power loads in a dc microgrid

abstract: A linear controller is proposed for dc microgrids with SEPIC, Cuk and Zeta power electronic converters supplying constant power loads. The controller is implemented in two stages. During the first stage, also known as active damping stage, limit cycle oscillations are damped by inserting a virtual resistance in series with the input inductor of each of the converters. In the second stage, an integral controller is added to the first stage to compensate for the voltage deviations due to the virtual resistance. The second stage, also known as voltage regulation stage maintains the microgrid voltage within acceptable limits in the event of source and load variation. Linearization and small signal analysis are used to derive stability conditions for the equilibrium points. Simulation and experiments performed on a prototype microgrid are used to verify the proposed control laws.


title: SQL-IDS: a specification-based approach for SQL-injection detection

abstract: Vulnerabilities in web applications allow malicious users to obtain unrestricted access to private and confidential information. SQL injection attacks rank at the top of the list of threats directed at any database-driven application written for the Web. An attacker can take advantages of web application programming security flaws and pass unexpected malicious SQL statements through a web application for execution by the back-end database. This paper proposes a novel specification-based methodology for the detection of exploitations of SQL injection vulnerabilities. The new approach on the one hand utilizes specifications that define the intended syntactic structure of SQL queries that are produced and executed by the web application and on the other hand monitors the application for executing queries that are in violation of the specification. The three most important advantages of the new approach against existing analogous mechanisms are that, first, it prevents all forms of SQL injection attacks; second, its effectiveness is independent of any particular target system, application environment, or DBMS; and, third, there is no need to modify the source code of existing web applications to apply the new protection scheme to them. We developed a prototype SQL injection detection system (SQL-IDS) that implements the proposed algorithm. The system monitors Java-based applications and detects SQL injection attacks in real time. We report some preliminary experimental results over several SQL injection attacks that show that the proposed query-specific detection allows the system to perform focused analysis at negligible computational overhead without producing false positives or false negatives. Therefore, the new approach is very efficient in practice.


Sentiment Identification Using Maximum Entropy Analysis of Movie Reviews


title: Dynamic consent: a patient interface for twenty-first century research networks

abstract: Biomedical research is being transformed through the application of information technologies that allow ever greater amounts of data to be shared on an unprecedented scale. However, the methods for involving participants have not kept pace with changes in research capability. In an era when information is shared digitally at the global level, mechanisms of informed consent remain static, paper-based and organised around national boundaries and legal frameworks. Dynamic consent (DC) is both a specific project and a wider concept that offers a new approach to consent; one designed to meet the needs of the twenty-first century research landscape. At the heart of DC is a personalised, digital communication interface that connects researchers and participants, placing participants at the heart of decision making. The interface facilitates two-way communication to stimulate a more engaged, informed and scientifically literate participant population where individuals can tailor and manage their own consent preferences. The technical architecture of DC includes components that can securely encrypt sensitive data and allow participant consent preferences to travel with their data and samples when they are shared with third parties. In addition to improving transparency and public trust, this system benefits researchers by streamlining recruitment and enabling more efficient participant recontact. DC has mainly been developed in biobanking contexts, but it also has potential application in other domains for a variety of purposes.


title: Electronic Geometry Textbook: A Geometric Textbook Knowledge Management System

abstract: Electronic Geometry Textbook is a knowledge management system that manages geometric textbook knowledge to enable users to construct and share dynamic geometry textbooks interactively and efficiently. Based on a knowledge base organizing and storing the knowledge represented in specific languages, the system implements interfaces for maintaining the data representing that knowledge as well as relations among those data, for automatically generating readable documents for viewing or printing, and for automatically discovering the relations among knowledge data. An interface has been developed for users to create geometry textbooks with automatic checking, in real time, of the consistency of the structure of each resulting textbook. By integrating an external geometric theorem prover and an external dynamic geometry software package, the system offers the facilities for automatically proving theorems and generating dynamic figures in the created textbooks. This paper provides a comprehensive account of the current version of Electronic Geometry Textbook.


Strategic Alignment: Leveraging Information Technology for Transforming Organizations


title: Ragulator-Rag Complex Targets mTORC1 to the Lysosomal Surface and Is Necessary for Its Activation by Amino Acids

abstract: Summary The mTORC1 kinase promotes growth in response to growth factors, energy levels, and amino acids, and its activity is often deregulated in disease. The Rag GTPases interact with mTORC1 and are proposed to activate it in response to amino acids by promoting mTORC1 translocation to a membrane-bound compartment that contains the mTORC1 activator, Rheb. We show that amino acids induce the movement of mTORC1 to lysosomal membranes, where the Rag proteins reside. A complex encoded by the MAPKSP1 , ROBLD3 , and c11orf59 genes, which we term Ragulator, interacts with the Rag GTPases, recruits them to lysosomes, and is essential for mTORC1 activation. Constitutive targeting of mTORC1 to the lysosomal surface is sufficient to render the mTORC1 pathway amino acid insensitive and independent of Rag and Ragulator, but not Rheb, function. Thus, Rag-Ragulator-mediated translocation of mTORC1 to lysosomal membranes is the key event in amino acid signaling to mTORC1.


Artificial General Intelligence


title: Tunable Photoinduced Carrier Transport of a Black Phosphorus Transistor with Extended Stability Using a Light-Sensitized Encapsulated Layer

abstract: In this article, we propose a novel approach to demonstrate tunable photoinduced carrier transport of a few-layered black phosphorus (BP) field-effect transistor (FET) with extended air stability using a “light-sensitized ultrathin encapsulated layer”. Titanium suboxide (TiOx) ultrathin film (approximately 3 nm), which is an amorphous phase of crystalline TiO2 and can be solution processed, simultaneously exhibits the unique dual functions of passivation and photoinduced doping on a BP FET. The photoinduced electron transfer at TiOx/BP interfaces provides tunable n-type doping on BP through light illumination. Accordingly, the intrinsic hole-dominated transport of BP can be gradually tuned to the electron-dominated transport at a TiOx/BP FET using light modulation, with enhanced electron mobility and extended air stability of the device. The novel device structure consisting of a light-sensitized encapsulated layer with controllable and reversible doping through light illumination on BP exhibits great pot...


title: Which group do you want to travel with?: a study of rating differences among groups on online travel reviews

abstract: The purpose of this paper is to empirically examine that which group the travelers are travelling with can have a significant impact on travelers' satisfaction with the hotel they visited to. The data was crawled and collected on Booking.com which is the most popular and well-known travel website by using our web crawler developed in Python. We analyzed 314 hotels rating data of two to five star hotels located in New York City conducting econometric analysis. Consequently, it is discovered that satisfaction of traveler groups decreases in the order of couple, friends, family, solo, and business. The group of couples expressed the highest satisfaction while the group of business travelers showed the lowest satisfaction. By conducting text analysis with 125,076 reviews, we found that such satisfaction differences can be caused by differences of travelers' experiences depending on groups.


title: The Chameleon Guitar—Guitar with a Replaceable Resonator

abstract: Abstract Each acoustic instrument is one of a kind. Its unique acoustic properties are transferred from the physical characteristics of its source materials and a handcrafted touch. In contrast, electronic and computer-based instruments lack this distinguishing trait. Though the technology support in musical instruments offers great flexibility, it tends to foster predictable and generic results, particularly with common use of easily-cloned digital presets. This paper presents a new approach to the design and fabrication of instruments that combine the advantage of acoustic and electric instruments—hybrid instruments—that exist simultaneously in both physical and digital environments. This approach exploits physical/acoustic properties via a replaceable physical object complemented by a simulated shape or other digital signal manipulation. The key concepts of this approach are presented through an example: The Chameleon Guitar, detailed in this paper along with evaluation from musicians and instrument ma...


title: Influence of phase error on OFDM-based 4096-QAM with turbo coding

abstract: The use of higher-order quadrature amplitude modulation (QAM) is an important approach for increasing data rates within a limited bandwidth. However, higher-order QAM is very sensitive to the amplitude and phase error, and needs to higher received SNR. This paper investigates the influence of phase error on the orthogonal frequency division multiplexing (OFDM)-based 1024- and 4096-QAM with turbo coding. The BER performance and the SNR penalty in the presence of the phase error are highlighted as parameters of the coding rates by link-level simulation for both OFDM-based 1024- and 4096-QAM.


title: Neurocircuitry of Mood Disorders

abstract: This review begins with a brief historical overview of attempts in the first half of the 20th century to discern brain systems that underlie emotion and emotional behavior. These early studies identified the amygdala, hippocampus, and other parts of what was termed the ‘limbic' system as central parts of the emotional brain. Detailed connectional data on this system began to be obtained in the 1970s and 1980s, as more effective neuroanatomical techniques based on axonal transport became available. In the last 15 years these methods have been applied extensively to the limbic system and prefrontal cortex of monkeys, and much more specific circuits have been defined. In particular, a system has been described that links the medial prefrontal cortex and a few related cortical areas to the amygdala, the ventral striatum and pallidum, the medial thalamus, the hypothalamus, and the periaqueductal gray and other parts of the brainstem. A large body of human data from functional and structural imaging, as well as analysis of lesions and histological material indicates that this system is centrally involved in mood disorders.


title: A survey of hardware implementations of elliptic curve cryptographic systems

abstract: Elliptic Curve Cryptography (ECC) has gained much recognition over the last decades and has established itself among the well known public-key cryptography schemes, not least due its smaller key size and relatively lower computational effort compared to RSA. The wide employment of Elliptic Curve Cryptography in many different application areas has been leading to a variety of implementation types and domains ranging from pure software approaches over hardware implemenations to hardware/software co-designs. The following review provides an overview of state of the art hardware implemenations of ECC, specifically in regard to their targeted design goals. In this context the suitability of the hardware/software approach in regard to the security challenges opposed by the low-end embedded devices of the Internet of Things is briefly examined. The paper also outlines ECC’s vulnerability against quantum attacks and references one possible solution to that problem.


title: Firearm Detection Using Wrist Worn Tri-Axis Accelerometer Signals

abstract: Gunshot detection traditionally has been a task performed with acoustic signal processing. While this type of detection can give cities, civil services and training institutes a method to identify specific locations of gunshots, the nature of acoustic detection may not provide the fine-grained detection accuracy and sufficient metrics for performance assessment. If however you examine a different signature of a gunshot, the recoil, detection of the same event with accelerometers can provide you with persona and firearm model level detection abilities. The functionality of accelerometer sensors in wrist worn devices have increased significantly in recent time. From fitness trackers to smart watches, accelerometers have been put to use in various activity recognition and detection applications. In this paper, we design an approach that is able to account for the variations in firearm generated recoil, as recorded by a wrist worn accelerometer, and helps categorize the impulse forces. Our experiments show that not only can wrist worn accelerometers detect the differences in handgun rifle and shotgun gunshots, but the individual models of firearms can be distinguished from each other. The application of this framework could be extended in the future to include real time detection embedded in smart devices to assist in firearms training and also help in crime detection and prosecution.


title: A Variational Approach to Medical Image Inpainting Based on Mumford-Shah Model

abstract: Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic services. Medical image inpainting is an important research field in CAD, which can be used to retouch and remove speckle noise and conceal spots and cracks in organic images. When processing damaged medical image, because the amount of data and computing of image is very large and traditional inpainting algorithms have early convergence problems, the quality of image restoration is poor. This paper discussed the problem of medical image inpainting by approaching a modified Mumford-Shah paradigm from a numerical approximation perspective. Within this framework an adaptive iterative algorithm for the numerical solving of the inpainting model was presented. First, we proposed a new nonparametric Mumford-Shah model for medical image inpainting. It improves the robustness and effectiveness by imposing some explicit smooth constrains of connection on the formation of discontinuous edges. Thus, the unknown inpainted curves in the model would be computed and identified as the smooth transition regions by several order parameters. Finally, the minimization was achieved by computing the gradient of energy evolving for the inpainting model. Experimental results on noisy medical images demonstrate the efficacy of the proposed algorithm.


title: TURBISCAN MA 2000: multiple light scattering measurement for concentrated emulsion and suspension instability analysis.

abstract: Emulsion or suspension destabilisation often results from coalescence or particle aggregation (flocculation) leading to particle migration (creaming or sedimentation). Creaming and sedimentation are often considered as reversible, while coalescence and flocculation spell disaster for the formulator. Thus, it is of prime importance to detect coalescence or cluster formation at an early stage to shorten the ageing tests and to improve the formulations. This work mainly concerns the independent and anisotropic scattering of light from an emulsion or suspension in a cylindrical glass measurement cell, in relation with the optical analyser TURBISCAN MA 2000. The propagation of light through a concentrated dispersion can be used to characterise the system physico-chemical stability. Indeed, photons undergo many scattering events in an optically thick dispersion before escaping the medium and entering a receiver aperture. Multiple scattering thus contributes significantly to the transmitted and backscattered flux measured by TURBISCAN MA 2000. We present statistical models and numerical simulations for the radiative transfer in a suspension (plane or cylindrical measurement cells) only involving the photon mean path length, the asymmetry factor and the geometry of the light receivers. We further have developed an imaging method with high grey level resolution for the visualisation and the analysis of the surface flux in the backscattered spot light. We compare the results from physical models and numerical simulations with the experiments performed with the imaging method and the optical analyser TURBISCAN MA 2000 for latex beads suspensions (variable size and particle volume fraction). We then present a few examples of concentrated emulsion and suspension instability analysis with TURBISCAN 2000. It is shown that the instrument is able to characterise particle or aggregate size variation and particle/aggregate migration and to detect these phenomena much more earlier than the operator's naked eye, especially for concentrated and optically thick media.


title: Scalable Attribute-Value Extraction from Semi-structured Text

abstract: This paper describes a general methodology for extracting attribute-value pairs from web pages. It consists of two phases: candidate generation, in which syntactically likely attribute-value pairs are annotated; and candidate filtering, in which semantically improbable annotations are removed. We describe three types of candidate generators and two types of candidate filters, all of which are designed to be massively parallelizable. Our methods can handle 1 billion web pages in less than 6 hours with 1,000 machines. The best generator and filter combination achieves 70% F-measure compared to a hand-annotated corpus.


title: Fog Removal from Color Images using Contrast Limited Adaptive Histogram Equalization

abstract: The images degraded by fog suffer from poor contrast. In order to remove fog effect, a Contrast Limited Adaptive Histogram Equalization (CLAHE)-based method is presented in this paper. This method establishes a maximum value to clip the histogram and redistributes the clipped pixels equally to each gray-level. It can limit the noise while enhancing the image contrast. In our method, firstly, the original image is converted from RGB to HSI. Secondly, the intensity component of the HSI image is processed by CLAHE. Finally, the HSI image is converted back to RGB image. To evaluate the effectiveness of the proposed method, we experiment with a color image degraded by fog and apply the edge detection to the image. The results show that our method is effective in comparison with traditional methods.


title: Generalized Zero-Shot Learning with Deep Calibration Network

abstract: A technical challenge of deep learning is recognizing target classes without seen data. Zero-shot learning leverages semantic representations such as attributes or class prototypes to bridge source and target classes. Existing standard zero-shot learning methods may be prone to overfitting the seen data of source classes as they are blind to the semantic representations of target classes. In this paper, we study generalized zero-shot learning that assumes accessible to target classes for unseen data during training, and prediction on unseen data is made by searching on both source and target classes. We propose a novel Deep Calibration Network (DCN) approach towards this generalized zero-shot learning paradigm, which enables simultaneous calibration of deep networks on the confidence of source classes and uncertainty of target classes. Our approach maps visual features of images and semantic representations of class prototypes to a common embedding space such that the compatibility of seen data to both source and target classes are maximized. We show superior accuracy of our approach over the state of the art on benchmark datasets for generalized zero-shot learning, including AwA, CUB, SUN, and aPY.


title: Benzyl isothiocyanate inhibits inflammasome activation in E. coli LPS-stimulated BV2 cells

abstract: Abstract Inflammasomes are multi-protein complexes that play a crucial role in innate immune responses. Benzyl isothiocyanate (BITC) is a naturally occurring compound found in cruciferous vegetables, and BITC exhibits potential as a chemopreventive agent. However, whether BITC exerts inflammasome-mediated regulatory effects on neuroinflammation is unknown. In this study, we examined the effects of BITC on inflammasome-mediated interleukin-1β (IL-1β) production in E. coli lipopolysaccharide (LPS)-stimulated BV2 microglial cells. IL-1β production is tightly regulated at the post-translational level through the inflammasoume. We measured the levels of IL-1β produced from the LPS-exposed BV2 microglial cells using enzyme-linked immunosorbent assays (ELISAs). The BITC regulatory mechanisms in inflammasome-mediated cellular signaling pathways were examined by RT-PCR, western blot analysis and electrophoretic mobility shift assays. BITC inhibited the secretion of IL-1β induced by LPS in the BV2 microglial cells. BITC inhibited inflammasome activation and NLR family, pyrin domain containing 3 (NLRP3)-mediated caspase-1 activation, and decreased the levels of inflammasome activation pro-inflammatory mediators, including mitochondrial reactive oxygen species (ROS) and adenosine triphosphate (ATP) secretion in the LPS-stimulated BV2 microglial cells. Furthermore, we demonstrated that nuclear factor-κB (NF-κB) activation induced by LPS was inhibited by BITC, which may contribute to the attenuated secretion of IL-1β. These BITC-mediated inhibitory effects on IL-1β expression may thus regulate neuroinflammation through the inflammasome-mediated signaling pathway.


title: Mobile Computing and Databases: a Survey

abstract: The emergence of powerful portable computers, along with advances in wireless communication technologies, has made mobile computing a reality. Among the applications that are finding their way to the market of mobile computing-those that involve data management-hold a prominent position. In the past few years, there has been a tremendous surge of research in the area of data management in mobile computing. This research has produced interesting results in areas such as data dissemination over limited bandwidth channels, location-dependent querying of data, and advanced interfaces for mobile computers. This paper is an effort to survey these techniques and to classify this research in a few broad areas.


title: Performance Evaluation of Microservices Architectures using Containers

abstract: Micro services architecture has started a new trend for application development for a number of reasons: (1) to reduce complexity by using tiny services, (2) to scale, remove and deploy parts of the system easily, (3) to improve flexibility to use different frameworks and tools, (4) to increase the overall scalability, and (5) to improve the resilience of the system. Containers have empowered the usage of micro services architectures by being lightweight, providing fast start-up times, and having a low overhead. Containers can be used to develop applications based on monolithic architectures where the whole system runs inside a single container or inside a micro services architecture where one or few processes run inside the containers. Two models can be used to implement a micro services architecture using containers: master-slave, or nested-container. The goal of this work is to compare the performance of CPU and network running benchmarks in the two aforementioned models of micro services architecture hence provide a benchmark analysis guidance for system designers.


title: Systems with Dynamic Real-Time Guarantees in Uncertain and Faulty Execution Environments

abstract: In many practical real-time systems, the physical environment and the system platform can impose uncertain execution behaviour to the system. For example, if transient faults are detected, the execution time of a task instance can be increased due to recovery operations. Such fault recovery routines make the system very vulnerable with respect to meeting hard real-time deadlines. In theory and in practical systems, this problem is often handled by aborting not so important tasks to guarantee the response time of the more important tasks. However, for most systems such faults occur rarely and the results of not so important tasks might still be useful, even if they are a bit late. This implicates to not abort these not so important tasks but keep them running even if faults occur, provided that the more important tasks still meet their hard real time properties. In this paper, we present Systems with Dynamic Real-Time Guarantees to model this behaviour and determine if the system can provide full timing guarantees or limited timing guarantees without any online adaptation after a fault occurred. We present a schedulability test, provide an algorithm for optimal priority assignment, determine the maximum interval length until the system will again provide full timing guarantees and explain how we can monitor the system state online. The approaches presented in this paper can also be applied to mixed criticality systems with dual criticality levels.


title: Celebrity's self-disclosure on Twitter and parasocial relationships: A mediating role of social presence

abstract: This study investigated how celebrities' self-disclosure on personal social media accounts, particularly Twitter, affects fans' perceptions. An online survey was utilized among a sample of 429 celebrity followers on Twitter. Results demonstrated that celebrities' professional self-disclosure (e.g., sharing their work-related life), personal self-disclosure (e.g., sharing their personal life such as friends and family), and fans' retweeting behavior, enhanced fans' feeling of social presence, thereby positively affecting parasocial interaction with celebrities. Further, the study found that the effects of self-disclosure and retweeting on parasocial interaction were mediated by social presence. Implications and future research directions are provided. Celebrities' professional and personal self-disclosure (SD) increase social presence.Fans' act of retweeting celebrities' tweets increases social presence.Social presence is positively related to parasocial interaction (PSI) experiences.Social presence mediates the relationship between SD and PSI experiences.Social presence mediates the relationship between retweeting and PSI experiences.


title: IDENTIFIABILITY ANALYSIS FOR NONLINEAR FEEDBACK LIMIT-CYCLE SYSTEMS USING HARMONIC BALANCE METHODS

abstract: Abstract This paper proposes a method for analyzing identifiability of inherently closed-loop systems with nonlinear feedback by determining the order of persistent excitation of the input to the linear part of the dynamics. The method is based on the harmonic balance and the double Fourier series which is used for approximately expressing the output of the nonlinearity in the feedback loop. It is shown that a multiplicative periodic reference signal enhances the identifiability of the system by the additional sinusoids with interweaving frequencies to the original unforced case.


title: When is it biased?: assessing the representativeness of twitter's streaming API

abstract: Twitter shares a free 1% sample of its tweets through the "Streaming API". Recently, research has pointed to evidence of bias in this source. The methodologies proposed in previous work rely on the restrictive and expensive Firehose to find the bias in the Streaming API data. We tackle the problem of finding sample bias without costly and restrictive Firehose data. We propose a solution that focuses on using an open data source to find bias in the Streaming API.


title: An Algorithmic Separating Hyperplane Theorem and Its Applications

abstract: We first prove a new separating hyperplane theorem characterizing when a pair of compact convex subsets $K, K'$ of the Euclidean space intersect, and when they are disjoint. The theorem is distinct from classical separation theorems. It generalizes the {\it distance duality} proved in our earlier work for testing the membership of a distinguished point in the convex hull of a finite point set. Next by utilizing the theorem, we develop a substantially generalized and stronger version of the {\it Triangle Algorithm} introduced in the previous work to perform any of the following three tasks: (1) To compute a pair $(p,p') \in K \times K'$, where either the Euclidean distance $d(p,p')$ is to within a prescribed tolerance, or the orthogonal bisecting hyperplane of the line segment $pp'$ separates the two sets; (2) When $K$ and $K'$ are disjoint, to compute $(p,p') \in K \times K'$ so that $d(p,p')$ approximates $d(K,K')$ to within a prescribed tolerance; (3) When $K$ and $K'$ are disjoint, to compute a pair of parallel supporting hyperplanes $H,H'$ so that $d(H,H')$ is to within a prescribed tolerance of the optimal margin. The worst-case complexity of each iteration is solving a linear objective over $K$ or $K'$. The resulting algorithm is a fully polynomial-time approximation scheme for such important special cases as when $K$ and $K'$ are convex hulls of finite points sets, or the intersection of a finite number of halfspaces. The results find many theoretical and practical applications, such as in machine learning, statistics, linear, quadratic and convex programming. In a forthcoming work we show how the algorithms can provide a certain approximation to NP-complete problems.


title: Full duplex device to device communication in cellular networks

abstract: In this paper, we investigate the performance improvements of single band full duplex device to device communication that can transmit and received on the same frequency band in cellular networks. In cellular networks, two separate frequencies are used to enable simultaneous transmission and reception for half duplex radios. Recently, full duplex radios that allows a wireless node to simultaneously transmit and receive in one frequency band were proposed. It was shown that it was effective for short-range communications. As such, full duplex communication is adequate for device to device (D2D) communication, which is usually a short range communication. Device to device communication is an underlay scheme for cellular networks that enables peer-to-peer local services with limited impact on the primary cellular network. When user devices are closer to each other than the base station, D2D communication can improve the bandwidth efficiency of the communication between the users. When full duplex communication is adopted for D2D communication, it requires only one frequency band for two way communication between the local users. It improves the bandwidth efficiency for D2D communication. We propose a simple full duplex D2D communication protocol and analyze the bandwidth performance gain of the protocol compared to the legacy cellular communication scheme.


title: Optimization of a Cost-Effective “Wire-Plate”-Type ESP for Installation in a Medical Waste Incinerator

abstract: Although research on electrostatic precipitators (ESPs) has studied and analyzed all the technical aspects of this device, their cost is, nowadays, the major constraint for manufacturers and users. Therefore, medical waste incinerators of hospitals in Algeria, as well as municipal waste incinerators, operate, in most cases, without flue gas filtration system due to the high costs that requires the installation of a cleaning system. This constraint is reflected in the Maghreb and African countries. The objective of this paper is to show that it is possible to build up a cost-efficient ESP, including a high-voltage power supply made up of a static converter and a step-up ferrite transformer. A home-made “wire-plate”-type half-scale prototype ESP was designed and served to optimize the filtration efficiency according to the interelectrode distance and to determine the optimum voltage to be applied without risk of breakdown.


title: An efficient FPGA-Based architecture for convolutional neural networks

abstract: The goal of this paper is to implement an efficient FPGA-based hardware architectures for the design of fast artificial vision systems. The proposed architecture is capable of performing classification operations of a Convolutional Neural Network (CNN) in realtime. To show the effectiveness of the architecture, some design examples such as hand posture recognition, character recognition, and face recognition are provided. Experimental results show that the proposed architecture is well suited for embedded artificial computer vision systems requiring high portability, high computational speed, and accurate classification.


title: The JFK BIG study: the impact of LSVT BIG® on dual task walking and mobility in persons with Parkinson’s disease

abstract: [Purpose] The aim of this study was to test the hypothesis that Lee Silverman Voice Treatment-BIG decreases the negative impact of hypokinesia on dual task performance in persons with Parkinson's disease. [Subjects and Methods] The records of 114 patients with Parkinson's admitted to outpatient rehabilitation at a suburban hospital were reviewed. Demographics and data for 8 outcome measures were extracted for subjects that completed 14 of 16 sessions of BIG. 93 of these subjects had records of pre and post-test Timed Up and Go, Timed Up and Go Motor, and Timed Up and Go Cognitive scores. Average age was 68.4 years (SD=10.6) and average disease duration was 4.9 years (SD=5.3). [Results] Subjects demonstrated statistically significant improvements for Timed Up and Go (3.3 SD=4.5), Timed Up and Go Motor (4.4 SD=5.8) and Timed Up and Go Cognitive (4.7 SD=5.4). Concurrent motor and cognitive performance remained stable. Dual task cost decreased at a statistically significant level for Timed Up and Go Cognitive (7% SD=31%) but not Motor (4% SD=32%). [Conclusion] These findings suggest that cueing strategies associated with LSVT BIG become internalized and decrease the negative impact of hypokinesia on mobility and cognitive performance while performing two tasks simultaneously in persons with Parkinson's.


title: Blast injuries

abstract: Health-care providers are increasingly faced with the possibility of needing to care for people injured in explosions, but can often, however, feel undertrained for the unique aspects of the patient's presentation and management. Although most blast-related injuries (eg, fragmentation injuries from improvised explosive devices and standard military explosives) can be managed in a similar manner to typical penetrating or blunt traumatic injuries, injuries caused by the blast pressure wave itself cannot. The blast pressure wave exerts forces mainly at air-tissue interfaces within the body, and the pulmonary, gastrointestinal, and auditory systems are at greatest risk. Arterial air emboli arising from severe pulmonary injury can cause ischaemic complications-especially in the brain, heart, and intestinal tract. Attributable, in part, to the scene chaos that undoubtedly exists, poor triage and missed diagnosis of blast injuries are substantial concerns because injuries can be subtle or their presentation can be delayed. Management of these injuries can be a challenge, compounded by potentially conflicting treatment goals. This Seminar aims to provide a thorough overview of these unique primary blast injuries and their management.


title: Vocal melody extraction using patch-based CNN

abstract: A patch-based convolutional neural network (CNN) model presented in this paper for vocal melody extraction in polyphonic music is inspired from object detection in image processing. The input of the model is a novel time-frequency representation which enhances the pitch contours and suppresses the harmonic components of a signal. This succinct data representation and the patch-based CNN model enable an efficient training process with limited labeled data. Experiments on various datasets show excellent speed and competitive accuracy comparing to other deep learning approaches.


title: Classification and comparative evaluation of PV panel integrated DC-DC converter concepts

abstract: The strings of photovoltaic panels have a significantly reduced power output when mismatch between the panels occurs, as, e.g., caused by partial shading. With mismatch, either the panel-integrated diodes are bypassing the shaded panels if the string is operated at the current level of the unshaded panels, or some power of the unshaded panels is lost if the string current is reduced to the level of the shaded panels. With the implementation of dc-dc converters on panel level, the maximum available power can be extracted from each panel regardless of any mismatch. In this paper, different concepts of PV panel-integrated dc-dc converters are presented and their suitability for panel integration is evaluated. The buck-boost converter is identified as the most promising concept and an efficiency/power density ( η- ρ) Pareto optimization of this topology is shown. Based on the optimization results, two 275 W converter prototypes with either Silicon MOSFETs with a switching frequency of 100 kHz or gallium nitride FETs with a switching frequency of 400 kHz are designed for an input voltage range of 15 to 45 V and an output voltage range of 10 to 100 V. The theoretical considerations are verified by efficiency measurements which are compared to the characteristics of a commercial panel-integrated converter.


title: A 100-nW Sensitive RF-to-DC CMOS Rectifier for Energy Harvesting Applications

abstract: A 100-nW sensitive differential drive CMOS RF-DC converter implemented in a 0.18 µm technology is developed. The circuit is meant to be used as a bootstrap or start-up circuit in an energy harvesting application. The 66-stage rectifier is tapered for optimal performance. Driving a 10 MO load, the circuit has a measured output greater than 100 mV, for an input power of 100 nW at 350 MHz. For an input power of 100 µW at 350 MHz, the circuit is measured to have an output of 1.25 V, for an output load of 10 MO. Measurement results include balun and matching network losses. For infinite output resistive loads, the circuit is simulated to have an output greater than 1 V, for input powers larger than-30 dBm.


title: Application of Artificial Intelligence (AI) in Search Engine Optimization (SEO)

abstract: This article discusses the application of artificial intelligence in the activities of Search Engine Optimization (SEO). Artificial intelligence is segmented into three methods: evolutionary computation, fuzzy logic, and classifiers and statistical models. Based on this division, the author seeks for scientific articles that describe the forms of application of artificial intelligence in SEO in the literature. Result obtained a number of prototypes such as Polidoxa, Fuzzy Inference System, commercial packages (SPSS Clementine and SearchDex Hyperloop), Support Vector Machine application, and the application of K-Nearest Neighbor Algorithm. Search efforts are constrained by the confidentiality of the algorithm used by SEO companies as well as from the search engines themselves.


title: Pre-print version The Double Role of Ontologies in Information Science Research

abstract: In philosophy, Ontology is the basic description of things in the world. In information science, an ontology refers to an engineering artifact, constituted by a specific vocabulary used to describe a certain reality. Ontologies have been proposed for validating both conceptual models and conceptual schemas; however, these roles are quite dissimilar. In this article, we show that ontologies can be better understood if we classify the different uses of the term as it appears in the literature. First, we explain Ontology (upper case O) as used in Philosophy. Then, we propose a differentiation between ontologies of information systems and ontologies for information systems. All three concepts have an important role in information science. We clarify the different meanings and uses of Ontology and ontologies through a comparison of research by Wand and Weber and by Guarino in ontology-driven information systems. The contributions of this article are twofold: (a) It provides a better understanding of what ontologies are, and (b) it explains the double role of ontologies in information science research.


title: Incomplete Label Multi-task Deep Learning for Spatio-temporal Event Subtype Forecasting

abstract: Due to the potentially significant benefits for society, forecasting spatio-temporal societal events is currently attracting considerable attention from researchers. Beyond merely predicting the occurrence of future events, practitioners are now looking for information about specific subtypes of future events in order to allocate appropriate amounts and types of resources to manage such events and any associated social risks. However, forecasting event subtypes is far more complex than merely extending binary prediction to cover multiple classes, as 1) different locations require different models to handle their characteristic event subtype patterns due to spatial heterogeneity; 2) historically, many locations have only experienced a incomplete set of event subtypes, thus limiting the local model’s ability to predict previously “unseen” subtypes; and 3) the subtle discrepancy among different event subtypes requires more discriminative and profound representations of societal events. In order to address all these challenges concurrently, we propose a Spatial Incomplete Multi-task Deep leArning (SIMDA) framework that is capable of effectively forecasting the subtypes of future events. The new framework formulates spatial locations into tasks to handle spatial heterogeneity in event subtypes, and learns a joint deep representation of subtypes across tasks. Furthermore, based on the “first law of geography”, spatiallyclosed tasks share similar event subtype patterns such that adjacent tasks can share knowledge with each other effectively. Optimizing the proposed model amounts to a new nonconvex and strongly-coupled problem, we propose a new algorithm based on Alternating Direction Method of Multipliers (ADMM) that can decompose the complex problem into subproblems that can be solved efficiently. Extensive experiments on six real-world datasets demonstrate the effectiveness and efficiency of the proposed model.


title: Neural-Symbolic Learning and Reasoning: A Survey and Interpretation

abstract: The study and understanding of human behaviour is relevant to computer science, artificial intelligence, neural computation, cognitive science, philosophy, psychology, and several other areas. Presupposing cognition as basis of behaviour, among the most prominent tools in the modelling of behaviour are computational-logic systems, connectionist models of cognition, and models of uncertainty. Recent studies in cognitive science, artificial intelligence, and psychology have produced a number of cognitive models of reasoning, learning, and language that are underpinned by computation. In addition, efforts in computer science research have led to the development of cognitive computational systems integrating machine learning and automated reasoning. Such systems have shown promise in a range of applications, including computational biology, fault diagnosis, training and assessment in simulators, and software verification. This joint survey reviews the personal ideas and views of several researchers on neural-symbolic learning and reasoning. The article is organised in three parts: Firstly, we frame the scope and goals of neural-symbolic computation and have a look at the theoretical foundations. We then proceed to describe the realisations of neural-symbolic computation, systems, and applications. Finally we present the challenges facing the area and avenues for further research.


title: Cholesterol effectively blocks entry of flavivirus

abstract: Japanese encephalitis virus (JEV) and dengue virus serotype 2 (DEN-2) are enveloped flaviviruses that enter cells through receptor-mediated endocytosis and low pH-triggered membrane fusion and then replicate in intracellular membrane structures. Lipid rafts, cholesterol-enriched lipid-ordered membrane domains, are platforms for a variety of cellular functions. In this study, we found that disruption of lipid raft formation by cholesterol depletion with methyl-β-cyclodextrin or cholesterol chelation with filipin III reduces JEV and DEN-2 infection, mainly at the intracellular replication steps and, to a lesser extent, at viral entry. Using a membrane flotation assay, we found that several flaviviral nonstructural proteins are associated with detergent-resistant membrane structures, indicating that the replication complex of JEV and DEN-2 localizes to the membranes that possess the lipid raft property. Interestingly, we also found that addition of cholesterol readily blocks flaviviral infection, a result that contrasts with previous reports of other viruses, such as Sindbis virus, whose infectivity is enhanced by cholesterol. Cholesterol mainly affected the early step of the flavivirus life cycle, because the presence of cholesterol during viral adsorption greatly blocked JEV and DEN-2 infectivity. Flavirial entry, probably at fusion and RNA uncoating steps, was hindered by cholesterol. Our results thus suggest a stringent requirement for membrane components, especially with respect to the amount of cholesterol, in various steps of the flavivirus life cycle.