title: Analysis, modeling and design of a True Bridgeless Single Stage PFC with galvanic isolation

abstract: Power Factor Correction (PFC) has been established for a long time to fulfill the harmonic standards. To meet the demand for a compact, efficient solution, a so-called True Bridgeless Single Stage PFC was recently introduced. By eliminating the input rectifier the efficiency is significantly improved. In addition, this topology provides galvanic isolation while employing only one single active switch. In this paper a True Bridgeless Single Stage PFC is analyzed, designed and characterized through measurements on a hardware realization. To optimize the converter with respect to efficiency, power density or cost, analytical expressions for all occurring voltages and currents in each component are derived. With the derived small signal model, the current and voltage compensator can be designed optimally, to ensure a stable and fast control behavior. In addition, a non-dissipative clamp circuit is introduced to limit the switch voltage without causing significant losses. The results of the theoretical analysis are verified by simulation and experimental measurements.


title: Efficient design and implement an electrically small HF antenna

abstract: HF small antennas are widely applied in military, mobile, radar and marine activities. In the design of electrically small antennas, there is a tradeoff between its size and parameters. In this paper, an electrically small monopole HF antenna with the height of 116cm, diameter of 19cm and weight of 7kg, covering 1.5 to 30MHz selective was designed, simulated and implemented. The method used in the paper is a capacitive top and inductive center loaded. Suitable resonance at operation frequencies, with desired performance, was achieved. Because of operating at the low frequencies, the bandwidth and radiation efficiency were degraded. These were improved using the lossy and large diameter of the material.


title: ADTool: Security Analysis with Attack-Defense Trees (Extended Version)

abstract: The ADTool is free, open source software assisting graphical modeling and quantitative analysis of security, using attack-defense trees. The main features of the ADTool are easy creation, efficient editing, and automated bottom-up evaluation of security-relevant measures. The tool also supports the usage of attack trees, protection trees and defense trees, which are all particular instances of attack-defense trees.


title: Sindhi Language Processing: A survey

abstract: In this era of information technology, natural language processing (NLP) has become volatile field because of digital reliance of today's communities. The growth of Internet usage bringing the communities, cultures and languages online. In this regard much of the work has been done of the European and east Asian languages, in the result these languages have reached mature level in terms of computational processing. Despite the great importance of NLP science, still most of the South Asian languages are under developing phase. Sindhi language is one of them, which stands among the most ancient languages in the world. The Sindhi language has a great influence on the large community in Sindh province of Pakistan and some states of India and other countries. But unfortunately, it is at infant level in terms of computational processing, because it has not received such attention of language engineering community, due to its complex morphological structure and scarcity of language resources. Therefore, this study has been carried out in order to summarize the existing work on Sindhi Language Processing (SLP) and to explore future research opportunities, also some potential research problems. This paper will be helpful for the researchers in order to find all the information regarding SLP at one place in a unique way.


title: Suppressor of Cytokine Signaling 1 Regulates an Endogenous Inhibitor of a Mast Cell Protease

abstract: Abstract Suppressor of cytokine signaling 1 (SOCS1) is a negative regulator of c-Kit and interleukin-3 (IL-3) receptor signaling. We examined the role of SOCS1 in regulating IL-3-induced cell growth of primary bone marrow-derived mast cells (BMMCs) from SOCS1–/– mice. Instead of showing increased proliferation, SOCS1-deficient BMMCs responded poorly to IL-3 and stem cell factor. SOCS1–/– BMMCs showed increased apoptosis and defective cell cycle entry. We show that the growth retardation of SOCS1–/– BMMCs was due to a cell intrinsic defect. Protein tyrosine phosphorylation following IL-3 stimulation was markedly diminished in SOCS1–/– BMMCs. Intriguingly, JAK2 and STAT5 proteins were selectively diminished in SOCS1–/– BMMCs, which also showed lower molecular mass products of p85 and Vav suggesting proteolytic degradation. Incubation of the SOCS1–/– BMMC lysate with STAT5, p85, and Vav immunoprecipitated from SOCS1+/+ cells directly demonstrated the dysregulated proteolytic activity in SOCS1–/– BMMCs. The proteolytic activity in SOCS1–/– BMMCs was selectively inhibited by phenylmethylsulfonyl fluoride and soybean trypsin inhibitor, suggesting that the protease regulated by SOCS1 is a tryptase. The dysregulated tryptase in SOCS1–/– BMMCs is unlikely to be mMCP6 or mMCP7, because the enzyme activity was not inhibited by Polybrene but was inhibited by normal mouse plasma. SOCS1+/+ BMMC lysate inhibited the proteolytic activity present in SOCS1–/– BMMC lysate, indicating that SOCS1–/– BMMCs lack an endogenous protease inhibitor. These results show that SOCS1 is required for the expression and/or stability of an endogenous protease inhibitor, which protects mast cells from their own proteolytic enzymes.


Microstrip Bandpass Filter for Ultra-Wideband Direct-Conversion Receiver ( 6-10 . 6 Ghz ) A


title: Joint Representation and Truncated Inference Learning for Correlation Filter based Tracking

abstract: Correlation filter (CF) based trackers generally include two modules, i.e., feature representation and on-line model adaptation. In existing off-line deep learning models for CF trackers, the model adaptation usually is either abandoned or has closed-form solution to make it feasible to learn deep representation in an end-to-end manner. However, such solutions fail to exploit the advances in CF models, and cannot achieve competitive accuracy in comparison with the state-of-the-art CF trackers. In this paper, we investigate the joint learning of deep representation and model adaptation, where an updater network is introduced for better tracking on future frame by taking current frame representation, tracking result, and last CF tracker as input. By modeling the representor as convolutional neural network (CNN), we truncate the alternating direction method of multipliers (ADMM) and interpret it as a deep network of updater, resulting in our model for learning representation and truncated inference (RTINet). Experiments demonstrate that our RTINet tracker achieves favorable tracking accuracy against the state-of-the-art trackers and its rapid version can run at a real-time speed of 24 fps. The code and pre-trained models will be publicly available at https://github.com/tourmaline612/RTINet.


title: An inference-based policy gradient method for learning options

abstract: In the pursuit of increasingly intelligent learning systems, abstraction plays a vital role in enabling sophisticated decisions to be made in complex environments. The options framework provides formalism for such abstraction over sequences of decisions. However most models require that options be given a priori, presumably specified by hand, which is neither efficient, nor scalable. Indeed, it is preferable to learn options directly from interaction with the environment. Despite several efforts, this remains a difficult problem: many approaches require access to a model of the environmental dynamics, and inferred options are often not interpretable, which limits our ability to explain the system behavior for verification or debugging purposes. In this work we develop a novel policy gradient method for the automatic learning of policies with options. This algorithm uses inference methods to simultaneously improve all of the options available to an agent, and thus can be employed in an off-policy manner, without observing option labels. Experimental results show that the options learned can be interpreted. Further, we find that the method presented here is more sample efficient than existing methods, leading to faster and more stable learning of policies with options.


title: Canonical Time Warping for Alignment of Human Behavior

abstract: Alignment of time series is an important problem to solve in many scientific disciplines. In particular, temporal alignment of two or more subjects performing similar activities is a challenging problem due to the large temporal scale difference between human actions as well as the inter/intra subject variability. In this paper we present canonical time warping (CTW), an extension of canonical correlation analysis (CCA) for spatio-temporal alignment of human motion between two subjects. CTW extends previous work on CCA in two ways: (i) it combines CCA with dynamic time warping (DTW), and (ii) it extends CCA by allowing local spatial deformations. We show CTW's effectiveness in three experiments: alignment of synthetic data, alignment of motion capture data of two subjects performing similar actions, and alignment of similar facial expressions made by two people. Our results demonstrate that CTW provides both visually and qualitatively better alignment than state-of-the-art techniques based on DTW.


title: Angle-of-arrival localization based on antenna arrays for wireless sensor networks q

abstract: Among the large number of contributions concerning the localization techniques for wireless sensor networks (WSNs), there is still no simple, energy and cost efficient solution suitable in outdoor scenarios. In this paper, a technique based on antenna arrays and angle-of-arrival (AoA) measurements is carefully discussed. While the AoA algorithms are rarely considered for WSNs due to the large dimensions of directional antennas, some system configurations are investigated that can be easily incorporated in pocket-size wireless devices. A heuristic weighting function that enables decreasing the location errors is introduced. Also, the detailed performance analysis of the presented system is provided. The localization accuracy is validated through realistic Monte-Carlo simulations that take into account the specificity of propagation conditions in WSNs as well as the radio noise effects. Finally, trade-offs between the accuracy, localization time and the number of anchors in a network are addressed.


title: Field programmable gate array based control of Dual Active Bridge DC/DC Converter for the UNIFLEX-PM project

abstract: This paper presents a Field Programmable Gate Array (FPGA) implemented control system for a Dual Active Bridge (DAB) DC/DC Converter. This implementation was required during the UNIFLEX-PM project to reduce the required computational burden on the Digital Signal Processor (DSP) used for the grid power flow control algorithms. The presented design is verified using one of the 25kVA Dual Active Bridge DC/DC Converters from the UNIFLEX-PM experimental prototype.


title: MDMA enhances emotional empathy and prosocial behavior

abstract: 3,4-Methylenedioxymethamphetamine (MDMA, �ecstasy�) releases serotonin and norepinephrine. MDMA is reported to produce empathogenic and prosocial feelings. It is unknown whether MDMA in fact alters empathic concern and prosocial behavior. We investigated the acute effects of MDMA using the Multifaceted Empathy Test (MET), dynamic Face Emotion Recognition Task (FERT) and Social Value Orientation (SVO) test. We also assessed effects of MDMA on plasma levels of hormones involved in social behavior using a placebo-controlled, double-blind, random-order, cross-over design in 32 healthy volunteers (16 women). MDMA enhanced explicit and implicit emotional empathy in the MET and increased prosocial behavior in the SVO test in men. MDMA did not alter cognitive empathy in the MET but impaired the identification of negative emotions, including fearful, angry and sad faces, in the FERT, particularly in women. MDMA increased plasma levels of cortisol and prolactin, which are markers of serotonergic and noradrenergic activity, and of oxytocin, which has been associated with prosocial behavior. In summary, MDMA sex-specifically altered the recognition of emotions, emotional empathy and prosociality. These effects likely enhance sociability when MDMA is used recreationally and may be useful when MDMA is administered in conjunction with psychotherapy in patients with social dysfunction or post-traumatic stress disorder.


title: A new approach to intrusion detection using Artificial Neural Networks and fuzzy clustering

abstract: Many researches have argued that Artificial Neural Networks (ANNs) can improve the performance of intrusion detection systems (IDS) when compared with traditional methods. However for ANN-based IDS, detection precision, especially for low-frequent attacks, and detection stability are still needed to be enhanced. In this paper, we propose a new approach, called FC-ANN, based on ANN and fuzzy clustering, to solve the problem and help IDS achieve higher detection rate, less false positive rate and stronger stability. The general procedure of FC-ANN is as follows: firstly fuzzy clustering technique is used to generate different training subsets. Subsequently, based on different training subsets, different ANN models are trained to formulate different base models. Finally, a meta-learner, fuzzy aggregation module, is employed to aggregate these results. Experimental results on the KDD CUP 1999 dataset show that our proposed new approach, FC-ANN, outperforms BPNN and other well-known methods such as decision tree, the naive Bayes in terms of detection precision and detection stability.


title: GaAs switched capacitor DC-to-DC converter

abstract: A switched capacitor DC-to-DC negative converter fabricated in GaAs MESFET technology is introduced in this paper. The converter has an oscillator that runs at 250 kHz, and requires two external capacitors, 0.1 and 1 /spl mu/F. The converter runs off a wide range of supply voltage, 2 to 10 V, and has a typical output impedance of 75 /spl Omega/. A typical open circuit voltage conversion efficiency of 99.6% is achieved. The circuit can be integrated with other GaAs circuits to provide an on-chip negative supply. Measured, simulated and analytical results are introduced in this paper.


title: The Adaptive Hough Transform

abstract: We introduce the Adaptive Hough Transform, AHT, as an efficient way of implementing the Hough Transform, HT, method for the detection of 2-D shapes. The AHT uses a small accumulator array and the idea of a flexible iterative "coarse to fine" accumulation and search strategy to identify significant peaks in the Hough parameter spaces. The method is substantially superior to the standard HT implementation in both storage and computational requirements. In this correspondence we illustrate the ideas of the AHT by tackling the problem of identifying linear and circular segments in images by searching for clusters of evidence in 2-D parameter spaces. We show that the method is robust to the addition of extraneous noise and can be used to analyze complex images containing more than one shape.


title: Learning Deep Face Representation

abstract: Face representation is a crucial step of face recognition systems. An optimal face representation should be discriminative, robust, compact, and very easy-to-implement. While numerous hand-crafted and learning-based representations have been proposed, considerable room for improvement is still present. In this paper, we present a very easy-to-implement deep learning framework for face representation. Our method bases on a new structure of deep network (called Pyramid CNN). The proposed Pyramid CNN adopts a greedy-filter-and-down-sample operation, which enables the training procedure to be very fast and computation-efficient. In addition, the structure of Pyramid CNN can naturally incorporate feature sharing across multi-scale face representations, increasing the discriminative ability of resulting representation. Our basic network is capable of achieving high recognition accuracy ($85.8\%$ on LFW benchmark) with only 8 dimension representation. When extended to feature-sharing Pyramid CNN, our system achieves the state-of-the-art performance ($97.3\%$) on LFW benchmark. We also introduce a new benchmark of realistic face images on social network and validate our proposed representation has a good ability of generalization.


title: Non-parametric model for background subtraction

abstract: Background subtraction is a method typically used to segment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a novel non-parametric background model and a background subtraction approach. The model can handle situations where the background of the scene is cluttered and not completely static but contains small motions such as tree branches and bushes. The model estimates the probability of observing pixel intensity values based on a sample of intensity values for each pixel. The model adapts quickly to changes in the scene which enables very sensitive detection of moving targets. We also show how the model can use color information to suppress detection of shadows. The implementation of the model runs in real-time for both gray level and color imagery. Evaluation shows that this approach achieves very sensitive detection with very low false alarm rates.


Smart Parking System Based On Reservation


title: Spatial frequency, phase, and the contrast of natural images

abstract: We examined contrast sensitivity and suprathreshold apparent contrast with natural images. The spatial-frequency components within single octaves of the images were removed (notch filtered), their phases were randomized, or the polarity of the images was inverted. Of Michelson contrast, root-mean-square (RMS) contrast, and band-limited contrast, RMS contrast was the best index of detectability. Negative images had lower apparent contrast than their positives. Contrast detection thresholds showed spatial-frequency-dependent elevation following both notch filtering and phase randomization. The peak of the spatial-frequency tuning function was approximately 0.5-2 cycles per degree (c/deg). Suprathreshold contrast matching functions also showed spatial-frequency-dependent contrast loss for both notch-filtered and phase-randomized images. The peak of the spatial-frequency tuning function was approximately 1-3 c/deg. There was no detectable difference between the effects of phase randomization and notch filtering on contrast sensitivity. We argue that these observations are consistent with changes in the activity within spatial-frequency channels caused by the higher-order phase structure of natural images that is responsible for the presence of edges and specularities.


Using Virtual Laboratories as Interactive Textbooks: Studies on Blended Learning in Biotechnology Classrooms


title: Emerging Frameworks for Tangible User Interfaces

abstract: We present steps toward a conceptual framework for tangible user interfaces. We introduce the MCRpd interaction model for tangible interfaces, which relates the role of physical and digital representations, physical control, and underlying digital models. This model serves as a foundation for identifying and discussing several key characteristics of tangible user interfaces. We identify a number of systems exhibiting these characteristics, and situate these within 12 application domains. Finally, we discuss tangible interfaces in the context of related research themes, both within and outside of the human-computer interaction domain.


title: Fast Food Intake Increases the Incidence of Metabolic Syndrome in Children and Adolescents: Tehran Lipid and Glucose Study

abstract: The aim of the study was to evaluate the association between fast food consumption and incidence of metabolic syndrome (MetS) and its components among children and adolescents over a 3.6 year follow-up. Dietary data of 424 healthy subjects, aged 6-18 years, was collected using a valid and reliable food frequency questionnaire. Metabolic syndrome was defined according to the Cook et al criteria. Consumption of fast foods including hamburgers, sausages, bologna (beef), and fried potatoes was calculated and further categorized to quartiles. Multiple logistic regression models were used to estimate the incidence of MetS and its components in each quartile of fast food intake. The incidence of MetS was 11.3% after a 3.6 year follow up. In the fully adjusted model, compared to the lowest quartile of fast food intake, individuals in the highest had odds ratios of 2.96 (95% CI: 1.02-8.63; P for trend<0.001), 2.82 (95% CI: 1.01-7.87; P for trend = 0.037), and 2.58 (95% CI: 1.01-6.61; P for trend = 0.009) for incidence of MetS, hypertriglyceridemia, and abdominal obesity, respectively. No significant association was found between fast food intakes and other components of MetS. Fast food consumption is associated with the incidence of MetS, abdominal obesity, and hypertriglyceridemia in Tehranian children and adolescents.


title: Summarizing court decisions

abstract: In the field of law there is an absolute need for summarizing the texts of court decisions in order to make the content of the cases easily accessible for legal professionals. During the SALOMON and MOSAIC projects we investigated the summarization and retrieval of legal cases. This article presents some of the main findings while integrating the research results of experiments on legal document summarization by other research groups. In addition, we propose novel avenues of research for automatic text summarization, which we currently exploit when summarizing court decisions in the ACILA project. Techniques for automated concept learning and argument recognition are here the most challenging.


title: User Perceptions of an Enterprise Content Management System

abstract: Enterprise Content Management (ECM) is an enterprise wide integrated approach to managing an organization's unstructured information such as documents, email, web pages, portals and other digital assets. ECM systems potentially leverage a knowledge repository to prevent information overload, as well as enable (1) better decision-making and increased efficiencies from enriched information sharing and collaboration; (2) compliance control; (3) lower web publishing costs; and (4) 're-usability' of the content for multiple media. However, these benefits rely on an appropriate corporate taxonomy and relevant metadata that will facilitate search in the repository. Users' perceptions of the ECM system are important since they will determine acceptance of the technology. This study assesses the factors that lead to user acceptance of an ECM system. Findings reveal the importance of cognitive engagement with the technology. The paper's main contribution is to show how a document perspective provides insights on the surprising results and highlight the importance of including the cognitive engagement construct in technology acceptance studies.


Scatter search approach for solving a home care nurses routing and scheduling problem


title: Mitigation of Loopback Self-Interference in Full-Duplex MIMO Relays

abstract: Full-duplex relaying is more spectrally efficient than half-duplex relaying as only one channel use is needed per two hops. However, it is crucial to minimize relay self-interference to render full duplex feasible. For this purpose, we analyze a broad range of multiple-input multiple-output (MIMO) mitigation schemes: natural isolation, time-domain cancellation, and spatial suppression. Cancellation subtracts replicated interference signal from the relay input while suppression reserves spatial dimensions for receive and transmit filtering. Spatial suppression can be achieved by antenna subset selection, null-space projection, i.e., receiving and transmitting in orthogonal subspaces, or joint transmit and receive beam selection to support more spatial streams by choosing the minimum eigenmodes for overlapping subspaces. In addition, minimum mean square error (MMSE) filtering can be employed to maintain the desired signal quality, which is inherent for cancellation, and the combination of time- and spatial-domain processing may be better than either alone. Targeting at minimal interference power, we solve optimal filters for each scheme in the cases of joint, separate and independent design. The performance of mitigation schemes is evaluated and compared by simulations. The results confirm that self-interference can be mitigated effectively also in the presence of imperfect side information.


title: Human Detection using HOG Features of Head and Shoulder Based on Depth Map

abstract: Conventional moving objects detection and tracking using visible light image was often affected by the change of moving objects, change of illumination conditions, interference of complex backgrounds, shaking of camera, shadow of moving objects and moving objects of self-occlusion or mutual-occlusion phenomenon. We propose a human detection method using HOG features of head and shoulder based on depth map and detecting moving objects in particular scene in this paper. In-depth study on Kinect to get depth map with foreground objects. Through the comprehensive analysis based on distance information of the moving objects segmentation extraction removal diagram of background information, by analyzing and comprehensively applying se g mentation a method based on distance information to extract pedestrian’s Histograms of Oriented Gradients (HOG) features of head and shoulder [1] , then make a comparison to the SVM classifier. SVM classifier isolate regions of interest (features of head and shoulder) and judge to achieve real-time detection of objects (pedestrian). The human detection method by using features of head and shoulder based on depth map is a good solution to the problem of low efficiency and identification in traditional human detection system. T he detection accuracy of our algorithm is approximate at 97.4% and the average time processing per fram e is about 51.76 ms.


title: Control of mode evolution in the multimode optical fiber for reliable evaluation of the multimode polymer optical waveguide

abstract: A standard evaluation method for the multimode polymer optical waveguides is necessary to obtain reliable experimental results. There are several categories of evaluation techniques proposed by the International Electro-technical Commission (IEC). We have developed a simple input launch configuration to control mode evolution in the multimode optical fiber by means of the Encircled Flux (EF) category. Furthermore, we have examined our input launch system by evaluating insertion loss of the multimode polymer optical waveguides. The experimental results demonstrated the insertion loss variation of less than 5 %.


title: Stabilizing video facial landmark detection and tracking via global and local filtering

abstract: Video facial landmark detection and tracking are important computer vision tasks with many applications such as face anti-spoofing, animation and recognition. Most of existing facial landmark detection and tracking methods, however, often suffer from the instability issue which will affect their effectiveness in real world applications. In this work we present a novel solution for stabilized facial landmark detection and tracking in video frames. The proposed solution addresses various kinds of challenging situations and provides effective remedies to solve them. The main contribution within our solution is a novel global and local filtering strategy, which guarantees the robustness of global whole facial shape tracking and the adaptivity of local facial parts tracking. The proposed solution does not depend on specific face detection and alignment algorithms, thus can be easily deployed into existing systems. Extensive experimental evaluations and analyses on different benchmark datasets verify the effectiveness of the proposed approach.


title: UnDEMoN: Unsupervised Deep Network for Depth and Ego-Motion Estimation

abstract: This paper presents an unsupervised deep learning framework called UnDEMoN for estimating dense depth map and 6-DoF camera pose information directly from monocular images. The proposed network is trained using unlabeled monocular stereo image pairs and is shown to provide superior performance in depth and ego-motion estimation compared to the existing state-of-the-art. These improvements are achieved by introducing a new objective function that aims to minimize spatial as well as temporal reconstruction losses simultaneously. These losses are defined using bi-linear sampling kernel and penalized using the Charbonnier penalty function. The objective function, thus created, provides robustness to image gradient noises thereby improving the overall estimation accuracy without resorting to any coarse to fine strategies which are currently prevalent in the literature. Another novelty lies in the fact that we combine a disparity-based depth estimation network with a pose estimation network to obtain absolute scale-aware 6 DOF Camera pose and superior depth map. The effectiveness of the proposed approach is demonstrated through performance comparison with the existing supervised and unsupervised methods on the KITTI driving dataset.


title: Twin-GAN -- Unpaired Cross-Domain Image Translation with Weight-Sharing GANs

abstract: We present a framework for translating unlabeled images from one domain into analog images in another domain. We employ a progressively growing skip-connected encoder-generator structure and train it with a GAN loss for realistic output, a cycle consistency loss for maintaining same-domain translation identity, and a semantic consistency loss that encourages the network to keep the input semantic features in the output. We apply our framework on the task of translating face images, and show that it is capable of learning semantic mappings for face images with no supervised one-to-one image mapping.


title: Steps Toward an Ecology of Infrastructure: Design and Access for Large Information Spaces

abstract: We analyze a large-scale custom software effort, the Worm Community System (WCS), a collaborative system designed for a geographically dispersed community of geneticists. There were complex challenges in creating this infrastructural tool, ranging from simple lack of resources to complex organizational and intellectual communication failures and tradeoffs. Despite high user satisfaction with the system and interface, and extensive user needs assessment, feedback, and analysis, many users experienced difficulties in signing on and use. The study was conducted during a time of unprecedented growth in the Internet and its utilities (1991--1994), and many respondents turned to the World Wide Web for their information exchange. Using Bateson's model of levels of learning, we analyze the levels of infrastructural complexity involved in system access and designer-user communication. We analyze the connection between systems development aimed at supporting specific forms of collaborative knowledge work, local organizational transformation, and large-scale infrastructural change.


title: Autophagy regulates adipose mass and differentiation in mice.

abstract: The relative balance between the quantity of white and brown adipose tissue can profoundly affect lipid storage and whole-body energy homeostasis. However, the mechanisms regulating the formation, expansion, and interconversion of these 2 distinct types of fat remain unknown. Recently, the lysosomal degradative pathway of macroautophagy has been identified as a regulator of cellular differentiation, suggesting that autophagy may modulate this process in adipocytes. The function of autophagy in adipose differentiation was therefore examined in the current study by genetic inhibition of the critical macroautophagy gene autophagy-related 7 (Atg7). Knockdown of Atg7 in 3T3-L1 preadipocytes inhibited lipid accumulation and decreased protein levels of adipocyte differentiation factors. Knockdown of Atg5 or pharmacological inhibition of autophagy or lysosome function also had similar effects. An adipocyte-specific mouse knockout of Atg7 generated lean mice with decreased white adipose mass and enhanced insulin sensitivity. White adipose tissue in knockout mice had increased features of brown adipocytes, which, along with an increase in normal brown adipose tissue, led to an elevated rate of fatty acid, beta-oxidation, and a lean body mass. Autophagy therefore functions to regulate body lipid accumulation by controlling adipocyte differentiation and determining the balance between white and brown fat.


title: Pediatric Audiology Report: Assessment and Revision of an Audiology Report Written to Parents of Children With Hearing Impairment

abstract: OBJECTIVE ::: The purpose of this study was twofold: first, to evaluate a typical pediatric diagnostic audiology report to establish its readability and comprehensibility for parents and, second, to revise the report to improve its readability, as well as the comprehension, sense of self-efficacy, and positive opinions of parent readers. ::: ::: ::: METHOD ::: In Experiment 1, a mock audiology report was evaluated via a readability analysis and semistructured interviews with 5 parents. In Experiment 2, the report was revised using best practice guidelines and parental recommendations from Experiment 1. The revision was verified by randomly assigning 32 new parent participants to read either the revised or unrevised report before their comprehension, self-efficacy, and opinions were assessed. ::: ::: ::: RESULTS ::: In Experiment 1, results confirmed that the report was difficult to read and understand. In Experiment 2, parents who read the revised report had significantly greater comprehension, self-efficacy, and opinion ratings than those who read the unrevised report. In addition, the readability of the revised report was markedly improved compared with the unrevised report. ::: ::: ::: CONCLUSIONS ::: This study shows that pediatric diagnostic audiology reports can be revised to adhere to best practice guidelines and yield improved readability, in addition to improving the comprehension, sense of self-efficacy, and positive opinions of parents of children with hearing impairment.


title: Analysis of the time and workers needed to conduct systematic reviews of medical interventions using data from the PROSPERO registry

abstract: OBJECTIVES ::: To summarise logistical aspects of recently completed systematic reviews that were registered in the International Prospective Register of Systematic Reviews (PROSPERO) registry to quantify the time and resources required to complete such projects. ::: ::: ::: DESIGN ::: Meta-analysis. ::: ::: ::: DATA SOURCES AND STUDY SELECTION ::: All of the 195 registered and completed reviews (status from the PROSPERO registry) with associated publications at the time of our search (1 July 2014). ::: ::: ::: DATA EXTRACTION ::: All authors extracted data using registry entries and publication information related to the data sources used, the number of initially retrieved citations, the final number of included studies, the time between registration date to publication date and number of authors involved for completion of each publication. Information related to funding and geographical location was also recorded when reported. ::: ::: ::: RESULTS ::: The mean estimated time to complete the project and publish the review was 67.3 weeks (IQR=42). The number of studies found in the literature searches ranged from 27 to 92 020; the mean yield rate of included studies was 2.94% (IQR=2.5); and the mean number of authors per review was 5, SD=3. Funded reviews took significantly longer to complete and publish (mean=42 vs 26 weeks) and involved more authors and team members (mean=6.8 vs 4.8 people) than those that did not report funding (both p<0.001). ::: ::: ::: CONCLUSIONS ::: Systematic reviews presently take much time and require large amounts of human resources. In the light of the ever-increasing volume of published studies, application of existing computing and informatics technology should be applied to decrease this time and resource burden. We discuss recently published guidelines that provide a framework to make finding and accessing relevant literature less burdensome.


title: MRI in the evaluation of facial dermal fillers in normal and complicated cases

abstract: OBJECTIVES ::: To ascertain by MRI the presence of filler injected into facial soft tissue and characterize complications by contrast enhancement. ::: ::: ::: METHODS ::: Nineteen volunteers without complications were initially investigated to study the MRI features of facial fillers. We then studied another 26 patients with clinically diagnosed filler-related complications using contrast-enhanced MRI. TSE-T1-weighted, TSE-T2-weighted, fat-saturated TSE-T2-weighted, and TIRM axial and coronal scans were performed in all patients, and contrast-enhanced fat-suppressed TSE-T1-weighted scans were performed in complicated patients, who were then treated with antibiotics. Patients with soft-tissue enhancement and those without enhancement but who did not respond to therapy underwent skin biopsy. Fisher's exact test was used for statistical analysis. ::: ::: ::: RESULTS ::: MRI identified and quantified the extent of fillers. Contrast enhancement was detected in 9/26 patients, and skin biopsy consistently showed inflammatory granulomatous reaction, whereas in 5/17 patients without contrast enhancement, biopsy showed no granulomas. Fisher's exact test showed significant correlation (p < 0.001) between subcutaneous contrast enhancement and granulomatous reaction. Cervical lymph node enlargement (longitudinal axis >10 mm) was found in 16 complicated patients (65 %; levels IA/IB/IIA/IIB). ::: ::: ::: CONCLUSIONS ::: MRI is a useful non-invasive tool for anatomical localization of facial dermal filler; IV gadolinium administration is advised in complicated cases for characterization of granulomatous reaction. ::: ::: ::: KEY POINTS ::: • MRI is a non-invasive tool for facial dermal filler detection and localization. • MRI-criteria to evaluate complicated/non-complicated cases after facial dermal filler injections are defined. • Contrast-enhanced MRI detects subcutaneous inflammatory granulomatous reaction due to dermal filler. • 65 % patients with filler-related complications showed lymph-node enlargement versus 31.5 % without complications. • Lymph node enlargement involved cervical levels (IA/IB/IIA/IIB) that drained treated facial areas.


J.(2000): Principles and Standards for School Mathematics: A Guide for Mathematicians


title: Common neural mechanisms supporting spatial working memory, attention and motor intention

abstract: The prefrontal cortex (PFC) and posterior parietal cortex (PPC) are critical neural substrates for working memory. Neural activity persists in these regions during the maintenance of a working memory representation. Persistent activity, therefore, may be the neural mechanism by which information is temporarily maintained. However, the nature of the representation or what is actually being represented by this persistent activity is not well understood. In this review, we summarize the recent functional magnetic resonance imaging (fMRI) studies conducted in our laboratory that test hypotheses about the nature of persistent activity during a variety of spatial cognition tasks. We find that the same areas in the PFC and PPC that show persistent activity during the maintenance of a working memory representation also show persistent activity during the maintenance of spatial attention and the maintenance of motor intention. Therefore, we conclude that persistent activity is not specific to working memory, but instead, carries information that can be used generally to support a variety of cognitions. Specifically, activity in topographically organized maps of prioritized space in PFC and PPC could be read out to guide attention allocation, spatial memory, and motor planning.


title: Learning Better Embeddings for Rare Words Using Distributional Representations

abstract: There are two main types of word representations: low-dimensional embeddings and high-dimensional distributional vectors, in which each dimension corresponds to a context word. In this paper, we initialize an embedding-learning model with distributional vectors. Evaluation on word similarity shows that this initialization significantly increases the quality of embeddings for rare words.


title: Combining Collaborative Filtering and Semantic Content-Based Approaches to Recommend Web Services

abstract: As the abundance of web services on the World Wide Web increase, designing effective approaches for web service selection and recommendation has become more and more important. In this paper we focus on an approach dynamically offering services that fit the end-users’ interests. To this end, we present a hybrid approach, coupling pure and classic collaborative-filtering methods and a semantic content-based method. On the one hand the former methods are used to automatically recommend services depending on other similar users, based on profiles, preferences and historical experience. On the other hand our semantic content-based approach performs Description Logic based reasoning on semantic descriptions of services, in order to analysis semantic similarity of services. This approach further restricts the potential results and then ensuring a semantic recommendation of services. Finally we discuss its advantages and weaknesses.


title: Dual active bridge buck-boost converter

abstract: A novel isolated bidirectional dc/dc converter suitable for high power applications is proposed. The proposed converter has bidirectional power flow capability with low device ratings for a wide source voltage range. The converter is controlled by varying the duty cycle and phase of the firing pulses, to achieve power flows in both directions and controlled current stresses, resulting in low total device rating (TDR) for a wide source voltage range. The proposed converter can scale to high power and uses system parasitics effectively. As a proof of concept, simulation results and comparison of TDR with conventional solutions based on analytical derivations are presented in a 100 kW level. Design considerations in building DAB3 converter in a 100kW level are presented.


title: Economic security metrics

abstract: This chapter surveys economic approaches for security metrics, among which we could identify two main areas of research. One has its roots in investment and decision theory and is mainly pursued in the field of information technology-oriented business administration. It has yielded a number of quantitative metrics that can be applied as guidelines in investment decisions as well as for the evaluation of existing security measures. The second area of research has ancestors in micro-economics. It deals with market concepts to gather security-relevant information and extract quantitative indicators on information security properties.


title: The influence of prisons on inmate misconduct: A multilevel investigation

abstract: This article presents the results of multilevel analyses of prisoners' misconduct for the population of over 120,000 federal prisoners incarcerated in June 2001. Prior research has focused on individual-level explanations of inmate misconduct, but this study explicitly examines whether prisons vary in their influence on such misconduct. The study demonstrates that model specification makes a difference in our understanding of which variables are related to misconduct, that the type of misconduct is important for understanding the effects of covariates of misconduct, and that results of multilevel models can easily be used to compare the performance of prisons.


title: Modeling cache performance beyond LRU

abstract: Modern processors use high-performance cache replacement policies that outperform traditional alternatives like least-recently used (LRU). Unfortunately, current cache models do not capture these high-performance policies as most use stack distances, which are inherently tied to LRU or its variants. Accurate predictions of cache performance enable many optimizations in multicore systems. For example, cache partitioning uses these predictions to divide capacity among applications in order to maximize performance, guarantee quality of service, or achieve other system objectives. Without an accurate model for high-performance replacement policies, these optimizations are unavailable to modern processors. We present a new probabilistic cache model designed for high-performance replacement policies. It uses absolute reuse distances instead of stack distances, and models replacement policies as abstract ranking functions. These innovations let us model arbitrary age-based replacement policies. Our model achieves median error of less than 1% across several high-performance policies on both synthetic and SPEC CPU2006 benchmarks. Finally, we present a case study showing how to use the model to improve shared cache performance.


title: 2011 Special Issue: A hierarchical ART network for the stable incremental learning of topological structures and associations from noisy data

abstract: In this article, a novel unsupervised neural network combining elements from Adaptive Resonance Theory and topology-learning neural networks is presented. It enables stable on-line clustering of stationary and non-stationary input data by learning their inherent topology. Here, two network components representing two different levels of detail are trained simultaneously. By virtue of several filtering mechanisms, the sensitivity to noise is diminished, which renders the proposed network suitable for the application to real-world problems. Furthermore, we demonstrate that this network constitutes an excellent basis to learn and recall associations between real-world associative keys. Its incremental nature ensures that the capacity of the corresponding associative memory fits the amount of knowledge to be learnt. Moreover, the formed clusters efficiently represent the relations between the keys, even if noisy data is used for training. In addition, we present an iterative recall mechanism to retrieve stored information based on one of the associative keys used for training. As different levels of detail are learnt, the recall can be performed with different degrees of accuracy.


title: The appearance culture between friends and adolescent appearance-based rejection sensitivity

abstract: Abstract Appearance-based rejection sensitivity (appearance-RS) is the tendency to anxiously expect, readily perceive, and overreact to signs of rejection based on one's appearance, and is associated with a number of psychological and social problems (Park, 2007). This study of 380 adolescents ( M age = 13.84) examined a model linking the appearance culture between friends with appearance-RS in adolescent boys and girls, via internalisation of appearance ideals, social comparison, and body dissatisfaction. Gender differences were also tested. Consistent with expectations, appearance-focused characteristics of the friendship context were associated with heightened appearance-RS via internalization of appearance ideals, social comparison, and body dissatisfaction. The appearance-focused friend characteristics that were associated with appearance-RS included exposure to friends' appearance conversations, appearance teasing that caused distress, and perceived pressure to be attractive. Notably, associations rarely differed for boys and girls, with one exception: the association between BMI and body dissatisfaction was stronger in girls than in boys.


title: Collaborative localization in visual sensor networks

abstract: Collaboration in visual sensor networks is essential not only to compensate for the limitations of each sensor node but also to tolerate inaccurate information generated by faulty sensors. This article focuses on the design of a collaborative target localization algorithm that is resilient to sensor faults. We first develop a distributed solution to fault-tolerant target localization based on a so-called certainty map. To tolerate potential sensor faults, a voting mechanism is adopted and a threshold value needs to be specified which is the key to the realization of the distributed solution. Analytical study is conducted to derive the lower and upper bounds for the threshold such that the probability of faulty sensors negatively impacts the localization performance is less than a small value. Second, we focus on the detection and correction of one type of sensor faults, error in camera orientation. We construct a generative image model in each camera based on the detected target location to estimate camera's orientation, detect inaccuracies in camera orientations and correct them before they cascade. Based on results obtained from both simulation and real experiments, we show that the proposed method is effective in localization accuracy as well as fault detection and correction performance.


title: From wafer level to panel level mold embedding

abstract: The constant drive to further miniaturization and heterogeneous system integration leads to a need for new packaging technologies which also allow large area processing and 3D integration with potential for low cost applications. Large area mold embedding technologies and embedding of active components into printed circuit boards (Chip-in-Polymer) are two major packaging trends in this area. Mold embedding is currently done on wafer level, typically with diameters of 8“ to 12”, for future process optimization, PCB technologies offer the potential of real large areas up to 610 × 457 mm2. For mold embedding as e.g. for fan-out wafer level packaging compression molding equipment is used in combination with liquid, granular or sheet epoxy molding compounds, with the boundary condition, that mold processes do need a product specific tool (with defined diameter & thickness). Within this paper the potential of tool-less lamination processes, a standard in PCB manufacturing, is evaluated. Lamination is done in panel format using well-known molding compounds from wafer level compression molding. To evaluate the potential of today's encapsulants for large area embedding processes, different liquid, granular and sheet molding compounds have been intensively evaluated on their processability, on process & material induced die shift and on resulting warpage - all on panel level. Acting as an interconnection layer, PCB based redistribution technologies using lamination of resin coated copper (RCC) films are used. Within the paper, different RCC materials are introduced and discussed concerning their reliability potential based on the available layer thicknesses and thermo-mechanical material properties. The feasibility of the proposed technologies is demonstrated using a two chip package. Dies are embedded in panel size by lamination technologies. Subsequently the wiring is done by lamination of an RCC film over the embedded components and on the panel backside for double sided redistribution. In a process flow also similar to conventional PCB manufacturing μvias to the die pads and through mold vias are drilled using a UV laser and are metalized by Cu-electroplating in one step. This way dies are connected to the front copper layer as well as front to backside of the panel. Conductor lines and pads are formed by Cu etching. Finally, a solder mask and a solderable surface finish are applied. If solder depots are necessary, e.g. for BGA packages, those can be applied by solder balling equipment - either by printing or by preform attach. In summary this paper describes the potential to move from wafer level to panel level mold embedding technology in combination with PCB based redistribution processes. The technology described offers a cost effective packaging solution for e.g. single chip packages as well as for future sensor/ASIC systems or processor/memory stacks in volume production.


title: Global $H_\infty$ Consensus of Multi-Agent Systems with Lipschitz Nonlinear Dynamics

abstract: This paper addresses the global consensus problems of a class of nonlinear multi-agent systems with Lipschitz nonlinearity and directed communication graphs, by using a distributed consensus protocol based on the relative states of neighboring agents. A two-step algorithm is presented to construct a protocol, under which a Lipschitz multi-agent system without disturbances can reach global consensus for a strongly connected directed communication graph. Another algorithm is then given to design a protocol which can achieve global consensus with a guaranteed $H_\infty$ performance for a Lipschitz multiagent system subject to external disturbances. The case with a leader-follower communication graph is also discussed. Finally, the effectiveness of the theoretical results is demonstrated through a network of single-link manipulators.


title: Controlling of Electrical Power System Network by using SCADA

abstract: Due to rapid development in automation system, the remote operation, control and monitoring are necessary for any modern system. The SCADA (Supervisory Control and Data Acquisition) provides this remote operation, control and monitoring for industrial automation. The SCADA is also widely used for overall operation of modern power system. The application of SCADA is still new in Bangladesh specially in power system. This study is about the application of SCADA in overall operation, control and monitoring of transmission and distribution electrical power system network of Dhaka city, Bangladesh. DPDC (Dhaka Power Distribution Company Limited) is the authority which is managing the transmission and distribution network of Dhaka city, Bangladesh. The 132 and 33KV circuit breakers of power system network of Dhaka city are generally operated through the SCADA system for uninterrupted power supply to the consumers. The daily operation, load management and system faults are monitored by the SCADA which improves the performance of overall system operation of DPDC. The SCADA system comprises of RTU (remote telemetry unit), microwave communication network and RCS (remote control server). The RTU is placed in every substation of the electrical power system network of Dhaka city. The SPIDER software is used for SCADA system of DPDC. The SPIDER uses UNIX based platform .The information for daily operation of the overall power system network of the Dhaka city is stored in the database of RCS, which is the processed by the SPIDER software. The overall scenario of power system network on daily basis is obtained by using this software. The SCADA system helps in managing the overall system of DPDC with minimum supervision and manpower. Moreover it improves the system efficiency.


title: Deep Belief Networks with Feature Selection for Sentiment Classification

abstract: Due to the complexity of human languages, most of sentiment classification algorithms are suffered from a huge-scale dimension of vocabularies which are mostly noisy and redundant. Deep Belief Networks (DBN) tackle this problem by learning useful information in input corpus with their several hidden layers. Unfortunately, DBN is a time-consuming and computationally expensive process for large-scale applications. In this paper, a semi-supervised learning algorithm, called Deep Belief Networks with Feature Selection (DBNFS) is developed. Using our chi-squared based feature selection, the complexity of the vocabulary input is decreased since some irrelevant features are filtered which makes the learning phase of DBN more efficient. The experimental results of our proposed DBNFS shows that the proposed DBNFS can achieve higher classification accuracy and can speed up training time compared with others well-known semi-supervised learning algorithms.


title: The Effect of Context-Based Video Instruction on Learning and Motivation in Online Courses

abstract: The purpose of this study was to investigate the potential of a constructivist approach to context-based video instruction for enhancing learning. To achieve this purpose, the authors examined whet...


title: Wideband Millimeter-Wave Substrate Integrated Waveguide Cavity-Backed Rectangular Patch Antenna

abstract: In this letter, a new type of wideband substrate integrated waveguide (SIW) cavity-backed patch antenna and array for millimeter wave (mmW) are investigated and implemented. The proposed antenna is composed of a rectangular patch with a backed SIW cavity. In order to enhance the bandwidth and radiation efficiency, the cavity is designed to resonate at its TE210 mode. Based on the proposed antenna, a 4 × 4 array is also designed. Both the proposed antenna and array are fabricated with standard printed circuit board (PCB) process, which possess the advantage of easy integration with planar circuits. The measured bandwidth (|S11| ≤ -10 dB) of the antenna element is larger than 15%, and that of the antenna array is about 8.7%. The measured peak gains are 6.5 dBi for the element and 17.8 dBi for the array, and the corresponding simulated radiation efficiencies are 83.9% and 74.9%, respectively. The proposed antenna and array are promising for millimeter-wave applications due to its merits of wide band, high efficiency, low cost, low profile, etc.


title: A brief history of electrical engineering education

abstract: Electrical engineering curricula made their first appearance in the U.S. in the early 1880's as options in physics that aimed to prepare students to enter the new and rapidly growing electrical manufacturing industry. As this industry developed, so did electrical engineering education, and within a decade made a place for itself as an equal among the older engineering departments. The curricula that evolved followed the needs of the industry, and before World War I were concentrated largely on the properties of dc and ac circuits and equipment and associated systems of power distribution. Before World War I, little graduate work was carried on, and what passed in academic institutions for "research" was typically advanced testing. The standard career pattern was to receive a B.S. deggee and then obtain a job where one could learn how practical electrical work was done. After World War I, developments in broadcasting and communication led to the appearance of communication options within electrical engineering departments. Concurrently, students having a special interest in teaching or in research were increasingly encouraged to obtain the master's degree. However, the numbers who did so were small, and practically no electrical engineers sought a doctor's degree. For example, at the Massachussetts Institute of Technology in 1925 there was only one member of that large faculty who held an earned doctorate, while the background of about half of the faculty consisted of a bachelor's degree plus practical experience. Under these circumstances research performed in academic institutions was in most cases superficial, although here and there some significant work was carried on by an unusual professor. When World War II came along and brought into being such new electrical and electronic techniques such as radar, microwaves, control systems, guided missiles, proximity fuses, etc., the electrical engineers were caught unprepared. As a group they had neither the fundamental knowledge required to think creatively about these new concepts, nor the research experience to carry through. Thus most of the great electrical developments of the war were produced not by engineers, but rather by scientists, particularly physicists who had turned engineers for the duration. In the decade after the war, electrical engineering education went throush a complete transformation. Prewar courses were drastically revised. Increased emphasis was placed on fundamentals, including particularly emphasis on physical and mathematical principles underlying electrical engineering. These results were achieved by reducing the time devoted to teaching engineering practice, by eliminating subjects such as surveying that were of little concern to electrical engineering, and by reducing the concentration on 60-cycle power. In addition, master's programs were developed that were direct extensions of the revised bachelor's program, and in time the master's degree became the recommended degree goal of the student who desired to follow a career in technical engineering. Concurrently, the doctor's degree became the objective of those who planned a career in academia or of research in industry, or who wanted training superior to that of their many classmates working for the master's degree. With government funds available, programs of studentfaculty research developed on many campuses that were the equal of the research being carried on in the best industrial laboratories. The combined effect of curriculum changes, more students carrying on graduate work, the existence of university research laboratories of the highest caliber with this research led by well-trained faculty aided by doctoral and master's candidates, has completely changed both the character and intellectual level of eletrical engineering on the campus. This is illustrated by the fact that in a 1969 survey of a representative group of major high technology firms, 82 percent agreed with the statement that "Engineers now learn enough science and mathematics so that they can adequately fill positions once occupied only by physicists." If another world emergency should arise, the electrical engineers will this time be ready to carry their share of the leadership.


Patent Strategy for Researchers and Research Managers


title: Control of lower limb exoskeleton for elderly assistance on basic mobility tasks

abstract: This paper presents the modelling, simulation and control of a lower limbs exoskeleton devices whose aim is to assist elderly people during standing-up and walking tasks. A humanoid and actuated exoskeleton frames were modelled in Solid Works and assembled in Visual Nastran 4D virtual environment. Control of exoskeletons actuators by means of PID and fuzzy controllers, together with a finite state machine, was designed. Simulations of the humanoid wearing an exoskeleton to perform the mentioned tasks, using controllers with set and adaptive orientation references as input, were performed. It is assumed that the humanoid, representing an old person, is only capable to provide 70% of the required torque, therefore the exoskeleton must supply 30% to complete the motions. With the aid of exoskeleton devices, the elderly will be able to perform motions of a physically able people. Optimization of fuzzy controller parameters for walking motion was done using SDA. The exoskeleton succeeded on assisting standing-up and walking motions but research is still needed to improve the performance and adaptability of the system.


Etiology and outcomes of anuria in acute kidney injury: a single center study


title: A Review on Fault-Tolerant Control for Unmanned Aerial Vehicles (UAVs)

abstract: The growing number of Unmanned Aerial Vehicles (UAVs) is considerable in the last decades. Many flight test scenarios, including single and multi-vehicle formation flights, are demonstrated using different control algorithms with different test platforms. In this paper, we present a brief literature review on the development and key issues of current researches in the field of Fault-Tolerant Control (FTC) applied to UAVs. It consists of various intelligent or hierarchical control architectures for a single vehicle or a group of UAVs in order to provide potential solutions for tolerance to the faults, failures or damages in relevant to UAV components during flight. Among various UAV test-bed structures, a sample of every class of UAVs, including single-rotor, quadrotor, and fixed-wing types, are selected and briefly illustrated. Also, a short description of terms, definitions, and classifications of fault-tolerant control systems (FTCS) is presented before the main contents of review.


title: Automatic Prediction of Friendship via Multi-model Dyadic Features

abstract: In this paper we focus on modeling friendships between humans as a way of working towards technology that can initiate and sustain a lifelong relationship with users. We do this by predicting friendship status in a dyad using a set of automatically harvested verbal and nonverbal features from videos of the interaction of students in a peer tutoring study. We propose a new computational model used to model friendship status in our data, based on a group sparse model (GSM) with L2,1 norm which is designed to accommodate the sparse and noisy properties of the multi-channel features. Our GSM model achieved the best overall performance compared to a non-sparse linear model (NLM) and a regular sparse linear model (SLM), as well as outperforming human raters. Dyadic features, such as number and length of conversational turns and mutual gaze, in addition to low level features such as F0 and gaze at task, were found to be good predictors of friendship status.


title: Equipment failures caused by power quality disturbances

abstract: This paper provides insight into a failure mechanism that impacts a broad range of industrial equipment. Voltage surges have often been blamed for unexplained equipment failure in the field. Extensive voltage monitoring data suggests that voltage sags occur much more frequently than voltage surges, and that current surges that accompany voltage sag recovery may be the actual culprit causing equipment damage. A serious limitation in equipment specification is highlighted, pointing to what is possibly the root-cause for a large percentage of unexplained equipment field failures. This paper also outlines the need for a standard governing the behavior of equipment under voltage sags, and suggests solutions to protect existing equipment in the field.


title: Emotion recognition through wireless signal

abstract: Emotion Recognition has expanding significance in helping human-PC collaboration issues. It is a difficult task to understand how other people feel but it becomes even worse to perceive these emotions through a computer. With the advancement in technology and increase in application of artificial intelligence, it has become a necessity to automatically recognize the emotions of the user for the human-computer interactions. The need for emotion recognition keeps increasing and it has become applicable in various fields now days. This paper explores the way to recognize different human emotions from our body through wireless signals.


title: A Role for the Superior Colliculus in Decision Criteria

abstract: Summary Simple decisions arise from the evaluation of sensory evidence. But decisions are determined by more than just evidence. Individuals establish internal decision criteria that influence how they respond. Where or how decision criteria are established in the brain remains poorly understood. Here, we show that neuronal activity in the superior colliculus (SC) predicts changes in decision criteria. Using a novel "Yes-No" task that isolates changes in decision criterion from changes in decision sensitivity, and computing neuronal measures of sensitivity and criterion, we find that SC neuronal activity correlates with the decision criterion regardless of the location of the choice report. We also show that electrical manipulation of activity within the SC produces changes in decisions consistent with changes in decision criteria and are largely independent of the choice report location. Our correlational and causal results together provide strong evidence that SC activity signals the position of a decision criterion. Video Abstract


title: Reviewing the flipped classroom research: reflections for computer science education

abstract: Recent technical and infrastructural developments posit flipped (or inverted) classroom approaches ripe for exploration. Flipped classroom approaches have students use technology to access the lecture and other instructional resources outside the classroom in order to engage them in active learning during in-class time. Scholars and educators have reported a variety of outcomes of a flipped approach to instruction; however, the lack of a summary from these empirical studies prevents stakeholders from having a clear view of the benefits and challenges of this style of instruction. The purpose of this article is to provide a review of the flipped classroom approach in order to summarize the findings, to guide future studies, and to reflect the major achievements in the area of Computer Science (CS) education. 32 peer-reviewed articles were collected from a systematic literature search and analyzed based on a categorization of their main elements. The results of this survey show the direction of flipped classroom research during recent years and summarize the benefits and challenges of adopting a flipped approach in the classroom. Suggestions for future research include: describing in-detail the flipped approach; performing controlled experiments; and triangulating data from diverse sources. These future research efforts will reveal which aspects of a flipped classroom work better and under which circumstances and student groups. The findings will ultimately allow us to form best practices and a unified framework for guiding/assisting educators who want to adopt this teaching style.


title: E-commerce Recommendation with Personalized Promotion

abstract: Most existing e-commerce recommender systems aim to recommend the right products to a consumer, assuming the properties of each product are fixed. However, some properties, including price discount, can be personalized to respond to each consumer's preference. This paper studies how to automatically set the price discount when recommending a product, in light of the fact that the price will often alter a consumer's purchase decision. The key to optimizing the discount is to predict consumer's willingness-to-pay (WTP), namely, the highest price a consumer is willing to pay for a product. Purchase data used by traditional e-commerce recommender systems provide points below or above the decision boundary. In this paper we collected training data to better predict the decision boundary. We implement a new e-commerce mechanism adapted from laboratory lottery and auction experiments that elicit a rational customer's exact WTP for a small subset of products, and use a machine learning algorithm to predict the customer's WTP for other products. The mechanism is implemented on our own e-commerce website that leverages Amazon's data and subjects recruited via Mechanical Turk. The experimental results suggest that this approach can help predict WTP, and boost consumer satisfaction as well as seller profit.


title: ITIL-based IT service support process reengineering

abstract: The Information Technology Infrastructure Library ITIL supports best practices, reengineering activities and IT service support processes. ITIL framework only provides recommendations, and companies need to utilize this framework to improve their IT service support processes and establish best practices. This study provides a methodology on how to apply the ITIL framework for evaluating the IT service support processes, its reengineering and alignment to best practices, and subsequent integration into a decision support system framework. A case study approach was used to identify a set of Key Performance Indicators KPI which were monitored by a decision support system DSS for triggering on-going reengineering of IT service support processes. This paper focuses on the implementation of the ITIL guidelines at the operational level, improvement of the service desk, and incident, problem, change, release, and configuration management. It also presents the implementation of the ITIL guidelines at the tactical level for the improvement of the service level, capacity, IT service continuity, service availability, and security management. We conclude by providing recommendations for future research.


title: Automatic text summarization based on sentences clustering and extraction

abstract: Technology of automatic text summarization plays an important role in information retrieval and text classification, and may provide a solution to the information overload problem. Text summarization is a process of reducing the size of a text while preserving its information content. This paper proposes a sentences clustering based summarization approach. The proposed approach consists of three steps: first clusters the sentences based on the semantic distance among sentences in the document, and then on each cluster calculates the accumulative sentence similarity based on the multi-features combination method, at last chooses the topic sentences by some extraction rules. The purpose of present paper is to show that summarization result is not only depends the sentence features, but also depends on the sentence similarity measure. The experimental result on the DUC 2003 dataset show that our proposed approach can improve the performance compared to other summarization methods.


title: A survey on the role of negation in sentiment analysis

abstract: This paper presents a survey on the role of negation in sentiment analysis. Negation is a very common linguistic construction that affects polarity and, therefore, needs to be taken into consideration in sentiment analysis. ::: ::: We will present various computational approaches modeling negation in sentiment analysis. We will, in particular, focus on aspects, such as level of representation used for sentiment analysis, negation word detection and scope of negation. We will also discuss limits and challenges of negation modeling on that task.


title: A video database of moving faces and people

abstract: We describe a database of static images and video clips of human faces and people that is useful for testing algorithms for face and person recognition, head/eye tracking, and computer graphics modeling of natural human motions. For each person there are nine static "facial mug shots" and a series of video streams. The videos include a "moving facial mug shot," a facial speech clip, one or more dynamic facial expression clips, two gait videos, and a conversation video taken at a moderate distance from the camera. Complete data sets are available for 284 subjects and duplicate data sets, taken subsequent to the original set, are available for 229 subjects.


title: Author-Topic over Time (AToT): A Dynamic Users’ Interest Model

abstract: One of the key problems in upgrading information services towards knowledge services is to automatically mine latent topics, users’ interests and their evolution patterns from large-scale S&T literatures. Most of current methods are devoted to either discover static latent topics and users’ interests, or to analyze topic evolution only from intra-features of documents, namely text content without considering directly extra-features of documents such as authors. To overcome this problem, a dynamic users’ interest model for documents using authors and topics with timestamps is proposed, named as Author-Topic over Time (AToT) model, and collapsed Gibbs sampling method is utilized for inferring model parameters. This model is not only able to discover latent topics and users’ interests, but also to mine their changing patterns over time. Finally, the extensive experimental results on NIPS dataset with 1,740 papers indicate that our AToT model is feasible and efficient.


title: A single-base deletion in soybean flavonol synthase gene is associated with magenta flower color

abstract: The Wm locus of soybean [Glycine max (L.) Merr.] controls flower color. Dominant Wm and recessive wm allele of the locus produce purple and magenta flower, respectively. A putative full-length cDNA of flavonol synthase (FLS), gmfls1 was isolated by 5' RACE and end-to-end PCR from a cultivar Harosoy with purple flower (WmWm). Sequence analysis revealed that gmfls1 consisted of 1,208 nucleotides encoding 334 amino acids. It had 59-72% homology with FLS proteins of other plant species. Conserved dioxygenase domains A and B were found in the deduced polypeptide. Sequence comparison between Harosoy and Harosoy-wm (magenta flower mutant of Harosoy; wmwm) revealed that they differed by a single G deletion in the coding region of Harosoy-wm. The deletion changed the subsequent reading frame resulting in a truncated polypeptide consisting of 37 amino acids that lacked the dioxygenase domains A and B. Extracts of E. coli cells expressing gmfls1 of Harosoy catalyzed the formation of quercetin from dihydroquercetin, whereas cell extracts expressing gmfls1 of Harosoy-wm had no FLS activity. Genomic Southern analysis suggested the existence of three to four copies of the FLS gene in the soybean genome. CAPS analysis was performed to detect the single-base deletion. Harosoy and Clark (WmWm) exhibited longer fragments, while Harosoy-wm had shorter fragments due to the single-base deletion. The CAPS marker co-segregated with genotypes at Wm locus in a F(2) population segregating for the locus. Linkage mapping using SSR markers revealed that the Wm and gmfls1 were mapped at similar position in the molecular linkage group F. The above results strongly suggest that gmfls1 represents the Wm gene and that the single-base deletion may be responsible for magenta flower color.


title: Plant regeneration from protoplasts of Musa acuminata cv. Mas (AA) via somatic embryogenesis

abstract: A protocol for plant regeneration from protoplasts of Musa acuminata cv. Mas (AA) via somatic embryogenesis was developed. Viable protoplasts were isolated from embryogenic cell suspensions at a yield of 1.2 × 107 protoplasts/ml packed cell volume (PCV). Liquid and feeder layer culture systems with medium-A and medium-B were used for protoplast culture. In liquid culture system, medium-B was more efficient for inducing cell division (17.5% at 14 days) and colony formation (6.7% at 28 days) than medium-A. However, all protoplast-derived cell colonies (PDCC) obtained from liquid culture system could not develop further. In feeder layer culture system, there was no significant difference between medium-A and medium-B on cell division and colony formation of the cultured protoplasts, and the cell division frequency at 14 days and colony formation frequency at 28 days were 24.5% and 11.2%, respectively, in medium-B. Comparative study on the effects of BAP (2.2 μM, 4.4 μM, 8.8 μM), zeatin (0.4 μM, 0.8 μM, 1.2 μM) and TDZ (0.2 μM, 0.4 μM, 0.6 μM) on embryo formation of PDCC from feeder-layer culture indicated that TDZ was best. TDZ at 0.4 μM induced 7906 mature embryos per ml PCV PDCC, which was 4-fold the frequency as with BAP at 4.4 μM, 7.5-fold as with zeatin at 0.8 μM and 150-fold as control medium (no mentioned cytokinins) after 45 days on M3 medium. About 44% of the mature embryos were converted into plantlets with poor root system after subculture on M4 medium. Root further development of regenerated plantlets was promoted by addition of activated charcoal (AC) to MS basal medium.


title: Optimal Estimation of Piece-Wise Linear Incremental Cost Curves for EDC

abstract: Real-time economic dispatch is performed most efficiently using a Sorted Table Method. This method requires that the incremental cost curve be represented by monotonically increasing piece-wise linear segments. The primary focus of this paper is the development and demonstration of a very practical method by which the number of linear segments and their corresponding "break points". are determined in an optimal manner. The problem of determining break points by manually plotting the IC curve and then applying a series of "educated guesses" is totally eliminated. A weighted least-squares multiple linear regression method is used to calculate the coeff icients of a cubic fuel cost (I/O) curve. A special constraint equation is included to insure that the incremental cost curve exhibits a monotonically increasing characteristic. Numerical examples are included to demonstrate practical results.


title: Conservative pretty printing

abstract: The main purpose of the pretty printing tool, presented here, is not so much the complete reformating of a program but is described better as finding and correcting formating errors.A set of relations is given describing the proper alignment of a piece of code in accordance with its syntactic structure. It is complemented by a simple algorithm to change any given source code to satisfy these relations.The relations are flexible enough to allow a variety of different formating styles while rejecting formating errors, i.e. code that is not formated according to its syntactic structure.Various examples illustrate the ideas, the problems, the goals, and the achievements.


title: On Improving Deep Reinforcement Learning for POMDPs

abstract: Deep Reinforcement Learning (RL) recently emerged as one of the most competitive approaches for learning in sequential decision making problems with fully observable environments, e.g., computer Go. However, very little work has been done in deep RL to handle partially observable environments. We propose a new architecture called Action-specific Deep Recurrent Q-Network (ADRQN) to enhance learning performance in partially observable domains. Actions are encoded by a fully connected layer and coupled with a convolutional observation to form an action-observation pair. The time series of action-observation pairs are then integrated by an LSTM layer that learns latent states based on which a fully connected layer computes Q-values as in conventional Deep Q-Networks (DQNs). We demonstrate the effectiveness of our new architecture in several partially observable domains, including flickering Atari games.


title: LIME: A Method for Low-light IMage Enhancement

abstract: When one captures images in low-light conditions, the images often suffer from low visibility. This poor quality may significantly degrade the performance of many computer vision and multimedia algorithms that are primarily designed for high-quality inputs. In this paper, we propose a very simple and effective method, named as LIME, to enhance low-light images. More concretely, the illumination of each pixel is first estimated individually by finding the maximum value in R, G and B channels. Further, we refine the initial illumination map by imposing a structure prior on it, as the final illumination map. Having the well-constructed illumination map, the enhancement can be achieved accordingly. Experiments on a number of challenging real-world low-light images are present to reveal the efficacy of our LIME and show its superiority over several state-of-the-arts.


title: Grounded Compositional Semantics for Finding and Describing Images with Sentences

abstract: Previous work on Recursive Neural Networks (RNNs) shows that these models can produce compositional feature vectors for accurately representing and classifying sentences or images. However, the sentence vectors of previous models cannot accurately represent visually grounded meaning. We introduce the DT-RNN model which uses dependency trees to embed sentences into a vector space in order to retrieve images that are described by those sentences. Unlike previous RNN-based models which use constituency trees, DT-RNNs naturally focus on the action and agents in a sentence. They are better able to abstract from the details of word order and syntactic expression. DT-RNNs outperform other recursive and recurrent neural networks, kernelized CCA and a bag-of-words baseline on the tasks of finding an image that fits a sentence description and vice versa. They also give more similar representations to sentences that describe the same image.


title: Communication Efficient Coresets for Empirical Loss Minimization

abstract: In this paper, we study the problem of empirical loss minimization with l2-regularization in distributed settings with significant communication cost. Stochastic gradient descent (SGD) and its variants are popular techniques for solving these problems in large-scale applications. However, the communication cost of these techniques is usually high, thus leading to considerable performance degradation. We introduce a novel approach to reduce the communication cost while retaining good convergence properties. The key to our approach is the construction of a small summary of the data, called coreset, at each iteration and solve an easy optimization problem based on the coreset. We present a general framework for analyzing coreset-based optimization and provide interesting insights into existing algorithms from this perspective. We then propose a new coreset construction and provide its convergence analysis for a wide class of problems that include logistic regression and support vector machines. Preliminary experiments show encouraging results for our algorithm on real-world datasets.


title: Introducing FIRESTARTER: A processor stress test utility

abstract: Processor stress test utilities are important tools for a number of different use cases. In particular, cooling systems need to be tested at maximum load in order to ensure that they fulfill their specifications. Additionally, a test system characterization in terms of idle and maximum power consumption is often a prerequisite for energy efficiency research. This creates the need for a simple yet versatile tool that generates near-peak power consumption of compute nodes. While in different research areas tools such as LINPACK and Prime95 are commonly used, these tools are just highly optimized and compute intense routines that solve specific computational problems. As stress test utilities they are unnecessarily hard to use and in many cases unreliable in terms of power consumption maximization. We propose FIRESTARTER, an Open Source tool that is specifically designed to create near-peak power consumption. Our experiments show that this task cannot be achieved with generic high-level language code. We therefore use highly optimized assembly routines that take the specific properties of a given processor microarchitecture into account. A study on four compute nodes with current or last generation x86_64 processors shows that we reliably exceed the power consumption of other stress tests and create very steady power consumption patterns.


title: SpeQuloS: a QoS service for BoT applications using best effort distributed computing infrastructures

abstract: Exploitation of Best Effort Distributed Computing Infrastructures (BE-DCIs) allow operators to maximize the utilization of the infrastructures, and users to access the unused resources at relatively low cost. Because providers do not guarantee that the computing resources remain available to the user during the entire execution of their applications, they offer a diminished Quality of Service (QoS) compared to traditional infrastructures. Profiling the execution of Bag-of-Tasks (BoT) applications on several kinds of BE-DCIs demonstrates that their task completion rate drops near the end of the execution. In this paper, we present the SpeQuloS framework which enhances the QoS of BoT applications executed on BE-DCIs by reducing the execution time, improving its stability, and reporting to users a predicted completion time. SpeQuloS monitors the execution of the BoT on the BE-DCIs, and dynamically supplies fast and reliable Cloud resources when the critical part of the BoT is executed. We present the design and development of the service and several strategies to decide when and how Cloud resources should be provisioned. Performance evaluation using simulations shows that SpeQuloS fulfill its objectives. It speeds-up the execution of BoTs, in the best cases by a factor greater than 2, while offloading less than 2.5% of the workload to the Cloud. We report on preliminary results after a complex deployment as part of the European Desktop Grid Infrastructure.


title: From model to FPGA: Software-hardware co-design for efficient neural network acceleration

abstract: This article consists only of a collection of slides from the author's conference presentation.


title: Approximating the minimum strongly connected subgraph via a matching lower bound

abstract: We present a 3/2-approximation algorithm for the problem of finding a minimum strongly connected spanning subgraph in a given directed graph. As a corollary we obtain a 3/2-approximation algorithm for the more general minimum equivalent digraph problem. The performance of our algorithm is measured against a lower bound obtained from a simple matching problem. The performance guarantee is optimal with respect to the lower bound.


title: A fast iterative nearest point algorithm for support vector machine classifier design

abstract: In this paper we give a new fast iterative algorithm for support vector machine (SVM) classifier design. The basic problem treated is one that does not allow classification violations. The problem is converted to a problem of computing the nearest point between two convex polytopes. The suitability of two classical nearest point algorithms, due to Gilbert, and Mitchell et al., is studied. Ideas from both these algorithms are combined and modified to derive our fast algorithm. For problems which require classification violations to be allowed, the violations are quadratically penalized and an idea due to Cortes and Vapnik and Friess is used to convert it to a problem in which there are no classification violations. Comparative computational evaluation of our algorithm against powerful SVM methods such as Platt's sequential minimal optimization shows that our algorithm is very competitive.


title: Handling requirements dependencies in agile projects: A focus group with agile software development practitioners

abstract: Agile practices on requirements dependencies are a relatively unexplored topic in literature. Empirical studies on it are scarce. This research sets out to uncover concepts that practitioners in companies of various sizes across the globe and in various industries, use for dealing with requirements dependencies in their agile software projects. Concepts were revealed through online focus group research, using an adapted forum for discussion, and grounded theory to analyze the responses. Our study resulted in the following findings: (1) requirements dependencies occur in agile projects and are important to these projects' success just as this is known for `traditional' software projects'; (2) requirements dependencies (i) were considered and treated as part of risk management, (ii) were deemed a responsibility of the individual team members, and (iii) mostly did affect project planning; (3) continuous communication and collaboration - two essential features of any agile method, were found critical to mitigating the risks due to dependencies; (4) a hybrid approach to architecture between agile and plan-driven methods was perceived to yield maximum scalability and help coping with dependencies; (5) `cross-cutting concerns', a category of dependencies, were not uniformly understood in an agile context and require more research.


title: Video based technology for ambient assisted living: A review of the literature

abstract: Ambient assisted living (AAL) has the ambitious goal of improving the quality of life and maintaining independence of older and vulnerable people through the use of technology. Most of the western world will see a very large increase in the number of older people within the next 50 years with limited resources to care for them. AAL is seen as a promising alternative to the current care models and consequently has attracted lots of attention. Recently, a number of researchers have developed solutions based on video cameras and computer vision systems with promising results. However, for the domain to reach maturity, several challenges need to be faced, including the development of systems that are robust in the real-world and are accepted by users, carers and society. In this literature review paper we present a comprehensive survey of the scope of the domain, the existing technical solutions and the challenges to be faced.


title: Synthetic on-line signature generation. Part I: Methodology and algorithms

abstract: The theoretical framework and algorithms of a novel method for the generation of synthetic on-line signatures are presented. This model-based approach combines the spectral analysis of real signatures with the Kinematic Theory of rapid human movements in order to generate totally synthetic specimens. Two different algorithms are also described in order to produce duplicated samples from the synthetic master signatures, so that the generation scheme as a whole is able to produce in a complete automatic fashion huge synthetic databases. Typical examples of synthetic specimens are presented to highlight their human-like appearance. The validation protocol and the test results are presented and discussed in a companion paper.


title: An Eight-Element 2–16-GHz Programmable Phased Array Receiver With One, Two, or Four Simultaneous Beams in SiGe BiCMOS

abstract: This paper presents an eight-element 2–16-GHz programmable phased array (PPA) receiver in a 0.13- $\mu \text{m}$ SiGe BiCMOS with the reconfigurable number of beams and with the digital beamforming (DBF) capabilities. The eight-element chip can be configured for one, two, or four simultaneous beams or as an element-level DBF receiver. This is achieved using reconfigurable input switching and output combining networks with wideband active switches and combiners. The phased array channel results in a 5-b performance at 3–14 GHz (rms error $P_{\text {1 dB}}$ of −20 dBm per channel when all channels are activated. The chip consumes 250 mW per channel, which is competitive knowing its bandwidth and linearity. The DBF function also results in a wideband response with a gain and an NF of 15–16 and 12–13 dB, respectively, and high linearity (input $P_{\text {1 dB}} = -16$ dBm) at 2–16 GHz. The programmable phased array receiver allows a single chip to be used over $S$ -, $C$ -, $X$ -, and $Ku$ -bands for a variety of applications such as satellite communications and point-to-point links. This results in faster and lower-cost phased array development since the same chip and its field-programmable gate array control can be reused from system to system, but with different antenna and grid spacing. The PPA removes the need to develop a different chip for every application and allows the development of phased arrays at commercial scales.


title: Building a SCADA Security Testbed

abstract: SCADA (Supervisory Control and Data Acquisition) systems control and monitor industrial and critical infrastructure functions, such as the electricity, gas, water, waste, railway and traffic. Recent attacks on SCADA systems highlight the need of a SCADA security testbed, which can be used to model real SCADA systems and study the effects of attacks on them. We propose the architecture of a modular SCADA testbed and describe our tool which mimics a SCADA network, monitors and controls real sensors and actuators using Modbus/TCP protocol. Using Distributed Denial of Service (DDoS) scenarios we show how attackers can disrupt the operation of a SCADA system.


title: A Reliability Assessment Approach for Integrated Transportation and Electrical Power Systems Incorporating Electric Vehicles

abstract: With the increasing utilization of electric vehicles (EVs), transportation systems and electrical power systems are becoming increasingly coupled. However, the interaction between these two kinds of systems are not well captured, especially from the perspective of transportation systems. This paper studies the reliability of integrated transportation and electrical power system (ITES). A bidirectional EV charging control strategy is first demonstrated to model the interaction between the two systems. Thereafter, a simplified transportation system model is developed, whose high efficiency makes the reliability assessment of the ITES realizable with an acceptable accuracy. Novel transportation system reliability indices are then defined from the view point of EV’s driver. Based on the charging control model and the transportation simulation method, a daily periodic quasi sequential reliability assessment method is proposed for the ITES system. Case studies based on RBTS system demonstrate that bidirectional charging controls of EVs will benefit the reliability of power systems, while decreasing the reliability of EVs travelling. Also, the optimal control strategy can be obtained based on the proposed method. Finally, case studies are performed based on a large scale test system to verify the practicability of the proposed method.


title: Fingertip Tactile Devices for Virtual Object Manipulation and Exploration

abstract: One of the main barriers to immersivity during object manipulation in virtual reality is the lack of realistic haptic feedback. Our goal is to convey compelling interactions with virtual objects, such as grasping, squeezing, pressing, lifting, and stroking, without requiring a bulky, world-grounded kinesthetic feedback device (traditional haptics) or the use of predetermined passive objects (haptic retargeting). To achieve this, we use a pair of finger-mounted haptic feedback devices that deform the skin on the fingertips to convey cutaneous force information from object manipulation. We show that users can perceive differences in virtual object weight and that they apply increasing grasp forces when lifting virtual objects as rendered mass is increased. Moreover, we show how naive users perceive changes of a virtual object's physical properties when we use skin deformation to render objects with varying mass, friction, and stiffness. These studies demonstrate that fingertip skin deformation devices can provide a compelling haptic experience appropriate for virtual reality scenarios involving object manipulation.