title: DART — A portable deep water hovering AUV

abstract: Autonomous Underwater Vehicles are remarkable machines that revolutionized the collection of data at sea. There are many examples of highly operational man-portable vehicles for shallow waters, but there was no similar solution for deep water operations. This paper describes the development of a portable, modular, hovering AUV for deep water operations. The vehicle has little over 50kg, 2.4m of length, and a depth rating of 4000m. The first version of the vehicle has been assembled, it has gone through the initial tests in water tanks, and it is being prepared for the first operations at sea.


title: Discrimination-aware data mining

abstract: In the context of civil rights law, discrimination refers to unfair or unequal treatment of people based on membership to a category or a minority, without regard to individual merit. Rules extracted from databases by data mining techniques, such as classification or association rules, when used for decision tasks such as benefit or credit approval, can be discriminatory in the above sense. In this paper, the notion of discriminatory classification rules is introduced and studied. Providing a guarantee of non-discrimination is shown to be a non trivial task. A naive approach, like taking away all discriminatory attributes, is shown to be not enough when other background knowledge is available. Our approach leads to a precise formulation of the redlining problem along with a formal result relating discriminatory rules with apparently safe ones by means of background knowledge. An empirical assessment of the results on the German credit dataset is also provided.


title: Increase of Regulatory T Cells in the Peripheral Blood of Cancer Patients 1

abstract: Purpose: T cells constitutively expressing both CD4 and CD25 are essential for maintenance of self-tolerance and therefore have been referred to as regulatory T cells (Treg). Experimental tumor models in mice revealed that Tregs are potent inhibitors of an antitumor immune response. The current study was designed to determine whether cancer patients exhibit an expanded Treg pool. Experimental Design: The frequency of Tregs in the peripheral blood of 42 patients suffering from epithelial malignancies and from 34 healthy controls was determined by flow cytometry. The immunoregulatory properties of CD4CD25 and CD4CD25 T cells were characterized by proliferation and suppression assays. Cocultures with natural killer (NK) cells were performed to determine the impact of Tregs on NK-mediated cytotoxicity. Results: Patients with epithelial malignancies show an increase of CD4CD25 T cells in the peripheral blood with characteristics of Tregs, i.e., they are CD45RA, CTLA-4, and transforming growth factor . Notably, CD4 T cells from cancer patients are characterized by an impaired proliferative capacity, which is restored to the extend of CD25depleted CD4 T cells from control persons by prior removal of CD25 T cells. In contrast to CD4CD25 T cells, isolated CD4CD25 T cells from cancer patients were anergic towards T cell receptor stimulation. In addition, CD4CD25 T cells suppressed the proliferation of CD4CD25 T cells. When cultured together with CD56 NK-cells, CD4CD25 T cells from cancer patients effectively inhibited NK-cell-mediated cytotoxicity. Conclusions: Thus, we provide evidence of an increased pool of CD4CD25 regulatory T cells in the peripheral blood of cancer patients with potent immunosuppressive features. These findings should be considered for the design of immunomodulatory therapies such as dendritic cell vaccination.


title: Image Denoising With 2D Scale-Mixing Complex Wavelet Transforms

abstract: This paper introduces an image denoising procedure based on a 2D scale-mixing complex-valued wavelet transform. Both the minimal (unitary) and redundant (maximum overlap) versions of the transform are used. The covariance structure of white noise in wavelet domain is established. Estimation is performed via empirical Bayesian techniques, including versions that preserve the phase of the complex-valued wavelet coefficients and those that do not. The new procedure exhibits excellent quantitative and visual performance, which is demonstrated by simulation on standard test images.


title: Soft shape context for iterative closest point registration

abstract: This paper introduces a shape descriptor, the soft shape context, motivated by the shape context method. Unlike the original shape context method, where each image point was hard assigned into a single histogram bin, we instead allow each image point to contribute to multiple bins, hence more robust to distortions. The soft shape context can easily be integrated into the iterative closest point (ICP) method as an auxiliary feature vector, enriching the representation of an image point from spatial information only, to spatial and shape information. This yields a registration method more robust than the original ICP method. The method is general for 2D shapes. It does not calculate derivatives, hence being able to handle shapes with junctions and discontinuities. We present experimental results to demonstrate the robustness compared with the standard ICP method.


COMP 322: Fundamentals of Parallel Programming Module 3: Locality and Distribution


title: Dynamically Composable Collaborations with Delegation Layers

abstract: It has been recognized in several works that a slice of behavior affecting a set of collaborating classes is a better unit of reuse than a single class. Different techniques and language extensions have been suggested to express such slices in programming languages. We propose delegation layers, an approach that scales the OO mechanisms for single objects, such as delegation, late binding, and subtype polymorphism, to sets of collaborating objects. Technically, delegation layers combine and generalize delegation and virtual class concepts. Due to their runtime semantics, delegation layers are more flexible than previous compile time approaches like mixin layers.


title: Exploring the Relationships between Design Measures and Software Quality in Object-Oriented Systems

abstract: Abstract One goal of this paper is to empirically explore the relationships between existing object-oriented (OO) coupling, cohesion, and inheritance measures and the probability of fault detection in system classes during testing. In other words, we wish to better understand the relationship between existing design measurement in OO systems and the quality of the software developed. The second goal is to propose an investigation and analysis strategy to make these kind of studies more repeatable and comparable, a problem which is pervasive in the literature on quality measurement. Results show that many of the measures capture similar dimensions in the data set, thus reflecting the fact that many of them are based on similar principles and hypotheses. However, it is shown that by using a subset of measures, accurate models can be built to predict which classes most of the faults are likely to lie in. When predicting fault-prone classes, the best model shows a percentage of correct classifications higher than 80% and finds more than 90% of faulty classes. Besides the size of classes, the frequency of method invocations and the depth of inheritance hierarchies seem to be the main driving factors of fault-proneness.


title: Learning the Dynamics of Embedded Clauses

abstract: Recent work by Siegelmann has shown that the computational power of recurrent neural networks matches that of Turing Machines. One important implication is that complex language classes (infinite languages with embedded clauses) can be represented in neural networks. Proofs are based on a fractal encoding of states to simulate the memory and operations of stacks. ::: ::: In the present work, it is shown that similar stack-like dynamics can be learned in recurrent neural networks from simple sequence prediction tasks. Two main types of network solutions are found and described qualitatively as dynamical systems: damped oscillation and entangled spiraling around fixed points. The potential and limitations of each solution type are established in terms of generalization on two different context-free languages. Both solution types constitute novel stack implementations—generally in line with Siegelmann's theoretical work—which supply insights into how embedded structures of languages can be handled in analog hardware.


title: Characterization of Polarization Diversity at the Mobile

abstract: Two new models used to characterize polarization diversity at the mobile are presented and discussed. The first model is built upon existing theoretical models at a base station to demonstrate how those principles apply to the mobile fading environment. Due to limitations of antennas at the mobile, this extended model, although relevant, is not sufficient to characterize polarization diversity of the antennas; therefore, this paper moves on to show how a new approach to polarization diversity at the mobile exists as an inherent feature within an angular diversity system. Results show that, for two polarizations in a fading environment, the best overall output occurs with a plusmn45deg element configuration, although the diversity combiner itself has optimum performance with a plusmn67.5deg configuration due to lower correlation at the input. The second model is also used to demonstrate how differently polarized dipoles are using polarization diversity inherent within an angular diversity system.


title: MobileRGBD, an open benchmark corpus for mobile RGB-D related algorithms

abstract: Since the commercialization of low cost RGB-D sensors, like the Kinect, more and more indoor robots have been equipped with this kind of sensors to perform tasks as people tracking or gesture recognition. Nevertheless, as far as we know from the literature, studies do not consider the limits of the sensors in term of motion speed, position of the sensor on the robot, etc. In this work, we propose to provide a corpus dedicated to low level RGB-D algorithms benchmarking. Originality of our approach is the use of dummies in order to play static users in the environment. This idea let us vary other variables that can impact algorithm performance: linear/angular speed of the robot, trajectory of the robot, RGB-D sensor height and vertical angle of view, number and relative position of dummies and furniture position. This paper first describes the experimental platform used to perform the acquisitions and the environment setup required to reproduce the dataset. Then, a precise description of all available data is given. We will see that, as this corpus contains a lot of configurations, it will allow researchers to investigate how these variables impact the results of their algorithms.


title: Small Imaging Depth LIDAR and DCNN-Based Localization for Automated Guided Vehicle †

abstract: We present our third prototype sensor and a localization method for Automated Guided Vehicles (AGVs), for which small imaging LIght Detection and Ranging (LIDAR) and fusion-based localization are fundamentally important. Our small imaging LIDAR, named the Single-Photon Avalanche Diode (SPAD) LIDAR, uses a time-of-flight method and SPAD arrays. A SPAD is a highly sensitive photodetector capable of detecting at the single-photon level, and the SPAD LIDAR has two SPAD arrays on the same chip for detection of laser light and environmental light. Therefore, the SPAD LIDAR simultaneously outputs range image data and monocular image data with the same coordinate system and does not require external calibration among outputs. As AGVs travel both indoors and outdoors with vibration, this calibration-less structure is particularly useful for AGV applications. We also introduce a fusion-based localization method, named SPAD DCNN, which uses the SPAD LIDAR and employs a Deep Convolutional Neural Network (DCNN). SPAD DCNN can fuse the outputs of the SPAD LIDAR: range image data, monocular image data and peak intensity image data. The SPAD DCNN has two outputs: the regression result of the position of the SPAD LIDAR and the classification result of the existence of a target to be approached. Our third prototype sensor and the localization method are evaluated in an indoor environment by assuming various AGV trajectories. The results show that the sensor and localization method improve the localization accuracy.


title: An empirical study of adopting mobile healthcare service: the family's perspective on the healthcare needs of their elderly members.

abstract: In an aging society, the issue of increased medical costs troubles both government agencies and families with aging parents. Many elderly people require long-term care, and the medical and financial problems associated with long-term care worry their entire family. Mobile healthcare service (MHS) has been widely applied by medical practitioners and researchers for years. Unfortunately, the elderly often fear both the technology and the cost its use incurs; hence, they seldom actively adopt MHS without the prompting and support of other family members. This study highlights this issue of long-term healthcare for the elderly and extracts the factors affecting their family's intentions in adopting MHS. Based on the integration of the Theory of Planned Behavior and the Technology Acceptance Model, the factors associated with the family's intention of the aging people toward MHS are explored. Data were collected from 200 students in the "Job Master" track in a local "Executive Master of Business Administration" program. Half of them had at least one immediate family member who was older than 65 years of age. A partial least squares (PLS) analysis shows that "attitude" significantly affected the behavioral intention of adopting MHS, and "perceived usefulness" and "perceived ease-of-use" had an indirect effect via "attitude." The PLS model explains the variance in intention (64.1%), attitude (58.1%), and perceived usefulness (33.8%). Overall, this study shows that attitude was an important determinant of MHS adoption. Gender also significantly affected the relationship between attitude and behavioral intention to adopt MHS.


title: Communication Needs of Elderly at Risk of Falls and their Remote Family

abstract: The aging population experiences increased health risks, both physical and emotional. Two such risks are those of isolation and falling. This papers draws from HCI literature in these two independent research areas to explore the needs of family communication with elderly parents at risk of falls. We report on a study with 7 elderly parents and 3 of adult children, as well as a group interview with 12 elderly living in a sheltered accommodation. Findings indicate important emotional needs on both parts: adult children's anxiety for the wellbeing of their parents at risk of falls, and elderly's need for autonomy and their appreciation for an aesthetic design. We concluded with implications of these findings for designing for family communication in this challenging context.


title: Robust removal of fixed pattern noise on multi-focus images

abstract: In this paper, we propose a novel method restoring multi-focus images based on convex optimization with new constraint for fixed pattern noise. Even weak fixed pattern noise on multi-focus images degrades all-in-focus images reconstructed by linear combination of them, especially, when using telecentric optical systems such as microscopes. Our novel method introduces constraint for additive fixed pattern noise into total variation minimization and then it is improved for multiplicative fixed pattern noise. The proposed method suppresses fixed pattern noise on multi-focus images very robustly to avoid such degradation on reconstructed images. Experimental results show that our method achieves high performance compared to simple total variation minimization.


title: Virtual Interpersonal Touch: Expressing and Recognizing Emotions Through Haptic Devices

abstract: ABSTRACT This article examines the phenomenon of Virtual Interpersonal Touch (VIT), people touching one another via force-feedback haptic devices. As collaborative virtual environments become utilized more effectively, it is only natural that interactants will have the ability to touch one another. In the work presented here, we used relatively basic devices to begin to explore the expression of emotion through VIT. In Experiment 1, participants utilized a 2 DOF force-feedback joystick to express seven emotions. We examined various dimensions of the forces generated and subjective ratings of the difficulty of expressing those emotions. In Experiment 2, a separate group of participants attempted to recognize the recordings of emotions generated in Experiment 1. In Experiment 3, pairs of participants attempted to communicate the seven emotions using physical handshakes. Results indicated that humans were above chance when recognizing emotions via VIT but not as accurate as people expressing emotions through nonmediated handshakes. We discuss a theoretical framework for understanding emotions expressed through touch as well as the implications of the current findings for the utilization of VIT in human-computer interaction.


title: Effect of soft reduction on the structure of continuously-cast slabs

abstract: A technique has been developed for computer prediction of the soft-rolling-related reduction in the axial chemical inhomogeneity of a continuous-cast steel billet. The resulting computer software enables the amount of axial chemical inhomogeneity in continuous-cast billets to be explored as a function of the continuous-casting parameters and the physical properties of the steel. Calculations performed for steel with two different initial carbon contents (0.09% and 0.6%) indicated that the proposed method for calculating the effects of soft reduction predicts a substantial (50‐55%) reduction in the axial chemical inhomogeneity of continuous-cast billets.


title: Gebauer Responding and Religiosity Religiosity as Self-Enhancement : A Meta-Analysis of the Relation Between Socially Desirable

abstract: In a meta-analysis, the authors test the theoretical formulation that religiosity is a means for self-enhancement. The authors operationalized self-enhancement as socially desirable responding (SDR) and focused on three facets of religiosity: intrinsic, extrinsic, and religion-as-quest. Importantly, they assessed two moderators of the relation between SDR and religiosity. Macro-level culture reflected countries that varied in degree of religiosity (from high to low: United States, Canada, United Kingdom). Micro-level culture reflected U.S. universities high (Christian) versus low (secular) on religiosity. The results were generally consistent with the theoretical formulation. Both macro-level and micro-level culture moderated the relation between SDR and religiosity: This relation was more positive in samples that placed higher value on religiosity (United States > Canada > United Kingdom; Christian universities > secular universities). The evidence suggests that religiosity is partly in the service of se...


title: Design of Dielectric-Covered Planar Arrays of Longitudinal Slots

abstract: The Elliott's procedure for the design of a waveguide longitudinal slot array has been extended to the case of dielectric-covered planar slot arrays. A protective dielectric cover is required in many different applications of waveguide slot arrays, especially in aerospace and satellite applications. The results of the synthesis procedure have been validated against a commercial FEM software.


title: Sensorless Control for SPMSM With Concentrated Windings Using Multisignal Injection Method

abstract: Surface-mounted permanent magnet synchronous machine with concentrated windings (cwSPMSM) is a high-performance drive machine and has been adopted in many applications. The difficulty of implementing its sensorless control at low and zero speeds is its multiple saliencies, which is much more significant than most other ac machines. The traditional decoupling methods provide successful results only under the condition that high-order saliencies are not stronger than half of the primary saliency. Furthermore, the behavior of the multiple saliencies is principally frequency dependent. Based on the characteristics of such machines, this paper proposes a multisignal injection method for realizing sensorless control. This method injects multiple high-frequency signals with different frequencies and magnitudes into the machine. Different frequency components in the response current signals are demodulated and then combined together to get the clear primary saliency signal, which is used to identify the rotor position. This new method was validated using a cwSPMSM at low speed. The experimental results proved the effectiveness and accuracy of the new method.


title: Statistics and bioinformatics in nutritional sciences: analysis of complex data in the era of systems biology.

abstract: Over the past 2 decades, there have been revolutionary developments in life science technologies characterized by high throughput, high efficiency, and rapid computation. Nutritionists now have the advanced methodologies for the analysis of DNA, RNA, protein, low-molecular-weight metabolites, as well as access to bioinformatics databases. Statistics, which can be defined as the process of making scientific inferences from data that contain variability, has historically played an integral role in advancing nutritional sciences. Currently, in the era of systems biology, statistics has become an increasingly important tool to quantitatively analyze information about biological macromolecules. This article describes general terms used in statistical analysis of large, complex experimental data. These terms include experimental design, power analysis, sample size calculation, and experimental errors (Type I and II errors) for nutritional studies at population, tissue, cellular, and molecular levels. In addition, we highlighted various sources of experimental variations in studies involving microarray gene expression, real-time polymerase chain reaction, proteomics, and other bioinformatics technologies. Moreover, we provided guidelines for nutritionists and other biomedical scientists to plan and conduct studies and to analyze the complex data. Appropriate statistical analyses are expected to make an important contribution to solving major nutrition-associated problems in humans and animals (including obesity, diabetes, cardiovascular disease, cancer, ageing, and intrauterine growth retardation).


title: Li-Ion Battery Charging with a Buck-Boost Power Converter for a Solar Powered Battery Management System

abstract: This paper analyzes and simulates the Li-ion battery charging process for a solar powered battery management system. The battery is charged using a non-inverting synchronous buck-boost DC/DC power converter. The system operates in buck, buck-boost, or boost mode, according to the supply voltage conditions from the solar panels. Rapid changes in atmospheric conditions or sunlight incident angle cause supply voltage variations. This study develops an electrochemical-based equivalent circuit model for a Li-ion battery. A dynamic model for the battery charging process is then constructed based on the Li-ion battery electrochemical model and the buck-boost power converter dynamic model. The battery charging process forms a system with multiple interconnections. Characteristics, including battery charging system stability margins for each individual operating mode, are analyzed and discussed. Because of supply voltage variation, the system can switch between buck, buck-boost, and boost modes. The system is modeled as a Markov jump system to evaluate the mean square stability of the system. The MATLAB based Simulink piecewise linear electric circuit simulation tool is used to verify the battery charging model.


title: A Privacy-Preserving Attribute-Based Authentication System for Mobile Health Networks

abstract: Electronic healthcare (eHealth) systems have replaced paper-based medical systems due to the attractive features such as universal accessibility, high accuracy, and low cost. As a major component of eHealth systems, mobile healthcare (mHealth) applies mobile devices, such as smartphones and tablets, to enable patient-to-physician and patient-to-patient communications for better healthcare and quality of life (QoL). Unfortunately, patients' concerns on potential leakage of personal health records (PHRs) is the biggest stumbling block. In current eHealth/mHealth networks, patients' medical records are usually associated with a set of attributes like existing symptoms and undergoing treatments based on the information collected from portable devices. To guarantee the authenticity of those attributes, PHRs should be verifiable. However, due to the linkability between identities and PHRs, existing mHealth systems fail to preserve patient identity privacy while providing medical services. To solve this problem, we propose a decentralized system that leverages users' verifiable attributes to authenticate each other while preserving attribute and identity privacy. Moreover, we design authentication strategies with progressive privacy requirements in different interactions among participating entities. Finally, we have thoroughly evaluated the security and computational overheads for our proposed schemes via extensive simulations and experiments.


title: Matching NIR Face to VIS Face Using Transduction

abstract: Visual versus near infrared (VIS-NIR) face image matching uses an NIR face image as the probe and conventional VIS face images as enrollment. It takes advantage of the NIR face technology in tackling illumination changes and low-light condition and can cater for more applications where the enrollment is done using VIS face images such as ID card photos. Existing VIS-NIR techniques assume that during classifier learning, the VIS images of each target people have their NIR counterparts. However, since corresponding VIS-NIR image pairs of the same people are not always available, which is often the case, so those methods cannot be applied. To address this problem, we propose a transductive method named transductive heterogeneous face matching (THFM) to adapt the VIS-NIR matching learned from training with available image pairs to all people in the target set. In addition, we propose a simple feature representation for effective VIS-NIR matching, which can be computed in three steps, namely Log-DoG filtering, local encoding, and uniform feature normalization, to reduce heterogeneities between VIS and NIR images. The transduction approach can reduce the domain difference due to heterogeneous data and learn the discriminative model for target people simultaneously. To the best of our knowledge, it is the first attempt to formulate the VIS-NIR matching using transduction to address the generalization problem for matching. Experimental results validate the effectiveness of our proposed method on the heterogeneous face biometric databases.


title: A Novel Compression for Enormous Motion Data in Video Using Repeated Object Clips [ROC]

abstract: Entertainment industry is roofed with audio, video, graphics and multimedia. It deals with large variety of data. As the data increases, it becomes a troublesome problem especially in large database or real- time and telepresence applications, where the memory, bandwidth and storages are limited. So, in this study we propose, a novel compression method, which is achieved by video content analysis using Repeated Object Clips (ROC). To achieve ROC, the key frame selection algorithm is used. In key frame selection process, we extract key frame from total number of frames. For selection process, initially frame separation process is carried out, then object detection and object segmentation is performed by level set method. By this novel technique moving object was tracked effectively and compression ratio increased significantly.


title: A few good lines: Suggestive drawing of 3d models

abstract: We present a method for rendering 3D models in the traditional line-drawing style used in artistic and scientific illustrations. The goal is to suggest the 3D shape of the object using a small number of lines drawn with carefully chosen line qualities. The system combines several known techniques into a simple yet effective non-photorealistic line renderer. Feature edges related to the outline and interior of a given 3D mesh are extracted, segmented, and smoothed, yielding chains of lines with varying path, length, thickness, gaps and enclosures. The paper includes sample renderings obtained for a variety of models.


title: Focused attention, open monitoring and automatic self-transcending: Categories to organize meditations from Vedic, Buddhist and Chinese traditions

abstract: This paper proposes a third meditation-category—automatic self-transcending— to extend the dichotomy of focused attention and open monitoring proposed by Lutz. Automatic selftranscending includes techniques designed to transcend their own activity. This contrasts with focused attention, which keeps attention focused on an object; and open monitoring, which keeps attention involved in the monitoring process. Each category was assigned EEG bands, based on reported brain patterns during mental tasks, and meditations were categorized based on their reported EEG. Focused attention, characterized by beta/gamma activity, included meditations from Tibetan Buddhist, Buddhist, and Chinese traditions. Open monitoring, characterized by theta activity, included meditations from Buddhist, Chinese, and Vedic traditions. Automatic self-transcending, characterized by alpha1 activity, included meditations from Vedic and Chinese traditions. Between categories, the included meditations differed in focus, subject/object relation, and procedures. These findings shed light on the common mistake of averaging meditations together to determine mechanisms or clinical effects.


title: Compact Offset Microstrip-Fed MIMO Antenna for Band-Notched UWB Applications

abstract: A compact multiple-input–multiple-output (MIMO) antenna is presented for ultrawideband (UWB) applications with band-notched function. The proposed antenna is composed of two offset microstrip-fed antenna elements with UWB performance. To achieve high isolation and polarization diversity, the antenna elements are placed perpendicular to each other. A parasitic T-shaped strip between the radiating elements is employed as a decoupling structure to further suppress the mutual coupling. In addition, the notched band at 5.5 GHz is realized by etching a pair of L-shaped slits on the ground. The antenna prototype with a compact size of $38.5 \times38.5~\hbox{mm}^{2}$ has been fabricated and measured. Experimental results show that the antenna has an impedance bandwidth of 3.08-11.8 GHz with reflection coefficient less than $-10~\hbox{dB}$ , except the rejection band of 5.03-5.97 GHz. Besides, port isolation, envelope correlation coefficient and radiation characteristics are also investigated. The results indicate that the MIMO antenna is suitable for band-notched UWB applications.


title: Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks

abstract: The term 'Big Data' has spread rapidly in the framework of Data Mining and Business Intelligence. This new scenario can be defined by means of those problems that cannot be effectively or efficiently addressed using the standard computing resources that we currently have. We must emphasize that Big Data does not just imply large volumes of data but also the necessity for scalability, i.e., to ensure a response in an acceptable elapsed time. When the scalability term is considered, usually traditional parallel-type solutions are contemplated, such as the Message Passing Interface or high performance and distributed Database Management Systems. Nowadays there is a new paradigm that has gained popularity over the latter due to the number of benefits it offers. This model is Cloud Computing, and among its main features we has to stress its elasticity in the use of computing resources and space, less management effort, and flexible costs. In this article, we provide an overview on the topic of Big Data, and how the current problem can be addressed from the perspective of Cloud Computing and its programming frameworks. In particular, we focus on those systems for large-scale analytics based on the MapReduce scheme and Hadoop, its open-source implementation. We identify several libraries and software projects that have been developed for aiding practitioners to address this new programming model. We also analyze the advantages and disadvantages of MapReduce, in contrast to the classical solutions in this field. Finally, we present a number of programming frameworks that have been proposed as an alternative to MapReduce, developed under the premise of solving the shortcomings of this model in certain scenarios and platforms. WIREs Data Mining Knowl Discov 2014, 4:380-409. doi: 10.1002/widm.1134


title: A k-core Decomposition Framework for Graph Clustering

abstract: Graph clustering or community detection constitutes an important task for investigating the internal structure of graphs, with a plethora of applications in several domains. Traditional techniques for graph clustering, such as spectral methods, typically suffer from high time and space complexity. In this article, we present CoreCluster, an efficient graph clustering framework based on the concept of graph degeneracy, that can be used along with any known graph clustering algorithm. Our approach capitalizes on processing the graph in an hierarchical manner provided by its core expansion sequence, an ordered partition of the graph into different levels according to the k-core decomposition. Such a partition provides an efficient way to process the graph in an incremental manner that preserves its clustering structure, while making the execution of the chosen clustering algorithm much faster due to the smaller size of the graph's partitions onto which the algorithm operates. An experimental analysis on a multitude of real and synthetic data demonstrates that our approach can be applied to any clustering algorithm accelerating the clustering process, while the quality of the clustering structure is preserved or even improved.


title: Randomized multi-modal motion planning for a humanoid robot manipulation task

abstract: Robots that perform complex manipulation tasks must be able to generate strategies that make and break contact with the object. This requires reasoning in a motion space with a particular multi-modal structure, in which the state contains both a discrete mode (the contact state) and a continuous configuration (the robot and object poses). In this paper we address multi-modal motion planning in the common setting where the state is high-dimensional, and there are a continuous infinity of modes. We present a highly general algorithm, Random-MMP, that repeatedly attempts mode switches sampled at random. A major theoretical result is that Random-MMP is formally reliable and scalable, and its running time depends on certain properties of the multi-modal structure of the problem that are not explicitly dependent on dimensionality. We apply the planner to a manipulation task on the Honda humanoid robot, where the robot is asked to push an object to a desired location on a cluttered table, and the robot is restricted to switch between walking, reaching, and pushing modes. Experiments in simulation and on the real robot demonstrate that Random-MMP solves problem instances that require several carefully chosen pushes in minutes on a PC.


An Equivalent LMI Representation of Bounded Real Lemma for Continuous-Time Systems


title: Spectroscopy of Single CdSe Nanoplatelets

abstract: We collect and resolve spectrally and temporally the photoluminescence of single CdSe nanoplatelets. The emission intensity of single nanoplatelets at room temperature shows ON and OFF periods with a usual blinking statistics, while at 20 K, their emission intensity can be extremely stable in time. At room temperature, the emission spectra of single nanoplatelets are similar to ensemble measurements with a full width at half-maximum of 40 meV. At 20 K, we obtain a resolution-limited spectral line width (<0.4 meV). The fluorescence lifetime of single nanoplatelets decreases when the temperature decreases to reach 200 ps at 20 K. This lifetime shortening is concomitant with an increase of the nanoplatelets’ emission intensity.


title: Malayalam text summarization: An extractive approach

abstract: Automatic summarization of text is on of the area of interest in the field of natural language processing. The proposed method utilizes the sentence extraction in a single document and produces a generic summary for a given Malayalam document (Extractive summarization). Sentences in the document are ranked based on the word score of each word present in it. Top N ranked sentences are extracted and arrange them in their chronological order for summary generation, where N represents the size of summary with respect to the percentage of original document size (condensation rate). The standard metric ROUGE is used for performance evaluation. ROUGE calculates the n-gram overlap between a generated summary and reference summaries. Reference summaries were constructed manually. Experiments show that the results are promising.


Impact of arthroscopic percutaneous poking reduction-fixation on affected limb function and quality of life of patients with fracture of tibial plateau


title: Towards Distributed Machine Learning in Shared Clusters: A Dynamically-Partitioned Approach

abstract: Many cluster management systems (CMSs) have been proposed to share a single cluster with multiple distributed computing systems. However, none of the existing approaches can handle distributed machine learning (ML) workloads given the following criteria: high resource utilization, fair resource allocation and low sharing overhead. To solve this problem, we propose a new CMS named Dorm, incorporating a dynamically-partitioned cluster management mechanism and an utilization-fairness optimizer. Specifically, Dorm uses the container-based virtualization technique to partition a cluster, runs one application per partition, and can dynamically resize each partition at application runtime for resource efficiency and fairness. Each application directly launches its tasks on the assigned partition without petitioning for resources frequently, so Dorm imposes flat sharing overhead. Extensive performance evaluations showed that Dorm could simultaneously increase the resource utilization by a factor of up to 2.32, reduce the fairness loss by a factor of up to 1.52, and speed up popular distributed ML applications by a factor of up to 2.72, compared to existing approaches. Dorm's sharing overhead is less than 5% in most cases.


title: From Infant Attachment Disorganization to Adult Dissociation: Relational Adaptations or Traumatic Experiences?

abstract: In 1997, Putnam [1] pointed out that relatively little was known about the etiology and development of dissociation other than the presumed etiologic role of trauma; however, the fact that nontraumatized individuals sometimes demonstrated dissociation and that not all trauma survivors dissociate suggested that there may be more to the etiology and development of dissociation than trauma alone. Putnam [1] explored the role of various potential moderating variables including age, sex, culture, genetic factors, and education/intelligence in the development of dissociation, and although moderating trends were found for some of these variables, existing research has not convincingly demonstrated that any of these variables significantly influence dissociation. ::: ::: Family environmental factors, however, are the one set of factors that have been most consistently related to dissociation. Factors such as inconsistent parenting or disciplining, [2–4] level of family risk [5], and parental dissociation, as measured by the Dissociative Experiences Scale [6], have been shown to be associated significantly with higher levels of dissociation in adulthood. Most available research on dissociation, however, has focused on trauma, leaving many unanswered questions regarding how other family factors intersect with familial abuse in the developmental trajectories leading to dissociative disorders. ::: ::: Barach [7] was one of the first theorists to connect dissociation with attachment theory. In his article, Barach [7] suggested that multiple personality disorder (now known as dissociative identity disorder) was a variant of an “attachment disorder.” He pointed out that individuals who had this disorder tended to demonstrate the extreme detachment, or emotional unresponsiveness, experienced by children faced with a loss of their primary caretaker, as described by Bowlby [8]. Barach [7] further suggested that children of unresponsive caretakers were also likely to engage in dissociative or “detached” behaviors. As one offshoot of attachment studies, developmental theorists and researchers have begun to explore the role of early childhood attachment and parenting in the etiology and development of dissociative symptomatology. ::: ::: Liotti’s [9] theorizing has more specifically implicated disorganized patterns of infant attachment behavior as potential precursors to the development of dissociation later in life. He pointed out that there are parallels between infant disorganization and dissociation. Both phenomena reflect a pervasive lack of behavioral or mental integration. This primary failure of integration in infancy may result in vulnerability to dissociative organization of mental life in the developing child and grown adult. Liotti’s view might be best conceptualized as a vulnerability model in which early dyadic processes lead to a “primary breakdown” or lack of integration of a coherent sense of self. Liotti’s model offers an alternative to the theory that the primary function and etiology of dissociation is as a defense against trauma. Although Liotti [9] did not suggest that disorganized attachment is the only etiologic factor in dissociation, he hypothesized that disorganized attachment patterns constitute an initial step in the developmental trajectories that leave an individual vulnerable to developing dissociation in response to later experiences of trauma. ::: ::: Bowlby [8] first suggested that infants may internalize unintegrated internal working models of their relationships with primary caregivers and of themselves in relation to those caregivers. Main and Hesse [10] further hypothesized that parents of disorganized infants may engage in frightened or frightening interactions with their children, thereby presenting the infant with the paradox that the parent is a source of threat and a source of protection. Under these paradoxic conditions, during times of stress when the attachment system is activated, contradictory internal working models of self and other may become evident. These seemingly incompatible models of the parent as a source of fear and a source of protection from fear are similar to Barach’s [7] model of an abusive parent causing a child to be faced with the incompatible notion that his parent is his protector and his persecutor. ::: ::: Main and Hesse [10] further theorized that when the parent appears frightened in his or her interactions with the infant, the infant may infer that there is something threatening in the environment that should be feared. Although such a perceived environmental threat would lead a securely attached infant to approach his parent for protection, a frightened parent may communicate apprehension to the child. Under these conditions, the infant may sense the helplessness of the parent in the face of threat and demonstrate conflict about approaching him or her for protection by displaying contradictory simultaneous or sequential approach-avoidance behaviors typical of disorganized detachment. Alternatively, the parent’s frightened stance may cause the child to infer that he, himself, is frightening the parent, again leading to conflict in approaching and further threatening an already frightened parent. Lyons-Ruth and colleagues [11, 12] demonstrated that parental withdrawal from the infant’s attachment overtures at times of infant arousal is also associated with infant disorganization, whether or not the parent’s behavior is directly frightened or frightening to the infant. Thus, the infant’s internalization of contradictory models of the self as frightened or threatening and of the parent as hostile or helpless/withdrawing can be conceptualized in terms of contradictory models that generate incompatible behavioral and mental tendencies. This primary lack of integration around basic strategies for seeking comfort and protection under stress is what Liotti [9] suggested may confer vulnerability to dissociative processes later in life. ::: ::: Liotti [9] further speculated that there are three pathways that disorganized infants might take toward (or away from) the development of dissociative symptomatology. In the first pathway, there is no further trauma, and interactions with the parent become less fear imbued and more consistent over the childhood years. Regardless of whether this consistency is positive or negative, Liotti [9] posited that this would result in the child’s eventually choosing one of the available incompatible working models of attachment relationships and developing in accordance with that working model. The second pathway, in which parent-child interactions continue to be inconsistent and contradictory but the child does not encounter severe trauma, would lead to infrequent dissociation during times of extreme stress. In this scenario, although the child is viewed as vulnerable to the development of dissociative symptoms, there arc not sufficient environmental stressors to potentiate this vulnerability, leaving the child asymptomatic or displaying only mild or fleeting dissociative symptoms. In the third pathway, the disorganized/disoriented infant is predisposed to dissociation, has ongoing severe stressors, and vulnerability is potentiated. Here, the child experiences continued reinforcement of increasingly unintegrated simultaneous/sequential contradictory internal working models of self-other relatedness and repetitive severe trauma. This child is likely to move toward the extreme of developing dissociative identity disorder. ::: ::: Liotti’s model of early difficulties in achieving an integrated set of behavioral and mental responses to fear or threat offers a strong hypothesis for why it is that some people exposed to trauma develop dissociation, whereas others do not. This model suggests that disorganized attachment negatively impacts the onset of early individually based processes of mental integration that become the basis for later dissociation. Although Liotti’s model sets forth the notion that infant disorganization lays the groundwork and acts as a key precursor for the development of dissociation, experiences of significant trauma remain an important and necessary factor in this diathesis-stress model.


title: Context-sensitive analysis without calling-context

abstract: Since Sharir and Pnueli, algorithms for context-sensitivity have been defined in terms of `valid' paths in an interprocedural flow graph. The definition of valid paths requires atomic call and ret statements, and encapsulated procedures. Thus, the resulting algorithms are not directly applicable when behavior similar to call and ret instructions may be realized using non-atomic statements, or when procedures do not have rigid boundaries, such as with programs in low level languages like assembly or RTL. ::: ::: We present a framework for context-sensitive analysis that requires neither atomic call and ret instructions, nor encapsulated procedures. The framework presented decouples the transfer of control semantics and the context manipulation semantics of statements. A new definition of context-sensitivity, called stack contexts, is developed. A stack context, which is defined using trace semantics, is more general than Sharir and Pnueli's interprocedural path based calling-context. An abstract interpretation based framework is developed to reason about stack-contexts and to derive analogues of calling-context based algorithms using stack-context. ::: ::: The framework presented is suitable for deriving algorithms for analyzing binary programs, such as malware, that employ obfuscations with the deliberate intent of defeating automated analysis. The framework is used to create a context-sensitive version of Venable et al.'s algorithm for analyzing x86 binaries without requiring that a binary conforms to a standard compilation model for maintaining procedures, calls, and returns. Experimental results show that a context-sensitive analysis using stack-context performs just as well for programs where the use of Sharir and Pnueli's calling-context produces correct approximations. However, if those programs are transformed to use call obfuscations, a context-sensitive analysis using stack-context still provides the same, correct results and without any additional overhead.


title: Combination of PSO Algorithm and Naive Bayesian Classification for Parkinson Disease Diagnosis

abstract: Parkinson is a neurological disease which quickly affects human’s motor organs. Early diagnosis of this disease is very important for its prevention. Using optimum training data and omitting noisy training data will increase the classification accuracy. In this paper, a new model based on the combination of PSO algorithm and Naive Bayesian Classification has been presented for diagnosing the Parkinson disease, in which optimum training data are selected by PSO algorithm and Naive Bayesian Classification. In this paper, according to the obtained results, Parkinson disease diagnosis accuracy has been 97.95% using the presented method, which is indicative of the superiority of this method to the previous models of Parkinson disease diagnosis.


title: Semantic Autoencoder for Zero-Shot Learning

abstract: Existing zero-shot learning (ZSL) models typically learn a projection function from a feature space to a semantic embedding space (e.g. attribute space). However, such a projection function is only concerned with predicting the training seen class semantic representation (e.g. attribute prediction) or classification. When applied to test data, which in the context of ZSL contains different (unseen) classes without training data, a ZSL model typically suffers from the project domain shift problem. In this work, we present a novel solution to ZSL based on learning a Semantic AutoEncoder (SAE). Taking the encoder-decoder paradigm, an encoder aims to project a visual feature vector into the semantic space as in the existing ZSL models. However, the decoder exerts an additional constraint, that is, the projection/code must be able to reconstruct the original visual feature. We show that with this additional reconstruction constraint, the learned projection function from the seen classes is able to generalise better to the new unseen classes. Importantly, the encoder and decoder are linear and symmetric which enable us to develop an extremely efficient learning algorithm. Extensive experiments on six benchmark datasets demonstrate that the proposed SAE outperforms significantly the existing ZSL models with the additional benefit of lower computational cost. Furthermore, when the SAE is applied to supervised clustering problem, it also beats the state-of-the-art.


title: The neurophysiology of dissociation and chronic disease

abstract: Dissociation as a clinical psychiatric condition has been defined primarily in terms of the fragmentation and splitting of the mind, and perception of the self and the body. Its clinical manifestations include altered perceptions and behavior, including derealization, depersonalization, distortions of perception of time, space, and body, and conversion hysteria. Using examples of animal models, and the clinical features of the whiplash syndrome, we have developed a model of dissociation linked to the phenomenon of freeze/immobility. Also employing current concepts of the psychobiology of posttraumatic stress disorder (PTSD), we propose a model of PTSD linked to cyclical autonomic dysfunction, triggered and maintained by the laboratory model of kindling, and perpetuated by increasingly profound dorsal vagal tone and endorphinergic reward systems. These physiologic events in turn contribute to the clinical state of dissociation. The resulting autonomic dysregulation is presented as the substrate for a diverse group of chronic diseases of unknown origin.


title: Too Many Pixels to Perceive: Subpixel Shutoff for Display Energy Reduction on OLED Smartphones

abstract: Organic light-emitting diode (OLED) has been widely recognized as the next-generation mobile display. Recently, smartphone manufacturers have been pushing up the pixel density of OLED display. Unfortunately, such an effort does not necessarily improve the everyday viewing because of the limitation in human visual acuity. Instead, high pixel density OLED can drain the battery power even more quickly since the power dissipation of OLED is determined by the number of displayed pixels and their RGB values, or subpixels. This paper presents a new design dimension to remedy this prevailing issue by leveraging the intuition that shutting off redundant subpixels of the display content on OLED can reduce power consumption without impacting viewing perception. We introduce ShutPix, a power-saving display system for OLED smartphones that can optimally shut off the redundant subpixels before the content is displayed. Inspired by the motivational studies, ShutPix is empowered by a suite of designs based on visual acuity, human perception, and content redundancy. Experimental results show that ShutPix can, on average, reduce 21% of display power and 15% of system power without degrading user viewing experience.


title: Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework

abstract: This paper explores how the remaining useful life (RUL) can be assessed for complex systems whose internal state variables are either inaccessible to sensors or hard to measure under operational conditions. Consequently, inference and estimation techniques need to be applied on indirect measurements, anticipated operational conditions, and historical data for which a Bayesian statistical approach is suitable. Models of electrochemical processes in the form of equivalent electric circuit parameters were combined with statistical models of state transitions, aging processes, and measurement fidelity in a formal framework. Relevance vector machines (RVMs) and several different particle filters (PFs) are examined for remaining life prediction and for providing uncertainty bounds. Results are shown on battery data.


title: Development of a MEMS technology CSFH based microgripper

abstract: This paper describes the design, simulation, construction process and experimental analysis of a microgripper, which makes use of a new concept hinge, called CSFH (Conjugate Surfaces Flexure Hinge). The new hinge combines a curved cantilever beam, as flexible element, and a pair of conjugate surfaces, whose contacts depend on load conditions. CSFH hinges improve accuracy and guarantee that minimum stress conditions hold within the flexible beam. This microgripper is designed for Deep Reactive-Ion Etching (D-RIE) construction process and comb-drive actuation. Theoretical basis and Finite Element Analysis (FEA) simulations have been employed in order to predict the feasibility of the device under construction. Finally, some experimental evidence of the construction process has been provided.


title: Exemplar-Based Interpolation of Sparsely Sampled Images

abstract: A nonlocal variational formulation for interpolating a sparsely sampled image is introduced in this paper. The proposed variational formulation, originally motivated by image inpainting problems, encourages the transfer of information between similar image patches, following the paradigm of exemplar-based methods. Contrary to the classical inpainting problem, no complete patches are available from the sparse image samples, and the patch similarity criterion has to be redefined as here proposed. Initial experimental results with the proposed framework, at very low sampling densities, are very encouraging. We also explore some departures from the variational setting, showing a remarkable ability to recover textures at low sampling densities.


title: BitCube: A Bottom-Up Cubing Engineering

abstract: Enhancing on line analytical processing through efficient cube computation plays a key role in Data Warehouse management. Hashing, grouping and mining techniques are commonly used to improve cube pre-computation. BitCube, a fast cubing method which uses bitmaps as inverted indexes for grouping, is presented. It horizontally partitions data according to the values of one dimension and for each resulting fragment it performs grouping following bottom-up criteria. BitCube allows also partial materialization based on iceberg conditions to treat large datasets for which a full cube pre-computation is too expensive. Space requirement of bitmaps is optimized by applying an adaption of the WAH compression technique. Experimental analysis, on both synthetic and real datasets, shows that BitCube outperforms previous algorithms for full cube computation and results comparable on iceberg cubing.


title: Support vector machines for collaborative filtering

abstract: Support Vector Machines (SVMs) have successfully shown efficiencies in many areas such as text categorization. Although recommendation systems share many similarities with text categorization, the performance of SVMs in recommendation systems is not acceptable due to the sparsity of the user-item matrix. In this paper, we propose a heuristic method to improve the predictive accuracy of SVMs by repeatedly correcting the missing values in the user-item matrix. The performance comparison to other algorithms has been conducted. The experimental studies show that the accurate rates of our heuristic method are the highest.


EVALUATING USER EXPERIENCE OF EARLY PRODUCT CONCEPTS


title: High-Performance Ternary Adder Using CNTFET

abstract: This paper presents two new designs to implement a ternary half adder using Carbon Nanotubes Field Effect Transistors (CNFETs). Ternary logic is a promising alternative to conventional binary logic, since it is possible to accomplish simplicity and energy efficiency in modern digital design due to reduced circuit overhead such as interconnect and chip area. In this paper the authors are presenting two different novel ternary half adder circuits using ternary decoders and binary logic gates. The circuits are simulated using HSPICE to obtain power, delay and power delay product. The circuit performances are compared with the recently reported designs. The proposed ternary adders show delay and power advantage up to 40 and 39% with less transistor count. So, use of these half adders in complex arithmetic circuits will be advantageous.


title: Wide-coverage array antenna using a dual-beam switching for UHF RFID applications

abstract: Based on a dual-beam switching, the wide-coverage array antenna with a 4 × 4 proposed matrix which generates three dual-beams is presented for the ultra high frequency (UHF) radio frequency identification (RFID) applications. The 4 × 4 proposed matrix generates the three dual-beams which can find the approximate location of a tag by covering the wide spatial coverage of 180°. The main beam directions can be controlled by selecting the appropriate input port of the proposed matrix. Due to the compact structure and very low reflection coefficient, the circular polarized square quadrifilar spiral antenna (QSA) array incorporated with the 4×4 proposed matrix has been configured. The fabricated array antenna operates at the 902-928 MHz band and produces three dual-beams at ±12°, ±39°, and ±68°.


title: Listening to Action-related Sentences Activates Fronto-parietal Motor Circuits

abstract: Observing actions made by others activates the cortical circuits responsible for the planning and execution of those same actions. This observation–execution matching system (mirror-neuron system) is thought to play an important role in the understanding of actions made by others. In an fMRI experiment, we tested whether this system also becomes active during the processing of action-related sentences. Participants listened to sentences describing actions performed with the mouth, the hand, or the leg. Abstract sentences of comparable syntactic structure were used as control stimuli. The results showed that listening to action-related sentences activates a left fronto-parieto-temporal network that includes the pars opercularis of the inferior frontal gyrus (Broca's area), those sectors of the premotor cortex where the actions described are motorically coded, as well as the inferior parietal lobule, the intraparietal sulcus, and the posterior middle temporal gyrus. These data provide the first direct evidence that listening to sentences that describe actions engages the visuomotor circuits which subserve action execution and observation.


title: The Impact of Technostress on Role Stress and Productivity

abstract: Based on empirical survey data, this paper uses concepts from sociotechnical theory and role theory to explore the effects of stress created by information and computer technology (ICT)-that is, "technostress"-on role stress and on individual productivity. We first explain different ways in which ICTs can create stress in users and identify factors that create technostress. We next propose three hypotheses: (1) technostress is inversely related to individual productivity, (2) role stress is inversely related to individual productivity, and (3) technostress is directly related to role stress. We then use structural equation modeling on survey data from ICT users in 223 organizations to test the hypotheses. The results show support for them. Theoretically, the paper contributes in three ways. First, the different dimensions of technostress identified here add to existing concepts on stress experienced by individuals in organizations. Second, by showing that technostress inversely affects productivity, the paper reinforces that failure to manage the effects of ICT-induced stress can offset expected increases in productivity. Third, validation of the positive relationship between technostress and role stress adds a new conceptual thread to literature analyzing the relationship between technology and organizational roles and structure. In the practical domain, the paper proposes a diagnostic tool to evaluate the extent to which technostress is present in an organization and suggests that the adverse effects of technostress can be partly countered by strategies that reduce role conflict and role overload.


title: Sporotrichosis: An Overview and Therapeutic Options

abstract: Sporotrichosis is a chronic granulomatous mycotic infection caused by Sporothrix schenckii, a common saprophyte of soil, decaying wood, hay, and sphagnum moss, that is endemic in tropical/subtropical areas. The recent phylogenetic studies have delineated the geographic distribution of multiple distinct Sporothrix species causing sporotrichosis. It characteristically involves the skin and subcutaneous tissue following traumatic inoculation of the pathogen. After a variable incubation period, progressively enlarging papulo-nodule at the inoculation site develops that may ulcerate (fixed cutaneous sporotrichosis) or multiple nodules appear proximally along lymphatics (lymphocutaneous sporotrichosis). Osteoarticular sporotrichosis or primary pulmonary sporotrichosis are rare and occur from direct inoculation or inhalation of conidia, respectively. Disseminated cutaneous sporotrichosis or involvement of multiple visceral organs, particularly the central nervous system, occurs most commonly in persons with immunosuppression. Saturated solution of potassium iodide remains a first line treatment choice for uncomplicated cutaneous sporotrichosis in resource poor countries but itraconazole is currently used/recommended for the treatment of all forms of sporotrichosis. Terbinafine has been observed to be effective in the treatment of cutaneous sporotrichosis. Amphotericin B is used initially for the treatment of severe, systemic disease, during pregnancy and in immunosuppressed patients until recovery, then followed by itraconazole for the rest of the therapy.


Detecting Asymmetric Semantic Relations in Context: A Case-Study on Hypernymy Detection


title: Load balancing cloud computing: State of art

abstract: The rapid development of Internet has given birth to a new business model: Cloud Computing. This new paradigm has experienced a fantastic rise in recent years. Because of its infancy, it remains a model to be developed. In particular, it must offer the same features of services than traditional systems. The cloud computing is large distributed systems that employ distributed resources to deliver a service to end users by implementing several technologies. Hence providing acceptable response time for end users, presents a major challenge for cloud computing. All components must cooperate to meet this challenge, in particular through load balancing algorithms. This will enhance the availability and will gain the end user confidence. In this paper we try to give an overview of load balancing in the cloud computing by exposing the most important research challenges.


title: Curriculum is not enough: the educational theory and research foundation of the exploring computer science professional development model

abstract: In recent years, the computer science education community has shown strong commitment to broadening participation in computing in K-12 classrooms. Educational research highlights the critical role of professional development in supporting teachers to attract and effectively teach underrepresented students in computing. In this paper we present the Exploring Computer Science (ECS) professional development model and the research on which it is based. We also present findings about the impact of ECS professional development on teachers' practice. As computing education initiatives become increasingly concerned with scaling up from a regional to a nationwide presence, it is important to consider how the essential components of effective professional development can drive this reform.


title: DeMoN: Depth and Motion Network for Learning Monocular Stereo

abstract: In this paper we formulate structure from motion as a learning problem. We train a convolutional network end-to-end to compute depth and camera motion from successive, unconstrained image pairs. The architecture is composed of multiple stacked encoder-decoder networks, the core part being an iterative network that is able to improve its own predictions. The network estimates not only depth and motion, but additionally surface normals, optical flow between the images and confidence of the matching. A crucial component of the approach is a training loss based on spatial relative differences. Compared to traditional two-frame structure from motion methods, results are more accurate and more robust. In contrast to the popular depth-from-single-image networks, DeMoN learns the concept of matching and, thus, better generalizes to structures not seen during training.


title: The content validity index: Are you sure you know what's being reported? critique and recommendations

abstract: Scale developers often provide evidence of content validity by computing a content validity index (CVI), using ratings of item relevance by content experts. We analyzed how nurse researchers have defined and calculated the CVI, and found considerable consistency for item-level CVIs (I-CVIs). However, there are two alternative, but unacknowledged, methods of computing the scale-level index (S-CVI). One method requires universal agreement among experts, but a less conservative method averages the item-level CVIs. Using backward inference with a purposive sample of scale development studies, we found that both methods are being used by nurse researchers, although it was not always possible to infer the calculation method. The two approaches can lead to different values, making it risky to draw conclusions about content validity. Scale developers should indicate which method was used to provide readers with interpretable content validity information. © 2006 Wiley Periodicals, Inc. Res Nurs Health 29: 489–497, 2006


title: SELF-EFFICACY FOR READING AND WRITING: INFLUENCE OF MODELING, GOAL SETTING, AND SELF-EVALUATION

abstract: Perceived self-efficacy, or students' personal beliefs about their capabilities to learn or perform behaviors at designated levels, plays an important role in their motivation and learning. Self-efficacy is a key mechanism in social cognitive theory, which postulates that achievement depends on interactions between behaviors, personal factors, and environmental conditions. Self-efficacy affects choice of tasks, effort, persistence, and achievement. Sources of self-efficacy information include personal accomplishments, vicarious experiences, social persuasion, and physiological indicators. At the outset of learning activities, students have goals and a sense of self-efficacy for attaining them. Self-evaluations of learning progress sustain self-efficacy and motivation. Research on academic learning is summarized, showing how modeling, goal setting, and self-evaluation affect self-efficacy, motivation, and learning. Suggestions for applying these ideas to teaching are provided.


title: Transverse flux machines with distributed windings for in-wheel applications

abstract: Transverse flux machine (TFM) useful for in-wheel motor applications is presented. This transverse flux permanent magnet motor is designed to achieve high torque-to-weight ratio and is suitable for direct-drive wheel applications. As in conventional TFM, the phases are located under each other, which will increase the axial length of the machine. The idea of this design is to reduce the axial length of TFM, by placing the windings around the stator and by shifting those from each other by electrically 120° or 90°, for three- or two-phase machine, respectively. Therefore, a remarkable reduction on the total axial length of the machine will be achieved while keeping the torque density high. This TFM is compared to another similar TFM, in which the three phases have been divided into two halves and placed opposite each other to ensure the mechanical balance and stability of the stator. The corresponding mechanical phase shifts between the phases have accordingly been taken into account. The motors are modelled in finite-element method (FEM) program, Flux3D, and designed to meet the specifications of an optimisation scheme, subject to certain constraints, such as construction dimensions, electric and magnetic loading. Based on this comparison study, many recommendations have been suggested to achieve optimum results.


title: A general theory of addictions: A new theoretical model

abstract: A general theory of addictions is proposed, using the compulsive gambler as the prototype. Addiction is defined as a dependent state acquired over time to relieve stress. Two interrelated sets of factors predispose persons to addictions: an abnormal physiological resting state, and childhood experiences producing a deep sense of inadequacy. All addictions are hypothesized to follow a similar three-stage course. A matrix strategy is outlined to collect similar information from different kinds of addicts and normals. The ultimate objective is to identify high risk youth and prevent the development of addictions.


title: Accelerated Embedded AKAZE Feature Detection Algorithm on FPGA

abstract: Feature detection is a major operation in various computer vision systems. The KAZE algorithm and its improved version, Accelerated-KAZE (AKAZE), are considered as the first algorithms to detect features by building a scale space using nonlinear diffusion. However, the detection part of the algorithm achieves only 6 fps on an Intel Core i7-4790 processor for an image resolution of 1024x768. This work proposes a pipelined architecture for a hardware accelerator that performs the AKAZE detection algorithm. Firstly, modifications are done to the original algorithm to reduce the amount of computations and memory accesses. Then, the accelerator is implemented on a Xilinx Zynq SoC and achieves 98 fps for the same resolution and a frequency of 100 MHz. Compared to the original algorithm, the design has an error in average inliers ratio by only 4%.


Scanpath Prediction for Visual Attention using IOR-ROI LSTM


title: Mortality Rate of Bali Cattle (Bos sondaicus) Calves in West Timor, Indonesia

abstract: High calf mortality has been reported to be the most prominent factor responsible for the low productivity of Bali cattle productivity in West Timor, Indonesia. Some studies recorded calf mortality in the range between 30% to 40% (Wirdahayati and Bamualim 1994), or as high as 50% in some herds (Fattah, 1998). A survey was carried out to investigate the mortality rate of Bali cattle calves in 4 districts in West Timor, Indonesia Timor, including the districts of Kupang, Timor Tengah Selatan (TTS), Timor Tengah Utara (TTU) and Belu. Data on the incidence and causes of calf mortality were collected from a total of 249 farmers during December 2007 using structured interviews based on a standard questionnaire. Data were statistically analysed using Proc. GLM (SAS Institute). Calf mortality varied significantly from 11.06% in TTU to 23.27% in Belu (Table 1). The overall average calf mortality rate was 17.9%, significantly below the calf mortality rate of 35% reported by Jelantik (2001). The differences in reported calf mortality could be due to a season effect or regional variation. Calf mortality varied from 7.6% in the sub-district of Miommafo Timur (in TTU) to 40% in the sub-district of Kupang Timur (Kupang District), but reached as high as 60% in some villages. 86% of the annual calf mortality occurred at the end of the dry season and beginning of rainy season (from October to December). According to farmers, the dominant factors causing calf death were diseases (53.7%), lack of milk (44.4%) and accidents (1.85%).


title: Multiple Physical Layer Pipes performance for DVB-T2

abstract: The DVB-T2 terrestrial television standard is becoming increasingly important, and have been extensively studied and developed to provide many types of services with higher spectral efficiency and better performance. The Physical Layer Pipes in DVB-S2 are logical channels carrying one or more services with modulation scheme and robustness. The main changes are found in the physical layer where DVB-T2 incorporates a new physical layer pipe (PLP). Each physical layer pipe contains an individual configuration of modulation, coding and interleaving. This new concept allows a transmission with multiple physical layer pipes where each service can be transmitted with different physical layer configuration. The Advanced Television Systems Committee (ATSC3.0) standard will add value to broadcasting services, allowing a extending reach by adding new business models, providing higher quality, improved accessibility, personalization and interactivity and more flexible and efficient use of the spectrum.


title: Facial Contouring by Targeted Restoration of Facial Fat Compartment Volume: The Midface

abstract: Background:Recent anatomical findings have suggested that facial fat distribution is complex and changes with age. Here, the authors developed a grafting technique based on the physiologic distribution and volume changes of facial fat compartments to achieve a youthful and natural-appearing face.Met


title: Error Minimized Extreme Learning Machine With Growth of Hidden Nodes and Incremental Learning

abstract: One of the open problems in neural network research is how to automatically determine network architectures for given applications. In this brief, we propose a simple and efficient approach to automatically determine the number of hidden nodes in generalized single-hidden-layer feedforward networks (SLFNs) which need not be neural alike. This approach referred to as error minimized extreme learning machine (EM-ELM) can add random hidden nodes to SLFNs one by one or group by group (with varying group size). During the growth of the networks, the output weights are updated incrementally. The convergence of this approach is proved in this brief as well. Simulation results demonstrate and verify that our new approach is much faster than other sequential/incremental/growing algorithms with good generalization performance.


title: An Improved Canny Edge Detection Algorithm

abstract: Traditional Canny edge detection algorithm uses a global threshold selection method, when large changes are in the background of the image and the target gray, global threshold method may lose some local edge information. For this problem, this paper therefore proposes an adaptive dynamic threshold improved Canny edge detection algorithm. The method uses image gradient variance as the criterion of the image block according to the four forks tree principle, then uses the Otsu method to get the corresponding sub-block threshold value for each sub-block, and obtains threshold value matrix by interpolation, finally, gets image edge with improved edge connected algorithm. Experimental results show that, the algorithm not only has good anti-noise performance, but also better detection accuracy.


title: Towards Model-Driven Engineering of Smart Contracts for Cyber-Physical Systems

abstract: Applications of Distributed Ledger Technologies (DLTs) in IoT and Cyber-Physical Systems (CPS) are rapidly emerging. However, developing correct and resilient smart contracts for these use cases is even less understood than it is for cryptocurrency-based contracts. This paper presents an initial approach for generating smart contracts for coordinating the usage of cyber-physical system elements from UML statecharts. While the current target platform is Ethereum, our approach can easily be extended to other blockchain platforms.


title: Teaching with Wikipedia in a 21st-century classroom: Perceptions of Wikipedia and its educational benefits

abstract: This article explores the current perception of Wikipedia in academia, focusing on both the reasons for its unpopularity among some and the reasons for its growing acceptance among others. First, the reasons that Wikipedia is still struggling to gain acceptance among many academics and higher education professionals are identified. These include common misconceptions about Wikipedia, doubts about its quality, uneasiness with the challenge that it poses to the traditional peer-review system, and a lack of career-enhancing motivations related to using Wikipedia. Second, the benefits of teaching with Wikipedia for educators, students, and the wider society, as discussed in the current teaching literature, are explored. Finally, the article presents an argument for using Wikipedia in a variety of ways to help students develop critical and academic writing skills.


Reactionary Modernism: Technology, Culture, and Politics in Weimar and the Third Reich


title: Neural basis of alertness and cognitive performance impairments during sleepiness. I. Effects of 24 h of sleep deprivation on waking human regional brain activity.

abstract: The negative effects of sleep deprivation on alertness and cognitive performance suggest decreases in brain activity and function, primarily in the thalamus, a subcortical structure involved in alertness and attention, and in the prefrontal cortex, a region subserving alertness, attention, and higher-order cognitive processes. To test this hypothesis, 17 normal subjects were scanned for quantifiable brain activity changes during 85 h of sleep deprivation using positron emission tomography (PET) and 18Fluorine-2-deoxyglucose (18FDG), a marker for regional cerebral metabolic rate for glucose (CMRglu) and neuronal synaptic activity. Subjects were scanned prior to and at 24-h intervals during the sleep deprivation period, for a total of four scans per subject. During each 30 min 18FDG uptake, subjects performed a sleep deprivation-sensitive Serial Addition/Subtraction task. Polysomnographic monitoring confirmed that subjects were awake. Twenty-four hours of sleep deprivation, reported here, resulted in a significant decrease in global CMRglu, and significant decreases in absolute regional CMRglu in several cortical and subcortical structures. No areas of the brain evidenced a significant increase in absolute regional CMRglu. Significant decreases in relative regional CMRglu, reflecting regional brain reductions greater than the global decrease, occurred predominantly in the thalamus and prefrontal and posterior parietal cortices. Alertness and cognitive performance declined in association with these brain deactivations. This study provides evidence that short-term sleep deprivation produces global decreases in brain activity, with larger reductions in activity in the distributed cortico-thalamic network mediating attention and higher-order cognitive processes, and is complementary to studies demonstrating deactivation of these cortical regions during NREM and REM sleep.


title: Learning to Juggle in an Interactive Virtual Reality Environment

abstract: Virtual reality environments are great tools for training as they are very cheap compared to on-site training for many tasks. While the focus has mostly been on the visual experience, we present a system that combines real world interactions with the virtual visual world to train motor skills that are applicable to the real world. Body pose tracking is combined with an Oculus Rift to create such an interactive virtual environment. As an example application, we taught users to juggle using a virtual training course. A third of the users were able to immediately transfer the newly acquired skills and juggle with real balls.


title: Measuring the readability of automatic speech-to-text transcripts

abstract: This paper reports initial results from a novel psycholinguistic study that measures the readability of several types of speech transcripts. We define a four-part figure of merit to measure readability: accuracy of answers to comprehension questions, reaction-time for passage reading, reaction-time for question answering and a subjective rating of passage difficulty. We present results from an experiment with 28 test subjects reading transcripts in four experimental conditions.


title: Open Issues in Scheduling Microservices in the Cloud

abstract: This article discusses the main advantages and challenges of adopting microservices in cloud computing. The microservices architecture allows software developers to build a distributed application as a set of independent components that work together. This model isn't new, but, applied in cloud systems, it increases datacenter scalability and reliability. The authors discuss available technologies for deploying and controlling microservices-based application architectures in the cloud.


title: Schemas for Narrative Generation Mined from Existing Descriptions of Plot

abstract: Computational generation of literary artifacts very often resorts to template-like schemas that can be instantiated into complex structures. With this view in mind, the present paper reviews a number of existing attempts to provide an elementary set of patterns for basic plots. An attempt is made to formulate these descriptions of possible plots in terms of character functions, an abstraction of plot-bearing elements of a story originally formulated by Vladimir Propp. These character functions act as the building blocks of the Propper system, an existing framework for computational story generation. The paper explores the set of extensions required to the original set of character functions to allow for a basic representation of the analysed schemata, and a solution for automatic generation of stories based on this formulation of the narrative schemas. This solution uncovers important insights on the relative expressive power of the representation of narrative in terms of character functions, and their impact on the generative potential of the framework is discussed.


The Search for Authenticity


title: Self-nonself discrimination in a computer

abstract: The problem of protecting computer systems can be viewed generally as the problem of learning to distinguish self from other. The authors describe a method for change detection which is based on the generation of T cells in the immune system. Mathematical analysis reveals computational costs of the system, and preliminary experiments illustrate how the method might be applied to the problem of computer viruses. >


title: Applying the Helmholtz illusion to fashion: horizontal stripes won't make you look fatter

abstract: A square composed of horizontal lines appears taller and narrower than an identical square made up of vertical lines. Reporting this illusion, Hermann von Helmholtz noted that such illusions, in which filled space seems to be larger than unfilled space, were common in everyday life, adding the observation that ladies' frocks with horizontal stripes make the figure look taller. As this assertion runs counter to modern popular belief, we have investigated whether vertical or horizontal stripes on clothing should make the wearer appear taller or fatter. We find that a rectangle of vertical stripes needs to be extended by 7.1% vertically to match the height of a square of horizontal stripes and that a rectangle of horizontal stripes must be made 4.5% wider than a square of vertical stripes to match its perceived width. This illusion holds when the horizontal or vertical lines are on the dress of a line drawing of a woman. We have examined the claim that these effects apply only for 2-dimensional figures in an experiment with 3-D cylinders and find no support for the notion that horizontal lines would be 'fattening' on clothes. Significantly, the illusion persists when the horizontal or vertical lines are on pictures of a real half-body mannequin viewed stereoscopically. All the evidence supports Helmholtz's original assertion.


title: Linear-complexity relaxed word Mover's distance with GPU acceleration

abstract: The amount of unstructured text-based data is growing every day. Querying, clustering, and classifying this big data requires similarity computations across large sets of documents. Whereas low-complexity similarity metrics are available, attention has been shifting towards more complex methods that achieve a higher accuracy. In particular, the Word Mover's Distance (WMD) method proposed by Kusner et al. is a promising new approach, but its time complexity grows cubically with the number of unique words in the documents. The Relaxed Word Mover's Distance (RWMD) method, again proposed by Kusner et al., reduces the time complexity from qubic to quadratic and results in a limited loss in accuracy compared with WMD. Our work contributes a low-complexity implementation of the RWMD that reduces the average time complexity to linear when operating on large sets of documents. Our linear-complexity RWMD implementation, henceforth referred to as LC-RWMD, maps well onto GPUs and can be efficiently distributed across a cluster of GPUs. Our experiments on real-life datasets demonstrate 1) a performance improvement of two orders of magnitude with respect to our GPU-based distributed implementation of the quadratic RWMD, and 2) a performance improvement of three to four orders of magnitude with respect to our distributed WMD implementation that uses GPU-based RWMD for pruning.


title: CrystalNet: Faithfully Emulating Large Production Networks

abstract: Network reliability is critical for large clouds and online service providers like Microsoft. Our network is large, heterogeneous, complex and undergoes constant churns. In such an environment even small issues triggered by device failures, buggy device software, configuration errors, unproven management tools and unavoidable human errors can quickly cause large outages. A promising way to minimize such network outages is to proactively validate all network operations in a high-fidelity network emulator, before they are carried out in production. To this end, we present CrystalNet, a cloud-scale, high-fidelity network emulator. It runs real network device firmwares in a network of containers and virtual machines, loaded with production configurations. Network engineers can use the same management tools and methods to interact with the emulated network as they do with a production network. CrystalNet can handle heterogeneous device firmwares and can scale to emulate thousands of network devices in a matter of minutes. To reduce resource consumption, it carefully selects a boundary of emulations, while ensuring correctness of propagation of network changes. Microsoft's network engineers use CrystalNet on a daily basis to test planned network operations. Our experience shows that CrystalNet enables operators to detect many issues that could trigger significant outages.


title: Current Mode Control Integrated Circuit with High Accuracy Current Sensing Circuit for Buck Converter

abstract: A current mode control integrated circuit with accuracy current sensing circuit ( CSC ) for buck converter is presented in this the proposed accurate integrated current sensed inductor with the internal ramp be used for DC-DC converter feedback proposed CSC doesn't need an op amp to implement, and has been fabricated with a standard 0.35 mum CMOS process. Simulation result show that the switching converter can be operated up to 1 MHZ. The supply is suitable for signal cell lithium-ion battery supply power efficiency is over 85% for supply voltage from 2.5 V to 5 V and output current is 200 mA. The performance of the proposed circuit is the good compared to the other circuits.


title: Cooperation and Interdependence: How Multiplayer Games Increase Social Closeness

abstract: Games have long been used as a bonding activity; however, research on establishing and maintaining social closeness through games uses different terms, different mechanics and controls, and different contexts of use. As a result, designers have little guidance on which multiplayer game mechanics are most effective. We summarize literature on game design for social closeness into a framework with two collaborative mechanics: cooperation and interdependence. We then created four versions of an online game to independently test the effects of these game mechanics on relationship formation between paired online strangers, showing that cooperation and interdependence are two distinct factors that both can be used to improve play experience and increase social bonds. Additionally, we unpack the effect of interdependence, showing that the improved social closeness can be explained by the increase in conversational turns.


title: Robust H∞ filter design for 2DFM model

abstract: This paper is concerned with the robust H∞ filtering problem for uncertain two-dimensional (2-D) systems described by the Fornasini-Marchesini model. The polynomially parameter-dependent idea is first utilized to solve the robust H∞ filtering problem, with sufficient conditions for existence of the desired H∞ filters expressed in terms of linear matrix inequalities (LMIs). These conditions are developed based on homogeneous polynomially parameter-dependent matrices of arbitrary degree. As the degree grows, test of increasing precision is obtained providing less conservative filter designs. An example is given to show the effectiveness of the proposed approach.


title: Tyrosine hydroxylase-synthesizing cells in the hypothalamus of prairie voles (Microtus ochrogaster): sex differences in the anteroventral periventricular preoptic area and effects of adult gonadectomy or neonatal gonadal hormones.

abstract: The vertebrate hypothalamus and surrounding region contain a large population of cells expressing tyrosine hydroxylase (TH), the rate limiting enzyme for synthesis of dopamine and other catecholamines. Some of these populations are sexually dimorphic in rats. We here examined sex differences in TH-immunoreactive populations in the forebrain of gonadally intact and gonadectomized prairie voles (Microtus ochrogaster), a species that sometimes shows unusual sexual differentiation of brain and behavior. A sex difference was found in the anteroventral periventricular preoptic area (AVPV; likely analogous to the rat rostral A14) only in gonadectomized subjects, which was due to a 50% reduction in the number of TH-immunoreactive cells after castration in males. There was no significant sex difference or effects of gonadectomy on the number of TH-immunoreactive cells in the anteroventral preoptic area (AVP), periventricular anterior hypothalamus (caudal A14), arcuate nucleus (A12), zona incerta (A13), or posterodorsal hypothalamus (A11). In a second experiment, testosterone propionate (TP; 500 microg), diethylstilbestrol (DES; 1 microg), or estradiol benzoate (EB; 30 microg) injected daily during the first week after birth each significantly reduced later TH expression in the AVPV of females by approximately 40-65% compared to oil-treated controls. Unlike rats, therefore, a sex difference in TH expression in the prairie vole AVPV is found only after removal of circulating gonadal hormones in males. Furthermore, unlike our previous findings on the generation of sex differences in extra-hypothalamic arginine-vasopressin expression in prairie voles, TH expression in the AVPV of female prairie voles can be highly masculinized by neonatal exposure to either aromatizable androgens or estrogens.


title: Limitations to maximum sprinting speed imposed by muscle mechanical properties

abstract: Abstract It has been suggested that the force–velocity relationship of skeletal muscle plays a critical limiting role in the maximum speed at which humans can sprint. However, this theory has not been tested directly, and it is possible that other muscle mechanical properties play limiting roles as well. In this study, forward dynamics simulations of human sprinting were generated using a 2D musculoskeletal model actuated by Hill muscle models. The initial simulation results compared favorably to kinetic, kinematic, and electromyographic data recorded from sprinting humans. Muscle mechanical properties were then removed in isolation to quantify their effect on maximum sprinting speed. Removal of the force–velocity, excitation–activation, and force–length relationships increased the maximum speed by 15, 8, and 4%, respectively. Removal of the series elastic force–extension relationship decreased the maximum speed by 26%. Each relationship affected both stride length and stride frequency except for the force–length relationship, which mainly affected stride length. Removal of all muscular properties entirely (optimized joint torques) increased speed (+22%) to a greater extent than the removal of any single contractile property. The results indicate that the force–velocity relationship is indeed the most important contractile property of muscle regarding limits to maximum sprinting speed, but that other muscular properties also play important roles. Interactions between the various muscular properties should be considered when explaining limits to maximal human performance.


title: Rough Set Based Feature Selection for Web Usage Mining

abstract: Web usage mining exploits data mining techniques to discover valuable information from navigation behavior of World Wide Web (WWW) users. The required information is captured by Web servers and stored in Web usage data logs. The first phase of Web usage mining is the pre processing phase. In the preprocessing phase, first, relevant information is filtered from the logs. Data preprocessing is a critical step in Web usage mining. The results of data preprocessing is relevant to the next steps, such as transaction identification, path analysis, association rule mining, sequential pattern mining, and so forth. Feature selection is a preprocessing step in data mining, and it is very effective in reducing dimensions, reducing the irrelevant data, increasing the learning accuracy and improving comprehensiveness. This paper proposes a novel approach for feature selection based on rough set theory for Web usage mining.


title: Persistence and periodicity in a dynamic proximity network

abstract: The topology of social networks can be understood as being inherently dynamic, with edges having a distinct position in time. Most characterizations of dynamic networks discretize time by converting temporal information into a sequence of network "snapshots" for further analysis. Here we study a highly resolved data set of a dynamic proximity network of 66 individuals. We show that the topology of this network evolves over a very broad distribution of time scales, that its behavior is characterized by strong periodicities driven by external calendar cycles, and that the conversion of inherently continuous-time data into a sequence of snapshots can produce highly biased estimates of network structure. We suggest that dynamic social networks exhibit a natural time scale \Delta_{nat}, and that the best conversion of such dynamic data to a discrete sequence of networks is done at this natural rate.