title: Image convolution processing: A GPU versus FPGA comparison

abstract: Convolution is one of the most important operators used in image processing. With the constant need to increase the performance in high-end applications and the rise and popularity of parallel architectures, such as GPUs and the ones implemented in FPGAs, comes the necessity to compare these architectures in order to determine which of them performs better and in what scenario. In this article, convolution was implemented in each of the aforementioned architectures with the following languages: CUDA for GPUs and Verilog for FPGAs. In addition, the same algorithms were also implemented in MATLAB, using predefined operations and in C using a regular x86 quad-core processor. Comparative performance measures, considering the execution time and the clock ratio, were taken and commented in the paper. Overall, it was possible to achieve a CUDA speedup of roughly 200× in comparison to C, 70× in comparison to Matlab and 20× in comparison to FPGA.


title: Compact Single- and Dual-Band Filtering Patch Antenna Arrays Using Novel Feeding Scheme

abstract: This paper presents two compact patch antenna arrays using a novel feeding scheme to integrate bandpass responses. The two arrays have no filtering circuits but reveal high filtering performance. For each array, only a microstrip feed line is coupled to radiating patches and specific coupling regions are employed to obtain the desired current distribution on the radiating patches. In the operating band, the induced currents on the patches are in phase, resulting in high boresight gain. At the out-of-band frequencies, the patches are not excited or the induced currents on them are 180° out of phase, resulting in radiation suppression. Using this method, out-of-band radiation can be suppressed without degrading the in-band performance. For demonstration, a four-element planar patch array is first implemented. Single-band bandpass response is observed in the experiment. Measured in-band gains are 12.6 dBi, whereas out-of-band suppression is more than 20 dB. Then the feeding scheme is employed to design two three-element subarrays to form a planar dual-band patch array. Also, dual-band bandpass responses are obtained with high frequency selectivity.


title: Modeling Kinect Sensor Noise for Improved 3D Reconstruction and Tracking

abstract: We contribute an empirically derived noise model for the Kinect sensor. We systematically measure both lateral and axial noise distributions, as a function of both distance and angle of the Kinect to an observed surface. The derived noise model can be used to filter Kinect depth maps for a variety of applications. Our second contribution applies our derived noise model to the KinectFusion system to extend filtering, volumetric fusion, and pose estimation within the pipeline. Qualitative results show our method allows reconstruction of finer details and the ability to reconstruct smaller objects and thinner surfaces. Quantitative results also show our method improves pose estimation accuracy.


title: Eye gaze patterns in conversations: there is more to conversational agents than meets the eyes

abstract: In multi-agent, multi-user environments, users as well as agents should have a means of establishing who is talking to whom. In this paper, we present an experiment aimed at evaluating whether gaze directional cues of users could be used for this purpose. Using an eye tracker, we measured subject gaze at the faces of conversational partners during four-person conversations. Results indicate that when someone is listening or speaking to individuals, there is indeed a high probability that the person looked at is the person listened (p=88%) or spoken to (p=77%). We conclude that gaze is an excellent predictor of conversational attention in multiparty conversations. As such, it may form a reliable source of input for conversational systems that need to establish whom the user is speaking or listening to. We implemented our findings in FRED, a multi-agent conversational system that uses eye input to gauge which agent the user is listening or speaking to.


title: Siamese Instance Search for Tracking

abstract: In this paper we present a tracker, which is radically different from state-of-the-art trackers: we apply no model updating, no occlusion detection, no combination of trackers, no geometric matching, and still deliver state-of-theart tracking performance, as demonstrated on the popular online tracking benchmark (OTB) and six very challenging YouTube videos. The presented tracker simply matches the initial patch of the target in the first frame with candidates in a new frame and returns the most similar patch by a learned matching function. The strength of the matching function comes from being extensively trained generically, i.e., without any data of the target, using a Siamese deep neural network, which we design for tracking. Once learned, the matching function is used as is, without any adapting, to track previously unseen targets. It turns out that the learned matching function is so powerful that a simple tracker built upon it, coined Siamese INstance search Tracker, SINT, which only uses the original observation of the target from the first frame, suffices to reach state-of-theart performance. Further, we show the proposed tracker even allows for target re-identification after the target was absent for a complete video shot.


title: A General Agnostic Active Learning Algorithm

abstract: We present an agnostic active learning algorithm for any hypothesis class of bounded VC dimension under arbitrary data distributions. Most previous work on active learning either makes strong distributional assumptions, or else is computationally prohibitive. Our algorithm extends the simple scheme of Cohn, Atlas, and Ladner [1] to the agnostic setting, using reductions to supervised learning that harness generalization bounds in a simple but subtle manner. We provide a fall-back guarantee that bounds the algorithm's label complexity by the agnostic PAC sample complexity. Our analysis yields asymptotic label complexity improvements for certain hypothesis classes and distributions. We also demonstrate improvements experimentally.


title: Performance Comparison of AODV, DSDV, DSR and TORA Routing Protocols in MANETs

abstract: Routing protocols have central role in any mobile ad hoc network (MANET). There are many routing protocol that exhibit different performance levels in different scenarios. In this paper we compare AODV, DSDV, DSR and TORA routing protocol in mobile ad hoc networks to determine the best operational conditions for each protocol. We analyses these routing protocols by extensive simulations in ns-2 simulator and show that how pause time and number of nodes affect their performance. In this study performance is measured in terms of Packet Delivery Ratio, Network Life Time, System Life Time, End-to-End Delay and Routing Overhead.


title: The importance of nuclear masses in the astrophysical rp-process

abstract: The importance of mass measurements for astrophysical capture processes in general, and for the rp-process in X-ray bursts in particular is discussed. A review of the current uncertainties in the effective lifetimes of the major waiting points 64Ge, 68Se, and 72Kr demonstrates that despite of recent measurements uncertainties are still significant. It is found that mass measurements with an accuracy of the order of 10 keV or better are desirable, and that reaction rate uncertainties play a critical role as well.


SentNet : The Effects of Sentiment on Information Propagation


title: Kernel-based tensor partial least squares for reconstruction of limb movements

abstract: We present a new supervised tensor regression method based on multi-way array decompositions and kernel machines. The main issue in the development of a kernel-based framework for tensorial data is that the kernel functions have to be defined on tensor-valued input, which here is defined based on multi-mode product kernels and probabilistic generative models. This strategy enables taking into account the underlying multilinear structure during the learning process. Based on the defined kernels for tensorial data, we develop a kernel-based tensor partial least squares approach for regression. The effectiveness of our method is demonstrated by a real-world application, i.e., the reconstruction of 3D movement trajectories from electrocorticography signals recorded from a monkey brain.


title: Fuzzy expert system for the risk identification of the hepatocellular carcinoma

abstract: Hepatocellular carcinoma is a cancer arising from the liver. It is also known as primary liver cancer or hepatoma. Hepatocellular carcinoma is the third most common cancer in the world. This paper aims at developing a fuzzy expert system for the risk identification of the hepatocellular carcinoma which will be useful to the doctors as a decision support system for the management of the hepatocellular carcinoma treatment. The developed system has five input variables (AFP, Tumor grade, Tumor size, Lymph node and albumin) and one output variable (Risk status). The output variable is a value from 1 to 4 representing low risk status, intermediate risk status and high risk status. This system is designed in MATLAB and uses Mamdani interface method.


Electrochromic Properties of Prussian Blue Thin Films Prepared by Chemical Deposition Method


title: The orbicularis retaining ligament of the medial orbit: closing the circle.

abstract: BACKGROUND ::: There exists some ambiguity regarding the exact anatomical limits of the orbicularis retaining ligament, particularly its medial boundary in both the superior and inferior orbits. Precise understanding of this anatomy is necessary during periorbital rejuvenation. ::: ::: ::: METHODS ::: Sixteen fresh hemifacial cadaver dissections were performed in the anatomy laboratory to evaluate the anatomy of the orbicularis retaining ligament. Dissection was assisted by magnification with loupes and the operating microscope. ::: ::: ::: RESULTS ::: A ligamentous system was found that arises from the inferior and superior orbital rim that is truly periorbital. This ligament spans the entire circumference of the orbit from the medial to the lateral canthus. There exists a fusion line between the orbital septum and the orbicularis retaining ligament in the superior orbit, indistinguishable from the arcus marginalis of the inferior orbital rim. Laterally, the orbicularis retaining ligament contributes to the lateral canthal ligament, consistent with previous studies. No contribution to the medial canthus was identified in this study. ::: ::: ::: CONCLUSIONS ::: The orbicularis retaining ligament is a true, circumferential "periorbital" structure. This ligament may serve two purposes: (1) to act as a fixation point for the orbicularis muscle of the upper and lower eyelids and (2) to protect the ocular globe. With techniques of periorbital injection with fillers and botulinum toxin becoming ever more popular, understanding the orbicularis retaining ligament's function as a partitioning membrane is mandatory for avoiding ocular complications. As a support structure, examples are shown of how manipulation of this ligament may benefit canthopexy, septal reset, and brow-lift procedures as described by Hoxworth.


title: MPC-based battery thermal management controller for Plug-in hybrid electric vehicles

abstract: This paper proposes a model predictive control (MPC) scheme for the battery thermal management system (BTMS) of a given plug-in hybrid electric vehicle, namely the Toyota Plug-in Prius. As temperature plays a key-role in battery life and performance, BTMS design has become a critical problem in all of the battery-based technologies. Although BTMS control design in its basic form can be well represented by a reference tracking problem, there exists only little research in the literature addressing this important control problem. Due to the importance of a prediction component in thermal systems, the idea in this paper is to design a concrete BTMS controller using the nonlinear model predictive control (NMPC) theory and examine its applicability to fill this gap. The promising simulation results indicate the prosperity of the proposed BTMS control methodology and thus pave the way for use of the model-based thermal management techniques in a wide range of upcoming battery-based devices.


title: Design of Matlab/Simulink based development board for fuzzy logic education

abstract: In this study, an application development board designed for education of fuzzy logic. Using this development board, students can learn how to design a fuzzy logic controller and test it. Also this development board ensures the consolidation of theoretical knowledge with various practical experiments. In this way, students' interest on the course has significantly increased. The most studied processes in industry are temperature and motor driver systems. Learning to control these processes is very important in engineering education. Development boards are specifically produced electronic cards that allow students to make various experiments for consolidation of theoretical knowledge via application in practice oriented courses. Today, in parallel to development of embedded systems, there are a lot of operating systems developed in this field. Open source developed Arduino development boards are being more preferable because of working independently from the platform. Arduino development boards also can operate in full compliance with Matlab / Simulink.


title: The brain basis of emotion: A meta-analytic review

abstract: Researchers have wondered how the brain creates emotions since the early days of psychological science. With a surge of studies in affective neuroscience in recent decades, scientists are poised to answer this question. In this target article, we present a meta-analytic summary of the neuroimaging literature on human emotion. We compare the locationist approach (i.e., the hypothesis that discrete emotion categories consistently and specifically correspond to distinct brain regions) with the psychological constructionist approach (i.e., the hypothesis that discrete emotion categories are constructed of more general brain networks not specific to those categories) to better understand the brain basis of emotion. We review both locationist and psychological constructionist hypotheses of brain-emotion correspondence and report meta-analytic findings bearing on these hypotheses. Overall, we found little evidence that discrete emotion categories can be consistently and specifically localized to distinct brain regions. Instead, we found evidence that is consistent with a psychological constructionist approach to the mind: A set of interacting brain regions commonly involved in basic psychological operations of both an emotional and non-emotional nature are active during emotion experience and perception across a range of discrete emotion categories.


title: Word Sense Disambiguation with LSTM: Do We Really Need 100 Billion Words?

abstract: Recently, Yuan et al. (2016) have shown the e ectiveness of using Long Short-Term Memory (LSTM) for performing Word Sense Disambiguation (WSD). Their proposed technique outperformed the previous state-of-the-art with several benchmarks, but neither the training data nor the source code was released. This paper presents the results of a reproduction study of this technique using only openly available datasets (GigaWord, SemCore, OMSTI) and software (TensorFlow). From them, it emerged that state-of-the-art results can be obtained with much less data than hinted by Yuan et al. All code and trained models are made freely available.


title: Performance of Nonlinear Approximate Adaptive Controllers

abstract: From the Publisher: ::: In recent years there has been a wide interest in non-linear adaptive control using approximate models, either for tracking or regulation, and usually under the banner of neural network based control. The authors present a unique critical evaluation of the approximate model philosophy and its setting, rigorously comparing the performance of such controls against competing designs. Analysing a very topical aspect of contemporary research and control practice this book highlights the situations in which approximate model based designs are most appropriate and indicates scenarios in which other designs could be used more productively. Throughout the text concepts are illustrated using a variety of examples, both academic problems and those based on physical examples. The work is designed to open the door to realistic applications. ::: Unified coverage of the theory and application of a wide range of control systems areas including neural network based control and control using the approximate modelPresents a mathematically well founded introduction to the area of intelligent controlA varied selecion of practical examples drawn from a variety of fields, including robotics and aerospace, illustrate theoretical principlesClear compaisons of a variety of control designsCross disciplinary approach to this leading edge topic ::: A valuable reference for control practitioners and theorists, artificial intelligence researchers and applied mathematicians, as well as graduate students and researchers with an interest in adaptive control and stability.


title: An Emphatic Approach to the Problem of Off-policy Temporal-Difference Learning

abstract: In this paper we introduce the idea of improving the performance of parametric temporal-difference (TD) learning algorithms by selectively emphasizing or de-emphasizing their updates on different time steps. In particular, we show that varying the emphasis of linear TD($\lambda$)'s updates in a particular way causes its expected update to become stable under off-policy training. The only prior model-free TD methods to achieve this with per-step computation linear in the number of function approximation parameters are the gradient-TD family of methods including TDC, GTD($\lambda$), and GQ($\lambda$). Compared to these methods, our _emphatic TD($\lambda$)_ is simpler and easier to use; it has only one learned parameter vector and one step-size parameter. Our treatment includes general state-dependent discounting and bootstrapping functions, and a way of specifying varying degrees of interest in accurately valuing different states.


title: Mapping Impervious Surface Distribution with Integration of SNNP VIIRS-DNB and MODIS NDVI Data

abstract: Data from the U.S. Defense Meteorological Satellite Program’s Operational Line-scan System are often used to map impervious surface area (ISA) distribution at regional and global scales, but its coarse spatial resolution and data saturation produce high inaccuracy in ISA estimation. Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite’s Day/Night Band (VIIRS-DNB) with its high spatial resolution and dynamic data range may provide new insights but has not been fully examined in mapping ISA distribution. In this paper, a new variable—Large-scale Impervious Surface Index (LISI)—is proposed to integrate VIIRS-DNB and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data for mapping ISA distribution. A regression model was established, in which LISI was used as an independent variable and the reference ISA from Landsat images was a dependent variable. The results indicated a better estimation performance using LISI than using a single VIIRS-DNB or MODIS NDVI variable. The LISI-based approach provides accurate spatial patterns from high values in core urban areas to low values in rural areas, with an overall root mean squared error of 0.11. The LISI-based approach is recommended for fractional ISA estimation in a large area.


title: Adequacy-fluency metrics: evaluating MT in the continuous space model framework

abstract: This work extends and evaluates a two-dimensional automatic evaluation metric for machine translation, which is designed to operate at the sentence level. The metric is based on the concepts of adequacy and fluency, aiming at decoupling both semantic and syntactic components of the translation process to provide a more balanced view on translation quality. These two elements are independently evaluated by using continuous space and n-gram language modeling frameworks, respectively. Two different implementations are evaluated: a monolingual version that fully operates on the target language side, and a cross-language version that has the main advantage of not requiring reference translations. Both implementations are evaluated by comparing their performance with state-of-the-art automatic metrics over a dataset involving five different European languages.


title: Classification of Skewed and Homogenous Document Corpora with Class-Based and Corpus-Based Keywords

abstract: In this paper, we examine the performance of the two policies for keyword selection over standard document corpora of varying properties. While in corpus-based policy a single set of keywords is selected for all classes globally, in class-based policy a distinct set of keywords is selected for each class locally. We use SVM as the learning method and perform experiments with boolean and tf-idf weighting. In contrast to the common belief, we show that using keywords instead of all words generally yields better performance and tf-idf weighting does not always outperform boolean weighting. Our results reveal that corpus-based approach performs better for large number of keywords while class-based approach performs better for small number of keywords. In skewed datasets, class-based keyword selection performs consistently better than corpus-based approach in terms of macro-averaged F-measure. In homogenous datasets, performances of class-based and corpus-based approaches are similar except for small number of keywords.


title: Brief paper Modified transpose Jacobian control of robotic systems �

abstract: The simplicity of Transpose Jacobian (TJ) control is a significant characteristic of this algorithm for controlling robotic manipulators. Nevertheless, a poor performance may result in tracking of fast trajectories, since it is not dynamics-based. Use of high gains can deteriorate performance seriously in the presence of feedback measurement noise. Another drawback is that there is no prescribed method of selecting its control gains. In this paper, based on feedback linearization approach a Modified TJ (MTJ) algorithm is presented which employs stored data of the control command in the previous time step, as a learning tool to yield improved performance. The gains of this new algorithm can be selected systematically, and do not need to be large, hence the noise rejection characteristics of the algorithm are improved. Based on Lyapunov's theorems, it is shown that both the standard and the MTJ algorithms are asymptotically stable. Analysis of the required computational effort reveals the efficiency of the proposed MTJ law compared to the Model-based algorithms. Simulation results are presented which compare tracking performance of the MTJ algorithm to that of the TJ and Model-Based algorithms in various tasks. Results of these simulations show that performance of the new MTJ algorithm is comparable to that of Computed Torque algorithms, without requiring a priori knowledge of plant dynamics, and with reduced computational burden. Therefore, the proposed algorithm is well suited to most industrial applications where simple efficient algorithms are more appropriate than complicated theoretical ones with massive computational burden.


title: Disposition (reduction) of (negative) partial product for Radix 4 Booth's Algorithm

abstract: Multiplier, being a very vital part in the design of microprocessor, graphical systems, multimedia systems, DSP system etc. It is very important to have an efficient design in terms of performance, area, speed of the multiplier, and for the same Booth's multiplication algorithm provides a very fundamental platform for all the new advances made for high end multipliers meant for faster multiplication with higher performance. The algorithm provides an efficient encoding of the bits during the first steps of the multiplication process. In pursuit of the same, Radix 4 booths encoding has increased the performance of the multiplier by reducing the number of partial products generated. Radix 4 Booths algorithm produces both positive and negative partial products and implementing the negative partial product nullifies the advances made in different units to some extent if not fully. Most of the research work focuses on the reduction of the number of partial products generated and making efficient implementation of the algorithm. There is very little work done on disposal of the negative partial products generated. The presented work in the paper addresses the issue of disposal of the negative partial products efficiently by computing the 2's complement avoiding the additional adder for adding 1 and generation of long carry chain, hence. The proposed mechanism also continues to support the concept of reducing the partial product and in persuasion of the same it is able to reduce the number of partial product and also improved further from n/2 +1 partial products achieved via modified booths algorithm to n/2. Also, while implementing the proposed mechanism using Verilog HDL, a mode selection capability is provided, enabling the same hardware to act as multiplier and as a simple two's complement calculator using the proposed mechanism. The proposed technique has added advantage in terms of its independentness of the number of bits to be multiplied. It is tested and verified with varied test vectors of different number bit sets. Xilinx synthesis tool is used for synthesis and the multiplier mechanism has a maximum operating frequency of 14.59 MHz and a delay of 7.013 ns.


title: Research challenges in legal-rule and QoS-aware cloud service brokerage

abstract: Abstract The ICT industry and specifically critical sectors, such as healthcare, transportation, energy and government, require as mandatory the compliance of ICT systems and services with legislation and regulation, as well as with standards. In the era of cloud computing, this compliance management issue is exacerbated by the distributed nature of the system and by the limited control that customers have on the services. Today, the cloud industry is aware of this problem (as evidenced by the compliance program of many cloud service providers), and the research community is addressing the many facets of the legal-rule compliance checking and quality assurance problem. Cloud service brokerage plays an important role in legislation compliance and QoS management of cloud services. In this paper we discuss our experience in designing a legal-rule and QoS-aware cloud service broker, and we explore relate research issues. Specifically we provide three main contributions to the literature: first, we describe the detailed design architecture of the legal-rule and QoS-aware broker. Second, we discuss our design choices which rely on the state of the art solutions available in literature. We cover four main research areas: cloud broker service deployment, seamless cloud service migration, cloud service monitoring, and legal rule compliance checking. Finally, from the literature review in these research areas, we identify and discuss research challenges.


title: An information-theoretic approach to detecting changes in multi-dimensional data streams

abstract: An ophthalmic lens for providing correction of distortion of the vertical position of an image in a lens prescribed for the condition of anisometropia comprises upper and lower portions having different optical centers. The lens surfaces of the upper and lower portions merge in a transverse band providing a smooth transition between the upper and lower lens surfaces over a vertical distance for example of 2 - 8 mm. The transverse band removes the conventional sharply visible boundary between the upper and lower lens surfaces and by introducing aberration into the lens at this point deters effective use of the lens over an angle of vision corresponding substantially to the angle of a cone of light entering the pupil of the eye and so prevents double vision occurring at the boundary of the lens surfaces. Methods of production of the lens are also disclosed.


title: A survey on context-aware recommender systems based on computational intelligence techniques

abstract: The demand for ubiquitous information processing over the Web has called for the development of context-aware recommender systems capable of dealing with the problems of information overload and information filtering. Contemporary recommender systems harness context-awareness with the personalization to offer the most accurate recommendations about different products, services, and resources. However, such systems come across the issues, such as sparsity, cold start, and scalability that lead to imprecise recommendations. Computational Intelligence (CI) techniques not only improve recommendation accuracy but also substantially mitigate the aforementioned issues. Large numbers of context-aware recommender systems are based on the CI techniques, such as: (a) fuzzy sets, (b) artificial neural networks, (c) evolutionary computing, (d) swarm intelligence, and (e) artificial immune systems. This survey aims to encompass the state-of-the-art context-aware recommender systems based on the CI techniques. Taxonomy of the CI techniques is presented and challenges particular to the context-aware recommender systems are also discussed. Moreover, the ability of each of the CI techniques to deal with the aforesaid challenges is also highlighted. Furthermore, the strengths and weaknesses of each of the CI techniques used in context-aware recommender systems are discussed and a comparison of the techniques is also presented.


The Architecture and Evolution of CPU-GPU Systems for General Purpose Computing


title: Immediate effect of a slow pace breathing exercise Bhramari pranayama on blood pressure and heart rate.

abstract: The study was carried out to evaluate the immediate effect Bhramari pranayama, a slow breathing exercise for 5 minutes on heart rate and blood pressure. Heart rate and blood pressure of volunteers were recorded. The subject was directed to inhale slowly up to the maximum for about 5 seconds and then to exhale slowly up to the maximum for about 15 sec keeping two thumbs on two external auditory canal, index and middle finger together on two closed eyes and ring finger on the two sides of the nose. During exhalation the subject must chant the word "O-U-Mmmma" with a humming nasal sound mimicking the sound of a humming wasp, so that the laryngeal walls and the inner walls of the nostril mildly vibrate (Bhramari pranayama, respiratory rate 3/min). After 5 minutes of this exercise, the blood pressure and heart rate were recorded again. Both the systolic and diastolic blood pressure were found to be'decreased with a slight fall in heart rate. Fall of diastolic pressure and mean pressure were significant. The result indicated that slow pace Bhramari pranayama for 5 minutes, induced parasympathetic dominance on cardiovascular system.


title: Mobile Homophily and Social Location Prediction

abstract: The mobility behavior of human beings is predictable to a varying degree e.g. depending on the traits of their personality such as the trait extraversion - introversion: the mobility of introvert users may be more dominated by routines and habitual movement patterns, resulting in a more predictable mobility behavior on the basis of their own location history while, in contrast, extrovert users get about a lot and are explorative by nature, which may hamper the prediction of their mobility. However, socially more active and extrovert users meet more people and share information, experiences, believes, thoughts etc. with others. which in turn leads to a high interdependency between their mobility and social lives. Using a large LBSN dataset, his paper investigates the interdependency between human mobility and social proximity, the influence of social networks on enhancing location prediction of an individual and the transmission of social trends/influences within social networks.


A multimodal corpus for integrated language and action


title: Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks

abstract: Mobile edge computing (MEC) is a promising paradigm to provide cloud-computing capabilities in close proximity to mobile devices in fifth-generation (5G) networks. In this paper, we study energy-efficient computation offloading (EECO) mechanisms for MEC in 5G heterogeneous networks. We formulate an optimization problem to minimize the energy consumption of the offloading system, where the energy cost of both task computing and file transmission are taken into consideration. Incorporating the multi-access characteristics of the 5G heterogeneous network, we then design an EECO scheme, which jointly optimizes offloading and radio resource allocation to obtain the minimal energy consumption under the latency constraints. Numerical results demonstrate energy efficiency improvement of our proposed EECO scheme.


title: A Review of Animal Models of Intervertebral Disc Degeneration: Pathophysiology, Regeneration, and Translation to the Clinic

abstract: Lower back pain is the leading cause of disability worldwide. Discogenic pain secondary to intervertebral disc degeneration is a significant cause of low back pain. Disc degeneration is a complex multifactorial process. Animal models are essential to furthering understanding of the degenerative process and testing potential therapies. The adult human lumbar intervertebral disc is characterized by the loss of notochordal cells, relatively large size, essentially avascular nature, and exposure to biomechanical stresses influenced by bipedalism. Animal models are compared with regard to the above characteristics. Numerous methods of inducing disc degeneration are reported. Broadly these can be considered under the categories of spontaneous degeneration, mechanical and structural models. The purpose of such animal models is to further our understanding and, ultimately, improve treatment of disc degeneration. The role of animal models of disc degeneration in translational research leading to clinical trials of novel cellular therapies is explored.


title: Dual-polarized K/Ka-band planar log-periodic antenna

abstract: This paper demonstrates an 18–40GHz four-arm planar log-periodic antenna with integrated wideband hybrid fabricated using printed circuit board (PCB) process. The two orthogonal linear polarizations are obtained by exciting the log-periodic structure with two microstrip lines perpendicularly oriented in two PCB layers. Two circular polarizations are obtained by monolithically integrating a quadrature hybrid with the antenna. The antenna with hybrid achieves return loss greater than 11dB, gain around 3dBi, and good radiation pattern consistency throughout the bandwidth.


title: Cervical nodal metastases in squamous cell carcinoma of the head and neck: What to expect

abstract: The treatment and management of malignancies of the head and neck is directly altered by the presence of metastatic cervical adenopathy. The treatment of nodal metastases in squamous cell carcinoma of the head and neck (HNSCCA) is determined by the lymphatic drainage of the upper aerodigestive tract. The lymphatic drainage is site-specific and occurs in a predictable manner. The purpose of this text is to provide an overview of the normal routes of lymphatic drainage in the head and neck and correlate this with the current nodal classification system. The specific aims of this manuscript are to 1) illustrate the expected lymphatic drainage patterns of HNSCCA arising in the different subsites (nasopharynx, oropharynx, oral cavity, larynx, and hypopharynx) and 2) review the expected frequency of metastases within nodal groups for HNSCCA that arise in these locations. An understanding of the topographical distribution and incidence of cervical lymph node metastases plays an integral role in the physical examination and radiological evaluation of patients with HNSCCA. For the neuroradiologist, this information may increases the ability to identify those nodal groups at risk for metastatic involvement.


title: Linkages Between In-Prison and Community-Based Health Services

abstract: This paper draws on a study of discharge planning for HIV-infected inmates in 10 large state correctional systems as well as on a review of literature to identify key elements associated with successful programs in the areas of organization and structure (e.g., dedicated staff and formal collaborations with health departments, community-based organizations, and parole agencies), program operations (e.g., continuity of care mechanisms, access to eligible clients, arrangement of specific appointments with community providers, provision of supplies of medications at release, and assistance with basic needs) and policy (e.g., dedicated funding, improved community-based services, and better and more timely access to public benefit programs).


title: AUV-Aided Localization for Underwater Sensor Networks

abstract: We propose a localization scheme for underwater acoustic sensor networks (UWSN) that does not require a priori infra-structure or synchronization between nodes. An autonomous underwater vehicle (AUV) aids in localizing the sensor nodes while roaming across the underwater sensor field. The objectives of this paper are to describe how to localize nodes using AUV and to describe the tradeoffs involved, i.e. ratio of localized nodes and localization accuracy. We show that localization success improves as the duration of the AUV localization process increases. In addition, we investigated localization using two methods, bounding-box and triangulation. The former achieves a higher localization ratio but with a higher error. In certain scenarios, we achieved 100% nodes localized with 3% error.


title: Hemodynamic effects of resistive breathing.

abstract: To examine the acute hemodynamic effects induced by large swings in intrathoracic pressure such as may be generated by obstructive lung disease, airway obstruction was simulated by means of two different fixed external alinear resistances and the results were compared with those for unobstructed breathing (C). Eight normal subjects breathed through external resistances during inspiration (I), expiration (E), or both (IE) at rest (Re) and exercise (Ex). The resistances were chosen to induce similar mouth pressure (Pm) swings at Re and Ex. Pleural pressures (Ppl) were found to correlate closely with Pm. During IE resistive breathing mean swings in Pm were -31 and +19 cmH2O at Re and -38 and +22 cmH2O at Ex, with a corresponding decrease in minute ventilation (-30 and -18%) and an increase in end-tidal PCO2 (+5.6 and +4.2 Torr); these were associated with an increase in heart rate (delta HR = 4 and 6 beats/min) and systolic systemic arterial pressure (delta Psas = 10 and 14 Torr at Re and Ex, respectively). O2 consumption and cardiac output did not change. The myocardial O2 consumption, estimated from the product HR X (Psas--Ppl), increased by 17 and 20% at Re and Ex, respectively. Changes in mechanics, gas exchange, and hemodynamics were less pronounced during I or E resistive loading. It is concluded that breathing through a tight external resistance during IE at Re and Ex increases the metabolic load on the myocardium.


title: B4: experience with a globally-deployed software defined wan

abstract: We present the design, implementation, and evaluation of B4, a private WAN connecting Google's data centers across the planet. B4 has a number of unique characteristics: i) massive bandwidth requirements deployed to a modest number of sites, ii) elastic traffic demand that seeks to maximize average bandwidth, and iii) full control over the edge servers and network, which enables rate limiting and demand measurement at the edge. These characteristics led to a Software Defined Networking architecture using OpenFlow to control relatively simple switches built from merchant silicon. B4's centralized traffic engineering service drives links to near 100% utilization, while splitting application flows among multiple paths to balance capacity against application priority/demands. We describe experience with three years of B4 production deployment, lessons learned, and areas for future work.


title: Indoor PDR performance enhancement using minimal map information and particle filters

abstract: For professional users such as firefighters and other first responders, GNSS positioning technology (GPS, assisted GPS) can satisfy outdoor positioning requirements in many instances. However, there is still a need for high-performance deep indoor positioning for use by these same professional users. This need has already been clearly expressed by various communities of end users in the context of WearIT@Work, an R&D project funded by the European Community's Sixth Framework Program. It is known that map matching can help for indoor pedestrian navigation. In most previous research, it was assumed that detailed building plans are available. However, in many emergency / rescue scenarios, only very limited building plan information may be at hand. For example a building outline might be obtained from aerial photographs or cataster databases. Alternatively, an escape plan posted at the entrances to many building would yield only approximate exit door and stairwell locations as well as hallway and room orientation. What is not known is how much map information is really required for a USAR mission and how much each level of map detail might help to improve positioning accuracy. Obviously, the geometry of the building and the course through will be factors consider. The purpose of this paper is to show how a previously published Backtracking Particle Filter (BPF) can be combined with different levels of building plan detail to improve PDR performance. A new in/out scenario that might be typical of a reconnaissance mission during a fire in a two-story office building was evaluated. Using only external wall information, the new scenario yields positioning performance (2.56 m mean 2D error) that is greatly superior to the PDR-only, no map base case (7.74 m mean 2D error). This result has a substantial practical significance since this level of building plan detail could be quickly and easily generated in many emergency instances. The technique could be used to mitigate heading errors that result from exposing the IMU to extreme operating conditions. It is hoped that this mitigating effect will also occur for more irregular paths and in larger traversed spaces such as parking garages and warehouses.


title: Falcon: fault localization in concurrent programs

abstract: Concurrency fault are difficult to find because they usually occur under specific thread interleavings. Fault-detection tools in this area find data-access patterns among thread interleavings, but they report benign patterns as well as actual faulty patterns. Traditional fault-localization techniques have been successful in identifying faults in sequential, deterministic programs, but they cannot detect faulty data-access patterns among threads. This paper presents a new dynamic fault-localization technique that can pinpoint faulty data-access patterns in multi-threaded concurrent programs. The technique monitors memory-access sequences among threads, detects data-access patterns associated with a program's pass/fail results, and reports dataaccess patterns with suspiciousness scores. The paper also presents the description of a prototype implementation of the technique in Java, and the results of an empirical study we performed with the prototype on several Java benchmarks. The empirical study shows that the technique can effectively and efficiently localize the faults for our subjects.


Hypertrichosis cubiti, a case report and literature review


title: Design and Analysis of a DC–43.5-GHz Fully Integrated Distributed Amplifier Using GaAs HEMT–HBT Cascode Gain Stage

abstract: Design and analysis of a dc-43.5-GHz fully integrated distributed amplifier (DA) using a GaAs high electron-mobility transistor (HEMT) heterojunction bipolar transistor (HBT) cascode gain stage is presented in this paper. The proposed DA is fabricated in a stacked 2-μm InGaP/GaAs HBT, 0.5-μm AlGaAs/GaAs enhancement- and depletion-mode HEMT monolithic microwave integrated circuit technology. A modified m -derived network and an HEMT-HBT cascode amplifier with inductive peaking technique are investigated to enhance the bandwidth of the DA. The bias networks of the DA are fully integrated in a single chip without off-chip bias-T or bias components. The measured average small-signal gain is 8.5 dB. The measured minimum noise figure is 4.2 dB. The measured maximum output 1-dB compression point (P1 dB) and the maximum output third-order intercept point are 8 and 18 dBm, respectively. Moreover, the DA is successfully evaluated with an eye diagram measurement, and demonstrates good transmission quality.


title: Dynamic binding in a neural network for shape recognition.

abstract: Given a single view of an object, humans can readily recognize that object from other views that preserve the parts in the original view. Empirical evidence suggests that this capacity reflects the activation of a viewpoint-invariant structural description specifying the object's parts and the relations among them. This article presents a neural network that generates such a description. Structural description is made possible through a solution to the dynamic binding problem: Temporary conjunctions of attributes (parts and relations) are represented by synchronized oscillatory activity among independent units representing those attributes


title: AIDE: Fast and Communication Efficient Distributed Optimization

abstract: In this paper, we present two new communication-efficient methods for distributed minimization of an average of functions. The first algorithm is an inexact variant of the DANE algorithm that allows any local algorithm to return an approximate solution to a local subproblem. We show that such a strategy does not affect the theoretical guarantees of DANE significantly. In fact, our approach can be viewed as a robustification strategy since the method is substantially better behaved than DANE on data partition arising in practice. It is well known that DANE algorithm does not match the communication complexity lower bounds. To bridge this gap, we propose an accelerated variant of the first method, called AIDE, that not only matches the communication lower bounds but can also be implemented using a purely first-order oracle. Our empirical results show that AIDE is superior to other communication efficient algorithms in settings that naturally arise in machine learning applications.


title: Reducing Overfitting in Deep Networks by Decorrelating Representations

abstract: One major challenge in training Deep Neural Networks is preventing overfitting. Many techniques such as data augmentation and novel regularizers such as Dropout have been proposed to prevent overfitting without requiring a massive amount of training data. In this work, we propose a new regularizer called DeCov which leads to significantly reduced overfitting (as indicated by the difference between train and val performance), and better generalization. Our regularizer encourages diverse or non-redundant representations in Deep Neural Networks by minimizing the cross-covariance of hidden activations. This simple intuition has been explored in a number of past works but surprisingly has never been applied as a regularizer in supervised learning. Experiments across a range of datasets and network architectures show that this loss always reduces overfitting while almost always maintaining or increasing generalization performance and often improving performance over Dropout.


title: Factors affecting the quality of life before and after surgery in patients with chronic thromboembolic pulmonary hypertension

abstract: PURPOSE ::: To test the hypothesis that quality of life (QoL) parameters before surgery in patients with chronic thromboembolic pulmonary hypertension (CTEPH) are influenced by clinical determinants related to the underlying disease and to examine QoL parameters affected in the long-term after the operation by complications presenting in the early postoperative period. ::: ::: ::: METHODS ::: This prospective cohort study included 128 patients who presented with CTEPH before and after pulmonary thromboendarterectomy (PTE; 1-year follow-up). All patients were examined regarding QoL using the Short-Form 36 Health Survey Questionnaire (SF-36). ::: ::: ::: RESULTS ::: In patients with CTEPH, PTE provided immediate improvement in terms of pulmonary hemodynamic parameters and favorable effects on long-term outcome, including QoL 1 year after surgery. Multivariate analysis showed that systolic pulmonary arterial pressure, right ventricular ejection fraction, and the presence of coronary artery disease and chronic obstructive pulmonary disease (COPD) were independent factors affecting QoL on several SF-36 subscales in patients with CTEPH prior to surgery. The factors that affect patient QoL 1 year after surgery on some SF-36 subscales included the presence of coronary artery disease, COPD, heart failure, residual pulmonary hypertension, and prolonged ventilation, neurological complications in the early postoperative period of PTE. ::: ::: ::: CONCLUSIONS ::: Surgical treatment for CTEPH leads to an increase in QoL in all SF-36 subscales, excluding general health perceptions. Factors affecting QoL in patients with CTEPH included severity of pulmonary arterial hypertension, comorbidity, and complications in the early postoperative period after PTE, such as heart failure, neurologic problems, residual pulmonary hypertension, and prolonged ventilation.


title: Scalability of control planes for Software defined networks: Modeling and evaluation

abstract: With the increasing popularity of Software defined network (SDN), designing a scalable SDN control plane becomes a critical problem. An effective approach to improving the scalability is to design distributed architecture of SDN control plane. However, how to evaluate the scalability of SDN control planes remains unexplored. In this paper, we propose a metric of scalability for SDN control planes, and study three typical SDN control plane structures, including centralized, decentralized and hierarchical architectures. We build performance models for response time, based on which we evaluate the scalability of these three structures. Furthermore, the comparison between different architectures are analyzed by mathematical methods. Numerical evaluations are also conducted to validate the conclusions drawn in this paper.


title: Repeated retrieval during learning is the key to long-term retention

abstract: Abstract Tests not only measure the contents of memory, they can also enhance learning and long-term retention. We report two experiments inspired by Tulving’s (1967) pioneering work on the effects of testing on multitrial free recall. Subjects learned lists of words across multiple study and test trials and took a final recall test 1 week after learning. In Experiment 1, repeated testing during learning enhanced retention relative to repeated studying, although alternating study and test trials produced the best retention. In Experiment 2, recalled items were dropped from further studying or further testing to investigate how different types of practice affect retention. Repeated study of previously recalled items did not benefit retention relative to dropping those items from further study. However, repeated recall of previously recalled items enhanced retention by more than 100% relative to dropping those items from further testing. Repeated retrieval of information is the key to long-term retention.


title: Design of smart lock system for doors with special features using bluetooth technology

abstract: Nowadays the use of Internet of Things (IoT) technology has developed that almost all aspects in human's life utilize IoT technology to increase the quality of life. Lock system is one of those aspects that has been impacted by the massive development of IoT, for example lock system that can be opened or closed by entering the password or by gadget to control it. The main component of smart home concept lays on the door, so the door lock system becomes an interesting topic to discuss. The paper presents a design of lock system for operating door without a control to open or lock it that brings a comfort and can be applied effectively. Besides, the lock system can be used for all kinds of human's physical condition. The system uses bluetooth technology with low power and is available on almost all gadgets. The design of the system is also completed with special feature to increase the security and the comfort of the users. The lock system indirectly supports the program of United Convention of Right People with Disabilities.


title: Simplified Design Methodology for a Slotless Brushless DC Motor

abstract: The paper presents a simplified analytical method to design a small two-pole slotless brushless dc motor. Using only a few approximations, the motor analytical model is formulated to generate a system of equations. The system can be solved analytically, producing a motor design for given specifications. The method is used to design a motor with the specifications 150 W, 10 000 rpm, and 18 V


title: Online Stability in Human-Robot Cooperation with Admittance Control

abstract: In the design of a compliant admittance controller for physical human-robot interaction, it is necessary to ensure stable and effective cooperation. The stability of the admittance controller is mainly threatened by a stiff environment. Many methods that guarantee stability in arbitrary environments, impose conservative control gains that limit the effectiveness of the cooperation. Inspired by previous work in frequency domain stability observers, a method is proposed in this paper to detect unstable behavior and stabilize the robot with online adaptation of the admittance control gains. The introduced instability index is based on frequency domain analysis, which very quickly detects unstable behavior by monitoring high frequency oscillation in the force signal. To treat the instability, an adaptation scheme of the admittance parameters is proposed, that relaxes conservative gains and improves the cooperation by considering the effect of variable admittance on the operators’ effort. We investigate two human-robot co-manipulation tasks; cooperation within a zero stiffness environment and cooperation in contact with a stiff double-wall virtual environment. The proposed methods are validated experimentally with a number of subjects in cooperation with an LWR manipulator.


title: Modeling astrocyte-neuron interactions in a tripartite synapse

abstract: Glial cells (microglia, oligodendrocytes, and especially astrocytes) play a critical role in the central nervous system by affecting in various ways the neuronal single cell level interactions as well as connectivity and communication at the network level, both in the developing and mature brain. Numerous studies (see, e.g., [1-3]) indicate an important modulatory role of astrocytes in brain homeostasis but most specifically in neuronal metabolism, plasticity, and survival. Astrocytes are also known to play an important role in many neurological disorders and neurodegenerative diseases. It is therefore important in the light of recent evidence to assess how the astrocytes interact with neurons, both in situ and in silico. The integration of biological knowledge into computational models is becoming increasingly important to help understand the role of astrocytes both in health and disease. We have previously addressed the role of transmitters and amyloid-beta peptide on calcium signals in rat cortical astrocytes [4]. In this work, we extend the work by using a modified version of the previously developed model [5] for astrocyte-neuron interactions in a tripartite synapse to explore the effects of various pre- and postsynaptic as well as extrasynaptic mechanisms on neuronal activity. We consider extending the model to include various additional mechanisms, such as the role of IP3 receptor function, recycling of neurotransmitters, K+ buffering by the Na+/K+ pump, and retrograde signaling by endocannabinoids. The improved tripartite synapse model for astrocyte-neuron interactions will provide an essential modeling tool for facilitating studies of local network dynamics in the brain. The model may also serve as an important step toward understanding mechanisms behind induction and maintenance of plastic changes in the brain.


title: A Broadband 3 dB Tandem Coupler Utilizing Right/Left Handed Transmission Line Sections

abstract: A new type of broadband 3 dB tandem coupler has been proposed featuring frequency characteristics of the resulting coupling similar to those of a classic 3 dB two-section asymmetric coupled-line directional coupler. The coupler is composed of two loosely coupled-line sections having electrical lengths close to quarter-wavelength connected by right-handed and left-handed transmission line sections. Theoretical analysis and design equations have been presented with an exemplary realization. Measurements of the manufactured tandem coupler operating at f0 = 1 GHz having wide operational bandwidth have been shown to validate the presented analysis.


title: Indoor positioning fusion algorithm for smartphones

abstract: In this paper, a particle filter based fusion algorithm running on smartphones is introduced. It adopts signals, camera and IMU to achieve an accurate indoor positioning. The fusion algorithm achieves a localization accuracy of 2 meter during 80% test time and the maximum error is 4.5 meter.


title: Simulation and singularity analysis of 3-PRS parallel manipulator

abstract: This work focuses on the modelling and simulation of 3-PRS (Prismatic — Revolute — Spherical) Tripod Parallel Manipulator. This tripod mechanism consists of base platform and movable platform, which are connected by means of three links or limbs. Spherical joints are used to connect one end of the link and the moving platform and the other end of the link is connected by revolute joint to the nut. This tripod type Parallel Manipulator is having two orientation freedoms and one translation freedom, which is actuated by means of screw pair, which in turn is operated by a stepper motor. This proposed tripod mechanism is modelled and simulated by using ADAMS®. The simulation results are obtained by considering the geometrical parameters, Transmission angle of the link and Singularity of the mechanism. From the simulation results a study is carried out based on torque at the joints, angular tilt and singular positions of the parallel manipulator.


title: Burs of free C-space: A novel structure for path planning

abstract: This paper presents a new approach to C-space exploration and path planning for robotic manipulators using the structure named bur of free C-space. This structure builds upon the so-called bubble, which is a local volume of free C-space, easily computed using the distance information in the workspace. We show how the same distance information can be used to compute the bur that can reach substantially beyond the boundary of the bubble. It is shown how burs can be used to form a rapidly exploring bur tree (RBT): a space-filling tree that resembles RRT. Such a structure can easily be used within a suitably tailored path planning algorithm. Simulation study shows how the RBT-based algorithm outperforms the classical RRT-based method.


title: Selective attention to pitch amid conflicting auditory information: context-coding and filtering strategies

abstract: An auditory Eriksen-flanker task was used to study how conflicting information interferes with selective attention to task-relevant differences in pure-tone frequency. Across the observation intervals of the discrimination task, the relevant frequency differences between target tones were positive, but within an observation interval, they could appear to be small or negative relative to conflicting differences in flanker tones leading or trailing the target. Being correct required attending to the between-target and ignoring the target–flanker pitch relation (across and within observation-interval, respectively). The interference index was an elevation of conflict-laden frequency discrimination thresholds (FDTs), relative to no-conflict FDTs. When conflicting differences in frequency or level (but not in duration) trailed the relevant differences, interference (i.e., FDT elevation) was large and persistent, increased with the target–flanker time proximity, but decreased with extensive training. Interference occurs when the target–flanker pitch relation is more prominent than the one between targets, and the physical and/or perceptual effects of relevant and conflicting differences tend to cancel one another, as with the above conflicting differences. With untrained participants, the target–flanker pitch relation is most prominent in conditions fostering both the perceptual grouping of the target and flanker (e.g., close time proximity), and the recency and salience of the conflicting differences (e.g., trailing conflicting difference); conversely, by lessening such grouping and salience, prolonged training decreases or nullifies the interference. The interference observed herein does not arise because the relevant and the conflicting differences each prompt separate decisions or responses that are in mutual conflict; instead, it arises from the early-stage interaction between their perceptual effects.


title: An analysis pattern for invoice processing

abstract: We discuss an analysis pattern for invoice processing. The pattern describes events such as the creation and validation of an invoice, followed by the payment process. This pattern is composed of two simpler patterns that describe the creation and payment of the invoice, respectively. The composite pattern represents a minimum application so that it can be applied to a variety of situations and it can be combined with other related patterns to describe more complex applications. The component patterns have value of their own and can be used independently.


title: Static hand gesture recognition based on HOG characters and support vector machines

abstract: Gesture recognition technology has important significance in the field of human-computer interaction (HCI), the gesture recognition technology which is based on visual is sensitive to the impact of the experimental environment lighting, and so, the recognition result will produce a greater change; it makes this technology one of the most challenging topics. HOG feature which is successfully applied to pedestrian detection is operating on the local grid unit of image, so it can maintain a good invariance on geometric and optical deformation. In this paper, we extracted the gradient direction histogram (HOG) features of gestures, then, a Support Vector Machines is used to train these feature vectors, at testing time, a decision is taken using the previously learned SVMs, and compared the same gesture recognition rate in different light conditions. Experimental results show that the HOG feature extraction and multivariate SVM classification methods has a high recognition rate, and the system has a better robustness for the illumination.


title: Ethereum transaction graph analysis

abstract: Cryptocurrency platforms such as Bitcoin and Ethereum have become more popular due to decentralized control and the promise of anonymity. Ethereum is particularly powerful due to its support for smart contracts which are implemented through Turing complete scripting languages and digital tokens that represent fungible tradable goods. It is necessary to understand whether de-anonymization is feasible to quantify the promise of anonymity. Cryptocurrencies are increasingly being used in online black markets like Silk Road and ransomware like CryptoLocker and WannaCry. In this paper, we propose a model for persisting transactions from Ethereum into a graph database, Neo4j. We propose leveraging graph compute or analytics against the transactions persisted into a graph database.


title: Evaluating and Comparing the IGraph Community Detection Algorithms

abstract: Complex networks became a very important tool in machine learning field, helping researchers to investigate and mine data. They can model real dynamic networks, aiding to unveil information's about the systems they model. Communities are notable groups that may exist in a complex network and the community detection problem is the focus of attention of many researchers. The igraph library implements a good set of community detection algorithms, allowing researchers to easily apply them to data mining tasks. But each algorithm uses a different approach, leading to different performances. In this paper, the community detection algorithms implemented in the igraph library are investigated and ranked according to their performances in a set of different scenarios. Results show walktrap and multi-level got the highest scores while leading eigenvector and spinglass got the lowest ones. These findings are an important contribution for aiding researchers to select or discard algorithms in their own experiments using igraph library.


title: Does hippotherapy improve balance in persons with multiple sclerosis: a systematic review.

abstract: AIM ::: Multiple sclerosis (MS) leads to changes in balance due to the breakdown of a number of neurological processes. Hippotherapy utilizes the movement of the horse to provide sensory feedback and has been used as a therapeutic intervention for different neurological conditions. Little is known about the effects of hippotherapy in MS. The purpose of this study is to systematically review and examine the evidence for hippotherapy as an intervention to improve balance in persons with MS. ::: ::: ::: METHODS ::: Major electronic databases were searched for articles relating to hippotherapy, MS and balance. Only full length articles published in peer reviewed journals that were written in English or translated into English were included. Articles were assessed using a modified quality index that was used for descriptive purposes only and did not exclude any study from the review. ::: ::: ::: RESULTS ::: All studies examined in this review were either case-control or case-series. Collectively all three studies reported improvements in balance. Pre-test and post-test Berg Balance Scale scores in two studies revealed that primary progressive MS demonstrated the greatest amount of change after hippotherapy compared to other subtypes of MS. ::: ::: ::: CONCLUSION ::: Hippotherapy has a positive effect on balance in persons with MS and has an added benefit of enhancing quality of life. The data is limited and further research will lead to a greater knowledge base and has the potential to increase accessibility for hippotherapy to be used as a rehabilitation modality.


A scaffolding approach to coreference resolution integrating statistical and rule-based models


ffects of mindfulness meditation training on anticipatory alpha modulation in rimary somatosensory cortex


title: Smart anti-theft vehicle tracking system for Bangladesh based on Internet of Things

abstract: With the emergence of new technology and innovations, people are searching smarter ways to protect/monitor their properties remotely. In accordance to that, at present GPS based tracking system is frequently used in vehicle tracking, children/pet tracking, aircraft tracking, any personal belongings tracking, fleet management and so on. This paper introduces a Smart Anti-Theft Vehicle System based on Internet of Things (IoT) for monitoring the movement of any equipped vehicle from anywhere in real time. At the implementation of this system, Global Positioning System (GPS), Global System for Mobile Communication (GSM)/General Packet Radio Service (GPRS) and Microcontrollers are used to enable users for monitoring their vehicles in a convenient manner. This system provides the access to check the movement and control (emergency stop by closing the fuel line) vehicles remotely by using mobile application. The hardware prototype of the proposed system and the user application for monitoring and controlling vehicles are presented in this paper.


title: BDMA in Multicell Massive MIMO Communications: Power Allocation Algorithms

abstract: We investigate power allocation strategies for beam division multiple access transmission in multicell massive multiple-input-multiple-output (MIMO) communications. Focusing on massive MIMO downlink with only statistical channel state information at serving base stations and multiantenna terminals, the eigenmatrices of channel transmit covariance matrices become identical and independent of terminals. Utilizing these eigenmatrices as precoding matrices, we consider power allocation of beam domain transmission. By treating cochannel user interferences as noises, the objective function of achievable ergodic sum-rate of the multicell massive MIMO downlink reduces to a difference of concave functions. We identify the orthogonality conditions for optimal power allocation. The results show that the transmit power allocated to the users should be nonoverlapping across beams defined by the channel transmit covariance matrices. We present two algorithms to optimize power allocation in the beam space. We also prove the convergence of the algorithms and show that the solution obtained by the algorithms satisfies the orthogonality conditions. Numerical results confirm the efficiency and the improved performance of the proposed algorithms.


title: Printed folded meander line dual-band monopole for TV White space and GSM

abstract: A probe-fed printed folded meander line monopole antenna with dual band operation in TV White space and GSM band for machine-to-machine application is presented. The compact antenna operates at 706 MHz and 940 MHz respectively with high efficiency and high gain across the frequency bands. A comparison between a simple printed folded (hairpin) monopole antenna and a printed folded meander line monopole is demonstrated.


title: An LLC Resonant DC–DC Converter for Wide Output Voltage Range Battery Charging Applications

abstract: In this paper, resonant tank design procedure and practical design considerations are presented for a high performance LLC multiresonant dc-dc converter in a two-stage smart battery charger for neighborhood electric vehicle applications. The multiresonant converter has been analyzed and its performance characteristics are presented. It eliminates both low- and high-frequency current ripple on the battery, thus maximizing battery life without penalizing the volume of the charger. Simulation and experimental results are presented for a prototype unit converting 390 V from the input dc link to an output voltage range of 48-72 V dc at 650 W. The prototype achieves a peak efficiency of 96%.


title: The computational rise and fall of fairness

abstract: The fair division of indivisible goods has long been an important topic in economics and, more recently, computer science. We investigate the existence of envyfree allocations of indivisible goods, that is, allocations where each player values her own allocated set of goods at least as highly as any other player's allocated set of goods. Under additive valuations, we show that even when the number of goods is larger than the number of agents by a linear fraction, envy-free allocations are unlikely to exist.We then show that when the number of goods is larger by a logarithmic factor, such allocations exist with high probability. We support these results experimentally and show that the asymptotic behavior of the theory holds even when the number of goods and agents is quite small. We demonstrate that there is a sharp phase transition from nonexistence to existence of envy-free allocations, and that on average the computational problem is hardest at that transition.


Digital axis of rotation measurements


Extension of heuristic evaluation method: a review and reappraisal


title: Modelling Microtubules in the Brain as n-qudit Quantum Hopfield Network and Beyond

abstract: Abstract The scientific approach to understand the nature of consciousness revolves around the study of the human brain. Neurobiological studies that compare the nervous system of different species have accorded the highest place to humans on account of various factors that include a highly developed cortical area comprising of approximately 100 billion neurons, that are intrinsically connected to form a highly complex network. Quantum theories of consciousness are based on mathematical abstraction and the Penrose–Hameroff Orch-OR theory is one of the most promising ones. Inspired by the Penrose–Hameroff Orch-OR theory, Behrman et al. have simulated a quantum Hopfield neural network with the structure of a microtubule. They have used an extremely simplified model of the tubulin dimers with each dimer represented simply as a qubit, a single quantum two-state system. The extension of this model to n-dimensional quantum states or n-qudits presented in this work holds considerable promise for even higher mathematical abstraction in modelling consciousness systems.


title: Classification using discriminative restricted Boltzmann machines

abstract: Recently, many applications for Restricted Boltzmann Machines (RBMs) have been developed for a large variety of learning problems. However, RBMs are usually used as feature extractors for another learning algorithm or to provide a good initialization for deep feed-forward neural network classifiers, and are not considered as a standalone solution to classification problems. In this paper, we argue that RBMs provide a self-contained framework for deriving competitive non-linear classifiers. We present an evaluation of different learning algorithms for RBMs which aim at introducing a discriminative component to RBM training and improve their performance as classifiers. This approach is simple in that RBMs are used directly to build a classifier, rather than as a stepping stone. Finally, we demonstrate how discriminative RBMs can also be successfully employed in a semi-supervised setting.


title: A support vector machine based naive Bayes algorithm for spam filtering

abstract: Naive Bayes classifiers are widely used to filter spam emails, however, the strong independence assumptions between features limit their performance in accurately identifying spams. To address this issue, we proposed a support machine vector based naive Bayes — SVM-NB — filtering system. The SVM-NB first constructs an optimal separating hyperplane that divides samples in the training set into two categories. For samples located nearby the hyperplane, if they are in different categories, one of them will be eliminated from the training set. In this way, the dependence between samples is reduced and the entire training sample space is simplified. With the trimmed training set, the naive Bayes algorithm is applied to classify emails in the test set. The SVM-NB system is evaluated with the dataset obtained from DATAMALL. Experiment results demonstrate that SVM-NB can achieve a higher spam-detection accuracy and a faster classification speed.


title: Lyapunov-Based Small-Gain Theorems for Hybrid Systems

abstract: Constructions of strong and weak Lyapunov functions are presented for a feedback connection of two hybrid systems satisfying certain Lyapunov stability assumptions and a small-gain condition. The constructed strong Lyapunov functions can be used to conclude input-to-state stability (ISS) of hybrid systems with inputs and global asymptotic stability (GAS) of hybrid systems without inputs. In the absence of inputs, we also construct weak Lyapunov functions nondecreasing along solutions and develop a LaSalle-type theorem providing a set of sufficient conditions under which such functions can be used to conclude GAS. In some situations, we show how average dwell time (ADT) and reverse average dwell time (RADT) “clocks” can be used to construct Lyapunov functions that satisfy the assumptions of our main results. The utility of these results is demonstrated for the “natural” decomposition of a hybrid system as a feedback connection of its continuous and discrete dynamics, and in several design-oriented contexts: networked control systems, event-triggered control, and quantized feedback control.


On the impossibility of informationally efficient markets


title: Exposure to Internet Pornography among Children and Adolescents: A National Survey

abstract: Estimates suggest that up to 90% or more youth between 12 and 18 years have access to the Internet. Concern has been raised that this increased accessibility may lead to a rise in pornography seeking among children and adolescents, with potentially serious ramifications for child and adolescent sexual development. Using data from the Youth Internet Safety Survey, a nationally representative, cross-sectional telephone survey of 1501 children and adolescents (ages 10–17 years), characteristics associated with self-reported pornography seeking behavior, both on the Internet and using traditional methods (e.g., magazines), are identified. Seekers of pornography, both online and offline, are significantly more likely to be male, with only 5% of self-identified seekers being female. The vast majority (87%) of youth who report looking for sexual images online are 14 years of age or older, when it is developmentally appropriate to be sexually curious. Children under the age of 14 who have intentionally looked at ...


Towards a Universal Sentiment Classifier in Multiple languages


To transfer or not to transfer


title: On time blood pressure prediction with the use of PPG signals

abstract: The article presents the compact system for predicting the blood pressure with the use of PPG (photoplethysmogram) curves. The algorithm for data measurement and analysis was proposed. The prototype system and initial experimental results were presented. In the system the filters were applied to the input signal for improving the peak detection algorithm. The measurement device allows the user to record the data and transmit to a remote location. In more compact form in future it can act as an Internet of Things wearable agent.


title: Online False Data Injection Attack Detection With Wavelet Transform and Deep Neural Networks

abstract: State estimation is critical to the operation and control of modern power systems. However, many cyber-attacks, such as false data injection attacks, can circumvent conventional detection methods and interfere the normal operation of grids. While there exists research focusing on detecting such attacks in dc state estimation, attack detection in ac systems is also critical, since ac state estimation is more widely employed in power utilities. In this paper, we propose a new false data injection attack detection mechanism for ac state estimation. When malicious data are injected in the state vectors, their spatial and temporal data correlations may deviate from those in normal operating conditions. The proposed mechanism can effectively capture such inconsistency by analyzing temporally consecutive estimated system states using wavelet transform and deep neural network techniques. We assess the performance of the proposed mechanism with comprehensive case studies on IEEE 118- and 300-bus power systems. The results indicate that the mechanism can achieve a satisfactory attack detection accuracy. Furthermore, we conduct a preliminary sensitivity test on the control parameters of the proposed mechanism.


title: Optical character recognition: an illustrated guide to the frontier

abstract: Optical character recognition (OCR) is the most prominent and successful example of pattern recognition to date. There are thousands of research papers and dozens of OCR products. Optical Character Rcognition: An Illustrated Guide to the Frontier offers a perspective on the performance of current OCR systems by illustrating and explaining actual OCR errors. The pictures and analysis provide insight into the strengths and weaknesses of current OCR systems, and a road map to future progress. Optical Character Recognition: An Illustrated Guide to the Frontier will pique the interest of users and developers of OCR products and desktop scanners, as well as teachers and students of pattern recognition, artificial intelligence, and information retrieval. The first chapter compares the character recognition abilities of humans and computers. The next four chapters present 280 illustrated examples of recognition errors, in a taxonomy consisting of Imaging Defects, Similar Symbols, Punctuation, and Typography. These examples were drawn from large-scale tests conducted by the authors. The final chapter discusses possible approaches for improving the accuracy of today's systems, and is followed by an annotated bibliography. Optical Character Recognition: An Illustrated Guide to the Frontier is suitable as a secondary text for a graduate level course on pattern recognition, artificial intelligence, and information retrieval, and as a reference for researchers and practitioners in industry.


title: Decentralized trust management

abstract: We identify the trust management problem as a distinct and important component of security in network services. Aspects of the trust management problem include formulating security policies and security credentials, determining whether particular sets of credentials satisfy the relevant policies, and deferring trust to third parties. Existing systems that support security in networked applications, including X.509 and PGP, address only narrow subsets of the overall trust management problem and often do so in a manner that is appropriate to only one application. This paper presents a comprehensive approach to trust management, based on a simple language for specifying trusted actions and trust relationships. It also describes a prototype implementation of a new trust management system, called PolicyMaker, that will facilitate the development of security features in a wide range of network services.


title: Multimodal emotion recognition in speech-based interaction using facial expression, body gesture and acoustic analysis

abstract: In this paper a study on multimodal automatic emotion recognition during a speech-based interaction is presented. A database was constructed consisting of people pronouncing a sentence in a scenario where they interacted with an agent using speech. Ten people pronounced a sentence corresponding to a command while making 8 different emotional expressions. Gender was equally represented, with speakers of several different native languages including French, German, Greek and Italian. Facial expression, gesture and acoustic analysis of speech were used to extract features relevant to emotion. For the automatic classification of unimodal data, bimodal data and multimodal data, a system based on a Bayesian classifier was used. After performing an automatic classification of each modality, the different modalities were combined using a multimodal approach. Fusion of the modalities at the feature level (before running the classifier) and at the results level (combining results from classifier from each modality) were compared. Fusing the multimodal data resulted in a large increase in the recognition rates in comparison to the unimodal systems: the multimodal approach increased the recognition rate by more than 10% when compared to the most successful unimodal system. Bimodal emotion recognition based on all combinations of the modalities (i.e., ‘face-gesture’, ‘face-speech’ and ‘gesture-speech’) was also investigated. The results show that the best pairing is ‘gesture-speech’. Using all three modalities resulted in a 3.3% classification improvement over the best bimodal results.


title: On the laminar flow in a free jet of liquid at high Reynolds numbers

abstract: This paper is concerned with the jet of liquid, open to the atmosphere, that emerges from a two-dimensional channel in which there is Poiseuille flow far upstream, the flow being driven by an applied pressure gradient. The problem is discussed with the aid of the method of matched asymptotic expansions; the small parameter involved is the inverse Reynolds number. A boundary layer forms adjacent to the free surface, and a classical boundary-layer analysis is applied to find the flow there (for moderate distances downstream); the influence of this boundary layer on the flow in the core of the jet is then investigated. Higher-order boundary-layer effects, such as indeterminacy and eigensolutions, are also discussed. The first few terms are found of an asymptotic expansion for the equation of the free surface, and considerations of momentum balance are applied to find the asymptotic contraction ratio of the jet.


title: Re-introduction and evaluation of an accurate, high capacity bioassay for melanocyte-stimulating hormone using the skin of Anolis carolinensis in vitro.

abstract: A simple and rapid assay for the quantitative determination of melanocyte-stimulating hormone (MSH) activity, using skin fragments of the lizard Anolis carolinensis in vitro, is described in detail. This assay, in which a quantal response (e.g. induction of a brownish-green colour) can be detected by visual observation, allows determination of MSH activity in up to 50 samples/day by one person, using the skin of one lizard. The mean dose found to induce this colour change was 0-15 ng synthetic alpha-MSH/ml (range 0-02-0-5 ng/ml). The assays shows high accuracy, reproducibility and specificity. Anterior and posterior lobe hormones as well as pituitary catecholamines do not interfere with the determination of pituitary MSH activitymthe method is compared with the assay using hypophysectomized frogs (Rana pipiens) in vivo. Determinations of MSH in pituitary extracts by both methods gave quantitatively similar results when determined with alpha-MSH as the reference substance. However, when beta-seryl MSH was used as a reference, the two assays gave different results for the MSH activity of the pituitary extractsmthis indicates that MSH from the rat pituitary gland has a biological activity similar to that of alpha-MSH rather than to that of beta-seryl MSH.


title: Reactome graph database: Efficient access to complex pathway data

abstract: Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types.


title: Exploring TED talks as linked data for education

abstract: In this paper, we present the TED Talks dataset which exposes all metadata and the actual transcripts of available TED talks as structured Linked Data. The TED talks collection is composed of more than 1800 talks, along with 35 000 transcripts in over 30 languages, related to a wide range of topics. In this regard, TED talks metadata available in structured, multilingual and HTTP-accessible form constitute a valuable resource, for instance, for schoolteachers, to explore controversial contemporary topics with their students in order to stimulate awareness and critical thinking or as a means for language learning. Moreover, being compliant with state-of-the-art Linked Data principles, our dataset facilitates the computation of links with related data and resources. The TED dataset is used by a number of educational applications, and it is included in the LinkedUp Data Catalog.


title: The Role of Intuition in the Generation and Evaluation Stages of Creativity

abstract: Both intuition and creativity are associated with knowledge creation, yet a clear link between them has not been adequately established. First, the available empirical evidence for an underlying relationship between intuition and creativity is sparse in nature. Further, this evidence is arguable as the concepts are diversely operationalized and the measures adopted are often not validated sufficiently. Combined, these issues make the findings from various studies examining the link between intuition and creativity difficult to replicate. Nevertheless, the role of intuition in creativity should not be neglected as it is often reported to be a core component of the idea generation process, which in conjunction with idea evaluation are crucial phases of creative cognition. We review the prior research findings in respect of idea generation and idea evaluation from the view that intuition can be construed as the gradual accumulation of cues to coherence. Thus, we summarize the literature on what role intuitive processes play in the main stages of the creative problem-solving process and outline a conceptual framework of the interaction between intuition and creativity. Finally, we discuss the main challenges of measuring intuition as well as possible directions for future research.


title: SNOW 2014 Data Challenge: Assessing the Performance of News Topic Detection Methods in Social Media

abstract: The SNOW 2014 Data Challenge aimed at creating a public benchmark and evaluation resource for the problem of topic detection in streams of social content. In particular, given a set of tweets spanning a time interval of interest, the Challenge required the extraction of the most significant news topics in short timeslots within the selected interval. Here, we provide details with respect to the Challenge definition, the data collection and evaluation process, and the results achieved by the 11 teams that participated in it, along with a concise retrospective analysis of the main conclusions and arising issues.


title: WirePrint: 3D printed previews for fast prototyping

abstract: Even though considered a rapid prototyping tool, 3D printing is so slow that a reasonably sized object requires printing overnight. This slows designers down to a single iteration per day. In this paper, we propose to instead print low-fidelity wireframe previews in the early stages of the design process. Wireframe previews are 3D prints in which surfaces have been replaced with a wireframe mesh. Since wireframe previews are to scale and represent the overall shape of the 3D object, they allow users to quickly verify key aspects of their 3D design, such as the ergonomic fit. To maximize the speed-up, we instruct 3D printers to extrude filament not layer-by-layer, but directly in 3D-space, allowing them to create the edges of the wireframe model directly one stroke at a time. This allows us to achieve speed-ups of up to a factor of 10 compared to traditional layer-based printing. We demonstrate how to achieve wireframe previews on standard FDM 3D printers, such as the PrintrBot or the Kossel mini. Users only need to install the WirePrint software, making our approach applicable to many 3D printers already in use today. Finally, wireframe previews use only a fraction of material required for a regular print, making it even more affordable to iterate.


title: HBPR: History Based Prediction for Routing in Infrastructure-less Opportunistic Networks

abstract: In Opportunistic Networks (OppNets), the existence of an end-to-end connected path between the sender and the receiver is not possible. Thus routing in this type of networks is different from the traditional Mobile Adhoc Networks (MANETs). MANETs assume the existence of a fixed route between the sender and the receiver before the start of the communication and till its completion. Routes are constructed dynamically as the source node or an intermediate node can choose any node as next hop from a group of neighbors assuming that it will take the message closer to the destination node or deliver to the destination itself. In this paper, we proposed a novel History Based Prediction Routing (HBPR) protocol for infrastructure-less OppNets which utilizes the behavioral information of the nodes to find the best next node for routing. The proposed protocol was compared with the Epidemic routing protocol. Through simulations it was found that the HBPR performs better in terms of number of messages delivered and the overhead ratio than the Epidemic protocol.


title: The causal Model of effective factors on Intention to use of information technology among payam noor and Traditional universities students

abstract: The objective of this study is presenting the causal modeling of intention to use technology among university student. Correlation is used as the method of research. Instrument of this study is standard questionnaire. The collected data is analyzed with AMOS software. The result indicate that facilitative condition, cognitive absorption, perceived enjoyment, perceived ease of use, and perceived usefulness have significant and direct effect on intention to use technology. Also, facilitative condition, cognitive absorption, perceived enjoyment, perceived ease of use and computer playfulness have significant and direct of effect on perceived usefulness. Facilitative condition, cognitive absorption, perceived enjoyment, and playfulness have significant and direct effect on perceived ease of use. (Hossien Zare,Sedigheh Yazdanparast. The causal Model of effective factors on Intention to use of information technology


title: Doppler effect on V2I path loss and V2V channel models

abstract: Characterizing the channel for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications in the 5 GHz frequency band is of great interest within the increasingly growing field of intelligent transportation systems. In this study, we determine the Doppler shift effect in a simulation scenario with a V2I path loss model and various V2V channel models. The existence of both Doppler shift and multipath effects in the V2V and V2I environments is confirmed in the various types of channel models. It is important to note that the Doppler spectrum for vehicular environments is only valid for a short period of time.


title: New antennas for Space applications

abstract: Metasurfaces (MTSs) are versatile, technologically advanced new materials, which have proven their capability to be successfully employed for constituting variable impedance plane and enabling precisely controlled radiation from equivalent apertures for antenna applications. Among the several requirements that can be desired in Space Communications environment the possibility of obtaining shaped beams is one of the most demanding features, in this framework MTS antennas assume a key role. In this work two new designs of shaped beam antennas are presented. These implement a low-complexity data-downlink aperture for Ka-band LEO missions and, in the second example, a printed MTS is applied for pattern shaping of a Ku-band horn for global Earth coverage.


title: The Goal Question Metric Approach

abstract: As with any engineering discipline, software development requires a measurement mechanism for feedback and evaluation. Measurement is a mechanism for creating a corporate memory and an aid in answering a variety of questions associated with the enactment of any software process. It helps support project planning (e.g., How much will a new project cost?); it allows us to determine the strengths and weaknesses of the current processes and products (e.g., What is the frequency of certain types of errors?); it provides a rationale for adopting/refining techniques (e.g., What is the impact of the technique XX on the productivity of the projects?); it allows us to evaluate the quality of specific processes and products (e.g., What is the defect density in a specific system after deployment?). Measurement also helps, during the course of a project, to assess its progress, to take corrective action based on this assessment, and to evaluate the impact of such action.


title: Improving content marketing processes with the approaches by artificial intelligence

abstract: Content marketing is todayâ€™s one of the most remarkable approaches in the context of marketing processes of companies. Value of this kind of marketing has improved in time, thanks to the latest developments regarding to computer and communication technologies. Nowadays, especially social media based platforms have a great importance on enabling companies to design multimedia oriented, interactive content. But on the other hand, there is still something more to do for improved content marketing approaches. In this context, objective of this study is to focus on intelligent content marketing, which can be done by using artificial intelligence. Artificial Intelligence is todayâ€™s one of the most remarkable research fields and it can be used easily as multidisciplinary. So, this study has aimed to discuss about its potential on improving content marketing. In detail, the study has enabled readersâ€™ to improve their awareness about the intersection point of content marketing and artificial intelligence. Furthermore, the authors have introduced some example models of intelligent content marketing, which can be achieved by using current Web technologies and artificial intelligence techniques.