nils-herrmann/clean_scirepeval huggingface dataset:
A Novel Energy Efficient Object Detection and Image Transmission Approach for Wireless Multimedia Sensor Networks
Venue: IEEE Sensors Journal

Energy efficient object detection and image transmission are one of the key issues in wireless multimedia sensor networks (WMSN) Recent approaches in the WMSN propose in node object detection and tracking algorithms. However, a little effort has been made to effectively detect object presence and absence in images in the WMSN. Since object detection has a direct relation with image transmission, therefore effective object detection algorithm would provide a reduction in the false transmission of image information. In this paper, a novel object presence model and an image transmission scheme are proposed for the WMSN. This scheme uses the transmission of image segments rather than a complete image. It guarantees in node energy conservation and minimal image content transmission to the sink node. The proposed scheme is evaluated based on in node energy consumption and reconstructed image peak signal to noise ratio (PSNR) Simulation results show that the proposed approach saves 95% of the node energy with the received image PSNR of 46 dB as compared with other state of the art approaches.
Information Networks: Evidence from Illegal Insider Trading Tips

This paper exploits a novel hand collected data set to provide a comprehensive analysis of the social relationships that underlie illegal insider trading networks. I find that inside information flows through strong social ties based on family, friends, and geographic proximity. On average, inside tips originate from corporate executives and reach buy side investors after three links in the network. Inside traders earn prodigious returns of 35% over 21 days, with more central traders earning greater returns, as information conveyed through social networks improves price efficiency. More broadly, this paper provides some of the only direct evidence of person to person communication among investors.
Differences between Student Teachers' Implementation and Perceptions of Teaching Styles.

Research studies on Spectrum of Teaching Styles (STS) theories have verified that mastering and implementing various teaching styles is the ideal way to match up the needs of diverse learners, the variety of content knowledge, and educational goals; however, little is known about how student teachers use and perceive various STS. The purpose of this study, therefore, was to explore student teachers' self report of how they use and perceive teaching styles from a physical education teacher education (PETE) program. Participants were 142 student teachers (96 male, 46 female; 84 undergraduate, 58 graduate) from a Spectrum of Teaching Styles based (STS) teaching strategies course. The tool used to investigate this was the STS Inventory adapted version (STSI AV Zeng, 2012) The participants expressed that they often use command, practice, reciprocal, and inclusion styles to teach PE lessons; among the nine styles in the STS, they believed that using command, practice, reciprocal, inclusion, guided discovery, convergent discovery, and divergent discovery styles in their teaching helps their students learn skills/ activities better. The student teachers also expressed that implementing command, practice, reciprocal, inclusion, convergent discovery, and divergent discovery styles would motivate their students to learn better. No significant differences were found between male and female student teachers regarding how they use and perceive the STS. Student teachers from different education levels, however, implement and perceive the STS differently. This study provides quantitative data and fresh insights into how student teachers implement and perceive the STS.
Simulation optimization: a review of algorithms and applications
Venue: Ann. Oper. Res.

Simulation optimization (SO) refers to the optimization of an objective function subject to constraints, both of which can be evaluated through a stochastic simulation. To address specific features of a particular simulation discrete or continuous decisions, expensive or cheap simulations, single or multiple outputs, homogeneous or heterogeneous noise various algorithms have been proposed in the literature. As one can imagine, there exist several competing algorithms for each of these classes of problems. This document emphasizes the difficulties in SO as compared to algebraic model based mathematical programming, makes reference to state of the art algorithms in the field, examines and contrasts the different approaches used, reviews some of the diverse applications that have been tackled by these methods, and speculates on future directions in the field.
Cold supply chain design with environmental considerations: A simulation optimization approach
Venue: Eur. J. Oper. Res.

In response to strict regulations and increased environmental awareness, firms are striving to reduce the global warming impact of their operations. Cold supply chains have high levels of greenhouse gas emissions due to the high energy consumption and refrigerant gas leakages. We model the cold supply chain design problem as a mixed integer concave minimization problem with dual objectives of minimizing the total cost including capacity, transportation, and inventory costs and the global warming impact. Demand is modeled as a general distribution, whereas inventory is managed using a known policy but without explicit formulas for the inventory cost and maximum level functions. We propose a novel hybrid simulation optimization approach to solve the problem. Lagrangian decomposition is used to compose the model into an integer programming subproblem and sets of single variable concave minimization subproblems that are solved using simulation optimization. We provide closed form expressions for the Lagrangian multipliers so that the Lagrangian bound is obtained in a single iteration. Furthermore, since the solution of the integer subproblem is feasible to the original problem an upper bound is obtained immediately. To close the optimality gap, the Lagrangian approach is embedded in a branch and bound framework. The approach is verified through extensive numerical testing on two realistic case studies from different industries, and some managerial insights are drawn.
Simulation optimization in the era of Industrial 4.0 and the Industrial Internet
Venue: J. Simulation

Simulation is an established tool for predicting and evaluating the performance of complex stochastic systems that are analytically intractable. Recent research in simulation optimization and explosive growth in computing power have made it feasible to use simulations to optimize the design and operations of systems directly. Concurrently, ubiquitous sensing, pervasive computing, and unprecedented systems interconnectivity have ushered in a new era of industrialization (the so called Industrial 4.0/Industrial Internet) In this article, we argue that simulation optimization is a decision making tool that can be applied to many scenarios to tremendous effect. By capitalizing on an unprecedented integration of sensing, computing, and control, simulation optimization provides the "smart brain" required to drastically improve the efficiency of industrial systems. We explore the potential of simulation optimization and discuss how simulation optimization can be applied, with an emphasis on the recent development of multi fidelity/multi scale simulation optimization.
A hybrid simulation optimization approach for solving the areal groundwater pollution source identification problems

In this study, a new simulation optimization approach is proposed for solving the areal groundwater pollution source identification problems which is an ill posed inverse problem. In the simulation part of the proposed approach, groundwater flow and pollution transport processes are simulated by modeling the given aquifer system on MODFLOW and MT3DMS models. The developed simulation model is then integrated to a newly proposed hybrid optimization model where a binary genetic algorithm and a generalized reduced gradient method are mutually used. This is a novel approach and it is employed for the first time in the areal pollution source identification problems. The objective of the proposed hybrid optimization approach is to simultaneously identify the spatial distributions and input concentrations of the unknown areal groundwater pollution sources by using the limited number of pollution concentration time series at the monitoring well locations. The applicability of the proposed simulation optimization approach is evaluated on a hypothetical aquifer model for different pollution source distributions. Furthermore, model performance is evaluated for measurement error conditions, different genetic algorithm parameter combinations, different numbers and locations of the monitoring wells, and different heterogeneous hydraulic conductivity fields. Identified results indicated that the proposed simulation optimization approach may be an effective way to solve the areal groundwater pollution source identification problems.
A questionnaire for measuring presence in virtual environments: factor analysis of the presence questionnaire and adaptation into Brazilian Portuguese
Venue: Virtual Reality

The increasing use of virtual reality (VR) environments in different domains of research and psychotherapy offers advantages over traditional treatment approaches. However, in order to feel immersed and involved by the VR experience, participants require VR scenarios that promote the subjective feeling of "being there," i.e. presence. The most utilized mean of operationalization of presence is through self report scales and questionnaires. This article aims to report the translation and adaptation of the presence questionnaire (PQ) into Brazilian Portuguese, comparing the factorial distribution of the adapted version with the original PQ. Translation and back translations were conducted by a team of Brazilian psychologists and computer science professionals with experience on the field. Participants (n 100) answered the Brazilian version of the questionnaire after wearing a head mounted display (HMD) and driving a virtual automobile in a VR scenario. The principal component analysis of the translated version generated factors consistently with the original study; however, items that had equivocal construct adequacy in the original PQ changed factors. The factor structure of the PQ is discussed. The growing use of VR environments requires instruments assessing the presence of immersed individuals, and the Brazilian Portuguese version of the PQ appears to be a viable option.
GPU enabled back propagation artificial neural network for digit recognition in parallel
Venue: The Journal of Supercomputing

In this paper, we show that the GPU (graphics processing unit) can be used not only for processing graphics, but also for high speed computing. We provide a comparison between the times taken on the CPU and GPU to perform the training and testing of a back propagation artificial neural network. We implemented two neural networks for recognizing handwritten digits; one consists of serial code executed on the CPU, while the other is a GPU based version of the same system which executes in parallel. As an experiment for performance evaluation, a system for neural network training on the GPU is developed to reduce training time. The programming environment that the system is based on is CUDA which stands for compute unified device architecture, which allows a programmer to write code that will run on an NVIDIA GPU card. Our results over an experiment of digital image recognition using neural network confirm the speed up advantages by tapping on the resources of GPU. Our proposed model has an advantage of simplicity, while it shows on par performance with the state of the arts algorithms.
A Comprehensive Review on Handwritten Digit Recognition using various Neural Network Approaches

Handwritten digit recognition has capability of the computer to receive information from sources such as paper documentation, camera, tablets and other devices. Handwritten digits are used in different types of data like cheque, post mail, address on home's name plate and exam form which also filled by hand etc. In recent years, handwritten digit recognition plays a main role for user authentication applications. In the proposed work, we will be developed gradient descent back propagation using neural network based on digit recognition system. Here introducing four phase: preprocessing, segmentation, feature extraction, classification. MNIST dataset contains CSV file from which image can be obtained by reading it. And this image acts as an input to the procedure. After that this image is preprocessed using RGB converter into binary form and contains some noise ,this noise will be remove using median filter and then convert into filtered image and also various techniques such as skeletonization, centering, and thresholding, are used for the preprocessing the image numerals If the characteristics for one class are distinct and remain constant with variations in this class, then we can term the features as good and desired. Neural Network Technique is used for classification and recognition of handwritten digits through training and testing.
Looking behind the mask: Social coping strategies of girls on the autistic spectrum

The socio communication deficits of individuals on the autistic spectrum are well documented. However, this has largely been based on the male population and less is known about how females with autism manage social relationships across the developmental period. Ten adolescent female participants with a diagnosis of autism were interviewed and Interpretative Phenomenological Analysis used to explore their experiences of managing their social relationships. The results showed that participants were motivated to develop and maintain friendships, but during adolescence this became increasingly difficult. Consequently, they developed explicit strategies to manage these relationships, including masking and imitation. The use of such strategies was both advantageous and disadvantageous, and such findings should be considered in developing gender sensitive assessment and developmentally appropriate support.
Parental stress, coping strategies and social support in families of children with a disability

The aim of this research was to compare parental stress, coping strategies and social support perceived in families of children with low functioning autism (n 8) high functioning autism (n 10) Down syndrome (n 12) and parents of typically developing children (n 20) Specifically, the objective was to investigate which variables (coping strategies and perception of social support available) might better predict different stress outcomes in the four groups. Parents were asked to fill in three questionnaires: Parent Stress Index, Coping Orientation to Problems Experienced and Social Support Questionnaire. Significant differences among groups in all of the variables considered were found. These results suggest the advisability of fostering functional coping strategies and social support received in families of children with disabilities, and especially in those with children with low functioning autism.
Face it, don't Facebook it: Impacts of Social Media Addiction on Mindfulness, Coping Strategies and the Consequence on Emotional Exhaustion.
Venue: Stress and health journal of the International Society for the Investigation of Stress

Addiction to social media has now become a problem that societies are concerned with. The aim of the present study is to investigate the impacts that social media addiction has on mindfulness and choice of coping strategy, as well as to explore the consequences on emotional exhaustion. The survey data were collected from 211 employees in 13 enterprises in Thailand. Results from partial least square structural equation modelling revealed that people who are highly addicted to social media tended to have lower mindfulness and tended to use emotion focused coping to deal with stress. Lack of mindfulness and the decision to use emotion coping strategy are also subsequently associated with higher emotional exhaustion.
A real time alphabets sign language recognition system using hands tracking
Venue: 2016 International Conference on Computational Intelligence and Cybernetics

Majority people can communicate through verbal language, but there are some people with limited abilities must use sign language with hand and finger movements to communicate even though not everyone is able to understand its meaning. The rapid development of information technology can assist in understanding and translating the gestures. This research aims to design and build a system gesture recognition of alphabet sign language that have the characteristic that fingers open by utilizing the Kinect camera. Recognition system built through two stages, i.e. the tracking process and the recognition process. Implementing the hands tracking method did the tracking process. The recognition process consists of two phases, i.e. the first process is to get input that will be used as reference data and data testers which is done by calculating the vectors and vector angle and, the second process is the gestures recognition process was done by calculating the Euclid distance. The system is able to recognize gestures alphabets of 69.79% of the average level of accuracy that is different in each case.
Experimental investigation of a solar adsorption refrigeration system working with silicagel/water pair: A case study for Bou Ismail solar data

The objective of the present work is to build and test a solar adsorption refrigeration device with an adsorbent adsorbate silicagel water pair in the weather conditions of Bou Ismail, Algeria. The refrigeration system proposed in this study consists of three major components: a solar collector (tubular adsorbent bed, reflecting surface, single glazed cover, and 4.5 kg of silicagel material) an air cooled condenser, an evaporator and supplementary system components. The working operation parameters of the cooling adsorption system were tested successfully. Experimental results indicated that the maximum temperature generated varied from 95 degC to 117 degC, 33 degC of average ambient temperature, the condensing temperature varied from 45 degC to 53 degC, +5 degC of minimum evaporator temperature, and the pressure values recorded in the adsorbent bed during the heating desorption period varied from 80 to 100 mbar. With a total energy received of around 19 MJ/m 2 this solar adsorption refrigeration device can provide a solar COP ranging from 0.083 to 0.09. Such results show the practicability of our solar adsorption refrigeration module and that it has a favorable design for use in medical storage in areas without an electrical network (e.g. the Algeria Sahara region)
The effect of individualized gradable stabilization exercises in patients with chronic low back pain: Case control study.
Venue: Journal of back and musculoskeletal rehabilitation

There is no evidence that one exercise program is better than another for rehabilitation of patients with chronic low back pain (CLBP)  To identify the safety and efficacy of a gradable stabilization exercise protocol in patients with CLBP.  This study is a retrospective cohort study with 65 patients. The exercise group received the gradable stabilization exercise protocol for 3 weeks over 6 8 visits, while the control group did not receive any exercise protocol. All subjects were evaluated with the visual analog scale (VAS) Oswestry Disability Index (ODI) Fear Avoidance Belief Questionnaire (FABQ) the active sit up test (AST) side support test (SST) and extensor endurance test (EET) RESULTS After gradable stabilization exercise, the exercise group showed significant improvement in VAS, FABQ W, ODI, AST, SST and EET (p< 0.05) And the exercise group showed better improvement than the control group in VAS, FABQ W, ODI, AST, SST and EET (p< 0.05) The rate of treatment success was 77.1% among patients assigned to the exercise group, as compared with 12.0% among those assigned to the control group.  This study showed that the gradable stabilization exercise protocol has the possibility to improve clinical and physical findings.
Effect of Trunk Stabilization Exercises using a Gym Ball with or without Electromyography Biofeedback in Patients with Chronic Low Back Pain: An Experimental Study

To investigate the effects of trunk stabilization exercise in combination with EMG biofeedback on transverse abdominis (TrA) activation capacity in patients with chronic low back pain (CLBP)  Ninety patients with CLBP participated to the study: 45 patients were randomly allocated to trunk stabilization exercises combined with EMG biofeedback, and the other 45 patients were allocated to trunk stabilization exercises with no EMG biofeedback. The primary outcome was TrA activation capacity, and the secondary outcomes were pain and the functional disability.  Both the group has shown significant improvements in all the outcomes (p  The addition of EMG biofeedback to trunk stabilization exercises compared to trunk stabilization exercises alone has shown greater gains in TrA activation capacity, reduction in pain intensity, and disability in patients with chronic low back pain.
Fluctuations of Two Dimensional Coulomb Gases

We prove a Central Limit Theorem for the linear statistics of two dimensional Coulomb gases, with arbitrary inverse temperature and general confining potential, at the macroscopic and mesoscopic scales and possibly near the boundary of the support of the equilibrium measure. This can be stated in terms of convergence of the random electrostatic potential to a Gaussian Free Field.Our result is the first to be valid at arbitrary temperature and at the mesoscopic scales, and we recover previous results of Ameur Hendenmalm Makarov and Rider Virag concerning the determinantal case, with weaker assumptions near the boundary. We also prove moderate deviations upper bounds, or rigidity estimates, for the linear statistics and a convergence result for those corresponding to energy minimizers.The method relies on a change of variables, a perturbative expansion of the energy, and the comparison of partition functions deduced from our previous work. Near the boundary, we use recent quantitative stability estimates on the solutions to the obstacle problem obtained by Serra and the second author.