nils-herrmann/clean_scirepeval huggingface dataset:
Real-time human gesture grading based on OpenPose

In this paper, we presented a real-time 2D human gesture grading system from monocular images based on OpenPose, a library for real-time multi-person keypoint detection. After capturing 2D positions of a person's joints and skeleton wireframe of the body, the system computed the equation of motion trajectory for every joint. Similarity metric was defined as distance between motion trajectories of standard and real-time videos. A modifiable scoring formula was used for simulating the gesture grading scenario. Experimental results showed that the system worked efficiently with high real-time performance, low cost of equipment and strong robustness to the interference of noise.
Low-Cost Dual-Band Circularly Polarized Switched-Beam Array for Global Navigation Satellite System

This paper presents the design and development of a dual-band switched-beam microstrip array for global navigation satellite system (GNSS) applications such as ocean reflectometry and remote sensing. In contrast to the traditional Butler matrix, a simple, low cost, broadband and low insertion loss beam switching feed network is proposed, designed and integrated with a dual band antenna array to achieve continuous beam coverage of ±25° around the boresight at the L1 (1.575 GHz) and L2 (1.227 GHz) bands. To reduce the cost, microstrip lines and PIN diode based switches are employed. The proposed switched-beam network is then integrated with dual-band step-shorted annular ring (S-SAR) antenna elements in order to produce a fully integrated compact-sized switched-beam array. Antenna simulation results show that the switched-beam array achieves a maximum gain of 12 dBic at the L1 band and 10 dBic at the L2 band. In order to validate the concept, a scaled down prototype of the simulated design is fabricated and measured. The prototype operates at twice of the original design frequency, i.e., 3.15 GHz and 2.454 GHz and the measured results confirm that the integrated array achieves beam switching and good performance at both bands.
Modeling and controller design for a voice coil actuated engine valve

This paper presents a physical model of a spark ignition (SI) engine valve actuated by a voice coil actuator (VCA) and proposes a novel control strategy that achieves fast transitions and low seating velocities with high precision position control. The control strategy is based on applying two different pulse width modulated (PWM) voltages for transient and steady state performance. This novel switching control strategy performs better than current strategies using electromechanical valve actuators to implement variable valve timing (VVT). The main improvement over electromechanical actuators is the fact that the novel control strategy achieves the conflicting performance requirements of very fast transition times while simultaneously exhibiting low contact velocities
Deformable Image Registration: A Survey

Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: i) multi-modality fusion, where information acquired by di erent imaging devices or protocols is fused to facilitate diagnosis and treatment planning; ii) longitudinal studies, where the development of phenomenon is studied over time; and iii) population modeling towards studying normal anatomical variability. In this research report, we attempt to give an overview of the deformable registration methods, putting emphasis on the most recent advances in the domain. Additional emphasis has been given to techniques applied to medical images. In order to study in depth image registration methods, their main components are identi ed and then studied independently. The most recent techniques are presented in a principled fashion.  Deformable registration, bibliographical review ∗ Center for Visual Computing, Department of Applied Mathematics, Ecole Centrale de Paris, Equipe GALEN, INRIA Saclay Étude Bibliographique sur le Recalage Déformable d'Images Résumé : Le recalage déformable d'images est une des tâches les plus fondamentales dans l'imagerie médicale. Parmi ses applications les plus importantes, on compte: i) la fusion d' information provenant des di érents types de modalités a n de faciliter le diagnostic et la plani cation du traitement; ii) les études longitudinales, oú le d'eveloppement d'un phénomène est etudié en fonction du temps; et iii) la modélisation de la variabilité anatomique normale d'une population. Dans ce rapport de recherche, nous essayons de donner un aperçu des di érentes méthodes du recalage déformables, en mettant l'accent sur les avancées les plus récentes du domaine. Nous avons particuliérement insisté sur les techniques appliquées aux images médicales. A n d'étudier en profondeur les méthodes du recalage d'images, leurs composants principales sont d'abord identi és puis étudiées de manière indeépendante, les techniques les plus récentes étant classi ées en suivant un schéma logique déterminé. Mots-clés : recalage déformable, étude bibliographique Deformable Image Registration: A Survey 3
Context-Sensitive Flow Graph and Projective Single Assignment Form for Resolving Context-Dependency of Binary Code

Program analysis on binary code is considered as difficult because one has to resolve destinations of indirect jumps. However, there is another difficulty of context-dependency that matters when one processes binary programs that are not compiler generated. In this paper, we propose a novel approach for tackling these difficulties and describe a way to reconstruct a control flow from a binary program with no extra assumptions than the operational meaning of machine instructions.
A new Big Five: fundamental principles for an integrative science of personality.

Despite impressive advances in recent years with respect to theory and research, personality psychology has yet to articulate clearly a comprehensive framework for understanding the whole person. In an effort to achieve that aim, the current article draws on the most promising empirical and theoretical trends in personality psychology today to articulate 5 big principles for an integrative science of the whole person. Personality is conceived as (a) an individual's unique variation on the general evolutionary design for human nature, expressed as a developing pattern of (b) dispositional traits, (c) characteristic adaptations, and (d) self-defining life narratives, complexly and differentially situated (e) in culture and social context. The 5 principles suggest a framework for integrating the Big Five model of personality traits with those self-defining features of psychological individuality constructed in response to situated social tasks and the human need to make meaning in culture.
Effect of Training Class Label Noise on Classification Performances for Land Cover Mapping with Satellite Image Time Series

Supervised classification systems used for land cover mapping require accurate reference databases. These reference data come generally from different sources such as field measurements, thematic maps, or aerial photographs. Due to misregistration, update delay, or land cover complexity, they may contain class label noise, i.e., a wrong label assignment. This study aims at evaluating the impact of mislabeled training data on classification performances for land cover mapping. Particularly, it addresses the random and systematic label noise problem for the classification of high resolution satellite image time series. Experiments are carried out on synthetic and real datasets with two traditional classifiers: Support Vector Machines (SVM) and Random Forests (RF). A synthetic dataset has been designed for this study, simulating vegetation profiles over one year. The real dataset is composed of Landsat-8 and SPOT-4 images acquired during one year in the south of France. The results show that both classifiers are little influenced for low random noise levels up to 25%–30%, but their performances drop down for higher noise levels. Different classification configurations are tested by increasing the number of classes, using different input feature vectors, and changing the number of training instances. Algorithm complexities are also analyzed. The RF classifier achieves high robustness to random and systematic label noise for all the tested configurations; whereas the SVM classifier is more sensitive to the kernel choice and to the input feature vectors. Finally, this work reveals that the cross-validation procedure is impacted by the presence of class label noise.
Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems

The purpose of this paper is to investigate neural network capability systematically. The main results are: 1) every Tauber-Wiener function is qualified as an activation function in the hidden layer of a three-layered neural network; 2) for a continuous function in S'(R(1 )) to be a Tauber-Wiener function, the necessary and sufficient condition is that it is not a polynomial; 3) the capability of approximating nonlinear functionals defined on some compact set of a Banach space and nonlinear operators has been shown; and 4) the possibility by neural computation to approximate the output as a whole (not at a fixed point) of a dynamical system, thus identifying the system.
A convolutional neural networks denoising approach for salt and pepper noise

The salt and pepper noise, especially the one with extremely high percentage of impulses, brings a significant challenge to image denoising. In this paper, we propose a non-local switching filter convolutional neural network denoising algorithm, named NLSF-CNN, for salt and pepper noise. As its name suggested, our NLSF-CNN consists of two steps, i.e., a NLSF processing step and a CNN training step. First, we develop a NLSF pre-processing step for noisy images using non-local information. Then, the pre-processed images are divided into patches and used for CNN training, leading to a CNN denoising model for future noisy images. We conduct a number of experiments to evaluate the effectiveness of NLSF-CNN. Experimental results show that NLSF-CNN outperforms the state-of-the-art denoising algorithms with a few training images.
The Impact of Task-based Approach on Vocabulary Learning in ESP Courses

This study investigates the teaching of vocabulary in ESP courses within the paradigm of task-based language teaching, concentrating on Persian literature students at Birjand University in Iran. Two homogenous groups of students who were taking their ESP courses participated in the study as a control and an experimental group. A teacher-made test of technical vocabulary knowledge was administered as the pre-test. Vocabularies in the control group were taught using a traditional approach, whereas in the experimental group, technical vocabularies were taught on the basis of task-based approach. At the end of the semester, a post-test was given to the students to determine the influence of the treatment on the experimental group. Data analysis showed that the task-based approach was more effective in teaching technical vocabularies compared to the traditional one. Furthermore, the results showed that in the experimental group the male learners outperformed the female learners.
A system of systems view on collaborative industrial automation

Industrial systems are increasingly integrating Internet and other emergent technologies, concepts, methods and tools, coming from the IT world, such as cloud- or service-based approaches. As a first main consequence, the industrial automation landscape is also increasing in complexity, presenting new challenges for engineers and practitioners. Examples include dealing with evolvable heterogeneous structures that do not appear fully formed and where functions and purposes are added, removed or modified along the life cycle; as well as managing emergent properties and behaviours of entire systems, e.g. resulting from integrating new systems being not localized to any single system component. Although the component systems keep their operational and managerial independence, when they are interconnected and integrated, collaboration, cooperation and competition relationships, appear all along three major collaboration axes (lifecycle, value chain and enterprise), which should be understood, controlled and managed. In this work an effort to examine those systems under the prism of System of Systems approach, and address first recommendations to determine architectures, evolutionary steps, benefits, roadblocks as well as migration approaches that need to be followed is presented.
Digital Innovation and Strategic Transformation

D igital technologies—and how we use them in our personal lives, work, and society—have changed the face of business and will continue to do so. Moreover, research organizations such as Gartner and Accenture, along with MIT professor Erik Brynjolfsson,1 indicate that the digital technologies that underlie computers, robots, and smart equipment are changing rapidly, becoming more powerful, and transforming organizations much faster than in the past (that is, the second machine age). We are in the Fourth Industrial Revolution, the digital revolution of cyber-physical systems that has been unfolding since the middle of the last century.2 The possibility of billions of people connected by mobile devices, in conjunction with unprecedented processing power, storage capacity, and access to knowledge via smart machines, creates enormous opportunities for entrepreneurs and innovative managers alike.
More than Bag-of-Words: Sentence-based Document Representation for Sentiment Analysis

Most sentiment analysis approaches rely on machine-learning techniques, using a bag-of-words (BoW) document representation as their basis. In this paper, we examine whether a more fine-grained representation of documents as sequences of emotionally-annotated sentences can increase document classification accuracy. Experiments conducted on a sentence and document level annotated corpus show that the proposed solution, combined with BoW features, offers an increase in classification accuracy.
Bus tracking and monitoring using RFID

The rapid growth in population in India causes more crowding at public bus stops. People long wait for arriving of buses and suddenly gather near bus when it arrives and travel in overcrowded buses on footboards which leads to accidents. Theft is another risk of overcrowding. All this happens due to lack of proper information of arriving of buses at many of the bus stops. To solve this problem in a cost effective way, we have developed an IoT based bus tracking system to show the current location of the bus and seat availability in the arriving buses. We have used RFID technology for tracking the bus and Thingspeak web server for displaying location of the bus and seat availability in android application in a smart phone. This system enables the commuters to know the exact location of the bus, and occupancy level in the bus, which enable the commuters to take decision, whether to board this bus or next. This reduces the waiting time and overcrowding at bus stops. It also reduces the risk of accidents and thefts.
Implantable Myoelectric Sensors (IMESs) for Intramuscular Electromyogram Recording

We have developed a multichannel electrogmyography sensor system capable of receiving and processing signals from up to 32 implanted myoelectric sensors (IMES). The appeal of implanted sensors for myoelectric control is that electromyography (EMG) signals can be measured at their source providing relatively cross-talk-free signals that can be treated as independent control sites. An external telemetry controller receives telemetry sent over a transcutaneous magnetic link by the implanted electrodes. The same link provides power and commands to the implanted electrodes. Wireless telemetry of EMG signals from sensors implanted in the residual musculature eliminates the problems associated with percutaneous wires, such as infection, breakage, and marsupialization. Each implantable sensor consists of a custom-designed application-specified integrated circuit that is packaged into a biocompatible RF BION capsule from the Alfred E. Mann Foundation. Implants are designed for permanent long-term implantation with no servicing requirements. We have a fully operational system. The system has been tested in animals. Implants have been chronically implanted in the legs of three cats and are still completely operational four months after implantation.
Authentication Using Mobile Phone as a Security Token

Today security concerns are on the rise in all areas industries such as banks, governmental applications, healthcare industry, militaryorganization, educational institutions etc, with one common weak link being “passwords”. Several proper strategies for using passwords have been proposed. Some of which are very difficult to use and others might not meet the company’s security concerns. The usage of passwords for authentication is no longer sufficient and stronger authentication schemes are necessary. Two factor authentication uses elements or devices such as tokens and ATM cards. We have proposed to resolve the password problem, which could be inconvenient for the user and costly for the service providers to combat otherwise. To avoid the usage of additional device, the mobile phone is adopted as security token. In this paper several different authentication solutions using the mobile as authentication token are discussed, where these solutions vary in complexity, strength, security and user friendliness. One of the authentication schemes (OTP solution) is implemented to verify their usability. Hence, a classification and evaluation of the different solutions is provided according to defined criteria. Keywords‐ Two-factor authentication, Security token, UPIF, IMSI, IMEI, one time password (OTP).
Perceptions of the School Psychological Environment and Early Adolescents ' Psychological and Behavioral Functioning in School : The Mediating Role of Goals and Belonging

In a sample of 296 8th-grade middle school students, the authors examined the role of personal achievement goals and feelings of school belonging in mediating the relation between perceptions of the school psychological environment and school-related beliefs, affect, and achievement. Sequential regression analyses indicated that perceiving a task goal structure in middle school was positively related to academic self-efficacy and that this relation was mediated through personal task goals. Perceiving an ability goal structure was related to academic self-consciousness and this relation was mediated through personal relative ability goals. Perceiving positive teacher-student relationships predicted positive school-related affect and this relation was mediated through feelings of school belonging. Feelings of academic efficacy and school belonging in turn were positively related to final-semester academic grades. Results are discussed in relation to current middle school reform efforts.
A Study of Birth Order , Academic Performance , and Personality

This study aimed to investigate birth order effect on personality and academic performance amongst 120 Malaysians. Besides, it also aimed to examine the relationship between personality and academic achievement. Thirty firstborns, 30 middle children, 30 lastborns, and 30 only children, who shared the mean age of 20.0 years (SD= 1.85), were recruited into this study. Participants’ Sijil Pelajaran Malaysia (SPM) results were recorded and their personality was assessed by Ten Item Personality Inventory (TIPI). Results indicated that participants of different birth positions did not differ significantly in terms of personality and academic performance. However, Pearson’s correlation showed that extraversion correlated positively with academic performance. Keywordsbirth order; personality; academic achievement
ECONOMIC ANALYSIS OF SUBJECTIVE WELL-BEING ‡ Two Happiness Puzzles

Economists, as well as psychologists and philosophers, have become increasingly interested in self-reported measures of well-being, what they mean, and whether they might be used for policymaking. This interest parallels a renewed awareness of the limitations of standard measures of GDP (and allied measures), as well as a wish to redirect measurement away from GDP in an era when growth rates are diminishing across much of the rich world. Various subjective well-being (SWB) measures have been used to provide new insights and to capture a number of difficult-to-measure phenomena, such as the trade-off between inflation and unemployment, the costs of air pollution, or the values attached to environmental amenities. In spite of those successes, the measures are neither fully accepted nor fully understood. Traditional economics has been skeptical of measures whose content is unclear, is largely up to the respondent, and is sometimes deeply affected by the wording of the questions or by the context in which they are put. Although cognitive testing in the laboratory can provide insights about how people understand well-being questions, more often the interpretation is deduced by analyzing the correlates of the answers ex post. This poses a problem: we cannot use a correlation between a SWB measure and a variable X both to validate the measure and to claim that we have demonstrated the welfare consequences of X. One symptom is the “happiness fork”: that results that conform to standard welfare analysis ECONOMIC ANALYSIS OF SUBJECTIVE WELL-BEING ‡
2–10 GHz multisection 2-way Wilkinson power divider with enhanced port match and isolation

This paper presents two broadband Wilkinson power dividers (WPDs) using single layer microstrip lines. Operation of these WPDs from 2 GHz to 10 GHz could be achieved by using multisectional structure. Presented WPDs have 6 sections and differ in the size of the isolation resistors which have size of 0402 and 0603. For experimental verifications two devices were fabricated and the measurement results match with the simulation results well. Measurement results of the two independent samples show a bandwidth from 2 GHz to 10 GHz with an insertion loss of lower than 0.4 dB, isolation of greater than 25 dB, amplitude and phase imbalance of lower than ±0.3 dB and ±3°, respectively. The realized WPDs exhibit better matching, isolation and phase/amplitude imbalance compared with other wideband power dividers published so far.
A genomic perspective on protein families.

In order to extract the maximum amount of information from the rapidly accumulating genome sequences, all conserved genes need to be classified according to their homologous relationships. Comparison of proteins encoded in seven complete genomes from five major phylogenetic lineages and elucidation of consistent patterns of sequence similarities allowed the delineation of 720 clusters of orthologous groups (COGs). Each COG consists of individual orthologous proteins or orthologous sets of paralogs from at least three lineages. Orthologs typically have the same function, allowing transfer of functional information from one member to an entire COG. This relation automatically yields a number of functional predictions for poorly characterized genomes. The COGs comprise a framework for functional and evolutionary genome analysis.