nils-herrmann/clean_scirepeval huggingface dataset:
A Systematic Review of Research on Open Source Software in Commercial Software Product Development

The popularity of the open source software development in the last decade, has brought about an increased interest from the industry on how to use open source components, participate in the open source community, build business models around this type of software development, and learn more about open source development methodologies.  The aim of this study is to review research carried out on usage of open source components and development methodologies by the industry, as well as companies’ participation in the open source community.  Systematic review through searches in library databases and manual identification of articles from the open source conference.  19 articles were identified.  The articles could be divided into four categories: open source as part of component based software engineering, business models with open source in commercial organization, company participation in open source development communities, and usage of open source processes within a company.
Development and Validation of a Learning Analytics Framework: Two Case Studies Using Support Vector Machines

Interest in collecting and mining large sets of educational data on student background and performance to conduct research on learning and instruction has developed as an area generally referred to as learning analytics. Higher education leaders are recognizing the value of learning analytics for improving not only learning and teaching but also the entire educational arena. However, theoretical concepts and empirical evidence need to be generated within the fast evolving field of learning analytics. The purpose of the two reported cases studies is to identify alternative approaches to data analysis and to determine the validity and accuracy of a learning analytics framework and its corresponding student and learning profiles. The findings indicate that educational data for learning analytics is context specific and variables carry different meanings and can have different implications across educational institutions and area of studies. Benefits, concerns, and challenges of learning analytics are critically reflected, indicating that learning analytics frameworks need to be sensitive to idiosyncrasies of the educational institution and its stakeholders.
Investigation of a non-anthropomorphic bipedal robot with stability, agility, and simplicity

This paper presents a novel bipedal robot concept and prototype that takes inspiration from humanoids but features fundamental differences that drastically improve its agility and stability while reducing its complexity and cost. This Non-Anthropomorphic Bipedal Robotic System (NABiRoS) modifies the traditional bipedal form by aligning the legs in the sagittal plane and adding a compliance to the feet. The platform is comparable in height to a human, but weighs much less because of its lightweight architecture and novel leg configuration. The inclusion of the compliant element showed immense improvements in the stability and robustness of walking gaits on the prototype, allowing the robot to remain stable during locomotion without any inertial feedback control. NABiRoS was able to achieve walking speeds of up to 0.75km/h (0.21m/s) using a simple pre-processed ZMP based gait and a positioning accuracy of +/- 0.04m with a preprocessed quasi-static algorithm.
Color-defective vision and computer graphics displays

A color space defined by the fundamental spectral sensitivity functions of the human visual system is used to assist in the design of computer graphics displays for color-deficient users. The functions are derived in terms of the CIE standard observer color-matching functions. The Farnsworth-Munsell 100-hue test, a widely used color vision test administered using physical color samples, is then implemented on a digitally controlled color television monitor. The flexibility of this computer graphics medium is then used to extend the Farnsworth-Munsell test in a way that improves the specificity of the diagnoses rendered by the test. The issue of how the world appears to color-deficient observers is addressed, and a full-color image is modified to represent a color-defective view of the scene. Specific guidelines are offered for the design of computer graphics displays that will accommodate almost all color-deficient users.<<ETX>>
The Impact of Selected Aerobic Aquatic Exercises on the Depression and Happiness Levels of Patients with Multiple Sclerosis ( M . S )

Multiple sclerosis (M.S) is one of the most common chronic diseases of the central nervous system. The chronic nature of the disease, lack of prognosis, lack of any definitive cure and affecting the individual in the young age will cause several mental disorders in patients, including depression and low rate of happiness.  Evaluation the effect of aquatic exercise programs on depression and happiness levels of the patients with multiple sclerosis (M.S).  In this quasi-experimental research, 40 patients with M.S. with grades 1 to 4 were randomly divided into two experimental and control groups. The exercise program was performed for the experimental group for eight weeks, three sessions per week with 50-60 percent of the maximum heart rate. The depression and happiness rates were evaluated using the Beck Depression questionnaire and the Oxford Happiness questionnaire at intervals before and after the exercise. Analysis of the data was performed by independent t test, and the data normalization was evaluated using the Kolmogorov-Smirnov test.  The test group, regarding the depression level (p < 0.001) and happiness level (p < 0.002) after exercise had significant changes compared to the pre-exercise time. Thus, the mean differences for depressions and happiness levels of these two groups were obtained respectively as 4.65 and -7.80.  Regular aquatic exercise provides more productive emotional communications and also causes the improvement of depression and increased happiness in M.S. patients. Hence, doing these exercises is recommended as an effective non-pharmacologic therapy method in addition to drug therapy.  Evaluation of Golshan Shabestari and Raz mashahed’s characteristics.  (ISSN:1097-8135). http://www.lifesciencesite.com.
Broadband, Single-Layer Dual Circularly Polarized Reflectarrays With Linearly Polarized Feed

A broadband single layer, dual circularly polarized (CP) reflectarrays with linearly polarized feed is introduced in this paper. To reduce the electrical interference between the two orthogonal polarizations of the CP element, a novel subwavelength multiresonance element with a Jerusalem cross and an open loop is proposed, which presents a broader bandwidth and phase range excessing 360° simultaneously. By tuning the x- and y-axis dimensions of the proposed element, an optimization technique is used to minimize the phase errors on both orthogonal components. Then, a single-layer offset-fed 20 × 20-element dual-CP reflectarray has been designed and fabricated. The measured results show that the 1-dB gain and 3-dB axial ratio (AR) bandwidths of the dual-CP reflectarray can reach 12.5% and 50%, respectively, which shows a significant improvement in gain and AR bandwidths as compared to reflectarrays with conventional λ/2 cross-dipole elements.
Sticky Actuator: Free-Form Planar Actuators for Animated Objects

We propose soft planar actuators enhanced by free-form fabrication that are suitable for making everyday objects move. The actuator consists of one or more inflatable pouches with an adhesive back. We have developed a machine for the fabrication of free-from pouches; squares, circles and ribbons are all possible. The deformation of the pouches can provide linear, rotational, and more complicated motion corresponding to the pouch's geometry. We also provide a both manual and programmable control system. In a user study, we organized a hands-on workshop of actuated origami for children. The results show that the combination of the actuator and classic materials can enhance rapid prototyping of animated objects.
VSE++: Improving Visual-Semantic Embeddings with Hard Negatives

We present a new technique for learning visual-semantic embeddings for cross-modal retrieval. Inspired by hard negative mining, the use of hard negatives in structured prediction, and ranking loss functions, we introduce a simple change to common loss functions used for multi-modal embeddings. That, combined with fine-tuning and use of augmented data, yields significant gains in retrieval performance. We showcase our approach, VSE++, on MS-COCO and Flickr30K datasets, using ablation studies and comparisons with existing methods. On MS-COCO our approach outperforms state-ofthe-art methods by 8.8% in caption retrieval and 11.3% in image retrieval (at R@1).
A Survey on Fault Detection, Isolation, and Reconfiguration Methods in Electric Ship Power Systems

One of the major challenges with electric shipboard power systems (SPS) is preserving the survivability of the system under fault situations. Some minor faults in SPS can result in catastrophic consequences. Therefore, it is essential to investigate available fault management techniques for SPS applications that can enhance SPS robustness and reliability. Many recent studies in this area take different approaches to address fault tolerance in SPSs. This paper provides an overview of the concepts and methodologies that are utilized to deal with faults in the electric SPS. First, a taxonomy of the types of faults and their sources in SPS is presented; then, the methods that are used to detect, identify, isolate, and manage faults are reviewed. Furthermore, common techniques for designing a fault management system in SPS are analyzed and compared. This paper also highlights several possible future research directions.
DESIGN , SIMULATION AND HARDWARE IMPLEMENTATION OF EFFICIENT SOLAR POWER CONVERTER WITH HIGH MPP TRACKING ACCURACY FOR DC MICROGRID APPLICATIONS

This work includes a high step up voltage gain DC-DC converter for DC microgrid applications. The DC microgrid can be utilized for rural electrification, UPS support, Electronic lighting systems and Electrical vehicles. The whole system consists of a Photovoltaic panel (PV), High step up DC-DC converter with Maximum Power Point Tracking (MPPT) and DC microgrid. The entire system is optimized with both MPPT and converter separately. The MPP can be tracked by Incremental Conductance (IC) MPPT technique modified with D-Sweep (Duty ratio Sweep). D-sweep technique reduces the problem of multiple local maxima. Converter optimization includes a high step up DC-DC converter which comprises of both coupled inductor and switched capacitors. This increases the gain up to twenty times with high efficiency. Both converter optimization and MPPT optimization increases overall system efficiency. MATLAB/simulink model is implemented. Hardware of the system can be implemented by either voltage mode control or current mode control.
Beamforming in Noninvasive Brain–Computer Interfaces

Spatial filtering (SF) constitutes an integral part of building EEG-based brain-computer interfaces (BCIs). Algorithms frequently used for SF, such as common spatial patterns (CSPs) and independent component analysis, require labeled training data for identifying filters that provide information on a subject's intention, which renders these algorithms susceptible to overfitting on artifactual EEG components. In this study, beamforming is employed to construct spatial filters that extract EEG sources originating within predefined regions of interest within the brain. In this way, neurophysiological knowledge on which brain regions are relevant for a certain experimental paradigm can be utilized to construct unsupervised spatial filters that are robust against artifactual EEG components. Beamforming is experimentally compared with CSP and Laplacian spatial filtering (LP) in a two-class motor-imagery paradigm. It is demonstrated that beamforming outperforms CSP and LP on noisy datasets, while CSP and beamforming perform almost equally well on datasets with few artifactual trials. It is concluded that beamforming constitutes an alternative method for SF that might be particularly useful for BCIs used in clinical settings, i.e., in an environment where artifact-free datasets are difficult to obtain.
Optimization of CCGT power plant and performance analysis using MATLAB/Simulink with actual operational data

In the Modern scenario, the naturally available resources for power generation are being depleted at an alarming rate; firstly due to wastage of power at consumer end, secondly due to inefficiency of various power system components. A Combined Cycle Gas Turbine (CCGT) integrates two cycles- Brayton cycle (Gas Turbine) and Rankine cycle (Steam Turbine) with the objective of increasing overall plant efficiency. This is accomplished by utilising the exhaust of Gas Turbine through a waste-heat recovery boiler to run a Steam Turbine. The efficiency of a gas turbine which ranges from 28% to 33% can hence be raised to about 60% by recovering some of the low grade thermal energy from the exhaust gas for steam turbine process. This paper is a study for the modelling of CCGT and comparing it with actual operational data. The performance model for CCGT plant was developed in MATLAB/Simulink.
Automatic Generation of Multiple Choice Questions from Slide Content using Linked Data

Assessment plays an important role in the process of learning. Multiple choice questions (MCQs) are suitable candidates to fulfill this role. We present an approach for automatically generating MCQs based on the content presented in slides. It extracts named entities from slides, and queries a knowledge base to create different varieties of MCQs and appropriate answer options. Users can choose between different levels of difficulty for the generated questions and answer options. The approach can be easily extended to generate other varieties of MCQs. Results from a user study confirm the applicability and appropriateness of the approach.
Improved phase generated carrier demodulation algorithm for eliminating light intensity disturbance and phase modulation amplitude variation.

In this paper we propose a novel, improved, phase generated carrier (PGC) demodulation algorithm based on the PGC-differential-cross-multiplying approach (PGC-DCM). The influence of phase modulation amplitude variation and light intensity disturbance (LID) on traditional PGC demodulation algorithms is analyzed theoretically and experimentally. An experimental system for remote no-contact microvibration measurement is set up to confirm the stability of the improved PGC algorithm with LID. In the experiment, when the LID with a frequency of 50 Hz and the depth of 0.3 is applied, the signal-to-noise and distortion ratio (SINAD) of the improved PGC algorithm is 19 dB, higher than the SINAD of the PGC-DCM algorithm, which is 8.7 dB.
A Review on Technology Forecasting Methods and Their Application Area

Technology changes have been acknowledged as a critical factor in determining competitiveness of organization. Under such environment, the right anticipation of technology change has been of huge importance in strategic planning. To monitor technology change, technology forecasting (TF) is frequently utilized. In academic perspective, TF has received great attention for a long time. However, few researches have been conducted to provide overview of the TF literature. Even though some studies deals with review of TF research, they generally focused on type and characteristics of various TF, so hardly provides information about patterns of TF research and which TF method is used in certain technology industry. Accordingly, this study profile developments in and patterns of scholarly research in TF over time. Also, this study investigates which technology industries have used certain TF method and identifies their relationships. This study will help in understanding TF research trend and their application area. Technology forecasting, technology industry, TF trend, technology trajectory.
Overview of NTCIR-13 Actionable Knowledge Graph ( AKG ) Task

This paper overviews NTCIR-13 Actionable Knowledge Graph (AKG) task. The task focuses on finding possible actions related to input entities and the relevant properties of such actions. AKG is composed of two subtasks: Action Mining (AM) and Actionable Knowledge Graph Generation (AKGG). Both subtasks are focused on English language. 9 runs have been submitted by 4 teams for the task. In this paper we describe both the subtasks, datasets, evaluation methods and the results of meta analyses.
Iteratively Trained Interactive Segmentation

Deep learning requires large amounts of training data to be effective. For the task of object segmentation, manually labelling data is very expensive, and hence interactive methods are needed. Following recent approaches, we develop an interactive object segmentation system which uses user input in the form of clicks as the input to a convolutional network. While previous methods use heuristic click sampling strategies to emulate user clicks during training, we propose a new iterative training strategy. During training, we iteratively add clicks based on the errors of the currently predicted segmentation. We show that our iterative training strategy together with additional improvements to the network architecture results in improved results over the state-of-the-art.
A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting

In the rst part of the paper we consider the problem of dynamically apportioning resources among a set of options in a worst-case on-line framework. The model we study can be interpreted as a broad, abstract extension of the well-studied on-line prediction model to a general decision-theoretic setting. We show that the multiplicative weightupdate rule of Littlestone and Warmuth [20] can be adapted to this model yielding bounds that are slightly weaker in some cases, but applicable to a considerably more general class of learning problems. We show how the resulting learning algorithm can be applied to a variety of problems, including gambling, multiple-outcome prediction, repeated games and prediction of points in R n . In the second part of the paper we apply the multiplicative weight-update technique to derive a new boosting algorithm. This boosting algorithm does not require any prior knowledge about the performance of the weak learning algorithm. We also study generalizations of the new boosting algorithm to the problem of learning functions whose range, rather than being binary, is an arbitrary nite set or a bounded segment of the real line.
Matrix-Based Ramanujan-Sums Transforms

In this letter, we study the Ramanujan Sums (RS) transform by means of matrix multiplication. The RS are orthogonal in nature and therefore offer excellent energy conservation capability. The 1-D and 2-D forward RS transforms are easy to calculate, but their inverse transforms are not defined in the literature for non-even function <formula formulatype="inline"><tex Notation="TeX">$ ({\rm mod}~ {\rm M}) $</tex></formula>. We solved this problem by using matrix multiplication in this letter.
A comparative study of the origin, structure, and indexing language of the Persian and English keywords of articles indexed in the IranMedex database and their compliance with the Persian medical thesaurus and Medical Subject Headings

In the present era, thesauri as tools in indexing play an effective role in integrating retrieval preventing fragmentation as well as a multiplicity of terminologies and also in providing information content of documents.


GOALS
This study aimed to investigate the keywords of articles indexed in IranMedex in terms of origin, structure and indexing situation and their Compliance with the Persian Medical Thesaurus and Medical Subject Headings (MeSH).



This study is an applied research, and a survey has been conducted. Statistical population includes 32,850 Persian articles which are indexed in the IranMedex during the years 1385-1391. 379 cases were selected as sample of the study. Data collection was done using a checklist. In analyzing the findings, the SPSS Software were used.



Although there was no significant difference in terms of indexing origin between the proportion of different types of the Persian and English keywords of articles indexed in the IranMedex, the compliance rates of the Persian and English keywords with the Persian medical thesaurus and MeSH were different in different years. In the meantime, the structure of keywords is leaning more towards phrase structure, and a single word structure and the majority of keywords are selected from the titles and abstracts.



The authors' familiarity with the thesauri and controlled tools causes homogeneity in assigning keywords and also provides more precise, faster, and easier retrieval of the keywords. It's suggested that a mixture of natural and control languages to be used in this database in order to reach more comprehensive results.
Idiopathic chylothorax in dogs and cats: nonsurgical and surgical management.

Idiopathic chylothorax is a debilitating disease that can lead to respiratory and metabolic compromise and fibrosing pleuritis. Several treatment options are available once a diagnosis has been made. Although large-scale studies on the outcome of treatment for idiopathic chylothorax are lacking, long-term resolution of clinical signs is possible. Pathophysiology, diagnosis, and thoracic duct imaging are discussed in a companion article. This article provides an overview of nonsurgical and surgical management techniques for idiopathic chylothorax in dogs and cats.
Real-Time Cloud Simulation Using Lennard-Jones Approximation

Cloud simulation is important for creating images of outdoor scenes. However, the complexity of this natural phenomenon makes the simulation of large-scale clouds difficult in real time. In this paper, we present a new method for 3D cloud simulation in which cloud animation is simplified and simulated by approximating Lennard-Jones Potential. To solve the N-body problem in Lennard-Jones Potential, we minimized the interaction between particles by dividing the simulation space into many cells and we defined a cutoff distance to perform calculation between neighboring particles. Additionally, a separate distance is introduced between particles to maintain the stability in the Lennard-Jones system. Our experimental results demonstrate that our method is computationally inexpensive and suitable for real time applications where large-scale simulation of clouds is required.
Psychological distress and related factors in female college students.

This study assessed the psychological distress in Spanish college women and analyzed it in relation to sociodemographic and academic factors.



The authors selected a stratified random sampling of 1,043 college women (average age of 22.2 years). Sociodemographic and academic information were collected, and psychological distress was assessed with the Symptom Checklist-90-Revised.



This sample of college women scored the highest on the depression dimension and the lowest on the phobic anxiety dimension. The sample scored higher than women of the general population on the dimensions of obsessive-compulsive, interpersonal sensitivity, paranoid ideation, psychoticism, and on the Global Severity Index. Scores in the sample significantly differed based on age, relationship status, financial independence, year of study, and area of study.



The results indicated an elevated level of psychological distress among college women, and therefore college health services need to devote more attention to their mental health.