Reviewerly/exHarmony huggingface dataset:
KEMAMPUAN MENGUBAH TEKS WAWANCARA DALAM BENTUK NARASI

These findings aim to obtain complete data and information about the ability to change the interview text in narrative form. The total student population was 76 students divided into three classes, while the sample was the total sample. The techniques used in data collection are documentation techniques and test techniques. The instrument used was in the form of an interview text which then the students were assigned to convert it into a narrative form. From the research results, it can be seen that students who get a score of 65 and above are 31 students (40.79%) and students who get a score of less than 65 are 45 students (59.21%). Based on the predetermined qualification standards, namely students who get a score of 65 and above at least 85%, it can be concluded that students have not been able to change the interview text into a narrative form. because it does not reach the predetermined qualification standards.
The Impact of Volunteer Work on Life Satisfaction of Male and Female Seniors : Focusing on the Mediating Effect of Self-esteem

본 연구는 노인의 자원봉사활동이 생활만족도에 미치는 영향과 자아존중감이 이들 간의 관계를 매개하는 지를 남성과 여성으로 구분하여 검증하고자 하였다. 이를 위해 본 연구에서는 2019년에 배포한 한국복지패널 13차년도 자료를 사용하였다. 연구대상자는 남성노인 1,316명, 여성노인 2,287명이었으며, 자료분석은 SPSS 25.0을 활용하였다. 분석결과는 다음과 같다. 첫째, 남성노인과 여성노인의 자원봉사활동은 생활만족도를 높이는 요인으로 나타났다. 둘째, 남성노인의 자아존중감은 자원봉사활동과 생활만족도 간을 매개하는 것을 검증하였다. 셋째, 여성노인의 자아존중감은 자원봉사활동과 생활만족도 간을 매개하는 것을 검증하였다. 이와 같은 연구결과는 노인의 생활만족도를 향상시킬 수 있는 예측요인으로서 자원봉사활동과 자아존중감을 실증적으로 살펴보았다는 점에서 연구의 의의가 있다. 특히, 자아존중감이라는 매개요인은 노인의 자원봉사활동으로 인한 결과인 동시에 그들의 생활만족도를 높일 수 있는 예측요인으로 작용함을 발견하였다. 이에 본 연구는 남성노인과 여성노인들의 자원봉사활동 참여의 향상과 함께 자아존중감 역량을 강화시켜주는 것을 통해 생활만족도를 높일 수 있는 실천적, 정책적 방안들을 논의하였다.The purpose of this study was to verify the impact of volunteer work on life satisfaction of the elderly and examine how self-esteem mediates their volunteer work and life satisfaction. The study used data from the 13th year of the Korea Welfare Panel, which was distributed in 2019. Subjects of this study were divided into two groups where were 1,316 male and 2,287 female, and the data analysis was used by SPSS 25.0. The results of the analysis are as follows: First, volunteer work was found to be a factor in increasing both male and female groups’ life satisfaction. Second, the self-esteem of male seniors was verified to mediate the relationship between volunteer work and life satisfaction. Third, the self-esteem of female seniors was verified to mediate the relationship between volunteer work and life satisfaction. The practice and policy implications were suggested to enhance life satisfaction of the elderly by improving.
Action Generative Networks Planning for Deformable Object with Raw Observations

Synthesizing plans for a deformable object to transit from initial observations to goal observations, both of which are represented by high-dimensional data (namely “raw” data), is challenging due to the difficulty of learning abstract state representations of raw data and transition models of continuous states and continuous actions. Even though there have been some approaches making remarkable progress regarding the planning problem, they often neglect actions between observations and are unable to generate action sequences from initial observations to goal observations. In this paper, we propose a novel algorithm framework, namely AGN. We first learn a state-abstractor model to abstract states from raw observations, a state-generator model to generate raw observations from states, a heuristic model to predict actions to be executed in current states, and a transition model to transform current states to next states after executing specific actions. After that, we directly generate plans for a deformable object by performing the four models. We evaluate our approach in continuous domains and show that our approach is effective with comparison to state-of-the-art algorithms.
비전통적 안보위협과 테러 대응 체계의 실효성 고찰 - 법령과 제도, 대응기능을 중심으로-

Since the year of 1990s, Post-Cold Wars and globalization have spread new security threats such as natural and social disasters, terror attack, and highly infectious diseases as well as the human movement and logistic revolution.As it became difficult to solve this problem with traditional security concepts alone, “non-traditional security concepts” appeared, and threats were extended to transnational and non-military fields.From a policy point of view, there are three factors need to be considered for future national security. ‘Potentiality’ as non-traditional security threats which does not show on usual time, ‘Unpredictability’ as not possible to predict a specific threat point in time, ‘Transnational connectivity’ as transcends targets and area. Therefore, efforts are needed to study countermeasures in terms of policies and functions.This study believes that it will be possible to increase its effectiveness when it can simultaneously respond to traditional and non-traditional security threats.However, since it is difficult to deal with all of the non-traditional threats, it has been presented a response method and means focused on terrorism; which is an significant threat in the 21st century across military and non-military fields.Order to achieve goal of this study, ‘non-traditional security threat’ was set as an independent variable, ‘effectiveness’ was set as a dependent variable, and ‘conceptual basis’, ‘laws and institutions’, and ‘functions and operations of responding organizations’ were set as parameters. Although it is impossible to ignore the practical limitations and opposite opinions, this study will address the urgent issues first in order to address the ever-increasing non-traditional security threats.
Signal Rich Art: Object Placement, Object Position Modulation and Other Advances

Signal rich art is an alternative paradigm for watermarking, in which we embed a signal in an image or software application such as a website or app as a visible artistic pattern. In this paper we present a new algorithm for generating signal carrying patterns from a dictionary of objects which we call object placement. In an alternative approach, called object position modulation, we locally perturb the positions of objects in a given pattern to embed the signal. We also present advances in previous techniques.
Terahertz auto oscillations in non-collinear coplanar metallic antiferromagnets

Owing to their nonlinear dynamics, frequency tunability, nanoscale size, and the ability to operate over broad temperatures, spin torque-driven ferromagnet (FM)-based oscillators are excellent candidates for various neuromorphic computing applications [1]. However, FM oscillators operate at gigahertz speed, which limits the net throughput of the architecture. Antiferromagnet (AFM)-based oscillators can operate at terahertz (THz) frequency due to a strong exchange interaction [2], and thus help overcome the limits of FM oscillators for neuromorphic computing. Also, the dynamics of AFMs can be tuned to display coherent rotation as well as non-coherent spikes [4], which have a similarity to the dynamics of neurons. Prior works have focused on the dynamics in collinear AFMs, such as NiO [2], [3], [4], while that in non-collinear AFMs is virtually unexplored even though their larger magnetoresistance and anomalous Hall effects should enable efficient detection. Here, we report a numerical analysis of the THz dynamics of non-collinear coplanar conducting AFMs such as Mn <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Ir and Mn <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Sn and compare their performance to that of NiO. Unlike NiO, the oscillations of the order parameter in metallic AFMs studied here are transduced into voltage signal using the tunnel anisotropy magnetoresistance (TAMR) measurement [6].
항공서비스 전공학생의 전공선택동기가 진로결정 자기효능감 및 취업준비행동에 미치는 영향

A study of purpose is identify and analyze The Effects of Major Selection Motivation of Students Majoring in Airline Service on their Career Decision-Making Self-Efficacy and Employment Preparation Behavior, to open better departmental education programs for students and to present efficient directions in the employmet preparation process, which is a step for future career goals and preparation. In summary, it was found that the higher the motivation for selecting a major for an aviation service major, the more a Career Decision-Making Self-Efficacy is affected. The Career Decision-Making Self-Efficacy of air service students, the more they were found to have an impact on the Employment Preparation Behavior, and only the future plan, which is a sub-factor of the independent counsel, did not significantly affect the informal and preliminary Employment Preparation Behavior. The implications of this study were intended to use the motivation for majors in college entrance exams so that students can live a smooth college life and achieve their desired jobs after admission.
A MAPE-K Loop Based Model for Virtual Machine Consolidation in Cloud Data Centers

Today, with the rise of cloud data centers, power consumption has increased and cloud infrastructure management has become more complex. On the other hand, meeting the needs of cloud users is an important goal in the cloud infrastructure. To solve such problems, an autonomous model with predictive capability is needed to do virtual machine consolidation at runtime effectively. In fact, using the feedback system of autonomous systems can make this process simpler and more optimized. The goal of this research is to propose a cloud resource management model that makes the virtual machine consolidation process autonomous, and by using a prediction method compromises between service level agreement violations and energy consumption reduction. In this research, an autonomous model is presented which detects overloaded servers in the analysis phase by a prediction algorithm. Also, at the planning phase, a multi heuristic algorithm based on learning automata is proposed to find proper servers for virtual machine placement. Cloudsim version 3.0.3 was used to evaluate the proposed model. The results show that the proposed model has reduced averagely the service level agreement violations, energy and migration counts by 67.08%, 11.61% and 70.64% respectively, compared to other methods.
Implementation of Secure Encrypted Image based Password

In an exceedingly planned methodology we tend to use the data encryption and steganography technique to secure the image arcanum generation to secure access on the info server’s files, for additional security splitting technique wont to the stegno image for verification server aspect and consumer aspect user knowledge. This system provides robust knowledge security to storage on local cloud server and that we additionally offer the robust network communication security to registered users during knowledge uploads and downloads user knowledge. In this system coated the thought of generating associate economical algorithm for generates secure image primarily based arcanum Authentication system.
Desks for Triple Monitors

A 3 monitor desk setup is an end game situation for a lot of computer enthusiasts. However, finding the right desk to fit them all can be a ...
" Mundos ideales”, un proyecto de investigación e incidencia en el contexto de la pandemia del covid-19 en México

This article describes the adaptation process that had to be carried out in a research and intervention project whose purpose is to establish inquiry communities to promote literacy as a tool for social inclusion in children who are in the last years of primary education in Mexico. The project responded to a specific call from the National Council of Science and Technology of this country published before the health emergency caused by COVID-19, so the initial plan could not be followed once the project was approved and funded. Given that the research took physical proximity for granted, these pages collect the experience of the changes due to the distance that the institutions forced due the pandemic. At the end, some findings of the field work for diagnostic purposes and some of their implications are discussed.
Research Data Infrastructure for High-Throughput Experimental Materials Science

The High-Throughput Experimental Materials Database (HTEM-DB, htem.nrel.gov) is the endpoint repository for inorganic thin-film materials data collected during combinatorial experiments at the National Renewable Energy Laboratory (NREL). This data asset is enabled by NREL’s Research Data Infrastructure (RDI) – a set of custom data tools that collect, process, and store experimental data and metadata. Here, we describe the experimental data-tool workflow from the RDI to the HTEM-DB to illustrate the strategies and best practices currently used for materials data at NREL. Integration of these data tools with experimental processes establishes a data communication pipeline between experimental and data science researchers. In doing so, this work motivates the creation of similar data workflows at other institutions to aggregate valuable data and increase their usefulness for future data studies. These types of efforts can greatly accelerate the pace of learning and discovery in the materials science domain, by making data accessible to new and rapidly evolving data analysis methods.
Making particle physics and cosmology accessible for high school students

In teaching science, you often need to decide on how far to introduce students to topics from an abstract scientific and mathematical perspective.Considering this question, we developed and tested educational materials on Particle Physics and Cosmology for students of grade 9 to 12 at secondary and upper secondary level, and for gifted students in special courses or academies, like Deutsche Schülerakademie or competitions like Jugend forscht, building on their prior knowledge.Our material also contains experiments supported by DESY and the University of Wuppertal.The theoretical parts of our course material cover electromagnetism and quantum mechanics up to Maxwell's equations, the Schrödinger equation and the Klein-Gordon equation, which require basic knowledge in differential equations and group theory.Some course participants were introduced to geometrical path lengths, tensors, and symmetries (according to [4], [12]).The evaluation of the results, the material, and the courses from a cognitive as well as a psychological point of view unfolds possibilities and necessities to elaborate on different parts of exercises and projects on different levels, and revealed new relations between these parts.Students' perception of physics and mathematics, their beliefs in understanding something and their workout of projects indicated relationships different from our expectations ([10], [11]).Results in connection with different types of courses are described below for experiments on (i) Differential Equations, (ii) Path Length and (iii) Symmetries.The topics are described in connection with courses, activities, or students' projects.
Compression of deep learning models through global weight pruning using ADMM

Deep learning, which has recently shown excellent performance, has a problem that the amount of computation and required memory are large. Model compression is very useful because it saves memory and reduces storage size while maintaining model performance. Model compression methods reduce the number of edges by pruning weights that are deemed unnecessary in the calculation. Existing weight pruning methods using ADMM construct an optimization problem by a layer-by-layer addition of pre-defined removal-ratio constraints. Decomposing into two subproblems through the ADMM process, one can solve them through gradient descent and projection. However, the layer-by-layer removal ratios must be structurally specified, causing a sharp increase in training time due to a large number of parameters, and hardly feasible to use for large models that actually require weight pruning. Our proposed method performs weight pruning, producing similar performance, by setting a global removal ratio for the entire model without prior knowledge of structural characteristics in order to solve the shortcomings of the existing ADMM weight-pruning methods. To effectively avoid performance degradation, the method removes a relatively small number of previous layers in charge of feature extraction. Experiments show high-quality performance, not necessarily setting layer-by-layer removal ratios. Additionally, experiments increasing layers yield an insight for feature extraction in pruned layers. The experiment of the proposed method to the LeNet-5 model using MNIST data results in a higher compression ratio of 99.3% outperforming those of other existing algorithms. We also demonstrate the effectiveness of the proposed method in YOLOv4, an object detection model requiring substantial computation.
Analysis of M-Learning Technologies and Approaches: A Survey

In this digital era, Mobile phones have taken over various aspects of our lives. Irrespective of the age group, the smartphone ownership is growing rapidly and this rapid growth has paved a way to utilize Mobile phones in our educational system as well. M-Learning platforms these days have exhibited a histrionic withdrawal from old-fashioned computing stages. M-Learning is an upcoming pedagogy which is being largely explored by various institutions to take education system to the next level. This article analyses various research works and identifies several advantages for utilizing these innovative pedagogies effectively via a survey oriented approach. The result of the comparative study identifies the rewards as well as the challenges of numerous M-learning platforms for the maximum utilization to boost the global teaching and learning skill. Moving in to M-learning will definitely make learning more innovative and interactive both in terms of students and teacher’s perspective. The various approaches, technologies used and specific applications of M-Learning process have been analysed in this work. Finally, it concludes the best suitable approach and technology is identified for teaching and learning process.
A Retinex-based Enhancement method for Ocean Remote Sensing Image

In order to effectively monitor important sea areas, one of the key issues is the detection of small dynamic targets such as ships. Besides monitoring the hull itself, the monitoring of small targets can also be achieved by detecting ship wakes, which means the sea image with clear texture feature is required. This paper firstly reviews the multiscale retinex (MSR) method, commonly used to enhance the image contrast. Then, it proposes a novel contrast enhancement algorithm base on the subband-decomposed multiscale retinex (SDMSR) method. Experimental results show that our proposed method can make a remarkable enhancement effect for ocean remote sensing images with clouds and whitecap, etc.
Deep Learning for Face Recognition under Complex Illumination Conditions Based on Log-Gabor and LBP

The complex light conditions, and this is one of the most important and difficult problems in practical face recognition, in this paper, we propose a new deep learning-based method to solve the problem of the effect of the light of the changes in the facial recognition process. First, the primary treatment of the lighting can be used to improve the negative effects of intensive changes in the lighting of a photo of a face, and for a second, the Log-Gabor filters in order to get the images used in the Log-Gabor features at different scales and in different directions, and then, the LBP (Local Binary Pattern) features on the image subblock is obtained. Finally, the histogram of the texture of the features of the formation and the visual layer of the deep belief network (DBN) to drop, and then the classification and the recognition is done with a deep-learning-DBN. The experimental results show that superior performance can be obtained in the application of the strategy in comparison to some of the modern technology.
Comparative analysis of blockchain consensus algorithms from Shariah perspective / Tasneem Darwish … [et al.]

Blockchain provides a distributed digital ledger platform for not only cryptocurrencies but also many other distributed applications. Blockchain platforms workflow and performance are controlled by the used consensus algorithms. Although many studies evaluated cryptocurrency from the Shariah perspective, they focused only on the Cryptocurrency concept and did not consider the underlying blockchain technology. However, designing a Shariah compliant application on top of a non Shariah compliant platform does not fulfil the requirements of Shariah. Therefore, it is necessary to use a Shariah compliant blockchain platform in order to produce Shariah compliant blockchain applications. To support the production of Shariah compliant blockchain applications, this study provides a comparative analysis of the most used consensus algorithms in blockchain platforms. In particular, the considered consensus algorithms are evaluated from a Shariah perspective. In conclusion, based on the conducted evaluation some of the widely used blockchain platforms (e.g. Bitcoin and Ethereum) are found to be not compliant with the Shariah rules due to using a consensus algorithm that is not Shariah compliant.
استخدام برنامج قائم علی استخدام العاب الکومبیوتر لتدریس القواعد لتنمیه مهارات طلاب الف السادس الابتدائی وتحسین اتجاههم نحو تعلم اللغه الانجلیزیة

ABSTRACT The present study was conducted to investigate the effect of using a grammar computer game-based learning program to develop sixth graders’ grammar achievement and attitudes towards learning English. A pre-post control group research design was used to achieve the research objectives. Sixty pupils were randomly divided into two groups: the experimental and the control groups. The experimental group pupils were trained in grammar computer game based program to develop their grammar achievement and attitudes towards learning English. The content was based on the Student’s Book” Time for English”. The control group pupils were taught the same content through the regular method of teaching. Instruments of the study included a pre-post grammar achievement test and an attitude scale. Analysis of the data obtained by pupils by using (t-test) and the attitude scale revealed that the experimental group significantly surpassed the control one in the post grammar achievement test and the post- performance of the attitude scale. Discussion of these findings, recommendations and suggestions for further researches are presented. Key words: Grammar, achievement, attitude and computer games.
PERANCANGAN VIDEO COMPANY PROFILE PT. DIAN PERMATA OMEGA SEBAGAI MEDIA PROMOSI

Company Profile can be interpreted as a media introduction to the company aimed at the audience who aims to inform, believe in, and persuade the audience to buy products or use the services of the company. PT. DIAN PERMATA OMEGA is a company engaged in the field of Entertainment and has several other divisions, but due to lack of promotional media, investors do not know about the company and several other divisions, so new promotional media are needed which will be in the form of company profile videos with motion graphic tectics, media video promotion was chosen because at the moment motion motion video is quite attractive to many people because it offers different things, besides that the presence of a video-based company profile will make the process of company introduction more time-saving, flexible, easy to remember and effective. It can be concluded that the Company Profile video was created with the aim to help the promotion process carried out by PT. DIAN PERMATA OMEGA.