Reviewerly/exHarmony huggingface dataset:
Pendampingan Bimbingan Belajar Bahasa Inggris dan Bakti Sosial di Yayasan Pendidikan dan Sosial Roudlotut Thullab

This community service stems from the anxiety of the English Education Study Program lecturers on the importance of the usefulness of the knowledge possessed by lecturers for better community education outside of educational activities on campus. Raudhatul Thullab's educational and social foundation lacks teaching staff, especially English teachers, while students who are high enough to speak English. The object/target of this service is Raudhatul Thullab Middle School and Vocational High School students, in carrying out this service that is with a learning assistance model that is conducted for 1 month. The material includes grammar, reading, speaking, pronunciation and writing. The results of community service activities received a positive response from the school, especially because this training was suitable for their needs. The motivation of the trainees was quite enthusiastic. This indicates a desire to improve their abilities in mastering English.
MULTIPERIODIC SOLUTIONS OF LINEAR SYSTEMS INTEGRO-DIFFERENTIAL EQUATIONS WITH Dc -OPERATOR AND  -PERIOD OF HEREDITARY

The article explores the questions of the initial problem and the problem of multiperiodicity solutions of linear systems integro-differential equations with an operator of the form mmctctcD∂∂++∂∂+∂∂=11τ, ()constcccm−=,,1 and with finite hereditary period 0>=conste by variable τ that describe hereditary phenomena. Along with the equation of zeros of the special differentiation operator cD are considered linear systems of homogeneous and inhomogeneous integro-differential equations, sufficient conditions are established for the unique solvability of the initial problems for them, both necessary and sufficient conditions of multiperiodic existence are obtained by ()t,τ with periods ()ωθ, of the solutions. The integral representations of multiperiodic solutions of linear inhomogeneous systems with the uniqueness property are determined 1) in the particular case when the corresponding homogeneous systems have exponential dichotomy and 2) in the general case when the homogeneous systems do not have multiperiodic solutions, except for the trivial one. The article proposes a research technique for solving problems that satisfy initial conditions and have the property of multiperiodicity with a given e heredity period for linear systems of integro-differential equations with a special partial differential operator cD. Multiperiodic solutions obtained along characteristics 00ττcctt−+= with fixed ()00,tτ are used as an application in the theory of quasiperiodic solutions of systems of integro-differential equations.
A State of Art Methodology for Real-Time Surveillance Video Denoising

Video de-noising is one of the most essential tasks in video processing. Noise elimination and video reconstruction are still remaining as a challenging problem in this area. In this paper a modified two dimensional block based least mean square algorithm (TDBLMS) proposed to reduce the noise in the video, which can increasingly improve the image quality. The processing includes updating the adaptive weight matrix to filter noisy frame block by block and achieve higher peak signal to noise ratio. The performance of the modified TDBLMS approach compares with existing TDBLMS algorithm and gives better PSNR and SSIM results.
CBIR using SIFT with LoG, DoG and PCA

Content based image retrieval using scale invariant feature remodel (SIFT) is employed to discover stable keypoint locations within the scale-space. The extraction of image options can be done by exploiting SIFT or K-means cluster. In the proposed work we can find feature extraction and locating scale-space extrema through SIFT-DoG & SIFT-LoG ways. Finally, planned ways, SIFT-DoG, SIFT-LoG, and PCA are compared.
Analysis of the Solar Tracking System for a Mobile Robot Prototype

Methods to detect the position of the sun and orientate a solar panel to its position are used in order to optimize the power generated.Two possible approaches are using light depending resistor (LDR) sensors, or using a GPS and equations that model the geometry between the Earth and the Sun.The main objective of this work is the proposal of a prototype system to optimize the harvesting of solar energy on photovoltaic panels.In this chapter, a mobile robot powered by a solar panel orientated by a LDR matrix and a GPS device was developed.The LDRs were used as the representation of vectors normal to a surface, where its sum resulted in the most lighted point.The GPS, in turn, provided location, date and time data, which were used in the calculations of the Sun's azimuth and zenith, used to orientate the panel.The obtained results show that an orientated photovoltaic panel has a better performance when compared to a static panel.Possibilities and opportunities of research tend to grow for the next years with many possible works to be done in the future, both in mobile robotics and in other systems powered by photovoltaic panels.
PERSEPSI SISWA TENTANG MANIFESTASI TUGAS-TUGAS PERKEMBANGAN REMAJA SISWA KELAS XI SMA.NEGERI 11 SAMARINDA

AbstractYouth development tasks are tasks that arise at or around a certain period of individual life, but in reality not all students are familiar with developing youth development tasks. The formulation of the problem in this study is "What are the students' perceptions about the manifestation of the youth development tasks of class XI in SMA. Negeri 11 Samarinda 2014/2015 Academic Year". While the purpose of this study was to study students' perceptions about the manifestation of the task of developing class XI youth in SMA Negeri Negeri 11 Samarinda in the Year of Learning. This type of research is descriptive qualitative where the focus of research is students' perceptions about the manifestation of youth development tasks. This research was carried out in high school. Negeri 11 Samarinda with research participation was a class XI student at SMA Negeri 11 Samarinda in the 2014/2015 academic year that encouraged 144 students to become writers taking a sample of 75% of the total population, namely 108 students. The data collection method used was a questionnaire as the main method and documentation as a complementary method. While the data analysis technique was the interval and percentage formula. From the results of data management in 108 class XI students of SMA Negeri 11 Samarinda, 108 respondents, then 47 students of respondents had a good perception, with a percentage of 43.51%, 19 students had a very good perception, with a percentage of 17.59%, 36 students have a pretty good perception, however there are still students who have a bad perception that can be seen from the data above about 6 students or 5.55%. The results of the study showed that students' perceptions about the manifestation of youth development tasks, GOOD, because seen from 108 students as many as 47 students with a percentage of 43.51% had a GOOD perception about the manifestation of youth development tasks in SMA Negeri XI Samarinda.Keywords: Perception, Manifestation, Youth Branching
Analisis Kompleksitas Algoritma Filter IRR Shen-Castan untuk Deteksi Tepi pada Citra Digital

This study aims to measurethe level of complexity of a Shen-Castan IIR filter algorithm for edge detection in digital images based on time complexity and space complexity. This analysis is very helpful when going to do an algorithm optimization and data structure that will be used in a system. Time complexity states how long an algorithm runs at runtime based on the input given. While space complexity states how much space in memory an algorithm needs when operating. The calculation of time complexity and space complexity is denoted by Big-O notation. From the results of time complexity calculations obtained if the Shen-Castan IIR filter algorithm has the complexity of the O (n) algorithm and requires space complexity O (n) where the algorithm will need at least N units of space in memory and depends on the length of the array.
An Enterprise Credit Evaluation Method for Power Grid Service Providers Based on Block Chain is Presented

As the main content of credit investigation, credit management is an important part of enterprise operation management, and it plays a dominant role in the management of enterprise personnel, funds, contracts, bidding and other management. The management of credit is essentially the management of data. Traditional credit investigation agencies collect user data through various technical means and establish a credit investigation management database. However, the reliability of data obtained in this way is not guaranteed. The emergence of blockchain theoretically solves the problem of data reliability, and provides a new method for credit investigation, but it can not guarantee the authenticity of the data itself, that is, the nodes that get the accounting can upload the fake data content to the blockchain without verifying the data content itself. How to reduce the damage caused by this uncertainty to the operation and management of enterprises is a major scientific problem that urgently needs to be solved.
Economic Dispatch of Multiple-Chiller Plants Using Wild Goats Algorithm

Use of multiple-chiller systems in air-conditioning applications is known as a major factor in increasing electricity consumption. To obtain a significant energy saving in building space cooling, optimal operation of chillers as an energy-efficient manner is necessary. Therefore, this chapter aims to obtain the best performance of the multi-chiller systems, which can be attained by minimizing the total power consumption of chillers considering their partial load ratios (PLRs) as decision variables. In this chapter, optimal chiller loading (OCL) problem is implemented on three different case studies using a novel evolutionary algorithm, called wild goats algorithm (WGA). This algorithm is inspired from wild goats’ climbing, living in groups and based on cooperation between members of groups. Numerical results show the effectiveness of the WGA to solve the OCL problem.
Hypothetically virtual approaches to the analysis of the mechanisms of neuropsychic activity

The main ideas of the book «the Call and all the rest» [1] and of the separately published «the Unexplored and Unexamined» chapters [2] on non-standard and not always well grounded approaches to the understanding of neuro-mental activity. «Staged» questions are considered and their solution cannot be completed without careful research study. It is proposed to use the following hypothetically formulated postulates: 1. Life processes that provide neuropsychic activity cannot be explained only by traditionally understood reflex mechanisms. 2. Any living structure has the biological ability not only to passively absorb information, but also to actively seek it out. 3. The conductor system uses muscle energy in every reflex action. Higher mental activity is formed by other energetic, both exogenous and endogenous flows. 4. Conscious (and perhaps not conscious) life events and behavioral experiences do not disappear from the functional «memory library». 5. Evolutionary unification, despite situational confrontations, is a vital necessity of the interaction process. Its neblinensis parts fall out of the further development cycle. This pattern determines the general theory of unification and development for biology and sociology.
Permissioned Blockchain Revisited: A Byzantine Game-Theoretical Perspective

Despite the popularity and practical applicability of blockchains, there is very limited work on the theoretical foundation of blockchains: The lack of rigorous theory and analysis behind the curtain of blockchains has severely staggered its broader applications. This paper attempts to lay out a theoretical foundation for a specific type of blockchains---the ones requiring basic authenticity from the participants, also called \textit{permissioned blockchain}. We formulate permissioned blockchain systems and operations into a game-theoretical problem by incorporating constraints implied by the wisdom from distributed computing and Byzantine systems. We show that in a noncooperative blockchain game (NBG), a Nash equilibrium can be efficiently found in a closed-form even though the game involves more than two players. Somewhat surprisingly, the simulation results of the Nash equilibrium implies that the game can reach a stable status regardless of the number of Byzantine nodes and trustworthy players. We then study a harder problem where players are allowed to form coalitions: the coalitional blockchain game (CBG). We show that although the Shapley value for a CBG can be expressed in a more succinct form, its core is empty.
A Study on School Education Satisfaction, Educational Needs, and Career Planing for Students in Specialized Vocational High Schools

이 연구에서는 특성화고 재학생의 특성화고에 대한 인식과 만족도를 조사하고 특성화고 교육에 대한 요구 및 진로 계획을 분석하여 특성화고 운영 방향 및 정책 설정에 필요한 기초자료를 제공하고자 한다. 이를 위하여 특성화고 151개교의 재학생을 대상으로 설문조사를 실시하여 총 7527명의 응답을 분석하였다. 연구 결과는 다음과 같다. 첫째, 특성화고 학생들의 특성화고 진학의 가장 주된 이유는 ‘취업에 유리해서’였다. 학생들은 대체로 학교생활과 학과에 만족하였고 전공과 적성&#8228;소질과의 부합 정도가 높을수록 만족도가 높았다. 둘째, 특성화고 학생들은 전문교과 수업이 전공 분야 능력 함양에, 보통교과 수업이 기초 학력 향상에, 진로교육이 진로 탐색에 도움이 된다고 인식하였고, 이러한 결과는 전공과 적성&#8228;소질과의 부합 정도가 높을수록 높았다. 그리고 전문교과 수업 방법으로 현장기반형 수업을, 보통교과 수업 방법으로 프로젝트식 수업을 가장 선호하였다. 셋째, 특성화고 학생들은 취업지도와 진로지도에 대체로 만족하였으며 전공과 적성&#8228;소질과의 부합 정도가 높을수록 만족도가 높았다. 특성화고 학생들의 66.9%(취업, 취업 및 진학 병행)가 취업을 희망하였고 전공과 적성&#8228;소질과의 부합 정도가 높을수록 취업 희망이 높았다. 그러나 고등학교 졸업 이후 직업세계에서의 성장 경로에 대해 제대로 알지 못하고 있었고 전공과 적성&#8228;소질과의 부합 정도가 높을수록 성장경로에 대한 인지 정도가 높았다. 이러한 연구 결과에 터한 제언으로 특성화고 인식 개선을 위한 특성화고 성과 평가 및 홍보 체계 개편, 고졸 취업의 질적 제고를 위한 사회 정책 강화, 미래 지향적인 취업지도 운영, 구성주의적 교수&#8231;학습 강화, 중학교 진로교육의 개편이 요구된다.This study to analyze awareness, satisfaction, and educational needs of specialized vocational high school (SVHS) students about SVHS education, and career planing for students in SVHS. The survey was performed with students in 151 SVHS, 7527 questionnaires were analyzed. The major results of this study are as following. First, the main reason for students to enter a SVHS was that ‘it increased the chance of employment.’ Students were satisfied with their school life and subjects, and their satisfaction levels were higher as their major suited their aptitude properly. Second, the students said that specialized subject class helped them to develop capability in their major area, general subject class helped them to improve their basic academic skills, and career education helped them to explore their career path. They preferred work-based class for specialized subject teaching method and project-type class for general subject teaching method the most. Third, the students were satisfied with vocational guidance and career guidance. Among the students in SVHS, 66.9% (employment or employment and high education at the same time) desired for employment. However, students were unaware of the career path in the world of vocation after graduating from high school. Therefore, it is necessary to reform performance evaluation and promotion system of SVHS for improving the awareness of SVHS, reinforce social policies for improving the quality of employment by high school graduates, operate future-oriented vocational guidance, reinforce constructive teaching and learning, and reorganize career education in middle schools.
Effects of Augmented Reality-Based Intervention on Community Domain Activities in Children with Mild Autism Spectrum Disorders

본 연구는 증강현실 기반의 중재가 경증 자폐성장애 유아의 지역사회 영역활동에 미치는 효과를 알아보았다. 연구가 시작되기 전 담당 교사들과 통합학급에서 이루어질 예정인 지역사회 영역 프로젝트 활동에 대해 논의하여 활동에 사용될 가능성이 높은 지역사회 기관 10개를 선정하여 중재를 진행하였다. 장애통합어린이집에 재학중인 경증 자폐성 장애로 진단받은 3명의 남아들에게 중다기초선설계를 적용하여 기초선, 중재, 유지, 일반화의 단계로 연구를 진행하였다. 증강현실을 활용한 중재는 연구에 참여한 유아들 모두에게서 통계적으로 유의한 효과가 있다는 긍정적인 결과를 확인하였다. 또한 증강현실 기반 중재에 대한 현장의 활용 가능성 측면을 알아보기 위해 사회적 타당도 조사를 통해 담임교사들의 중재에 대한 인식과 더불어 중재의 장ㆍ단점을 알아보았다. 연구에서 도출된 결과를 바탕으로 경증 자폐성장애 유아들을 위한 증강현실 기반 중재의 활용 가능성에 대해 제안하였다. 끝으로, 본 연구의 제한점 및 추후 연구에 대해 논의하였다.This study examined the effects of AR-based intervention on community domain activities in children with mild ASD. Prior to conducting the study, the researcher discussed with teachers in charge of the children about community domain project activities that are planned to be carried out in inclusive educational settings and selected 10 community organizations that are likely to be used for the project activities. Then, the intervention was implemented with three boys who have been diagnosed with mild ASD and are attending in the kindergarten. Applying a multiple probe design across subjects, the study was conducted in steps; baseline, intervention, maintenance, and generalization. As a result, a positive outcome was confirmed that the intervention using AR has significant effect on all the children who participated in the study (Tau- U = .965, p = .000). In addition, a social validity survey investigating the applicability of AR-based intervention in inclusive settings was conducted to examine the teachers’ perception of the intervention and the strengths and weaknesses of the intervention. Based on the findings of the empirical study, this study proposed the applicability of AR-based interventions for children with mild ASD. Lastly, the limitations of this study and possible follow-up studies were discussed.
Accelerating QUIC’s Connection Establishment on High-Latency Access Networks

A significant amount of connection establishments on the web require a prior domain name resolution by the client. Especially on high-latency access networks, these DNS lookups cause a significant delay on the client's connection establishment with a server. To reduce the overhead of QUIC's connection establishment with prior DNS lookup on these networks, we propose a novel QuicSocks proxy. Basically, the client delegates the domain name resolution towards the QuicSocks proxy. Our results indicate, that colocating our proxy with real-world ISP-provided DNS resolvers provides great performance gains. For example, 10% of our 474 sample nodes distributed across ISP's in Germany would save at least 30 ms per QUIC connection establishment. The design of our proposal aims to be readily deployable on the Internet by avoiding IP address spoofing, anticipating Network Address Translators and using the standard DNS and QUIC protocols. In summary, our proposal fosters a faster establishment of QUIC connections for clients on high-latency access networks.
Support for the publication activity of scientists in the Ural Federal District

Today research libraries pay special attention to research information support. Publication activity is one of the most important indicators of the effectiveness of a scientific organization and reflects the level of science development in the state and separate regions. The article presents the statistics of publications of Russian authors according to Web of Science and Scopus. The contribution of Ural scientists to the all-Russian volume of publications on key indicators was analyzed. It shows the common development vector and a noticeable input of the Ural physicists, astronomers, chemists, mathematicians, specialists in engineering and material science in the Science in Russia. In order to achieve better results, the author proposes the creation of a publication activity support service. The review of existing Russian and foreign services is presented, as a result of which the list of actual types of services, the request form and the content of the future service is formed and described.
Research on Artificial Intelligence Visualization Application under Internet of Things Big Data

Machine learning is an inevitable outcome of the development of artificial intelligence research to a certain stage. It has become the most popular technology in the fields of computer vision and natural language processing. Learning techniques such as inductive logic programming, neural network-based connectionist learning technology, and statistical learning theory are constantly evolving. The shortcomings of various learning techniques in data representation and result processing have become a concern of many scholars. As one of the cutting-edge science and technology in the 21st century, artificial intelligence has a profound impact on education. This research is based on the artificial intelligence in Visualization Application for nearly 12 years. It has carried out visual analysis of research hotspots and frontiers. In addition, this study also discusses the research content through cluster analysis, discusses the influence of artificial intelligence on Chinese education field, and reflects on it.
Axiomatic Analysis of Contact Recommendation Methods in Social Networks: An IR Perspective

Contact recommendation is an important functionality in many social network scenarios including Twitter and Facebook, since they can help grow the social networks of users by suggesting, to a given user, people they might wish to follow. Recently, it has been shown that classical information retrieval (IR) weighting models – such as BM25 – can be adapted to effectively recommend new social contacts to a given user. However, the exact properties that make such adapted contact recommendation models effective at the task are as yet unknown. In this paper, inspired by new advances in the axiomatic theory of IR, we study the existing IR axioms for the contact recommendation task. Our theoretical analysis and empirical findings show that while the classical axioms related to term frequencies and term discrimination seem to have a positive impact on the recommendation effectiveness, those related to length normalization tend to be not desirable for the task.
Vehicle Detection Using Point Cloud and 3D LIDAR Sensor to Draw 3D Bounding Box

In recent times, Autonomous driving functionalities is being developed by car manufacturers and is revolutionizing the automotive industries. Hybrid cars are prepared with a wide range of sensors such as ultrasound, LiDAR, camera, and radar. The results of these sensors are integrated in order to avoid collisions. To achieve accurate results a high structured point cloud surroundings can be used to estimate the scale and position. A point cloud is a set of Data points used to represent the 3D dimension in X, Y, Z direction. Point cloud divides data points into clusters that are processed in a pipeline. These clusters are collected to create a training set for object detection. In this paper, the cluster of vehicle objects and other objects are extracted and a supervised neural network is trained with the extracted objects for the binary classification of the objects representing vehicles or other objects. By learning global features and local features the vehicle objects represented in the point cloud are detected. These detected objects are fitted with a 3D bounding box to represent as a car object.
Cultured Artificial Fish Swarm Algorithm: An Experimental Evaluation

In this work, a Weighted Cultural Artificial Fish Swarm Algorithm (wCAFSA) which is an amendment of standard artificial fish swarm algorithm (AFSA) is proposed. This algorithm can adaptively select its parameters at every generation in order to reduce the ease at which standard AFSA falls into local optimal. We first introduce inertial weight to adaptively determine visual distance and step size of AFSA thereafter, the Situational and Normative knowledge inherent in cultural algorithm are used to develop new variants of weighted cultural AFSA (wCAFSA Ns, wCAFSA sd, wCAFSA Ns+Sd and wCAFSA Ns+Nd). A collection of sixteen (16) optimization benchmark functions are used to test the performance of the algorithms. The simulation results disclosed that all the new variants of the wCAFSA outclassed the AFSA.