Reviewerly/exHarmony huggingface dataset:
Non-destructive evaluation of internal cracks in glass fiber-reinforced polymers using digital shearing interferometry

Shearography is one of the advanced methods of non-destructive techniques based on the interference of laser beams that have been reflected from the surface of the specimen. This method, which has high speed and accuracy, can evaluate the displacement derivative on the sample surface at once. In this paper, the possibility of sub-surface cracks detection with different lengths and angles in composite samples was investigated by shearography method and thermal stimulation system. For this purpose, in composite samples, controlled cracks were created with different lengths and angles. After calibration of the performance of the shearography setup, two heat sources of radiation were used to load samples. Loading quantity, the amount and direction of the shear, the cracks length, and their angles were chosen as the studied parameters. The results of this paper showed that the optimum loading amount plays a more critical role in the quality of the results than shear amount, and this value is related to the materials of the samples. To achieve the best results in crack detection on the selected specimens, optimum thermal loading was obtained between 12 and 15 seconds from in front of the specimen. Also, the optimum shear amount in the composite specimens was estimated at about 0.1 image width recorded by the camera. With the optimized values, all sub-surface cracks were identified.
STRATEGI PENCEGAHAN KEBAKARAN LAHAN BERBASIS MASYARAKAT DESA KUALA TERUSAN KECAMATAN PANGKALAN KERINCI KABUPATEN PELALAWAN

The formulation of a strategy to prevent community-based land fires in Kuala Terusan Village was carried out in October 2018 to October 2019. The research method is survey method. Key informants included the Head of the Pelalawan District Disaster Management Agency, the Head of the Fire Regulations of the Pelalawan Regency Plantation Office, the Head of the Kuala Terusan Village, Community Leaders, the Chair of the Tuah Negeri farmer group and the Head of the Tanjung Mandiri farmer group. Key informants can increase if met by other parties who also play a role in preventing land fires in Kuala Terusan Village. Data analysis using SWOT analysis. The results of the formulation of the strategy are to increase community knowledge and attitudes towards preventing land fires through socialization, guidance and training, increasing community participation through institutional strengthening and providing incentives by the government to the Fire Concerned Farmers Group and Fire Concerned Communities, utilizing government resources and community capacity villages as a preventive measure for preventing land fires through building reservoirs, building canal blocks and providing infrastructure for preventing land fires for farmer groups, increasing collaboration between the government and the community through the establishment of a Patrol Team in efforts to prevent land fires and conducting routine patrol / supervision of migrants to the village which has the potential to cause a fire, maintain local wisdom of land clearing or preparation by not burning through the provision of assistance with tools and social assistance and issuing village regulations to improve ur rights, responsibilities and criminal provisions (legal sanctions) for communities in land management.
The Expansion of Lifelong Education Through University-Local Community Cooperation: Focusing on Japanese Universities’ Center of Community (COC) Projects

본 논문은 최근 사회인 입학을 위하여 우리나라의 대학평생교육의 구조가 변화하는 가운데, 대학이 지역과 연계하여 지역과제에 대응하며 기존의 지역평생교육과는 차별화된 다양한 대학 평생교육을 창출하는 일본의 대학COC정책을 분석하였다. 이를 위하여 연구자는 일본의 대학 COC포털에 게시된 82개의 대학COC사업방향을 분석하고 나아가 사례고찰을 통하여 대학COC사 업이 만들어내는 교육의 특징을 도출하였다. 연구결과에 따르면 일본의 대학COC사업은 공개강 좌뿐 만 아니라 공개수업을 통하여 질 높은 고등교육의 양적 확산을 도모하였고 나아가 연구의 성과를 활용하여 특별한 지역과제해결에 참여하며 지역산업발전이나 고용에 기여하는 전문적 실무적 교육기회를 제공하고 있다. 그리고 대학 내 뿐만 아니라 지역분산시스템을 만들어 내어 고등교육의 전문적 지식을 확산시키고 있다. 이러한 특징은 지역사회와 대학이 양자모두 지역에서 지속가능한 존속을 위하여 매력있고 안정된 지역사회의 기반을 필요로 하고 있어 사회형성자로서 함께 파트너십을 구축하는 과정에서 평생학습기회가 만들어진다는 점을 시사한다.As South Korean universities are changing their lifelong education systems to better meet the needs of working adults, this paper explores the Center of Community (COC) policies of universities in Japan, which provide various lifelong learning courses at universities unlike the traditional ones provided by local community organizations. In this study, the researcher analyzed COC projects of 82 Japanese universities posted on their COC portals and then identified the characteristics of university COC projects in Japan. The analysis shows that Japanese universities provide not only lectures open to the public but also publicly available courses to increase access to quality higher education. In addition, research results from COC projects contribute to resolving the challenges of local communities. These universities also offer practical professional learning opportunities to develop local industries and increase employment. Furthermore, universities have established local dispersion systems to spread their knowledge to local communities. These results suggest that both local communities and universities need attractive and stable local bases in order to ensure local sustainability and that lifelong learning opportunities are created when they form partnerships to better society.
Sphynx: a parallel multi-GPU graph partitioner for distributed-memory systems.

Graph partitioning has been an important tool to partition the work among several processors to minimize the communication cost and balance the workload. While accelerator-based supercomputers are emerging to be the standard, the use of graph partitioning becomes even more important as applications are rapidly moving to these architectures. However, there is no distributed-memory parallel, multi-GPU graph partitioner available for applications. We developed a spectral graph partitioner, Sphynx, using the portable, accelerator-friendly stack of the Trilinos framework. In Sphynx, we allow using different preconditioners and exploit their unique advantages. We use Sphynx to systematically evaluate the various algorithmic choices in spectral partitioning with a focus on the GPU performance. We perform those evaluations on two distinct classes of graphs: regular (such as meshes, matrices from finite element methods) and irregular (such as social networks and web graphs), and show that different settings and preconditioners are needed for these graph classes. The experimental results on the Summit supercomputer show that Sphynx is the fastest alternative on irregular graphs in an application-friendly setting and obtains a partitioning quality close to ParMETIS on regular graphs. When compared to nvGRAPH on a single GPU, Sphynx is faster and obtains better balance and better quality partitions. Sphynx provides a good and robust partitioning method across a wide range of graphs for applications looking for a GPU-based partitioner.
A COMPOSITIONAL APPROACH FOR TRAFFIC DISTRIBUTION EVALUATION OF TRIPLE LEFT-TURN LANES FROM AN INDIVIDUAL PERSPECTIVE

This study analysed unbalanced traffic distribution on Triple Left-Turn Lanes (TLTLs) at signalized intersections that is caused by left-turn drivers’ unequal lane preferences. To develop statistical bonding between the multilane traffic flow and individual lane choices, the lane volumes are formatted as compositional data to subject the sum-constant constraint. One-way and two-way Compositional ANalysis Of VAriance (CANOVA) models were formulated respectively to estimate the independent effect of one factor and its joint effects with other factors on the multilane traffic distribution. TLTL volume composition was the dependent variable of the models, while the factors of geometric design and traffic control that could affect left-turn drivers’ lane choice were the independent variables. Results indicate that variance of vehicle turning curve, length of the upstream segment, the location of triple left-turn sign, signal phase / cycle length, could affect the traffic distribution, and its balance could be achieved at specific levels of a factor. The joint effects of some factor couples could improve the unbalanced traffic distribution while others could not work.
A mathematical model to evaluate return on investment in higher education

Subject. The article assesses the effectiveness of investments in higher education. Objectives. The aim is to assess the performance of investments in higher education for a Master’s student at the Peter the Great St. Petersburg Polytechnic University, in the field of Economics, Business Analyst Specialty. Methods. The methodology, presented in the study, includes three stages. The first assesses the demand for skills, the second assesses how the supply of skills match the demand, and the third – the effectiveness of investments in higher education, based on the developed mathematical model, scenario analysis, and decision tree. Results. We revealed that for a business analyst, the most important categories of skills are project management, decision-making, organizational competencies, communication, and knowledge of corporate software. The most required skills in these categories are the knowledge of business processes, project documentation, systems thinking, teamwork, communication, and well-bred speech. The analysis of correspondence between the competencies required by employers and those acquired in the training process showed that Master’s graduates meet the demand for the position of a business analyst in the labor market by 69%. Conclusions. The evaluation of the effectiveness of investment in higher education for a Master’s student of the Peter the Great St. Petersburg Polytechnic University, in the field of Economics, Business Analyst Specialty, shows that it is more profitable for a Bachelor graduate to continue studying for a Master's degree, rather than go straight to work.
The Effectiveness of Jigsaw Learning Model by Using Numbered Cards: Strategy for Increasing Mathematics Learning Motivation Students in Elementary School

This study aims to increase the motivation of learning mathematics in elementary school through the implementation of the Jigsaw learning model based on the use of numbered cards as an effective strategy to increasing students’ motivation to learn mathematics by involving research samples of 52 students.  this study analyzed using a descriptive quantitative approach with Quasi Experiment Nonequivalent Control Group Design. Collecting research data using instruments such as teacher and student observation sheets and questionnaire instruments that have been validated by expert validators. The results of this study indicate that the students’ motivation in the experimental class is better than the control class, with evidence that there has been an increase in the learning process which has an impact on increasing students’ motivation to learn mathematics consistently from the first meeting to the third meeting with the good assessment categories.   the results of this study are that the use of numbered cards makes it easier to organize students’ group learning activities through the implementation of the Jigsaw learning model, stimulates the development of students learning concentration, and is even more enthusiastic for students to be actively involved in completing their learning tasks.
fake review detection using machine learning

Online reviews play a very important role in today's e-commerce for decision-making. Large part of the population i.e. customers read reviews of products or stores before making the decision of what or from where to buy and whether to buy or not. As writing fake/fraudulent reviews comes with monetary gain, there has been a huge increase in deceptive opinion spam on online review websites. Basically fake review or fraudulent review or opinion spam is an untruthful review. Positive reviews of a target object may attract more customers and increase sales; negative review of a target object may lead to lesser demand and decrease in sales. These fake/fraudulent reviews are deliberately written to trick potential customers in order to promote/hype them or defame their reputations. Our work is aimed at identifying whether a review is fake or truthful one.
Virtue in Algorithms?

Two central transformations occurred in the second decade of twenty-first century. The first is a whole new level of access to information about peoples’ habits. This is the ‘big data’ revolution: never before had it been possible to gather so much information about so many people, with such accuracy – specially gathered by huge online service providers such as Facebook, Google or Amazon, which record each of the action of their users. Thus, while marketing strategists or political campaigns have always sought to know the preferences of particular segments of the population, big data makes possible a truly high-resolution profiling of behaviours, which reflects the habits of specific individuals, and not only of demographic groups or certain geographical areas.
Role of Artificial Intelligence in Combating Cyber Threats in Banking

With the advances in information technology, various cyberspaces are used by criminals to enhance cybercrime. To mitigate this cybercrime and cyber threats, the bank and financial industry try to implement artificial intelligence. Various opportunities are provided by AI techniques, which help the banking sector to increase prosperity and growth. To maintain trust in artificial intelligence, it is important to maintain transparency and explain ability. Information about customer's behavior and interest is provided by artificial intelligence techniques. Robo-advice is an automated platform that is maintained by AI. Artificial Intelligence is also involved in protecting personal data. Proper design provided by AI towards the banking sector, by which they are able to identify fraud in transactions. AI directly linked with the domain of cyber security. Various kinds of cybercrimes are prevented and identified by AI-based fraud detection systems. However, implementation and maintenance of artificial intelligence consist of the high cost. Along with this unemployment rate is increased by AI techniques.
Gradual Pattern Mining Tool on Cloud

This paper describes an approach that illustrates how gradual pattern mining algorithms are integrated into a containerized Docker Cloud platform that implements OGC (Open Geospatial Consortium) SensorThings API (application interface). We present a practical application of the SensorThings API as a source of real-time data streams and propose an architecture that allows for extraction of gradual patterns among these data streams.
IMPROVED FRIEND RECOMMENDATION SYSTEM FOR SOCIAL NETWORKING SITE THROUGH FP-GROWTH AND ANT COLONY OPTIMIZATION ALGORITHM

: Recommender systems have established to be of high-quality useful resource in dealing with the issue of information overload by using enhancing the person's experience through best recommendations, with the speedy improvement of clever metropolis services, the social network plays a higher role in giant areas with smart technology. Social Networking allows customers to create keywords such as tags in social tagging systems to describe sources that are of activity to them, assisting to organize and share these assets with different users in the network, friend advice is important and inevitable in the social network. however, many recommendation techniques of social networks are not necessarily steady with user's interests. in order to avoid the randomness and unreliability of friend recommendation in the social community, we proposed an improved friend recommendation system for social networking website thru FP-growth and ant colony optimization algorithm, the outcomes of our test are weighted to adjust for a higher accurate result, which ultimately forms recommendation lists for the target users. Finally, the experimental results on the Delicious dataset for friend suggestion show that the effectiveness and achieved accurate outcomes and a strong recommendation.
Model of practical training in the university for future social sphere professionals

The conceptual development of a model for the practical training of future professionals in the social sphere at the university is substantiated. It is noted that the core of the social sphere is social work as an active tool of the state’s social policy in working with various categories of the population. In the course of the study, block-structural model of the practical training of future professionals in the social sphere at the university is developed, including the following blocks: productive-purposeful, conceptual, software-technological, evaluative-reflective. The productive-purposeful block is associated with competence indicators, determined by the main indicators of professional knowledge, skills and abilities, the requirements for professionals in solving social problems and the goals of theoretical and practical training of future specialists in the social sphere, in accordance with professional standards. The conceptual block of the model includes re-search approaches (competence-based, androgogical, socio-cultural) and their corresponding prin-ciples. The software-technological block contains programs for organizing the passage and train-ing work with students and representatives of social organizations – bases of educational, research and industrial practices, a program for monitoring student practice and individual support. The evaluative-reflective block of the model assumes an awareness of how students achieve their learning goals in practical training is of paramount importance, this is important for understanding their professional role in the practice of social work. Practical training at a university is an integral part of the social education curriculum, taking into account the essence of helping professions and the specifics of the social sphere. The results of the interviewing, the included observation show the relationship between changes in practical training programs and the positive dynamics of the quality of practical training of students, an increase in the parameters of personal, social and tech-nological competencies among students of the “Social Work” Programme.
Implementasi Kebijakan Pemerintah Daerah Tentang Bantuan Operasional Sekolah Daerah (BOSDA) Bagi Siswa yang Kurang Mampu Studi pada SMA Negeri 16 Bandar Lampung

BOSDA is a program of lampung provincial government in the form of direct funding to the Secondary Education Unit both public and private in the city of Bandar Lampung where the amount of grants received in schools is calculated based on the number of students unable to each school and the unit cost (Unit Cost) assistance. According to Lampung Governor Regulation Number 29 Year 2017 concerning Technical Guidelines for Operational Assistance of Lampung Provincial Schools in 2017. Schools that received Bosda Assistance in Lampung Province are Bandar Lampung City, West Lampung Regency, North Lampung Regency and Way Kanan Regency. Researchers want to find out the implementation of BOSDA policy in SMA Negeri 16 Bandar Lampung, because in the pre-survey stage there is some disagreement between the residence and the income of parents of BOSDA recipient students. The purpose of this research is to find out the implementation of BOSDA policy and to know the factors that hinder BOSDA in SMA Negeri 16 Bandar Lampung. The research method used is descriptive qualitative with data collection techniques derived from observation, documentation and based on the results of in-depth interviews. The results of this study were described using Charles O. jones toeri namely 1). The organization has an organizational structure issued in accordance with the Decree of the Provincial Education Office ranging from supervisors, persons in charge, chief executives, secretaries, treasurers and survey teams, 2) Inteprertasi the school conducts socialization of the implementation of BOSDA with the announcement and dissemination of information to the community directly, so that the implementation and implementation of BOSDA can be heard by the community directly, 3) Application that the implementation of BOSDA in accordance with technical guidelines and verify prospective BOSDA students with home surveys , facilities owned, parental work, ownership of KIP cards, as well as information from neighbors around the house, BOSDA funds expenditure is also issued according to the RKS submitted to the Provincial Education Office. Bosda implementation is in response by students is very good but needs to be added again quota while the inhibition factor is the disbursement of funds at the end of the semester makes the school have to find loan funds to finance students BOSDA
Effective Web Service Classification Using a Hybrid of Ontology Generation and Machine Learning Algorithm

Efficient and fast service discovery becomes an extremely challenging task due to the proliferation and availability of functionally-similar web services. Service classification or service grouping is a popular and widely applied technique to classify services into several groups according to similarity, in order to ease up and expedite the discovery process. Existing research on web service classification uses several techniques, approaches and frameworks for web service classification. This study focused on a hybrid service classification approach based on a combination of ontology generation and machine learning algorithm, in order to gain more speed and accuracy during the classification process. Ontology generation is applied to capture the similarity between complicated words. Then, two machine learning classification algorithms, namely, Support Vector Machines (SVMs) and Naive Bayes (NB), were applied for classifying services according to their functionality. The experimental results showed significant improvement in terms of accuracy, precision and recall. The hybrid approach of ontology generation and NB algorithm achieved an accuracy of 94.50%, a precision of 93.00% and a recall of 95.00%. Therefore, a hybrid approach of ontology generation and NB has the potential to pave the way for efficient and accurate service classification and discovery.
Face Mask Detection Using VGG-16 Net for Low Computation Power Devices

With the current ongoing pandemic, wearing masks are the newest style apparel on the market. It has become a written rule that anyone who ventures out of their house must wear a mask. It has become imperative that face mask detection is a field to research on. The paper aims at creating a low computation power requirement model, using VGG-16 net. In this paper, we employ transfer learning on VGG-16 net to reduce training time and achieve maximum results. The dataset has many classes and has elaborate confusion classes that make the model stand apart. The model is easily deployable and works with both images and live video feed.
율곡의 사도가 현대교사에게 주는 시사점

The purpose of this study is to find implications for modern teachers through the apostles of Yulgok. Looking at the current public education, which was in crisis due to Yulgok''s efforts to restore the collapsed apostles, it was necessary to establish the identity of teachers as part of overcoming the crisis. The apostle is a teacher who lives a decent life by establishing a firm will for adults. The teacher''s teachings are based on ‘deok’ and ‘yeah’ to restore universal morality, and are completed through blood cell guidance. These teachings should be realized through study and discipline. The study of apostles is based on ‘faith’ and ‘honesty’ to practice ‘geogyeong’, ‘gungri’ and ‘yeokhaeng’ in everyday life. Yulgok says that the practice of human life, the attitude of “sincerity” and “honesty” in daily life, and consideration and respect for students are necessary for teachers.