Reviewerly/exHarmony huggingface dataset:
Edukasi Bahaya Sampah Plastik pada Perairan dan Biota Laut di Sekolah Alam, Pantai Bajulmati, Kabupaten Malang, Jawa Timur

Plastic is one of the most common pollutants found in marine waters. The direct negative impact of plastic waste on marine organisms is causing blockages in the digestive tract if eaten either intentionally or unintentionally. One of the efforts to reduce plastic waste is to build public awareness and readiness to actively participate in solving the problem of plastic waste. Therefore, Marine Science Study Program, FFMS, Universitas Brawijaya is dedicated to provide education about the dangers of plastic waste for aquatic communities and marine biota at a pioneering nature school for the Bajulmati Sea Turtle Conservation (BSTC) community in Bajulmati Beach, Malang Regency, East Java. In general, community service activities take place in online and offline manner. The educational methods given to students are a participatory and collaborative learning method, namely by providing an understanding of the material through class discussions and practical waste sorting activities in the field. The results of educational activities on the dangers of plastic waste can increase public knowledge and awareness, especially students at the BSTC nature school so that later it will have an effect on wiser plastic use behavior. Through this activity, it is expected that the resulted knowledge and awareness can foster a sense of love for the environment and can also affect a better use of plastic.
Peculiarities of Organization of Students’ Online Educational Internship

The paper sets out to present the experience of organizing students’ online educational internship. The educational internship for the bachelors of Education, majoring in Health and Safety & Physical Education, is introductory, the first one in the curriculum. The distance educational internship was organized on the MS Teams digital platform using team work. The students’ online activities involved analyzing scientific, popular science, methodological and official information on health and safety and physical education, as well as on the disciplines that provide the meta-subject approach and inter-subject communications when teaching these subjects at school. The key methods were the project method and the case method. The students were given different cases, such as to analyze the content of video clips and websites, to develop environmental excursions and algorithms for modeling the volcano, to determine the optimal physical recreation and its components for people of different ages. The main advantages of students’ distance educational internship are a larger number of tasks completed by students compared to the full-time format, the use of different methods and technologies to organize students’ team work. The main problems concerning the distance educational internship include teachers significantly overloaded with the task development and evaluation, the long hours students spend working at the computer and technical issues. It is important to find a reasonable compromise between the amount of the proposed work with the information, the optimal time and safe operation in an electronic environment when organizing internships in an online format.
PENGEMBANGAN LKPD ELEKTRONIK DENGAN PENDEKATAN STEM BERBASIS PROJECT-BASED LEARNING MATERI ENERGI DAN PEMANFAATANNYA

Currently there is still a need for the development of teaching materials and no electronic LKPD has been found with a project-based STEM approach on energy materials and their utilization. The purpose of this study was to develop and determine the feasibility of electronic LKPD with a PjBL-based STEM approach on energy materials and their utilization. The research method used was RnD research with a development procedure that refered to the ADDIE development model. However, this research was only up to the development stage. The experimental subjects consisted of expert and test subjects, namely learning, material, language, media and teacher experts. The types of data were qualitative and quantitative data. Qualitative data were obtained from the results of expert and teacher reviews in the form of suggestions, input, and comments. Meanwhile, quantitative data were obtained from the scores on the assessment sheet. Data collection instruments used assessment sheets and interviews. The product trial used the developed electronic LKPD and assessment sheet. The results of the development showed that the final score of the learning experts was 86.7 that belonged to the very good category, the material expert got 86.7 in the very good category, the linguist got 91.4 in the very good category, the media expert got 78.9 in the good category, teacher I and teacher II obtained final grades of 97.5 and 88.7, that belonged to the very good categories. If it was calculated as a whole, the final score of 531 was included in the very good category. Therefore, the development of electronic LKPD with a PjBL-based STEM approach on energy materials and their utilization was appropriate to be used as teaching materials in class IV for theme 2 sub-theme 1.
Developing the Self-Learning Interactive Module using ADDIE Model for Year 5 Primary School Students

Due to a number of circumstances, learning English as a second language can be difficult.One of the reasons is because grammatical components known as tenses do not exist in one's mother tongue, making it difficult to learn.In order to compose sentences in English utilising tenses, people must play with words and times.Previous research has found that Malaysian students struggle with the usage of tenses, despite the fact that they have been learning them for a long time and that they are widely spoken by Malaysians, whether it is due to the learning process, the effect of mother tongue, or the learning materials.The goal of developing a self-learning interactive module using Microsoft PowerPoint Presentation is to assist students in improving their learning efficacy by applying the ADDIE model approach which was the methodology used in the study.The participants are 10 year five primary school students from a Malaysian public school.This study will provide new perspectives in addressing the tenses issues of year 5 students through the module and schools may prepare other modules or programmes to help students' learning process.The final outcome based on the regression study revealed that all of the participants enjoy learning English tenses in this manner, and that it has increased their knowledge and self-esteem when it comes to applying English tenses.Participants also expressed a desire to be taught via this type of module in the future for other topics which proved that their learning efficacy is boosted.Regardless, future research could continue to explore the learning efficacy in a larger sample size.
Analisis Kualitas Butir Soal Ulangan Harian di Sekolah Dasar dengan Model Rasch

Item analysis can be used to help improve the quality of items through revision or discarding ineffective questions, and can be used as diagnostic information for students, whether they have understood the material that has been taught. In this scientific paper, the researcher will analyze the daily test items using the Rasch model which involves one parameter to measure the level of difficulty of the questions in the class VI circle material at SDN Klakahrejo I/578. The purpose of this study was to determine the quality of the items and the ability of elementary school students, especially SDN Klakahrejo I/578. This research is an evaluative research with a quantitative descriptive approach. The results showed that all the questions tested on the test takers were valid and reliable. Results The difficulty level of the 10 questions tested was 4 questions classified as easy, 4 questions classified as moderate and 2 questions classified as very difficult. Based on the research that has been done, it can also be seen that the estimated value of the ability of the 31 students varies in the range of -0.69 to 3.05. This shows that students' abilities are classified as moderate to very high.
The Open Corpus of the Veps and Karelian Languages: Overview and Applications

Abstract. A growing priority in the study of Baltic-Finnic languages of the Republic of Karelia has been the methods and tools of corpus linguistics. Since 2016, linguists, mathematicians, and programmers at the Karelian Research Centre have been working with the Open Corpus of the Veps and Karelian Languages (VepKar), which is an extension of the Veps Corpus created in 2009. The VepKar corpus comprises texts in Karelian and Veps, multifunctional dictionaries linked to them, and software with an advanced system of search using various criteria of the texts (language, genre, etc.) and numerous linguistic categories (lexical and grammatical search in texts was implemented thanks to the generator of word forms that we created earlier). A corpus of 3000 texts was compiled, texts were uploaded and marked up, the system for classifying texts into languages, dialects, types and genres was introduced, and the word-form generator was created. Future plans include developing a speech module for working with audio recordings and a syntactic tagging module using morphological analysis outputs. Owing to continuous functional advancements in the corpus manager and ongoing VepKar enrichment with new material and text markup, users can handle a wide range of scientific and applied tasks. In creating the universal national VepKar corpus, its developers and managers strive to preserve and exhibit as fully as possible the state of the Veps and Karelian languages in the 19
A Weight Based Hierarchical Vector Quantization Algorithm for Space Environment Volume Data

Visualization has been widely applied in space environment domain. However, compressed volume rendering algorithms based on VQ are concerned on fidelity and compression rate, not combined with specific application. To fulfill the specific visualization requirements for space environment volume data, an application-driven compression and rendering algorithm is proposed, which is Weight Based Hierarchical Vector Quantization (WHVQ). The volume data is initially partitioned into disjoint 4<sup>3</sup> blocks. Weights are assigned to the blocks according to their importance. The blocks are then decomposed into a three level hierarchical representation and each block is represented by a mean value and two detail vectors. To the top two levels, a splitting based on principal component analysis and weight is adopted to form their initial codebooks. Then, LBG algorithm based on weight is conducted for codebook refinement and quantization. The experimental results show that WHVQ is able to improve the quality of reconstruction in interested area on the premise of the good overall fidelity.
Knowledge Sharing and Business Performance: The Role of Innovative Behavior

The purpose of this study was to analyze the antecedent variables that affect business performance in the handicraft sector SMEs in Central Java.The population of this study are all owners of handicraft SMEs in Central Java.Samples were taken using purposive sampling method.Data were collected through questionnaires, and processed using Structural Equation Modeling analysis.The loading factor value of each indicator on the latent variable shows a significant value.Based on the results showed a significant positive effect on the direct effect of knowledge sharing on innovative behavior, and innovative performance behavior on business performance.The direct relationship of knowledge sharing on innovative behavior shows the dominant influence value.The indirect effect of knowledge sharing on MSME business performance is mediated by innovative behavior.The results of this study contribute to strengthening social capital theory, the concept of organizational citizenship behavior, resource based view and knowledge based view theory.
Similarity based TOPSIS with linguistic-quantifier based aggregation using OWA

In this paper we present similarity based TOPSIS with OWA operators.The motivation behind this new method is the fact that in many real world problems it is more important to consider the amount of criteria that a particular alternative is able to satisfy instead of simply concentrating on the importance of particular criteria.Here with OWA operators we can tackle this problem together with multi-criteria decision making method called TOPSIS by aggregating alternatives' similarities towards positive ideal solution and negative ideal solution and aggregating these similarities using OWA.The use of linguistic quantifiers represented by OWA weights generated by a selected RIM quantifier allows for the reflection of decision-maker's attitude to risk in the calculation of the similarities of the alternative with positive and negative ideal solutions.
Why Answer this Question? Experts’ Behaviors on Educational Community Question-Answering Platforms

This study explores the factors that influence experts’ regular contribution to educational community question-answering (CQA) platforms. Providing answers is essential for sharing knowledge on CQA platforms, but it also affects learners’ progressive inquiry. Therefore, the purpose of this study is to develop and test a theoretical model that aims to explain which factors influence whether experts answer questions on educational CQA platforms and how these factors correlate with each other to form a “map” of experts’ respective behavior. We examined experts’ perceptions of three dimensions: the CQA platform’s usability, the quality of questions asked, and the added value of answering these questions. We examined the factors involved in these dimensions from the perspective of the Theory of Planned Behavior to connect them with the experts’ perceptions, intentions, and actions on a CQA platform. As our case study, we took the 100mentors web and mobile app, a small-scale platform that addresses learning communities around the world, and we conducted a survey for their registered experts (N=126). The factorial structure indicated that experts first perceived the question quality mostly based on its relevance to their expertise or experience (question quality); secondly, that their intention to answer was mainly set by their motives to make a difference for the learner and partially by the user-friendliness of the platform (added value of answering and CQA platform’s usability); and finally, that their actions were connected to the regular use of the platform for answer-sharing (CQA platform’s usability). A future research challenge is to test the factorial structure in large-scale educational CQA platforms. The further confirmation of the expert behavior pattern can have a practical implication for the platforms to guide their expert community more efficiently and for the learners to pursue their learning through progressive inquiry.
Descriptive Review of ISTL: The Journal of the Science and Technology Section of ACRL

Issues in Science and Technology Librarianship (ISTL), a publication of the Science and Technology Section (STS) of the Association of College and Research Libraries (ACRL), was created as a web-based, open access journal in 1996. This article is a descriptive review of ISTL contributions during the last twenty-five years.
DETECTION OF SEMANTIC RELATIONS BASED ON KNOWLEDGE GRAPH

Semantic relations have been applied to many applications in recent years, especially on Sematic Web, Information Retrieval, Information Extraction, and Question and Answer. Purpose of semantic relations is to get rid of conceptual and terminological confusion. It accomplishes this by specifying a set of generic concepts that characterizes the domain as well as their definitions and interrelationships. This paper describes how to detect semantic relations, including synonym, hyponym and hypernym relations based on WordNet and entities of Knowledge Graph. This Knowledge graph is built from two main resources: Wikipedia and unstructured files from ACM Digital Library. We used Natural Language Processing (NLP) and Deep Learning for processing data before putting into Knowledge Graph. We choose 5 of 245 categories in the ACM Digital Library to evaluate our results. Results generated show that our system yields superior performance.
The Serbian Part of the ELTeC Collection Through the Magnifying Glass of Metadata

In this paper we present the metadata assigned to the Serbian EL-TeC sub-collection, analyse them and draw some conclusions about titling practices of Serbian narrative literature in the period 1840-1920, authors' gender and age, publication places, modes of publication, as well as about institutions and individuals that are due credits for the production of Sr-pELTeC.
History of the SPIE Medical Imaging Digital Pathology Conference

The term "digital pathology" (DP) broadly refers to the process of digitizing glass whole-slide images (WSIs) using a digital whole-slide scanner as these WSIs are also used to render a diagnosis. Artificial intelligence (AI), on the other hand, is broadly defined as the application of machine-based algorithms to make a prediction, just like an intelligent human who has access to the necessary knowledge to make said prediction. Deep learning is a specific type of AI that has become very popular for the analysis and interpretation of DP images over the last decade because of the recent increase in computational power and advancements in whole-slide scanning. AI-enabled DP analysis of routine hematoxylin and eosin-stained tissues has shown increasing utility in characterizing complex tissue architecture to render disease diagnoses, prognoses, and predicting therapeutic response. A PubMed search for "digital pathology" yielded 310 hits in articles published in 2020; for those published in 2010, the same search yielded only 12 hits. The Digital Pathology Conference was initiated in 2011 by the authors (Drs. Madabhushi and Gurcan), two early pioneers in computational pathology, in anticipation of the expected explosion of research and clinical interest in this space.
Target-Aware Deep Feature Compression for Power Intelligent Inspection Tracking

Deep learning has brought revolutionary progress to computer vision, so intelligent inspection equipment based on computer vision has developed rapidly. However, due to the large number of existing deep features, it is difficult to deploy it on mobile devices to achieve real-time tracking speed. This paper presents a target-aware deep feature compression for power intelligent inspection tracking. First, a negative balance loss function is designed to mine channel features suitable for the current inspection scene by shrinking the contribution of pure background negative samples and enhancing the impact of difficult negative samples. Based on this, the deep feature compression model is combined with Siamese tracking framework to achieve real-time and robust tracking. Finally, we evaluate the proposed method on real application scenarios and general data to prove the practicability of the proposed method.
Pseudocoloring Of Medical Images: A Research

A color mapping is a process by which we transfer the particular range of colors from source to the target image. This paper says about a novel method for medical images using pseudocolor by pre existence of color mapping. Conversion of grey scale image to color has no exact way or approach, direct way to colorize is tedious by which the entire range of colors can be changed, but in color mapping the conversion is done by converting the whole black and white image into color. This novel method presents black and white image to various colors. By the creation of color map that color map is applied for colorizing the medical grey scale images. This approach can be used for grey scale medical images irrespective of size and shape such that the intensity and aspect of the image can be improved.
Cognitive Analysis of Auditory Temporal Sequence Information Difference Based on Network Switching

Auditory sense is an important way for people to receive and interact with foreign information. In different environment, the auditory sense changes. Therefore, it is necessary to find a detection method that can detect hearing in a timely manner. In this paper, EEG experiments were used to construct and compare brain functional networks in different states, and auditory state models were constructed with different auditory input signals. Secondly, the cross-correlation method is used to slice the signal and construct the adjacency matrix. Louvain community detection algorithm is used to process the data and calculate the network conversion rate under different parameters. It is concluded that the network conversion rate can be used to analyze the temporal variation of auditory information under the condition of controlled parameters. This indicates that the network conversion rate can also be used as a method to analyze auditory signals in the future.
Examination Of Factors Affecting The Utilization Of Information Technology

Data innovation incorporates PC innovation and correspondence innovation used to measure and disperse data, both money related and non-monetary. Interests in data innovation require huge assets and will increment from year to year. The measure of assets gave expects associations to utilize data innovation. The powerful utilization of data innovation should be possible if every person in the association can utilize this innovation. This article gives a clarification of the components that impact the utilization of data innovation by directing a hypothetical report. &#x0D; In view of hypothetical investigations and an audit of the aftereffects of past examination identified with the utilization of data innovation, there are six factors that impact the utilization of data innovation, in particular: social variables, influence factors, multifaceted nature factors, task appropriateness, long haul result factors and encouraging conditions.
Perlustrate Study on Cloud Security and Vulnerabilities

In this modern technology,cloud computing plays an integral role which is also the fastest emerging technology. Cloud computing refers to manipulating,configuring and accessing the applications online. It offers online data storage,infrastructure and application. It is both a combination of software and hardware based computing resources delivered as a network service. High Quality services with improved performance and with reduced cost made the cloud computing a popular paradigm. Cloud computing has numerous advantages to the customer, like its ability to scale and recover from various problems agility and flexibility. As every technology emerges with its own pros and cons cloud computing is vulnerable to certain threats regarding security issues which makes the clients a lack of confidence to adopt cloud technologies. The main reason why companies are leaving the cloud is due to security concerns. Cloud security measures are often inadequate to protect sensitive data. This work aims at presenting a survey of various security issues faced by clients and the necessary measures to counter these threats.
TEACHING WRITING THROUGH PICTURE FOR JUNIOR HIGH SCHOOL STUDENTS

This research was conducted with the aim of finding the usefulness and benefits of picture as a teaching strategy or media of teaching to teach writing skill to the students. The method in this research was classroom action research method, which was carried out in two cycles. Subjects or participants in this study were the students at SMP Negeri 7 Pematangsiantar, precisely the IX-4 students. The researchers collected data from the test results of students on the implementation of picture in writing a text. In addition, the data were also obtained through observation results carried out in the learning process. Based on the results of research that the researchers obtained, it was proven that the use of picture had effects on student learning abilities. Their writing abilities increased after using pictures as medium in writing a text.