Reviewerly/exHarmony huggingface dataset:
Data augmented multi-loss hybrid learning for cross-modality person re-identification

The main challenges are the intra-class differences of person images and the cross-modal differences between visible and infrared images for cross-modal person re-identification. How to reduce the cross-modal differences becomes the key to cross-modal person re-identification. In this paper, we propose a hybrid learning strategy using Cross-Entropy loss and weighted squared triplet loss as identity (ID) loss to solve the intra-modal and inter-modal person identity classification problem, while supervising the network to extract more effective modal shared features to form specific feature descriptors. Besides, for cross-modal person image attributes, a data augmentation method of channel-swapped random erasure is used to improve the robustness of the model to color changes, simulating different degrees of image occlusion, reducing the risk of overfitting and further enriching the image diversity. Experimental results on the public dataset SYSU-MM01 demonstrate the effectiveness of the proposed method, with an average accuracy mAP of 60.08% even in the most difficult full-search single-shot mode.
A Content Analysis of Writing Tasks in English Textbook “Think Globally Act Locally” of Junior High School

The purpose of the study is to explore and describe how well the type of writing task offered in the textbook matches up to the type of writing task proposed by Paul Nation. The study used qualitative research with a content analysis technique. Based on Louis Cohen the study process of data analysis technique through content analysis are follow: Selecting, classification, analyzing, and Inference. To calculate the results of data results, the researcher calculates percentages using Arikunto’s quality categorization schema. The data obtained from the English textbook “Think Globally Act Locally” for Junior High School’s Ninth Grade Depending on the theory that researcher used on English textbook, analysis found three kinds of writing tasks: experience tasks, guided tasks, and independent tasks. However, neither of the writing tasks were completed.supplied by this textbook suit the sorts of shared tasks. The dominant of writing task way found on this English textbook was guided task (51.7%).
A dataflow execution engine for automatic visual inspection of production lines

Automatic visual inspection is used to control the quality of the assembly steps of a product. By allowing the early detection of faults in the production line, it can have a large economic impact. In this work, we propose an execution environment for supporting the development of automatic visual inspection applications and running them in the production line. The applications are described as graphs, which are executed by the engine. Debugging features for use during development and production are provided. Also, the engine provides means to trace the results, such that a fault detected after production could be traced to the cause. Another key aspect is the seemingly integration of external libraries to extend the modeling capacity of the applications. As an example, we describe the integration of the Halcon library and its use in a test case. Our approach accelerates the creation of complex algorithms for visual inspection by eliminating compilation steps and improving the debugging experience.
Blockchain Research and its Significance in the National Technology Initiative

The National Technology Initiative of Türkiye, which it has been putting into action over the past several years, has enabled the country to make significant advancements in domestic production and Türkiye’s momentum in this sector is obvious among nations that are on the same level as Türkiye. The accomplishments in sectors of the national defense industry are particularly noteworthy. However, attempts to increase production on a national and domestic scale were not confined to only one domain; rather, they were dispersed throughout multiple sectors, including health, education, transportation and informatics. Blockchain technology which is now one of the most emerging topics in the context of new technologies has already demonstrated itself as one of Türkiye’s strategic national technological priorities. A large number of works have also been published in Türkiye addressing the significance of blockchain technology, which has found application in various areas of the country’s economy, most notably in the fields of banking, business and information technology. At this point, the importance of a study that will explain the position of the world and Türkiye in the context of blockchain with a comparative scholarly literature growth analysis to be made in Web of Science (WoS) databases has also increased. This chapter examines the R&amp;D and scientific policies of countries from the viewpoint of blockchain research in the context of national and international literature. According to the result of the analyses carried out in the databases of scientific literature, the research and application areas of blockchain technology in Türkiye are comparable to those that exist in developed nations. Moreover, another result of analyses scanning the world’s scientific literature shows that Asian nations have more scientific works pertaining to blockchain technology. The number of applications and patents also filed by companies is the highest in Asia. On the other hand, the universities in Türkiye have recently begun to include coursework on blockchain technology in their programs. In addition, particularly the institutions in the country’s financial and banking system the public institutions and private companies of Türkiye have focused on the country’s national technology initiative and thus technology is continuing to develop on a daily basis. Despite the fact that interest in and utilization of this technology on a sectoral level in Türkiye catch up partially with its global level, it is important to focus more on blockchain technology in terms of resource allocation and prioritization.
Pictogram Prediction in Alternative Communication Boards: a Mapping Study

Alternative communication boards (ACB) are tools that try to compensate for the difficulties faced by people with complex communication needs. Generally, these tools consist of a mobile application in which the user can construct sentences by arranging pictograms (picture+label pair representing a concept) in sequence. This study systematically maps the literature on pictogram prediction in ACBs. We analyzed eight studies to investigate how computational methods are used for pictogram prediction, how these proposals are evaluated, and the studies' outcomes regarding user communication improvement. The main findings indicate the usage of different methods for pictogram prediction and a mixture of automatic and expert evaluation, which lead to inconclusive outcomes regarding user communication improvement.
Edukasi pencegahan konsumsi alkohol pada remaja di SMK Muhammadiyah 3 Singosari Malang

Alcohol use in adolescents needs serious attention because of the negative impact on adolescent health and development. The prevalence of alcohol consumption among adolescents in Indonesia is 3.3% of them starting to drink at the age of 10, and most of them are traditional alcoholic beverages (38.7%). This community service program aims to reduce alcohol consumption among teenagers. There are two activities involved in this community service: education on alcohol prevention and screening of alcohol consumption. We carried the activity at Muhammadiyah 3 Singosari Vocational High School Malang. The participants were 57 students. This activity resulted in an increase in students' understanding of preventing alcohol consumption, with an average before the education of 5.40. In contrast, after being given education, it's score increased to 6.16. Most of the students at SMK do not consume alcohol or are shown in the normal category of 86.9%. However, some still consume 3.3% alcohol in the heavy category. This activity concludes that the provision of education can increase the understanding of adolescents, and then it is hoped that it will prevent alcohol consumption among adolescents. Follow-up efforts from the screening results are carried out by continuing to provide education, counseling, and further diagnostic examinations for adolescents.
An Implementation of Divide and Conquer Clustering Technique for Improving the Interoperability in Hybrid Cloud Environment

Cloud computing provides users with pool of resources ubiquitously on demand. While the resources are provided to the users, interoperability needs to be considered. Interoperability is the ability of the cloud environment to transfer the data internally or between the data centers seamlessly. Interoperability is the least studied issue in the field of cloud computing. This paper implements hybrid cloud as a solution to interoperability. Hybrid cloud is chosen for its powerful combination of high configured and secured private clouds and fast accessible and scalable public clouds. The interoperability is then proposed to be enhanced by implementing divide and conquer algorithm of clustering in hybrid cloud.
Development of Integrated QR Code Module on Physics Learning Module to Increase Learning Interest and Knowing Students' Digital Literacy

A solution for learning in the form of a module integrated with a QR code is offered to assist lecturers in delivering material to students of Physics Education Study Program. With the integrated QR code physics learning module, it is able to increase interest improve students' digital literacy. The method of research is research and development and the analysis was carried out based on the questionnaire data processing. The result shows that the increase of average percentage value of the measurement of interest in learning is 22.24% and the average percentage value of the measurement of digital literacy ability is 80.90%. Based on the results, the conclusions are the integrated QR code on physics learning module is effective to increase interest in learning and students have high digital literacy skills because they are able to take advantage of digital media for the learning process
The Study of an Attendance Confirmation System for KMUTNB Staffs

The study's principal objective is to set up online attendance confirmation templates which can be adapted by all administrative units so that applicable information tailored to the specific needs can be garnered. Based on system analysis and comparison with the traditional mode of attendance confirmation, the online approach can eliminate wasteful spending on office supplies and significantly reduce the amount of staff's working hours. Ongoing trials on the e-RSVP system reveal user satisfaction level, inspiring continuous improvement towards a more effective and consistent application. Recommendations and suggestions are thereby presented for improving the system efficacy. The size of a sample group was 150 recipients, including KMUTNB administrators, faculty, staffs and students as well as all those who had participated in events organized by the University.The result showed that feedback showed positive attitudes towards the system; acquired responses disclosed a highest level. This practical and user-friendly online RSVP platform helps improve workplace efficiency and features its own advantages of the utilization. Appropriate technology adoption within the workplace can ensure the reduction of working time and smooth working process. By the same token, the study exposes a practical strategy for reducing the amount of papers and resource consumption in offices.
NewsIN: A News Summarizer and Analyzer

Abstract: A summary condenses a lengthy document by highlighting salient features. It helps the reader to understand completely just by reading a summary so that the reader can save time and also can decide whether to go through the entire document. Summaries should be shorter than the original article so make sure to select only pertinent information to include the article. The main goal of a newspaper article summary is, the readers to walk away with knowledge on what the newspaper article is all about without the need to read the entire article. This work proposes a news article summarization system which access information from various local online newspapers automatically and summarizes information using heterogeneous articles. To make ad-hoc keyword-based extraction of news articles, the system uses a tailor-made web crawler which crawls the websites for searching relevant articles. Computational Linguistic techniques mainly Triplet Extraction, Semantic Similarity calculation and OPTICS clustering with DBSCAN is used alongside a sentence selection heuristic to generate coherent and cogent summaries irrespective of the number of articles supplied to the engine. The performance evaluation is one using the ROUGE metric. The rapid progresses in digital data acquisition techniques have led to a huge volume of news data available in the news websites. Most of such digital news collections lack summaries. Due to that, online newspaper readers are overloaded with lengthy text documents. Also, it is a tedious task for human beings to generate an abstract for a news event manually since it requires a rigorous analysis of the news documents. An achievable solution tothis problem is condensing the digital news collections and taking out only the essence in the form of an automatically generated summary which allows readers to make effective decisions in less time. The graph based algorithms for text summarization have been proven to be very successful over other methods for producing multi document summaries. The summary generated fromknowledge graphs is more in line with human reading habits and possesses the logic of human reasoning. Due to the fast-growing need of retrieving information in abstract form, we are proposing a novel approach for abstractive news summarization using the knowledge graphs to fulfill the need of having more accurate automatic abstractive news summarization and analyzer
«HOUSE OF THE FREE CHILD» – AN EXPERIMENTAL SOCIAL AND EDUCATIONAL INSTITUTION (1906–1909)

A retrospective analysis of the activity of the «House of the Free child» by Kostiantyn Mykolaiovych Venttsel has been made in the article. It has been found that K. Venttsel founded the House of the Free Child» based on the idea of a pedagogical community where adults and children are equal, where pedagogical communication is cross-pollinated, where every moment of a child’s life is filled with meaning, where punishments, force, fixed timetable are unacceptable, where there is no place for curricula and manuals. The time spent at school was divided into five periods, namely: community service; satisfying children’s curiosity or assisting children in meeting their scientific inquiries; systematic but free production labor; free art classes; a breakfast break, free exercise, children’s games, and more. The cycle of school subjects, their contents, timetable – all these was determined by children themselves and thus became the embodiment of their conscious self-will and expression of desires.
It’s Happy Hour Somewhere: Videoconferencing Guidelines for Traversing Time and Space

Time seems to be moving at lightning speed with busyness unsustainably being “celebrated” and not allowing for sufficiently deep interaction with learning content, others, and the experience of which we are part, including our interactions in videoconferencing sessions. One benefit of videoconferencing is that it can address time and distance boundaries. With this advantage also comes a challenge - the pressures of time and time not being used purposefully often negatively impact the online learning experience and the digital wellness of its participants. Considering that, the reported study inquired: what are the videoconferencing guidelines in relation to temporal space to support digital wellness in online learning in higher education? Drawing on a systematic review of the relevant literature of the last decade, temporal guidelines have been distilled to promote the design of videoconferencing-based learning that is conducive to successful learning while maintaining digital well-being. The article organizes the literature review findings according to the categories identified through the secondary data analysis of its three preceding studies. Based upon 42 articles that met the inclusion and exclusion criteria in the first phase of the research design, we negotiated and determined thirteen temporal guideline themes described as time management, essentialism, purposefulness, agility, social presence, attention, inclusion, cooperation, respect, technology preparedness, creativity, evaluation, and safety. Further research is recommended to explore the various aspects of design in more depth and tackle the less frequently addressed themes of creativity, evaluation, and safety, focusing on pedagogy and human-centred approaches.
A General Evaluation on the Piano Works of the Soviet Composer Dmitry Kabalevsky for Children and the Sample of the Piano Album “Thirty Pieces for Kids Op.27”

While it is aimed to form basic behaviors for students in piano education, it is important to develop piano playing skills in a way that will attract the attention of children, with materials suitable for the individual characteristics, age group, perception level, and level of the students.Therefore, it is necessary to choose a balanced and correct repertoire suitable for the level of the student.Choosing the appropriate repertoire is about a careful balancing of skills, physical competence, musical interest, pedagogical value, and the student's emotional maturity.There are many works written for this purpose in our country and the world.In this context, this study aims to examine the place of the piano album "30 pieces for children Op.27" in piano education by making a general evaluation on the piano works for children by Kabalevsky, who has made great contributions to piano education as a composer and educator.The research is a qualitative study and the relevant literature was examined through document analysis and Kabalevsky's piano albums for children, which are used in piano education, were reached.In addition, the composer's piano album "30 pieces for children Op.27" was examined and interpreted in terms of content and technical studies.As a result of the study, Kabalevsky's piano works for children in terms of gaining the behaviors that form the basis of piano education were evaluated and suggestions that could guide piano educators were tried to be developed.Furthermore, it is thought that these works will contribute to the use of piano education, to the introduction of the works, and to diversify the educational repertoire.
A proof-of-concept meaning discrimination experiment to compile a word-in-context dataset for adjectives – A graph-based distributional approach

Abstract The Word-in-Context corpus, which forms part of the SuperGLUE benchmark dataset, focuses on a specific sense disambiguation task: it has to be decided whether two occurrences of a given target word in two different contexts convey the same meaning or not. Unfortunately, the WiC database exhibits a relatively low consistency in terms of inter-annotator agreement, which implies that the meaning discrimination task is not well defined even for humans. The present paper aims at tackling this problem through anchoring semantic information to observable surface data. For doing so, we have experimented with a graph-based distributional approach, where both sparse and dense adjectival vector representations served as input. According to our expectations the algorithm is able to anchor the semantic information to contextual data, and therefore it is able to provide clear and explicit criteria as to when the same meaning should be assigned to the occurrences. Moreover, since this method does not rely on any external knowledge base, it should be suitable for any low- or medium-resourced language.
DEVELOPMENT OF ONLINE INTERACTIVE LEARNING MEDIA USING GeoGebra APPLET ON PROBABILITY

This study is intended to determine the feasibility of online interactive learning media using the Geogebra Applet on the probability material developed. The use of the model in this development research is the ADDIE (Analysis, Design, Development, Implementation, Evaluation) model. The research subjects included mathematics teachers and class VIII B students of Gema Nurani Integrated Islamic Junior High School. The data collection technique used was observation in the form of needs analysis and interviews and questionnaires. The results of the study were obtained based on the percentage of validity test scores by two expert validators including material experts and media experts as well as a questionnaire response from mathematics teachers and students to obtain the feasibility of the developed learning media. Based on the results of the assessment by the material expert validator, the percentage is 94.64% in the very appropriate category and media experts at 73.08% in the appropriate category. While the results of the feasibility of the mathematics teacher response questionnaire showed a percentage of 92.5% with a very decent category and a student response questionnaire of 88.04% with a very decent category. Thus, the use of the Geogebra Applet in the probability material is very feasible to be applied as an online interactive learning medium in class VIII.
A Deep Transfer Learning Based Visual Complexity Evaluation Approach to Mobile User Interfaces

Visual complexity is an important factor affecting the efficiency and functionality of user interfaces. Its impact on the user's impression and the usability is significant, especially for mobile applications with constraints such as layout size, on screen keys and small input fields. Conventional approaches for visual complexity evaluation of user interfaces are either based on user evaluations with surveys or based on pre-specified formal metrics or on heuristics. Alternatively, in this study, we have explored the effectiveness of deep learning models for visual complexity evaluation, specifically, of mobile user interfaces. We have experimented with five state of the art pre-trained deep learning models known to be effective for computer vision tasks, namely, VGG16, DenseNet121, MobileNetv2, GoogleNet and ResNet152 were trained with 3635 different mobile user interface images as login, menu, search and settings. Furthermore, in order to validate the effectiveness of this approach, a new validation dataset and survey application was developed and an evaluation study was conducted with 98 participants where 7309 comparison result were obtained from the study. It was found that the agreement rate between the results of deep learning models and the user evaluations was up to 78% and 74% on the average. The high to moderate agreement rate between the results of deep learning models and the user evaluations reveals that this approach can be useful for designers in visual complexity evaluation of mobile user interfaces.