Reviewerly/exHarmony huggingface dataset:
SiamUT: Siamese Unsymmetrical Transformer-like Tracking

Siamese networks have proven to be suitable for many computer vision tasks, including single object tracking. These trackers leverage the siamese structure to benefit from feature cross-correlation, which measures the similarity between a target template and the corresponding search region. However, the linear nature of the correlation operation leads to the loss of important semantic information and may result in suboptimal performance when faced with complex background interference or significant object deformations. In this paper, we introduce the Transformer structure, which has been successful in vision tasks, to enhance the siamese network’s performance in challenging conditions. By incorporating self-attention and cross-attention mechanisms, we modify the original Transformer into an asymmetrical version that can focus on different regions of the feature map. This transformer-like fusion network enables more efficient and effective fusion procedures. Additionally, we introduce a two-layer output structure with decoupling prediction heads, improved loss functions, and window penalty post-processing. This design enhances the performance of both the classification and the regression branches. Extensive experiments conducted on large public datasets such as LaSOT, GOT-10k, and TrackingNet demonstrate that our proposed SiamUT tracker achieves state-of-the-art precision performance on most benchmark datasets.
Using a Video Project to Enhance Students’ Speaking Ability

Speaking is a skill often considered the benchmark of student’s success in learning English. Many studies have been conducted to examine the approaches, methods, and media that work best in improving the students’ speaking ability. One of the methods that can be used in teaching speaking is making a video project. This paper aims to find out how using a video project enhances the students’ speaking ability. This study was conducted using a descriptive method, taking the students at senior high schools in Medan as the participants. The data were collected using an observation method. The data were analyzed to show how a video project was used in teaching speaking and how it enhances the students’ speaking ability. The results indicate that using a video project in teaching speaking motivates the students to show their best speaking performance, eliminates their shyness and inhibition in speaking, and improves the students’ speaking fluency in English. Thus, the results recommend the use of a video project as a good method in teaching speaking English to senior high school students.
STRATEGI GURU DALAM MENGATASI ANAK DISLEKSIA KELAS 3 DI SDN 31 CAKRANEGARA

Dyslexia is a learning disorder that affects a person's ability to read, spell and write. This disorder is not related to intelligence problems or visual deficiencies, but is caused by difficulties in processing and understanding letters, words and written symbols. This study aims to explore the strategies used by teachers in overcoming dyslexic children in grade 3 of SDN 31 Cakranegara. The research method used is qualitative method with descriptive type. The researcher observed and interviewed a grade 3 teacher who has experience in teaching dyslexic children. The results showed that teachers used strategies in overcoming dyslexic children in grade 3, namely learning material adjustment strategies, multisensory approaches, individualized support, and collaboration with parents.
Higher Education in a Digital Era through Project-based E-learning: Contributes of the RESTART4EDU Project

Higher education has received increasing attention from researchers due to a marked growth and differentiation over the last forty years. Recent data (Eurydice, 2020) show that the student population in higher education is mostly female, except in Germany, Greece and Liechtenstein, and there is a higher number of men attending Bachelor’s degrees, while women are attending Master’s degrees. Considering this higher education institutions cannot be, therefore, indifferent to these changes in their student population. Although these changes, especially the exponential increase of students, are the result of an advance in terms of democratic educational policies, and search for lifelong learning opportunities that better prepare individuals for an unstable and competitive labor market (Hirschi, 2018). At the same time, they are associated with increased difficulties since higher education institutions have presented many difficulties in promoting a renewed and innovative teaching and learning process that should be focused on the students. These difficulties have been leading to consequences such as the increase of academic failure, particularly at the level of the academic transition year, change of course or academic dropping out (Azevedo &amp; Faria, 2001). The studies that have been dealing with these issues present a multivariate set of conditions associated both with the context of the study cycle (particularly related to the teaching process, the reception of students and, also, the pedagogical relationship) and with the psychosocial characteristics of young adults who have been undergoing changes in their developmental indicators, which translate into academic experiences, expectations, learning methods, social support network and academic preparation.
Deep Learning-based Segmentation and Computer Vision-based Ultrasound Imagery Techniques

Biomedical imaging has been a game-changer in the medical field because of how it facilitates the analysis of human body issues. The best possible diagnosis may now be made thanks to the development of computer science and its integration with medical imaging. The state-of-the-art in biological image processing has been demonstrated by methods based on deep learning. Thanks to these approaches' inherent capacity for self-learning, manually constructed features are no longer necessary. It has given a world-class solution with trustworthy outcomes for medical image processing in this way. This effort is being done to help with better diagnosis by addressing the key challenges mentioned above. These approaches' inherent capacity for self-learning has rendered custom enhancements superfluous. This has supplied an excellent solution with trustworthy outcomes in the field of medical image processing. In order to better diagnose health problems, the current effort is conducted to solve the aforementioned key challenges. Therefore, the study aims to create novel segmentation and classification methods for identifying the different types of breast masses from US pictures. The elastic characteristics of tissues can now be imaged thanks to a novel method called elastography. In our studies, we use ultrasound elastography as well as ultrasound B-mode to categorise breast tumours.
PERFORMANCE EVALUATION OF DNA PATTERN MATCHING ALGORITHMS

Bioinformatics is a new area of research in which DNA, RNA and proteinssequences are dealt. To store, retrieve, analyze, match, align, search, and process these sequencesdifferent techniques are existed. Currently a lot of advancements in sequence analysis cause the drasticincrease in the DNA database sizes that require more efficient approaches encompass accuracy. Searchand analysis of DNA patterns can be performed by using various pattern matching algorithms in thecomputational biology. The aim of present study is to present taxonomy and performance evaluation ofthese pattern matching algorithms. The objective of this SLR is to set a research trend and to find amathematical model to estimate execution search time before scanning whole DNA sequence byfollowing a search strategy.
Neural Architecture Search: Practical Key Considerations

The rapid development of deep neural networks has highlighted the importance of research in this domain. Neural Architecture Search (NAS) has emerged as a pivotal technique for automating and optimizing neural network designs. However, due to the complex and evolving nature of this field, staying up to date with the latest research, trends, and best practices is challenging. This article addresses the need for practical considerations, best practices, and open frameworks to guide practitioners in NAS endeavors. It discusses key considerations, challenges, opportunities, and open problems, along with a compilation of best practices and open frameworks. Readers will gain a practical guide for developing, testing, or applying NAS techniques.
Job Evaluation for Production Roles with Fuzzy Cognitive Map: An Empirical Study in the Manufacturing Industry

Job evaluation is a critical process in organizations, particularly in the manufacturing industry, where production roles play a vital role in overall operational success.Traditional job evaluation methods often rely on subjective judgments and can be prone to bias.This study considered the application of Fuzzy Cognitive Maps (FCMs) as a novel approach to job evaluation in the manufacturing industry.FCMs provide a framework to capture and represent the complex relationships and interdependencies between various job attributes and their impact on overall job performance.The objective of this empirical study is to demonstrate the effectiveness of FCMs in job evaluation for production roles in the manufacturing industry.The collected data will be used to construct FCMs, where nodes represent job attributes (e.g., technical skills, communication, problemsolving) and edges capture the strength and direction of relationships between attributes.The FCMs will be validated and calibrated using statistical techniques, ensuring their reliability and accuracy.The final evaluation framework will provide a quantitative method for assessing the relative importance of job attributes and determining the overall value of production roles within the organization.
Kursi sebagai Simbol Transisi Dampak Negatif Kehidupan Manusia pada Karya Seni Patung Kontemporer

The journey of life that humans go through is a long journey, full of twists and turns and through stages that will surely become a process of growth and development from time to time. Because there are negative things, the impact on his life is caused by individual, family, environmental, social, cultural, political, educational and other factors. In the embodiment of the work, the chair is used as a symbol of the negative impacts that occur on human life starting from the infant phase to the elderly. There are several stages carried out in accordance with the method used in making the work, namely: preparation is observing the environment and preparing the tools and materials used in the work, Elaboration is the manufacturing stage that solidifies the main ideas related to the title, Synthetic is the sketching stage, Relations The concept is the stage of the work process and completion is the final stage in the work. Description of the work consisting of 7 works where each work is given a different title, namely: (1) infancy, (2) childhood, (3) childhood, (4) adolescence, (5) childhood young adults, (6) old adults, and (10) elderly people. The work will be exhibited for 2 days, and carry out the recording, as well as the production report.
Image Enhancement using Local Histogram Matching with Normal Distribution

Image enhancement aims at improving the quality of an image for better visualization. Histogram equalization (HE) is an image enhancement technique based on image histogram modification and this algorithm flats the given image histogram and produces better result on the global scale but the HE technique shifts the mean brightness of original image. Rather than flattening the given histogram, matching the given image with some specified distribution might help to resolve the issue. However, when the goal is to extract information on the local scale, local enhancement techniques, e.g. local HE (LHE), contrast limited adaptive HE (CLAHE), are required. Although the local histogram modification techniques manage to extract local information, however, compromises the visual quality (e.g. over enhancement, shifts in mean brightness, etc.) of the image. In this paper, a novel technique called Local Histogram Matching with Normal Distribution (LHMND), is proposed to extract local information and enhance the image quality by taking advantage of the Normal histogram matching on the local scale. Experiment shows that our proposed method performs better in terms of preserving the mean brightness and contrast enhancement to some extent, in comparison with the relevant HE techniques, e.g. HE, LHE, and CLAHE.
Risk Factors of Malaria Infection among School-Aged Children in Rural-Urban Areas, Taraba State, Nigeria

Introduction: Malaria is a mosquito born infectious disease of human and other animals caused by parasitic protozoans belonging to the genus Plasmodium. Malaria parasite among school aged children is a disease that poses a great challenge to human health in Nigeria. Malaria contributes significantly to the burden of disease especially among children less than five years. Efforts aimed in controlling malaria, prevalence is still high.&#x0D; Study Design: This study was designed to investigate the risk factor associated with malaria infection among school aged children in Jalingo and Sardauna LGAs of Taraba State, Nigeria.&#x0D; Place and Duration of Study: Urban-Rural areas (Jalingo ans Sardauna LGA Taraba State Nigria), studied from July-December 2022.&#x0D; Methodology: Structured questionnaire was used to obtain demographic information and Microscopy was also used to determine Parasitaemia level among the school aged children (2-15years). A total of 1000 children less than 15 years old from ten (10) selected communities of the study areas whose parent or guardian gives consent were selected.&#x0D; Results: The results revealed that out of the 1000 subjects, 359(35.9%) were infected with malaria parasites. Ages between 2-5 year were found to have the highest prevalence of 212(21.2%) while age 11-15 group had least prevalence of 21(2.1%). The overall prevalence of malaria parasite was moderate among the study population. This is probably due to the seasonal variation in malaria parasite intensity and the good knowledge of caregivers on malaria infection and management.&#x0D; Conclusion: There is therefore the need to sustain the current media and health facility-based campaigns on malaria prevention strategy and maintenance of clean environmental condition.
Analisis Sentimen Pada Ulasan Pelayanan Suku Dinas Kependudukan Dan Pencatatan Sipil Kota Administrasi Jakarta Barat Menggunakan Algoritme K-Nearest Neighbor

Population administration plays an important role in Indonesia as it is involved in various activities. At the regional government level, the Population and Civil Registration Office is responsible for these matters. In West Jakarta, the Sub-district Population and Civil Registration Office is a government body that handles the technical aspects of population administration. Based on data from 2020, the population in West Jakarta reached 2,434,511 people. This office is responsible for providing services to the community, which involves various responses and opinions from the public. Some opinions are positive and constructive, while others may be dissatisfied with the services provided or have unmet expectations. This research aims to analyze public perspectives on the administration services of the Sub-district Population and Civil Registration Office in West Jakarta using machine learning approach, specifically the CountVectorizer feature extraction and K-Nearest Neighbor algorithm. The dataset used is sourced from an online form accessible by society. The analysis results from 386 reviews show that there are 311 (80.57%) positive reviews and 75 (19.43%) negative reviews, with the best testing performed using a K value of 3, achieving an accuracy rate of 83%, precision of 82%, and recall of 100%.
Pelatihan Pembuatan Media Pembelajaran Berbasis Mobile Bagi Guru SMP

The development of information technology has now affected various aspects of life, including the world of education. An educator is required to be able to follow and apply technology along with the times in the teaching and learning process. The application of this technology can be used in mobile-based learning media, as a solution so that the material delivered by educators looks more attractive. Thus, community service activities were carried out in the form of training in making mobile-based learning media for junior high school teachers. This activity aims to improve the ability of educators to create mobile-based learning media. The training activities were attended by 40 science teachers from the Cisompet sub-district. The training is carried out in stages, namely 1) preparation; 2) material exposure; 3) making learning media by participants; 4) task collection; and 5) evaluation. The results of the participants' responses to this training activity were positive. From the questionnaire distributed to the participants, 90.3% stated that the training material was very good and useful for the participants.
Aplikasi Smart Inventory System Menggunakan Framework CodeIgniter di Toko Sumber Barokah Kraksaan

Sumber Barokah Kraksaan store sells various types of staples as well as other household needs. However, currently Sumber Barokah Stores do not yet use a computerized system so that managing stock and sales data takes a long time, as well as financial reports that are sometimes felt to be inaccurate to store owners because they still use conventional methods, namely recording in books. Shop owners often make mistakes in recording goods that have been sold, resulting in errors when ordering the next item, which results in excess stock and costs of procuring the wrong goods, causing losses for the shop owner. Monitoring goods data automatically using the ROP and ROQ methods. The research method used is the Research and Development method and the system development model uses the Prototype method. The resulting application can make it easier for store owners to monitor goods and inventory, and also make it easier to find out the results of income reporting analysis at Sumber Barokah stores, as well as make it easier for shop owners to transact with customers.
Investigative Study for Identification &amp; Categorization of Leukaemia Cell

Leukaemia is a deadly disease based on cancer that affects people of all ages, involving young children, adults and is a leading cause of death worldwide. It is directly associated to White Blood Cells (WBC). This is followed by an increase in the quantity of immature cells and causes bone marrow and blood damage. As the result, a timely and accurate cancer diagnosis is important for successful therapy to improve survival chances. Currently, to diagnose this condition, a manual examination of blood samples collected using microscopic pictures is performed, which is typically very slow, time-consuming and inaccurate. Furthermore, in the microscopic investigation of leukemic cells look and form structures extremely similar to normal cells making identification more challenging. Deep learning using Convolutional Neural Networks (CNN) has given state-of-the-art methodologies for image categorization challenges in recent decades, yet there is still room for improvement in terms of efficacy, learning technique and performance. In this research survey we compare and study different available approaches for leukaemia detection including machine learning and deep-learning techniques. As a result, in this research investigation, we aim to develop a novel deep-learning algorithm variation to detect leukaemia illness by examining microscopic pictures of blood samples.
A universal model for higher professional education: The case of educational psychologists training

Introduction. The article puts forward ideas of higher education modernization which is needed in order to adjust Russia’s education system to the current situation in society. Market economy that emerged in Russia 30 years ago was not effectively integrated into university management practices which were developed based on the socialist model. As a result, Russia’s university education deteriorated, as it became a hybrid of the Soviet and the Bologna education systems, borrowing the most negative features from both of them. The incompatibility of these systems led to bureaucratization and blocking of teachers’ initiatives and teachers’ potential, as well as to rejection of scientific foundations which used to underpin the design of higher education programs. Scientific studies of changes in qualification requirements for different professions are being replaced by a quasi-scientific competency-based approach. Materials and Methods. The article identifies the problems which should be solved in order to foster the production of relevant knowledge and train those who carry this knowledge (i. e., fully educated professionals), which is the main factor of socio-economic development of society. Results. The article considers the key problems of four basic models that make up the universal construct of higher professional education: a) the economic model of education—which reveals the directions of education system modernization in universities as subjects of changed economic relations; b) the cognitive model of knowledge integration—which describes levels of knowledge integration and conditions for their implementation in education; c) the step-by-step model of educational process—which characterizes the stages of fundamental, applied and practical training; d) the qualification model of specialists—which suggests the introduction of professional ranks system. The proposed ideas are illustrated based on educational psychologists training. Conclusions. The proposed ideas can be considered as a sketch for the project of professional education at a new stage of modernizing the system which is aimed at reproducing the intellectual potential of social development and forming an individual as a subject of professional activity.
Corrigendum

In the published article [Distribution Alignment Using Complement Entropy Objective and Adaptive Consensus-Based Label Refinement for Partial Domain Adaptation], there was an error in the Data Availability statement. The following corrections should be noted: In the section 4.2. “Parameters λ and η, which regulate the learning from adaptive complement entropy objective, are set to 1, 8,and 0.3, 1 for Office-31 and Office-Home, respectively.” should be “ Parameters λ and η, which regulate the learning from adaptive complement entropy objective, are set to 0.7, 8, and 0.3, 1 for Office-31 and Office-Home, respectively.” and the setting valuable of Table 1 for parameters λ should be 0.7; In Table 5 the mean accuracy for different values of parameters λ on Office-31 should be 96.63, 96.98, 97.07, 97.19, 97.25, 96.71 and 96.31 respectively. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. Reference Choudhuri, S., Adeniye, S., &amp; Sen, A. (2023). Distribution Alignment Using Complement Entropy Objective and Adaptive ConsensusBased Label Refinement For Partial Domain Adaptation. Artificial Intelligence and Applications, 1(1), 43–51. https://doi.org/10. 47852/bonviewAIA2202524