Reviewerly/exHarmony huggingface dataset:
TFAtrack: Temporal Feature Aggregation for UAV Tracking and a Unified Benchmark

Research on object detection and tracking has achieved remarkable progress in recent years. Due to the superior viewing angle and maneuverability advantages of unmanned aerial vehicles (UAVs), the application of UAV-based tracking is also undergoing rapid development. But since the targets captured by UAVs are tiny and all have similarities and low recognition, this leads to the great challenge of multiple-object tracking (MOT). To solve the two problems mentioned above, We propose TFATracking, a comprehensive framework that fully exploits temporal context for UAV tracking. To further reflect the effectiveness of the algorithm and promote the development of UAV object tracking, we present a large-scale, high-diversity benchmark for short-term UAV multi-object tracking named T2UAV in this work. It contains 20 UAV-captured video sequences with a total number of frames over 12k and an average video length of over 600 frames. We conduct a comprehensive performance evaluation of 8 MOT algorithms on the dataset and present a detailed analysis. We will release the dataset for free academic use.
Should teachers be agile Postulating the self-determination theory

This paper aims to bridge the gap of literature in workforce agility among employees in educational institutions, postulating on Self-Determination Theory by examining the relationship between digital competence, employee empowerment, knowledge sharing, social media usage and workforce agility. Further, the moderating effect of social media usage is also investigated. Findings based on the data collected from 217 respondents using PLS-SEM showed all exogenous constructs are significant, however the moderating analysis proved otherwise. It can be inferred that age, years of working experience, generations gaps and also egocentrism attributed to the findings. The outcomes of this work would assist policymakers and school administrators in Malaysia to facilitate and promote an agile workforce in educational organisations besides manifesting motivation in employees, in achieving the goals of the third wave of transformation in MEB 2013-2025. This paper also concludes that future studies should employ IPMA and also PLS-MGA for further in-depth analysis.
Professionalism of Government Agency Information Service and Management Officers

The government issued a policy of Law no. 14 of 2008 concerning Public Information Disclosure.It aims to create good governance, especially in the transparency of state administration.However, there are many government agencies that have not carried out these regulatory instructions.This unpreparedness can be seen from various factors, including human resources who do not understand the substance of the contents of the law, the limited number of staff and education to the public about the practice of public information disclosure.The implementation of public information disclosure is managed by the Communication and Information Office of Central Java Province as the Main Information Management and Documentation Officer, assisted by the Information Management and Documentation Officer at the Regional Apparatus Organization level as an Assistant Officer.The Department of Communication and Information Technology of Central Java Province has a strategic role as the coordinator of the implementation of public information disclosure, as well as carrying out an evaluation role on the performance of information and documentation managers at the auxiliary level.
Virtual Currency Societal Impact Today: Mitigate the Risks through Regulatory Framework

Virtual currency has been at the heart of debates for a long time.The difficulty comes from the fact that being electronic, it is elusive and states have not finished thinking about the best way to limit its risks on the economy in general.Basis of capital outflow and presenting an open risk to the fight against money laundering, virtual currency is subject to regulation by countries.While some have clear-cut legislation, others are still struggling to find an adequate legal framework.Meantime, initiatives are well underway.Whether national laws are important to reduce the risks of virtual currency, cooperation between states is just as relevant.This work reviews the risks of the use of virtual currency in society, provides an overview of national legislation and international initiatives in adopting rules on the matter before making recommendations.
Distributed multi-user QoS-aware service selection

Previous research on service selection in cloud environments often assumes a centralised broker that keeps track of all candidate services and selects the appropriate candidate for each user request based on quality of service (QoS). As the number of users and services increases, the centralised service selection algorithm becomes a bottleneck. We propose a distributed, multi-broker selection algorithm that enables real-time processing of a large number of user requests. Each broker keeps track of a subset of users and a subset of service candidates, and rebalancing is performed to ensure that no broker is overloaded. The selection procedure considers the user QoS requirements, service QoS values and their processing capacities. Simulations demonstrate a clear advantage of the proposed approach over a single-broker approach by up to 96% in terms of QoS satisfaction when using 100 brokers, and especially in terms of response time satisfaction, showing positive impact of user and service balancing, and analysing various selection algorithms run by the brokers.
TRENDS IN THE DEVELOPMENT OF STUDENTS 'INDEPENDENT SCIENTIFIC WORK IN THE ACTIVITIES OF SCIENTIFIC SOCIETIES AND CIRCLES: 1905–1916

Introduction. At the end of the XIX – beginning. XX century scientific traditions in the national university education were supported and further developed, which were actualized in the activity of scientific societies, circles, public organizations. It is necessary to emphasize the interdependence of socio-political events in the country and the diversity of activities and goals of clubs, societies, which accordingly forced the Ministry of Education to raise the issue of intensification and expansion of independent scientific work of students. The activity of scientific societies, circles, and, accordingly, the independent scientific work of students of this period was due to the introduction of government circulars. Purpose. The purpose of the study: to reveal and update the features and trends of further development of scientific traditions in university education, which were relevant in the activities of scientific societies, circles, organizations (1905–1916). Methods. To achieve the goal of the scientific article, the integration of methods was used: chronological-systemic – aimed at revealing trends in the development of independent work in higher education as a didactic category; personifiedbibliographic – for the analysis of epistolary heritage, the contribution of pedagogical personalities in the development of the problem; historical-diachronic – for scientific substantiation of the genesis and evolution of the content of independent work of students in the educational process of higher educational institutions of a certain period. Results. Independent scientific work of a student of higher education of Ukraine in the period under study was carried out in extracurricular activities (literary, scientific circles and societies; educational events, art competitions, scholarship competitions, medal tasks), aimed at educating students' amateur personality, skills for independent activity in life, etc. Originality. The results of the research confirm that the voluntary participation of students in scientific societies and circles, organizations contributed to the conscious fulfillment of statutory requirements, development of selfawareness of the importance of self-acquired knowledge, self-improvement to achieve goals and the need for individual collective decision-making. Conclusion. Historical and diachronic analysis suggests the need for further research on the historical and pedagogical origins of the formation and evolution of the content of independent work, transformation of its types and forms of performance with value-motivational orientation of the student in a modern higher education institution.
Attention-based Neighbor Selective Aggregation Network for Camouflaged Object Detection

Camouflaged Object Detection (COD) aims to discover objects that are finely disguised in the environment. Its challenge is that the targets generally have similar textures and colors to their surroundings. In this paper, we propose a novel network, named attention-based neighbor selective aggregation network (ANSA-Net), which can effectively and efficiently detect camouflaged objects. Specifically, our ANSA-Net contains two novel modules, namely, neighbor selective aggregation (NSA) and high-level feature guided attention (HLGA). The NSA is designed to locate concealed targets by fusing multi-scale features adaptively. Furthermore, the HLGA is designed to improve the semantic information of features by employing attention maps derived from high-level features. Experiments show that ANSA-Net exhibits relatively accurate detection performance on four COD datasets, outperforming existing state-of-the-art methods.
An exploratory study of analyzing JavaScript online code clones

Online code clones occur due to reusing code snippets in software repositories from online resources such as GitHub and Stack Overflow. Previous works have shown that snippets from Stack Overflow are reused in other open-source projects and vice versa. Analysis of online code reusing patterns could identify outdated code, understand developers' practices, and help to design new code search engines. This study analyzed JavaScript online code clones between Stack Overflow and GitHub repositories. We first developed a JavaScript code corpus to search online clones. The clone search results reported 12,579 online clones between 276,547 non-trivial syntactically validated Stack Overflow snippets and 292 GitHub repositories. We manually classified the top 10% (1257) pairs of clones in seven online clone patterns. We observed that around 70% of JavaScript snippets in Stack Overflow posts are copied from GitHub repositories or from other external sources. Moreover, only 30.59% of JavaScript Snippets in Stack Overflow accepted answers could be considered as reusable snippets.
Analisis Hambatan Dalam Perkuliahan E-Learning Berbasis Android Di Prodi Tadris Matematika Pada Pandemi Covid-19

The purpose of the study was to determine the process, obstacles (internal and external) and efforts to overcome obstacles to android-based E-Learning lectures in the TMM Study Program during the Covid-19 pandemic. This type of descriptive qualitative research. Data collection technique; Observation, interview and documentation. The research subjects were lecturers and students (16 people) who took the Differential Calculus course. Data analysis techniques: data reduction, data presentation and conclusion drawing. The results showed that the E-Learning lecture process used the WhatsApp Group and Google Classroom applications. Barriers to E-Learning lectures, namely, internal factors (1) student health conditions. (2) learning equipment or learning media that are incomplete. Barriers from external factors, (1) the implementation time of the learning process that is less disciplined. (2) the surrounding environment is not conducive. (3) students' motivation and interest in learning are lacking because lectures are individual. Efforts to overcome obstacles to E-Learning lectures, namely: quota assistance from the government; Lectures using Zoom and Google Meet; The internet network is evenly distributed in every area; Increase self-motivation and interest; Presentation of concise material in the form of video; Discipline in college time; using web-based E-Learning; based learning; The assignment is in the form of making videos to practice creativity and presentations to see student activity and creativity.
Study on a Shooting Device to Support a Wire-Driven Bridge Inspection Robot

In recent years, the deterioration of many bridges built during the period of rapid economic growth has become a problem. As a solution of it, preventive measures such as visual inspections and repairs by humans have been taken, but these methods have problems in terms of cost and safety. If inspection by robots becomes possible, both of these problems will be improved and it is expected to contribute greatly to the maintenance and management of bridges. Therefore, a number of robots have been developed for the purpose of bridge inspection. The among such inspection robots, wire-driven robots, which have less risk of falling and can perform close proximity or contact inspection, are attracting attention. However, one of the problems with this type of robot is that it is difficult to place the wire under the bridge when there is a river or road underneath it, or when it is very high. Thus, in this study, a shooting device for shooting arrows with attached strings was developed to solve this problem. We then conducted a shooting experiment and confirmed that the device aimed at the target automatically and shot the arrow. In addition, we created a simulation model of an arrow with a string attached to it to obtain information such as the shooting angle of the arrow in advance. Then, the flight trajectory and horizontal flight distance of the arrows were compared between the actual and simulated data, and the consistency was confirmed.
Patch-based CNN model for 360 image quality assessment with adaptive pooling strategies

Patch-based training for 360-degree images allows to significantly reduce the complexity compared to multichannel models while maintaining good performances.Differently from multichannel models where multi neural networks are trained in parallel to predict the score of the whole 360-degree image, a pooling stage is required to map local qualities to the global one.This step is often neglected by using a simple arithmetic mean, which does not account for (i) the non-uniformity distribution of quality and (ii) the variability among local qualities.In this paper, we analyze several pooling strategies, including basic statistic methods and adaptive pooling ones.Additionally, we propose a pooling strategy based on scene exploration behavior relying on visual scan-path.The performance analysis showed the benefit of using adaptive pooling over arithmetic mean, as well as the incorporation of perceptual properties during the pooling stage.Besides, the comparison with state-of-the-art multichannel models asserts the effectiveness of patch-based training compared to multichannel models.
Modelling different aspects of final exam scheduling problems for a graph-based state space reduction method

Final exam scheduling is a subtopic of scheduling where various special requirements with different levels of strictness should be managed. The formalisation of these requirements can be a challenge in itself. The number of possible schedules that should be examined is usually large, so the state space is vast. However, many of these schedules can be excluded completely at an early stage based on their inconsistency with the hard requirements, thus reducing the state space. The modelling approach for different aspects of final exam scheduling problems is presented in this paper through the modelling of an actual, complex problem. The created model was used as the basis for a state space reduction method. The results show that the method could handle all the hard and soft constraints of the problem and reduce the state space significantly based on them. The modelling approach can be used for formalising the requirements of various final exam scheduling and similar problems.
Infrastructure Capability Aggregation and Exposure in Cloud Environments

In today’s large-scale distributed cloud environments, there are usually multiple layers involved when performing orchestration. It is important to decide what capability is visible at a specific physical location in the different layers of abstraction. Considering the diversity and heterogeneity of the infrastructure, it is critical to decide how data centers/clusters aggregate and expose their capabilities to the user to be accessible from the orchestration environment. In this paper, we propose a capability aggregation and exposure method. The proposed method relies on the detailed information of the underlying resource which can be extracted using OS built-in tools. It then aggregates and exposes this information using different algorithms. Our proposed method has many advantages such as applicability and flexibility. We evaluated the performance of the different algorithms and demonstrated the one that has the best performance.
The Effect of Snowball Throwing Model on The Student’s Vocabulary Mastery at SMA Swasta Rakyat Pancur Batu

The objective of the research is to find out the effect of applying snowball throwing on the student’s vocabulary mastery of SMA Swasta Rakyat Pancur Batu at tenth grade academic year 2021/2022. This research was used experimental research. The population were 40 students of two classes. The researcher using class X IPA 1 and X IPA 2 as the sample. Class X IPA 1 as the experimental group and X IPA 2 as the control group. The experimental group was taught and treatment by snowball throwing and control group without snowball throwing model. The instrument used to collect data in this research was test there are pre-test and post-test. The researcher found that there was a significant difference between the students‟ score in experimental group and control group. It was known by the mean score of the post-test in experimental group was higher than mean score of post-test in control group. The value of the t-observed 9.26 was higher than t-table 1.68 at the level of significant 0.05 with degree of freedom (df)=40. Based on the result of this research, the The researcher found that there are the significant effect of applying snowball throwing on the student’s vocabulary mastery of SMA Swasta Rakyat Pancur Batu at tenth grade.
American Sign Language Recognition Based on Machine Learning and Neural Network

Numerous disabilities such as deaf and mute are suffered from not being capable of communicating with normal people, it is necessary to find a way to solve this problem. A feasible method is Sign Language Recognition (SLR) which is a sort of pattern recognition technique. In this paper, machine learning and deep learning methods are applied to recognize and classify American Sign Language (ASL), and only 24 English letters are classified because letter J and Z require fingers to move. First, Principal Component Analysis (PCA) and manifold algorithms are used to do dimension reduction to accelerate the training of machine learning and visualize it. Second, various machine learning methods such as Random Forest Classification (RFC), K-Nearest Neighbor (KNN), Gaussian Naïve Bayes (GNB), Support Vector Machine (SVM), and Stochastic Gradient Descent (SGD) are applied to classify the pattern. Since the SVM algorithm has several hyperparameters, this study uses the Grid Search method to find the best combination of hyperparameter which lead to predicting more accurately. It is found that different dimensionality reduction algorithms have unequal effects on the accuracy of each prediction model, and it can be concluded that the manifold algorithm is the best dimension reduction algorithm only for KNN but not for other prediction models, and PCA is much more feasible than KNN applied in such machine learning algorithms except KNN. Two deep learning algorithms such as Convolutional Neural Networks (CNN) and Deep Neural Networks (DNN) are also used in classification and their accuracy is highest among such algorithms mentioned above.
Analisis Ungkapan Idiomatik pada Buku Siswa Kelas II Tema 1 Sub Tema 1

Analysis of Idiomatic Expressions in Student Book of Class Two Theme 1 and Sub-theme 1. This study aimed to describe the results of the analysis that associated with the kind, structure and meaning of idiomatic expressions in the second-grade student book, theme 1: Living in Harmony. This study used a descriptive qualitative approach by analyzing qualitative data within the kind words or sentences that containing idiomatical expressions. Among ten idiomatic expressions, there are two partial idioms and eight full idioms. The structure of the idioms was (1) noun + noun, (2) adjective + noun, and (3) noun + adjective. Regarding on the meaning, there are idiomatic expressions that still have a connection with the lexical meaning of one of its constituent elements. However, most of the idiomatic expressions that have emerged have new meanings that are completely separated from the lexical meaning of the constituent words. The Idiomatic Expressions that contained in Student Book of class II Theme 1 Sub theme 1 are in the line with development of students who have just started learning in class 2 and already have knowledge about nouns and adjectives.
The role of scientific and educational strategies in innovative environment formation in Africa

The paper is devoted to the development of the scientific research and professional education problems in Africa. Nowadays in accordance with the ‘Sustainable Development Goals’ (2016-2030), UN Technology Facilitation Mechanism (TFM) was launched and adopted by all African states in the program” Science, Technology and Innovation Strategy for Africa-2024” (STISA). Additionally, Continental Education Strategy (CESA 2016-2025) was created for promoting innovation in the entire education and skills development ecosystems taking advantage of the digital revolution. Based on the SWOT-analysis of scientific-technological and educational strategies improvement in some countries (Egypt, Nigeria, South Africa, Senegal, Kenya) authors have received the results. In spite of the fact that national component contributes small part to the scientific-technological potential of African countries, this situation could be improved by means of their fruitful scientific and educational co-operation on the regional, continental and international levels, including the positive perspectives of Russian-African co-operation, especially in the sphere’s innovations in energy technology.
Weighted Adaptive Perturbations Adversarial Training for Improving Robustness

Adversarial Training (AT) is one of the most effective defense methods against adversarial examples, in which a model is trained on both clean and adversarial examples. Although AT improves the robustness by smoothing the small neighborhood, it reduces accuracy on clean examples. We propose Weighted Adaptive Perturbation Adversarial Training (WAPAT) to reduce the loss of clean accuracy and improve robustness, which is motivated by the adaptive learning rate of the model optimizer. In the adversarial examples generation stage of adversarial training, We introduce weights based on feature changes to adaptively adjust the perturbation step size for different features. In iterative attacks, if a feature is frequently attacked, we increase the attack strength of this area, otherwise, we weaken the attack strength of this area. WAPAT is a data augmentation method that shortens the distance of adversarial examples to the classification boundary. The generated adversarial examples maintain good adversarial effects while retaining more clean examples information. Therefore, such adversarial examples can help us to obtain a more robust model while reducing the loss of recognition accuracy for clean examples. To demonstrate our method, we implement WAPAT in three adversarial training frameworks. Experimental results on CIFAR-10 and MNIST show that WAPAT significantly improves adversarial robustness with less sacrifice of accuracy.