Reviewerly/exHarmony huggingface dataset:
Temporal-aware Mechanism with Bidirectional Complementarity for Video Q&amp;A

Video question answering (Video Q&A) is a challenging task as it requires a sufficient understanding of the video and question information. Video is composed of frame sequence, which contains multi-scale temporal relationships and corresponding contextual information. A model competently tackle Video Q&A task that needs to be able to: 1) construct long-term and neighborhood dependencies in frame sequences to extract global and local contextual features that can reflect multi-scale temporal dependencies, and deduce the temporal-aware refined features, and 2) identify static and dynamic features from pertinent moments of a video, while filtering away question-irrelated dependencies of feature sequences, to yield the most precise and reasonable temporal-aware overall contextual features. In response to the above requirements, we propose a novel Video Q&A mechanism which consists of Bidirectional Complementary Attention(BCA) module and Adaptive Temporal-aware(ATA) module. Bidirectional complementary attention module stacks multi-head self-attention layer and convolutional layer in different orders to designed two kinds of attention units, which is able to make bidirectional multi-step reasoning based on complete global information and accurate local information to obtain temporal-aware refined features. Adaptive temporal-aware module is used to filter away question-irrelated dependencies in the feature sequence to yield the most precise and reasonable temporal-aware overall contextual features. Comprehensive comparative experiments are conducted on publicly available benchmark datasets. An extended ablation study is further conducted to show the usefulness of each module of the solution in acquiring its computational Q&A capabilities.
IMPLEMENTATION OF E-LEARNING AS A MEDIA FOR BIOLOGY LEARNING BY HIGH SCHOOL TEACHERS IN BIREUEN DISTRICT

The advantages of developing and implementing information technology in education include increased learning effectiveness and flexibility, as well as making the learning process easier for teachers and students. The study was conducted in the even semester of the 2018/2019 academic year in Bireuen Regency to determine the use of e-learning as a medium for high school biology learning. Mix methods research was used in this study. The participants in this study were all Bireuen Regency public high school teachers. The participants in this study were 12 biology teachers from SMAN 1 Bireuen, SMAN 2 Bireuen, and SMAN 2 Peusangan. A questionnaire is used to collect information. The data were analyzed using the percentage formula. The results showed that the use of e-learning as a medium for biology learning by teachers at SMA Bireuen Regency in terms of several criteria, namely e-learning planning was 77.08% and e-learning implementation was 72.50%. So it can be concluded that the use of e-learning as a medium for learning biology by teachers in senior high schools in Bireuen Regency as a whole is effective.
Gerakan “Aku Senang Membaca” Melalui Pembentukan Taman Baca Anak Serta Pelatihan Membaca dan Health Literacy

Indonesian children still have limited access to books, and reading activities have not become a culture in Indonesia. This problem worsens with the Covid-19 pandemic because many schools were closed or changing the method to learning from home. In addition to reading, health literacy is also crucial during this pandemic. This service activity aims to increase interest in reading through training and establishing the children's reading park. The method used was training and diffusion of science and technology. The training was conducted online through video conferencing applications and live streaming via popular video sites. Evaluation of activities was carried out using a pre-test and post-test. More than 80 participants joined the training activities. From the questionnaire results, there was an increase in the average score of the participants after receiving the training. The children's reading park has been formed and is ready to be opened to the public. The procurement of books was carried out through grants from donors, and more than 300 reading books were collected.
Readiness Of Flood Disaster Preparedness In High Risk Area Communities In North Aceh District

Abstract: Indonesia is a country prone to floods. Flood disasters can occur anytime and anywhere. Aceh Province has a very large disaster potential, this is influenced by geographical, geological, hydrological, and demographic conditions. One of the areas in North Aceh that is often hit by floods every year, therefore it is important for the community to have good preparedness in dealing with flood disasters.&#x0D; Purpose: This research is to find out the description of flood disaster preparedness in the community.&#x0D; Patients and methods: This study is a descriptive study with a cross-sectional approach. The sampling technique used is stratified random sampling, with a total of 98 respondents residing in the North Aceh Regency. Data collection was done by distributing questionnaires.&#x0D; Results: The results showed that most of the community had a level of preparedness in the good category (56.1 %), then the community in the sufficient category (25.5%), and the community with a low level of preparedness (18.4%).&#x0D; Conclusion: this research is most of the community has a level of preparedness to face flood disasters in high-risk areas in North Aceh Regency in the good category.
Sistem Informasi Akuntansi menggunakan Metode Framework for the Application of System Thinking (FAST)

This study is an accounting information system development using Access 365. The problem discovered was that PT. Ebiz Prima Nusa's accounting information system was insufficient for the scale of the company and not in conformity with financial accounting standards. The goal is to analyze how the accounting information system now in use and to design a suitable accounting information system. The method employed is qualitative, with data gathered through observations, documentation, and interviews. The study is carried out at PT. Ebiz Prima Nusa, a new company that was established in September 2021. Researchers developed a basic application system that can cover the sales, cash receipts, and cash disbursements cycles, as well as the ensuing output, namely financial statements that comply with financial accounting standards in Indonesia.
ASSESSING THE IMPACT OF EMPLOYEE ENGAGEMENT, EXPERIENCE AND SATISFACTION ON ORGANISATIONAL PERFORMANCE

We hope to discover how employee engagement, employee satisfaction, and overall organisational performance are related to each other in this study. This study employed a descriptive research design. In order to test a hypothesis, a questionnaire and convenience sampling approach were used. Using SPSS 22, exploratory factor analysis was performed on a sample of 180 employees from various private banking organisations in Delhi-NCR. The study's findings based on regression analysis, show that improving the performance of Delhi-private NCR's banking firms has been mostly attributed to a rise in staff involvement, satisfaction, and experience. Effective use has been made of the concepts of employee involvement, experience, and satisfaction to raise company performance. Keywords: Private banking, Regression, employee satisfaction, Employee engagement, employee experience
THE EFFECTS OF DIGITAL REVOLUTION IN PERSONAL TRADITIONAL BANKING

Purpose: The prime objective of the study is to explains the concept of IoT in Banking services and also explain the variety of possibilities opens up particularly in the retail banking sector with the use of IoT in banking sector. Design/Research Methodology/approach: The whole analysis is based on secondary data collected from different journals, published reports, books, megazines and relevant official website. Findings: This study is conceptual in nature. It has been found that IoT has opens several opportunities to the banking sector to come out from their traditional method of operating at one hand. And on the other hand, the IoT has created the privacy and security issues of the customers. Research Implications: This study throws light on the significant contribution of IoT in banking sector. It has drawn attention of the practioners and policy makers and they are forced to implement IoT in their day to day banking operation particularly in retail banking. Scope for future work / Research limitations: As this study is based on secondary data. A thorough study based on primary data using quantitative and qualitative method may contribute more fruitful and generalizable results. Originality/value: The descriptive analysis based on secondary data has found that there are various studies on IoT and its impact on different technical sectors . The paper describes how IoT has benefitted customers and bankers in the retail banking services operation. Key Words: Retail banking, IoT, digtisation of banking, Banking of thing Paper type: Conceptual paper
WORK VALUES AS A DETERMINANT FOR ECONOMIC GROWTH

Aim of the Study: The findings in this study attempt to answer the question; Do work values predict economic growth? Methodology: World Values data was used to explore the aim of the study through multiple linear regression statistical analysis. Findings: The results indicate that work ethic does have a relatively evident relationship to economic growth and are significant predictors of GNI per capita and GDP per capita. These results indicated that work ethic changes as countries’ priorities change from having higher motivation to work in poorer economies to having lower motivation to work in wealthier economies. Managerial Implications: Leveraging the World Values Survey, this study shows that work priorities have shifted from working for material security/necessity in poorer economies to working for intrinsic needs in wealthier countries. This indicates an unusual non-generational shift in values indicating that employees can have large value shifts as wealth increases. Keywords: work ethics, work priorities, work values, economic growth, work motivation, priority shifting, GDP/GNI per capita JEL Classification: J11
Apps and Software Troubleshooting

Software is probably one of the most complex and convoluted aspects of a modern PC as there’s just so much variety now supported. You can run a DOS script from 1981, a 32-bit application from Windows 95, a 64-bit program that was written a week ago, or a Windows Store app that was introduced with Windows 8. Now it’s even more complex with the addition of Android apps installed from the Amazon Appstore. If we add the ability to run programs and scripts designed for GNU/Linux and the BASH command line, then things get more complex still.
Configuring Windows 11

A hugely important part of configuring a PC so as to make it as bombproof as possible is in the initial setup and making sure that your user accounts and overall configuration are managed in such a way so as to help avoid problems occurring later on.
Integrity and Updating Troubleshooting

How many times had you had or heard of a Windows Update causing problems on a PC, from instabilities to causing the system to completely fail to boot? To be honest, if I had a dollar for each time I’d heard this, I’d be enjoying a fair few more nights in fancy restaurants than I currently do.
Professional standardization: requirements for the competences of a library and information specialist

The purpose of the article is to outline the information-digital and socio-educational competencies of a library and information specialist taking into account the interdisciplinary nature of library and information activities in the use of digital technologies and in accordance with current regulatory documents, as well as the practice of library activities. The research methodology is based on such methods as information analysis of the current Digital Competence Framework and Professional Standards of Specialists, content analysis of the subject field of the research subject – semantic and logical analysis of the document collection (academic papers, information content of Internet resources); the hypothetical method enabled us to formulate the relevant competencies of a library and information specialist based on the analysis of information resources. The scientific novelty of the research is to substantiate the current competences of a library and information specialist as a basis for the development of the Professional Standard Project. Conclusions. The need to develop the Professional Standard of a library and information specialist requires an outline of the information-digital and socio-educational competencies of a library and information specialist taking into account the interdisciplinary nature of library and information activities in the application of digital technologies. The analysis of a wide array of library information resources (websites, Facebook pages, blogs, Telegram channels, and others), which present the current state of job functions and actions performed by librarians, the Framework of Digital Competences of scientific and academic and teaching personnel and the Professional Standard of teaching personnel, extrapolation of the presented data on the competence field of a library and information specialist made it possible to formulate the information-digital, social-educational and psychological-pedagogical competences of a specialist. The personal competences of a specialist are formulated within the scope of the tasks of their professional development in the digital environment, reflection, and assessment of the level of their own digital competence. The obtained results regarding the types of activities and the necessary competencies of a modern library specialist might be the basis for completing the structure of the Professional Standard of the Library and Information Specialist Project. &#x0D; Keywords: specialist in library and information activities, professional standard, competences, job functions.
Android-based Al-qur'an application development and culture "Nggahi Mbojo"

To overcome AL-Qur'an illiteracy in TPQ students can us the Qiroati method, Iqro`, An Nahdliyah, Yanbu`a, and Tartili, but are not very effective. The learning model applied by Al-Qur`an teachers is currently less attractive because they are still using the old method they are used to learning to use "Nggahi Mbojo" in every Qur'an learning, this study aims to produce the Qur'an, The Android-Based Application and Local Culture “Nggahi Mbojo” is of good quality with valid, practical and effective criteria. This research is a development research (Development Research) by developing learning tools that include, Al-Qur'an Learning Applications and IQRO Reading Ability Assessment Instruments, this research procedure refers to the 4-D model (Four D model) which is carried out on TPQ Santri total 40 people, in Pajo District, Dompu Regency in 2022, Data analysis in this study uses quantitative data analysis, through analysis of the validity of the device by experts, practicality analysis and analysis of the effectiveness of the device seen from student learning outcomes, the results of the analysis show that the learning tools used are of good quality with categories Valid, Practically effective for use in the process learning to read the Koran for students.
Retrieval-Based Factorization Machines for Human Click Behavior Prediction

Human click behavior prediction is crucial for recommendation scenarios such as online commodity or advertisement recommendation, as it is helpful to improve the quality and user satisfaction of services. In recommender systems, the concept of click-through rate (CTR) is used to estimate the probability that a user will click on a recommended candidate. Many methods have been proposed to predict CTR and achieved good results. However, they usually optimize the parameters through a global objective function such as minimizing logloss or root mean square error (RMSE) for all training samples. Obviously, they intend to capture global knowledge of user click behavior but ignore local information. In this work, we propose a novel approach of retrieval-based factorization machines (RFM) for CTR prediction, which can effectively predict CTR by combining global knowledge which is learned from the FM method with the neighbor-based local information. We also leverage the clustering technique to partition the large training set into multiple small regions for efficient retrieval of neighbors. We evaluate our RFM model on three public datasets. The experimental results show that RFM performs better than other models in metrics of RMSE, area under ROC (AUC), and accuracy. Moreover, it is efficient because of the small number of model parameters.
mlr3shiny—State-of-the-art machine learning made easy

mlr3shiny provides a simple accessible and user-friendly web-application, combining the graphical user interface with state-of-the-art ML functionalities in order to enable researchers less familiar with machine learning and programming to apply this methodology in their field and build experience with machine learning practice.
Detection and Tracking of Livestock Herds from Aerial Video Sequences

Autonomous herding research is becoming increasingly relevant. In this work, a model for sheep detection in herds from aerial video sequences is proposed, using the convolutional neural network Mask R-CNN. Several trainings with different datasets have been performed for achieving the model. An improvement in the detection metrics, through a visual tracking tool, allows not only detecting the individual sheeps in the herd, but also tracking them along the different frames in aerial video sequences. This system could be used, for example, in a drone to carry out livestock supervision, in addition to obtaining metrics that allow knowing the status of the herd. Finally, the method has been validated using several tests on images and videos of livestock in real outdoor environments.
Development and Validation of a Digital-Artificial Intelligent (AI) enabled Assay to predict early-stage breast cancer recurrence

Background: Breast cancer (BC) is the most frequently diagnosed cancer worldwide and the second leading cause of cancer-related deaths. To advance predictive recurrence models we developed an AI-image analysis platform that utilizes whole slide images (WSI) to phenotype invasive BC (IBC) at the tissue-cell architectural level. The objective was to produce an AI-IBC phenotype that includes a novel methodology to grade BC along with additional features that reflect biological pathways. We sought to combine these extracted and complex image feature sets with standard clinical pathology data to develop readily accessible models that predict early-stage BC recurrence.
RGBD Data Analysis for the Evaluation of Trajectory Planning Algorithms in Human Robot Interaction Environments for Rehabilitation

Robotic platforms are a great solution to ensure assistance and rehabilitation for disabled people using human-robot interaction capabilities. However, safe path planning trajectories are required by the robotic platform to avoid any collision between the human and the robot during the assistance or rehabilitation process. This paper proposes an intelligent robotic system that supervises the environment using 3D data from an RGB-Depth sensor and performs safe trajectories of the collaborative robot manipulator. Human-robot interactions are focused on upper-limb rehabilitation exercises about reaching a point using a collaborative robot UR3. Finally, several planning algorithms from Open Motion Planning Library (OMPL) are evaluated in order to obtain some metrics of the human-robot interaction and to find out the best one.
VR Games for Chronic Pain Management

Chronic pain is a continuous ailment lasting for long periods after the initial injury or disease has healed. Chronic pain is challenging to treat and affects the daily lives of patients. Distraction therapy is a proven method of relieving patients’ discomfort by taking their attention away from the pain. Virtual reality (VR) is a platform for distraction therapy by immersing the user in a virtual world detached from reality. However, there is little research on how physical interactions in VR affect pain management. We present a study to evaluate the effectiveness of physically active, mentally active, and passive interventions in VR using games with chronic pain patients. Our results indicate that physical and mental activities in VR are equally effective at reducing pain. Furthermore, These actively engage patients, while the effects of observing relaxing content persist outside VR. These findings can help inform the design of future VR games targeted at chronic pain management.
Kesulitan Membaca Al-Qur’an di TPQ/TPSQ Mushala Nurul Haq Kenegarian Sungai Dareh

In this era, reading the Quran is not a difficult thing to do, this is due to technological advances and so on. Reading the Quran can be done through a smartphone or through other technological sophistication. However, in the kenagarian sungai dareh, children are still taught manually, namely learning to recite at TPQ/TPSQ or mushalah. This is useful so that when learning to read the Quran children or students understand and understand better and are precise in the pronunciation of makhrajul letters. The method used in this study is to use survey research with qualitative descriptive techniques, where this study aims to produce data analysis through data collection instruments with observation techniques, interviews, and documentation. The results showed that there are still many students who have difficulty in reading the Quran, such as difficulties for young students who are just starting to learn to recite and not infrequently there are also students who have grown up who are still not taught in reading the Quran. this is due to the presence of internal factors and external factors. The role of parents is very much required in guiding their children in learning to recite not only at TPQ / TPSQ but at home it is also necessary to do so that their children can read the Quran more fluently and precisely in the pronunciation of makhrajul letters.
MFinBERT: Multilingual Pretrained Language Model For Financial Domain

There has been an increasing demand for good semantic representations of text in the financial sector when solving natural language processing tasks in Fintech. Previous work has shown that widely used modern language models trained in the general domain often perform poorly in this particular domain. There have been attempts to overcome this limitation by introducing domain-specific language models learned from financial text. However, these approaches suffer from the lack of in-domain data, which is further exacerbated for languages other than English. These problems motivate us to develop a simple and efficient pipeline to extract large amounts of financial text from large-scale multilingual corpora such as OSCAR and C4. We conduct extensive experiments with various downstream tasks in three different languages to demonstrate the effectiveness of our approach across a wide range of standard benchmarks.