Reviewerly/exHarmony huggingface dataset:
New Digital Order and its Implications on Indian Family Relationships

The extensive adoption of mobile devices in India has revolutionized family communication patterns, presenting new dynamics and challenges. This study investigates the role of mobile communication in various aspects of family relationships, including parent-child interactions, marital relationships, and intergenerational dynamics. The aim is to see the evolving landscape of family relations in the digital era on family communication patterns, psychological well-being, and social connectedness. Mobile devices facilitate frequent and convenient communication, allowing family members to stay connected despite physical distances. It has also been observed to increase monitoring and supervision by parents, which may positively influence parent-child relationships. However, excessive mobile usage and dependency may lead to neglect of face-to-face interactions, resulting in reduced family interactions and communication. It is essential to explore the potential consequences of excessive mobile usage and identify strategies to promote healthy mobile communication practices within Indian families. The researcher conducted ten semi-structured interviews in a suburban housing society in Mumbai suburbs with similar socioeconomic strata. The aim was to know more about how mobile phones affect family communications. Qualitative grounded theory analysis was used to find themes and interpret results. (Creswell, 2013) The study explores the role of mobile communication in family relationships, emphasizing the need for effective management of mobile device usage within households. Setting time limits, boosting digital literacy, and encouraging family activities offline are among tactics that could help lessen the detrimental effects of mobile communication on family dynamics. Furthermore, understanding the cultural context of Indian families is crucial, as it can influence the adoption and interpretation of mobile technology within familial relationships. The research concludes that the role of mobile communication and usage in Indian family relations is a complex and multifaceted process. While mobile devices offer convenience and connectivity, their impact on family dynamics must be considered. This research abstract highlights the need for further investigation into the effects of mobile communication on different aspects of family relationships in the Indian context.
Generative AI Images and Indian Media Industry: An Overview of Opportunities and Challenges

Artificial Intelligence (AI) has gained initial momentum in the past few years. Another side of this is Generative AI, which is growing and has the capacity to transform journalism and media content. There are speculations about the consequences of AI from creating warfare to the making of movies. This article considers notable platforms like Shutterstock, providers of stock photographs, music and editing tools and secondly, DALL.E 2-Open AI, a generative AI platform of Chat GPT.The proposed research article aims to find out the effects of generative AI images in the media industry, the opportunities of AI generative visuals and the challenges faced by the industry due to the innovative technology. This article will also try to demonstrate the capacity and the limitations of generative AI content and reflect on the implications of generative AI for media education and journalism.
Emerging Trends in Contemporary Accounting - A Comprehensive Study

In the contemporary landscape of the corporate realm, the indispensability of accounting and its corresponding professionals cannot be overstated. The maintenance of accurate books of accounts is an essential requirement for every business entity, as it serves multiple crucial purposes. Firstly, it enables businesses to assess their profitability and effectiveness, providing them with valuable insights into their financial performance. This information is vital for making informed decisions and implementing strategies that can enhance the overall efficiency and success of the organization. Furthermore, accurate bookkeeping plays a pivotal role in ensuring the survival and sustainability of businesses in the highly competitive contemporary market. By meticulously recording and organising financial transactions, businesses can gain a comprehensive understanding of their financial position, enabling them to identify potential areas of improvement and address any existing shortcomings. This proactive approach allows businesses to adapt to changing market dynamics, optimise their operations, and maintain a competitive edge. Moreover, accurate bookkeeping facilitates compliance with legal and regulatory requirements imposed by relevant authorities. By maintaining meticulous records of financial transactions, businesses can demonstrate transparency and accountability, mitigating the risk of legal disputes and penalties. This adherence to legal obligations not only safeguards the business's reputation but also fosters trust and confidence among stakeholders, including investors, creditors, and customers. In conclusion, the imperative for businesses to maintain accurate books of accounts cannot be overstated.
DETEKSI CACAT BANTALAN GELINDING BERBASIS ALGORITMA DECISION TREES DAN PARAMETER STATISTIK

Rolling bearings are a common machine element found in rotary machines. The components in the rolling bearing such as the inner race, outer race, rolling element, and cage are the parts that are often damaged. Traditionally spectrum analysis is used to diagnose bearing defects. However, spectrum analysis is not effectively applied to bearings with early defects because the vibration signal generated is dominated by frequency components from other machine elements, so the frequency of bearing defects cannot be observed. This study proposes an alternative method of detecting bearing defects based on vibration signals using machine learning with a decision tree algorithm. This method is more effective than the spectrum analysis method because machine learning is based on feature extraction and pattern recognition of vibration signal data, therefore, providing classification results directly without further analysis. Vibration signals were recorded using an accelerometer mounted on a bearing housing on a test rig. Nine-time domain statistical parameters and six frequency domain statistical parameters were extracted from the vibration signal and then used as input for decision trees. The results show that the decision trees algorithm gives an accuracy of 94.4% for classifying three rolling bearing conditions using the input of 6 selected frequency domain statistical parameters.
Analsisis Penerapan Media Pembelajaran dalam Proses Belajar Mengajar pada Jenjang Sekolah Dasar

Learning media in elementary schools is increasingly needed to facilitate the teaching and learning process. There is an urgency for learning media in elementary schools in the current digital era. First, increase the attractiveness of learning. Interactive and interesting learning media can provide a pleasant learning experience for students so that it can increase motivation and interest in learning. Second, increase the effectiveness of learning. Learning media can help students understand concepts more easily and quickly. Third, increase student participation. This can increase student involvement and participation in learning. Fourth, increase student creativity. Learning media with features such as image and video content can stimulate imagination and open up students' possibilities for creativity and innovation. Fourth, facilitate distance learning. Currently, in the COVID-19 pandemic situation, the use of learning media is very important to support distance learning in elementary schools. Therefore, the use of learning media in elementary schools in the current digital era needs to be implemented well and integrated into the curriculum, so that it can provide maximum benefits for students in the learning process. For this reason, this research focuses on analyzing the application of learning media in the learning and teaching process at the elementary school level. The aim of this research is to find out a clear picture of how learning media is implemented at the elementary school level, specifically in the West Kalimantan-Malaysia border area. The stages of the research method used are in the first stage, preparing data collection tools. The second stage in the research carried out was data collection and collection. The initial activity was observation by inspecting elementary schools in Bengkayang Regency. A literature review is carried out to look for data or source support that is relevant to the research. Interviews and Focus Group Discussions (FGD) will be conducted online and offline. The questionnaire that has been prepared will be shared online using Google Forms. The third or final stage is the stage of data preparation and recapitulation.Keywords: instructional media, elementary school
Optimization of Historic Buildings Recognition: CNN Model and Supported by Pre-processing Methods

Several cities in Indonesia, such as Cirebon, Bandung, and Bogor, have several historical buildings that date back to the Dutch colonial period. Several Dutch colonial heritage buildings can be found in several areas. The existence of historical buildings also would attract foreign or local tourists who visit one of an area. We need a technology or model that would support the recognition and identification of buildings, including their characteristics. However, recognizing and identifying them is a problem in itself, so technology would be needed to help them. The technology or model that would be implemented in this research is the Convolutional Neural Network model, a derivative of Artificial Intelligent technology focused on image processing and pattern recognition. This process consists of several stages. The initial stage uses the Gaussian Blur, SuCK, and CLAHE methods which are useful for image sharpening and recognition. The second process is feature extraction of the image characteristics of buildings. The results of the image process will support the third process, namely the image retrieval process of buildings based on their characteristics. Based on these three main processes, they would facilitate and support local and foreign tourists to recognize historic buildings in the area. In this experiment, the Euclidean distance and Manhattan distance methods were used in the retrieval process. The highest accuracy in the retrieval process for the feature extraction process with the DenseNet 121 model with the initial process is Gaussian Blur of 88.96% and 88.46%, with the SuCK method of 88.3 and 87.8%, and with CLAHE of 87.7%, and 87.6%. We hope that this research can be continued to identify buildings with more complex characteristics and models.
Curriculum Management Systems for Blended Learning Support

The ongoing COVID-19 has left some serious impacts on education, bringing academic activities to a halt, and restrictions have been in place to hamper the proliferation of the virus. The utilization of technology these days plays a vital role in assisting students in attending education online or blended learning and keeping academic activities running. However, limited learning management systems present a new problem in online learning, especially in higher education. Thus, a new information system is required to resolve this issue. This study aims to develop the Bauran information system to assist lecturers in higher education with curriculum design and semester lesson plans and to evaluate the effectiveness of Bauran's implementation using the ISO 25010 model. The material used during the research process included the Bauran application, Guidelines for Developing Higher Education Curriculum, and some data from relevant users to test the application. Meanwhile, during the development stage of the research, the prototype method was used to adjust the development to the feedback given by stakeholders. This application received positive feedback from relevant users regarding the curriculum development flow in line with the Guidelines of Curriculum Drafting for Higher Education. Using the ISO 25010 model during the testing process, the results of user evaluations demonstrated its effectiveness with an average score of 4.84 out of 5. Future research is expected to evaluate the long-term effectiveness of Bauran using a larger sample size and a different software evaluation model
Optimization of General Threshold Value for Preprocessing in Plasmodium Parasites Detection

The high mortality rate of malaria makes it a severe disease that spreads throughout all-region by infected female Anopheles mosquitoes, especially in tropical countries. Accurate early malaria detection is one of the ways to reduce the mortality rate. Microscopy-based malaria examinations are still considered the gold standard. Due to numerous large malaria patients with limited parasitologists, an automated detection system is needed as a second opinion to assist parasitologists. This study proposed an optimization method for finding an optimal global threshold value for pre-processing parasite detection. There were three stages of the proposed method. The first is to pre-process digital microscopic images using color channel selection, contrast stretching, and morphological operation. The second is to find the global threshold value using multiple modified Otsuâ€™s. The third is to determine the optimum global threshold value. In the last stage, predicted threshold values are generated using a pattern recognition approach to determine the optimum global threshold value. The proposed method evaluated 468 microscopic images captured from hundreds of thin smear blood slides. The slides are provided by the Department of Parasitology-UGM and the Eijkman Institute for Molecular Biology. The set image contains 691 malaria parasites in all types and life stages of malaria parasites. The proposed method obtained a sensitivity of 99.6 % and the smallest FPs number compared to without the optimization.Â It indicates that the proposed method has the potential to be implemented in the initial stages of the malaria detection system.
Pandawa Seraja (Pramuka Mawas Bencana Sehat Raga dan Jiwa) in SMP Negeri 2 Martapura Timur Banjar Regency

Floods are the most frequent disasters globally and cause significant impacts and losses. One of the impacts is psychological impact in the form of fear and anxiety. One-third of the victims were children which can result in psychological "trauma" to victims.East Martapura District is one of seven sub-districts in Banjar Regency which is often affected by flooding.Know that 47 adolescents aged 15-24 years in Banjar Regency were directly affected by the 2021 floods.This activity aims to reduce negative impacts such as stress, depression and others.This activity begins with flood education games by telling experiences or things that are known about flooding, delivering educational videos about flooding and flood preparedness, education about "The Importance of Mental Health During Floods". And finally, students are invited to color the prepared pictures using colored pencils. Evaluation of activities was carried out using a pre-post test.The results of the evaluation showed an increase in knowledge of 83.33%. Apart from that, the psychological assistance provided aims to provide mental readiness for SMPN 2 Martapura scout members to face challenges. Thus, this service not only enriches knowledge, but also helps in developing the physical and mental well-being of active scout participants at SMPN 2 Martapura Timur.
Penetration Testing: Analysis of Emerging Technologies and Their Impact on Pen Testing

The analysis of emerging technologies and their impact on penetration testing is a crucial aspect of staying ahead in the ever-evolving field of cybersecurity. As new technologies continue to emerge, so do new vulnerabilities and attack vectors that malicious actors can exploit. Therefore, it is imperative for penetration testers to stay updated on the latest trends and advancements in technology in order to effectively assess and mitigate risks. We highlighted the benefits of penetration testing such as compliance to industry regulations, vulnerability identification, enhancing the effectiveness of security controls, strengthening cybersecurity defences, among others. The result of our analysis identifies some of the key features and advancements in the analysis of emerging technologies and their implications for penetration testing.
Methoden des visuomotorischen Trainings für Sportler/Leistungssportler

Purpose. Training methods to improve the performance of the visual system are repeatedly described in the popular media. This review article focuses on the scientific aspect of this subject, presenting and discussing studies and techniques for enhancing visual and visuomotor performance in high-performance athletes. Material and Methods. To conduct the literature review on visual performance enhancement, relevant scientific databas- es, specialized articles, and academic books from fields such as sports science, optometry, medicine, and partially technical disciplines were comprehensively searched. Keywords eye-hand coordination, visual performance enhancement, stroboscopic visual training, anticipation
Improved Rational Unified Process (RUP) MODEL using Agile Features

Communication plays a crucial role during the software development process using various models. However, it is not sufficiently practiced in some effective models, which impairs its performance. Diverse customized models used in the software industry such eXtreme Programming (XP) and Rational Unified Process (RUP). Each of these models has advantages that distinguish it from the other and make it unique. Agile models such as XP is distinguished from others as 'RUP' by its focus on effective practical activities, including communication practices for better customer satisfaction and engineering practices. But the shortcomings in document-driven approach as RUP limits its capabilities, makes it not adapt to changing requirements, and does not provide best practices for simplicity. Communication between the user and the owner of the product with the work team is a valuable aspect of the software development process and should not be neglected. The purpose of this paper is to focus on using communication practices that take place in XP model as one of the agile methodologies and how they can enhance performance of RUP model. In this paper, a new enhanced RUB framework will be proposed for better communication practices through the software development process.
Optimasi Mix Design Beton Melalui Teknologi Machine Learning

The concrete mix design is a crucial step in ensuring the quality of concrete used in construction projects. Traditional mix design methods rely on trial and error, which can be time-consuming and escalate construction costs. In recent years, machine learning technology has been developed to predict concrete properties and optimize mix designs for high-quality concrete. This study aims to explore the application of machine learning in high-quality concrete mix design, considering theoretical conditions, methods, and related research. The focus of this research is to test the use of machine learning techniques in predicting concrete properties and optimizing mix designs for high-quality concrete. The theory and concepts of machine learning will be applied to concrete mix design datasets and relevant properties. The methods employed will include data pre-processing, feature selection, and model training and evaluation. The performance of the machine learning model will be compared with traditional mix design methods to determine its effectiveness. Furthermore, the results and benefits of this study will demonstrate the potential advantages of using machine learning in determining high-performance concrete mix designs. By accurately predicting concrete properties and optimizing mix designs, construction projects can be completed more efficiently and with higher quality. This technology also has the potential to reduce costs associated with trial and error methods and minimize the environmental impact of concrete production. The success of this study will pave the way for further research and development in the field of machine learning for high-performance concrete mix designs.
Investigating Accounting Students' Comprehension During Online Learning: a Case Study in a Muslim University

This research aims to explore students' understanding of introduction to accounting courses during online learning. The type of research used by the researcher is descriptive research with a qualitative approach. There were obstacles found that consist of unsipported network, and lack of students' understanding of material provided especially in practice making financial reports.&nbsp; Although, there were some advantages from online learning such as more efficient learning costs,&nbsp; for example for boarding, transportation as well as food, and that online learning provides more practical solution, the results of research indicate that such learning mode in a Muslim university was less effective.
MENINGKATKAN HASIL BELAJAR SISWA PADA PEMBELAJARAN TEMATIK SEKOLAH DASAR DENGAN CONCEPT ATTAINMENT MODEL

This classroom action research aims to make students more able to understand the sub-theme The Importance of Maintaining Healthy Food Intake in Thematic Learning. The research was conducted in Semester 1 of the 2022/2023 Academic Year. Eight grade 5 students at SD Negeri 3 Riang Gede were used as research subjects. The research was carried out for two cycles, with each cycle consisting of planning, implementing, observing and evaluating results, as well as reflecting on the findings. Using learning achievement tests, direct descriptive qualitative and quantitative analyzes were used to collect and analyze data. Success is shown by the average KKM learning outcomes of 60.00 and completeness of 85.00 percent. The analysis produces the following results: 1) With an average acquisition of 53.75 in the Pre-Cycle, 60.63 in Cycle one, and 68.13 in Cycle two, the Concept Achievement Model can improve student learning outcomes; (2) By using the Concept Acquisition Model, student learning completeness can increase by 37.50 percent in Pre-Cycle, 75.00 percent in Cycle one, and 100.00 percent in Cycle two. The conclusion is that students can understand the sub-themes given.
Anomaly detection in image streams with explainable AI

We define an anomaly as an unlikely occurrence that deviates from a typical behavior [1]. An anomaly could be a defect in a production line, sudden stock market fluctuations or natural disasters such as deforestation, volcanic eruptions, or floods [2] [3]. The assistance of an intelligent system to identify such disturbances would be very beneficial to initiate methods to prevent such situations in the early stages. This study forwards an AI based anomaly detection system and its testing stages primarily focused on the detection of deforestation, where when deforestation occurs, it shows an anomalous scenario which deviates from the typical sights of lush green forests.