Reviewerly/exHarmony huggingface dataset:
The Impact of Work-Life Balance Policies on Job Performance (Applied study of small and medium-sized enterprises operating in the field of implementing telephone networks in Egypt)

Proceedings of The 6th International Conference on Research in Business, Management and Finance Year: 2023 DOI: https://www.doi.org/10.33422/6th.icrbmf.2023.09.102 [PDF] The Impact of Work-Life Balance Policies on Job Performance (Applied study of small and medium-sized enterprises operating in the field of implementing telephone networks in Egypt) Suheir Zaki Abdel Majeed, Mohamed Wahba, Mohamed A.Elsalam,Dalia Emara ABSTRACT: The current study aimed to evaluate the impact of work-life balance on job performance and measure the modifying effect of using talent management, servant leadership style, and organizational commitment by conducting a field study on employees of small and medium-sized companies working in the field of implementing telephone networks in the Arab Republic of Egypt from During the analysis of the questionnaire data obtained from 408 technical workers, administrators, supervisors and managers in companies working in the field of implementing telephone networks in Egypt, the 26SPSS and AMOS26 programs were used to analyze the data obtained. Through this program, the study hypotheses were tested, which resulted in: work life balance has a significant impact on job performance. keywords: WLB, Job performance, servant leadership, organizational commitment
Augmented reality with Marker Based Tracking for Introduction to Hydroponics

This research explains the implementation of Augmented Reality (AR) technology with Marker Based Tracking method in the hydroponic recognition system at Pesantren Nurul Huda. This system can assist students in the learning process about the maintenance of hydroponic plants by adding visual and interactive information to the hydroponic plants in the pesantren. In addition, this system can also assist in the management of hydroponic plants by adding features for monitoring the condition of the plants and providing appropriate care recommendations. The results of this research are expected to increase students' interest in agriculture and help in the management of hydroponic plants at Pesantren Nurul Huda. Augmented Reality (AR) can be implemented based on image or picture detection, commonly known as Marker Based Tracking method. By pointing the camera towards the printed image or marker. AR can be applied in 3D hydroponic plant learning system by displaying objects such as types of plants, systems, and growing media. The marker will be detected by the camera and display 3D objects of hydroponic plants, systems, and growing media so that the hydroponic object can be observed in reality. The multimedia development uses Blender and Unity 3D.&#x0D; &#x0D; Keywords: Augmented realit , Marker Based Tracking, Hydroponics&#x0D;
Soft Governance Across Digital Platforms Using Transparency

Platform governance helps align the activities of participating actors to deliver value within the platforms. These platforms can operate in environments where governance is intentionally or conventionally weak in favor of open access, frictionless transactions, or free speech. Such low- or no-governance environments leave room for illegitimate actors to penetrate platforms with illegitimate content or transactions. We propose that an external observer can employ transparency mechanisms to establish "soft" governance that allows participants in a low-governance environment to distinguish between sources of legitimate and illegitimate content. We examine how this might work in the context of disinformation internet domains by training a machine learning classifier to discern between low-legitimacy from high-legitimacy content providers based on website registration data. The results suggest that an independent observer can employ such a classifier to provide an early, although imperfect, signal of whether a website is intended to host illegitimate content. We show that the independent observer can be effective at serving multiple platforms by providing intermediate prediction results that platforms can align with their unique governance priorities. We expand our analysis with a signaling game model to ascertain whether such a soft governance structure can be resilient to adversarial responses.
Perceptions of High School Students on AI Chatbots Use in English Learning: Benefits, Concerns, and Ethical Consideration

This study explored high school students’ perceptions of using AI chatbots in English learning. Specifically, it aimed to gauge the breadth of chatbot utilization and discern perceptions surrounding potential challenges linked to their use. Thirty students from a high school took part in the survey. Data analysis involved frequency, mean and an independent sample t-test. The findings are as follows. First, students recognized the importance and value of chatbots highly and perceived their usability positively. However, their previous experience with chatbots did not sway this perception. Second, students perceived using chatbots in English learning as very beneficial. Especially, those with chatbot usage experience have a more positive perception compared to those without experience. Third, students were relatively aware of potential ethical issues with using chatbots. They were particularly concerned about plagiarism and copyright issues and potential personal information breaches regardless of their experience with chatbots. They also perceived potential educational issues, fearing over-reliance on chatbots might hinder their exploratory learning or lead to copying assignments directly, missing out on learning opportunities. However, those without experience were more skeptical than those with experience. The implications and suggestions derived from these findings are also discussed.
Employee Relationships in the Tourism Industry: A Systematic Literature Review (SLR) and Bibliometric

This study aims to explore the phenomenon of employee relationships in the tourism industry, as well as provide an overview for managers in dealing with their employees. The study is a systematic literature review using the Scopus database by analyzing 55 articles related to employee relations. Bibliometric analysis is also used with the help of Vos Viewer software to view visualizations of the analysis results. This study shows that employee relationships are critical to the success of any organization. When employees feel valued, supported, and respected, employees are more likely to be more motivated, productive, and loyal.
Density Map Guided Region Localization for End-to-End Small Object Detection

<p id="C1">With the advancement of society and science and technology, the demand for detecting small objects in practical scenarios becomes stronger. Such objects are only represented by relatively small coverage of pixels, and the features are degraded severely after being extracted by a deep convolutional neural network, which is detrimental to the detection performance for small objects. Therefore, an intuitive solution is to increase the resolution of small objects by cropping the original image. In this paper, we propose a simple but effective object density map guided region localization module (DMGRL) to locate and crop the regions of interest where small objects may exist. Firstly, the density map of the objects is estimated by object density map estimation network, and then the coordinates of the small object regions are calculated; Secondly, the continuous differentiable affine transformation is utilized to crop these regions so that the detector with DMGRL can be trained end-to-end instead of two-stage training. Finally, the all prediction results of input image and cropped region images are merged together to output the final detection results by non maximum suppression (NMS). Extensive experiments demonstrate the superior performance of the detector incorporated DMGRL.
Enhancing Traffic Management with Embedded Machine Learning for Vehicle Detection

In recent years, vehicle detection has become vital for applications ranging from autonomous driving to traffic control, surveillance, and monitoring. The demand for efficient real-time detection systems has surged, prompting the integration of machine learning algorithms into embedded platforms as a promising approach. This paper focuses on developing a robust and efficient system deployable on the NVIDIA Jetson Nano 2GB Developer Kit. The system harnesses machine learning algorithms tailored for resource-constrained embedded systems to achieve high detection accuracy in realtime. The process encompasses data preparation, preprocessing, feature extraction, and classification. Deep learning models used are You Only Look Once (YOLO) algorithm, YOLOv5n, and YOLOv7-tiny, trained on labeled datasets to classify regions of interest based on unique vehicle attributes. For inference on the Jetson Nano, both are chosen for their real-time capabilities and high object detection accuracy, are employed. To leverage the Jetson Nano’s GPU power, NVIDIA’s Compute Unified Device Architecture (CUDA) toolkit is installed, enabling parallel computing and deep learning model optimization. Results indicate that YOLOv7-tiny achieves the better precision-confidence at 92.7% and a recall-confidence of 94% compared to YOLOv5n. This study also uses various other evaluation metrics such as accuracy, precision, recall, confusion matrix, and F1 score to measure system performance and examine computational efficiency, to help in the selection of appropriate models for embedded systems.
Handwritten Signature Recognition using Deep Learning

Handwritten signature recognition plays a crucial role in verifying document authenticity and preventing fraudulent activities. That’s why this paper focuses on the development of a deep learning-based system for recognizing handwritten signatures. The main objectives include creating a diverse dataset of signatures, implementing a deep learning architecture for accurate signature recognition, and evaluating the system’s performance using various metrics.The VGG16 architecture was chosen due to its effectiveness compared to other methods, and it served as the framework for further enhancements. The results demonstrate the model’s outstanding accuracy. Specifically, the proposed model, trained on the merged dataset, achieved remarkable performance with a training accuracy of 99.78% and a validation accuracy of 99.75%. During testing, the model exhibited an impressive accuracy of 98.96%, confirming its effectiveness in identifying genuine signatures. Furthermore, the model trained on the collected dataset had shown an accuracy of 98.9% which ensures an efficient handwritten signature recognition.
AS-LR Emergency Detection Scheme for Biomedical Applications

The fast development of medical sensors allowed the emergence of a contemporary biomedical application called Body Sensor Network (BSN). BSN allows medical personnel to monitor the status of the person, through analyzing physiological parameters (Heart Rate (HR), Blood Pressure (BP), body temperature (To), etc.) collected by miniature medical sensors placed on the human body. The main aim of BSN is to enhance people's life through detecting emergency cases as fast as possible and taking proper actions before it is too late. Since sensors in BSN have very limited energy that should be preserved, the challenge arises in designing schemes that ensure correct and fast emergency detection while maintaining low energy consumption of nodes. Machine Learning (ML) techniques are vastly adopted nowadays for anomaly detection due to the large amount of data collected by the sensors. Even though these techniques provide high percentage of accuracy in detecting emergencies, they operate over the whole dataset which quickly drains the energy of nodes due to the large amount of data that should be transmitted. Thus, in this article, we propose an algorithm that efficiently decreases the amount of transmitted data through dynamically adapting the sampling rate of every sensor based on the risk of emergency detected by the Linear Regression (LR) ML model. Adaptive sampling is used to reduce the energy consumption of nodes and to accelerate the detection of emergencies, while LR is used to identify true urgent cases. Several simulations were conducted to evaluate the performance of the proposed scheme. Results show that the suggested algorithm outperforms other ML based anomaly detection schemes presented in the literature and succeeds in addressing the BSN challenges.
Remotely Muti-Collaboration for the Online Teaching of Architectural Design: A Pilot Study Based on a Distributed Version Control Solution

During the Covid-19 pandemic, the use of online meeting platforms has been effective in ensuring orderly teaching on campus and has demonstrated positive value. However, huge gap existed in online teaching and learning on architecture curricula, where spatial analysis and drawing analysis are the core elements of teaching. The existing online teaching method has shown obvious inappropriateness in online teaching and learning on architecture curricula. In this regard, our team proposes a solution for multiparty remote collaboration in architecture teaching based on the principle of distributed version control system with the reference of multiparty remote collaboration of software engineers. In the scheme advancement stage within the design group, each student can make simultaneous modifications to the same design scheme document and be submitted to the shared design project with additional information marking the modifier and modification time. In the program teaching and research stage, different design improvement solutions are displayed simultaneously through the online platform, and the teacher explains and discusses within the group to finally determine the rejection or adoption of design modifications, thus realizing real-time updates and efficient communication of the program design. At this stage, the distributed version control program represented by Git mostly uses row data as the data unit for parsing, which is not suitable for version control of large binary files. For the future, how to optimize and improve the distributed version control from the characteristics of architecture and urban planning professional teaching is an important issue to improve the efficiency of multiparty remote collaboration.
Phenomenological study of teenagers wayang fans

Recently, there has been a phenomenon of the existence of wayang fan groups as traditional art among teenagers, which is an element supporting the existence of wayang in the postmodern era. The purpose of this study is to explore the meaning of wayang and the activities of wayang art fans among teenagers. This study used a phenomenological approach by conducting interviews as a data search technique to seven teenager members of Sanggar BALADEWA. The results showed that: (1) the identity of wayang art fans was formed from the background as a ‘puppeteer family’ and a ‘fan family’ which created differences in meaning in wayang; (2) wayang fans are divided into active fans and passive fans as seen from their activities in Sanggar BALADEWA as a wayang fandom; (3) the existence of wayang for wayang art fans has shifted its function as entertainment due to mass production through digital platforms; (4) Teenagers who are fans of wayang not only have collections related to wayang, but also become ‘dalang muda’ as a form of wayang performance production. This study concludes that the art of wayang can adapt to the conditions of the times and there is also a shift in the function of religion to become an entertainment function that contains commercial practices.
The Impact of Strategic Orientations on Supply Chain Flexibility at Munir Sukhtian Group Company

This study aimed to investigate the impact of strategic orientations on supply chain flexibility at munir sukhtian group company. strategic orientations are measured through three dimensions: market orientation, learning orientation, and entrepreneurial orientation. flexibility of the supply chain was measured through three dimensions: sourcing flexibility, production flexibility, and logistics flexibility. the study used the quantitative method after obtaining the answers of 220 managers through an electronic questionnaire that was developed to collect the required data. A group of statistical methods were used, such as the mean, standard deviation, and simple and multiple regression coefficients. The study revealed that there are high application levels for the dimensions of strategic orientations and dimensions of the flexibility of supply chain at munir sukhtian group company, and that there is a significant impact of strategic orientations on the flexibility of supply chain and strategic orientations affects each dimension strategic orientations. It was found that there was a strong and statistically positive significant relationship between several variables of strategic orientations and flexibility of the supply chain. The study recommended promoting a culture of entrepreneurship within the organization by encouraging innovation, risk-taking, and proactive decision-making, and invest in market intelligence and customer-focused strategies to further enhance market orientation, and establish robust monitoring and evaluation mechanisms to assess the effectiveness of strategic orientation initiatives on an ongoing basis.
Aprendizaje colaborativo en una universidad del centro de México

Anti-pandemic policies, through strategies of confinement and distancing of people, led to the emergence of collaborative learning which lies in expectations of interaction and contribution. In this sense, the objective of the study was to compare the theoretical structure of eleven factors with respect to an observed four-factor model. An exploratory, transversal and psychometric work was carried out with a sample of 100 students assigned to health institutes. The results demonstrate that four factors prevail, related to experience, expectations, contributions and interactions, which explained 79% of the total variance. In relation to the state of the art, it was recommended not to reject the hypothesis that predicts significant differences between theory and empirical testing. The limits of the sample and the instrument are recognized, although the contrast of the four factors found is recommended.
Student Team Formation Using SCRUM

SCRUM (Scrum) is a popular framework for developing and sustaining complex products. It is designed to be an agile methodology that emphasizes collaboration, flexibility, and customer satisfaction. At its core, Scrum is built around the concept of a small, self-organizing team of people, known as a Scrum Team. This team works together to achieve a common goal, each member taking on a specific role and responsibility. In this paper, we propose a modified Scrum Team structure as a model for student teams in academic project environments. Our modification involves identifying specific roles within the team to provide more structure and align with industry practices. By doing this, we hope to help students better understand the importance of roles and responsibilities in project management and improve their project outcomes. The proposed approach involves providing a Scrum mapping for student teams of three and four members, with each member taking on a specific role based on Scrum principles. In our proposed approach, roles will rotate after each new assignment or a set number of times, giving students the opportunity to experience different roles and responsibilities within the team. We believe this approach will provide further exposure to the popular agile design approach and help students develop critical project management skills. We implemented our modified approach in a computer engineering course with lab components focused on microcontrollers to test our modified approach. Our experience using this approach was positive, with students reporting a greater understanding of project management concepts and improved project outcomes. Finally, we believe that our modified Scrum Team structure will also aid in the assessment of ABET's student outcome 5, which focuses on teamwork, communication, and project management. By providing a clear framework for project management and emphasizing the importance of roles and responsibilities within the team, we hope to help students develop the skills they need to succeed in their future careers.
Cell Tour: Learning About the Cellular Membrane Using Virtual Reality

Virtual reality (VR) technology has emerged as a promising tool in education, offering new possibilities for learning in immersive environments. This paper explores the application of VR in biology education, specifically focusing on teaching the functionality of the cell membrane. The traditional methods of textbook reading and microscopic observation lack interactivity and engagement, motivating the development of a VR-based learning approach designed as a game-like experience. The study compares the knowledge gain of participants who played the VR game with a control group who watched instructional videos. Surprisingly, the control group exhibited a higher knowledge gain compared to the VR group. Analysis suggests that the VR participants were more distracted by the immersive nature of the VR environment and focused less on the instructional content. Future research involving larger and more motivated participant groups, such as freshmen or high school students, may yield different results. Despite the observed limitations, this study highlights the importance of balancing immersive experiences with focused instructional content for better learning outcomes.
Pengaruh Critical Success Factors terhadap Keberhasilan E-Learning dalam Mendukung Pembelajaran : Systematic Literature Review

E-learning is considered less successful to replace normal learning methods amid the impact of the COVID-19 pandemic. The purpose of this study is to answer the question of what are the critical success factors (CSF) of the successful implementation of e-learning. This study applies the Systematic Literature Review method. Based on the results of a systematic literature review, the researcher found 162 Scopus articles in a search using Publish or Perish with Scopus Search which were then filtered into 13 selected articles for descriptive analysis. The findings show that there are 23 factors divided into five domains, namely students, instructors, design and content, systems and technology and institutions that can be considered in implementing or developing e-learning learning methods.