Reviewerly/exHarmony huggingface dataset:
Homomorphic Encryption

Abstract Homomorphic encryption is a technique in cryptography that allows for performing operations on encrypted data. The encrypted result can then be decrypted to obtain the operation result, making it possible to perform computations on sensitive data without revealing it. homomorphic encryption was first proved possible in 2009, and since then, many improvements have been made to increase performance, though it still has limitations. With recent advancements and the increasing demand for data protection, homomorphic encryption is expected to become more relevant and be used in multiple industries. In Switzerland, IBM, Inpher, and Tune Insight are among the companies that have developed homomorphic libraries and offer solutions for secure computation. These solutions can provide better protection and reduce the data vulnerability entrusted to companies and governments.
ETHEREUM CRYPTOCURRENCY PRICE MOVEMENT PREDICTION SYSTEM USING TRIPLE EXPONENTIAL SMOOTHING METHOD

An innovation that was sparked is an alternative currency to replace conventional currency, namely digital currency that is secured using a cryptographic method called Cryptocurrency. However, cryptocurrency prices cannot be controlled, causing massive fluctuations. Cryptocurrency price changes are very stable due to several factors such as speculation from users and the nature of the follow-up from new to one of the causes. The cause of this bandwagon is due to extreme price increases in a short time, even within a day the price of Crypto can experience a difference of millions of rupiah for each increase and decrease. To answer this question, we need a software that can predict the Rupiah exchange rate. By using the Triple Exponential Smoothing prediction method. In implementing Triple Exponential Smoothing, historical data is needed which will later be processed to produce prediction results, for that we need parameters that can be used as historical data counters, in this study used parameters 0.40 as parameters Xt and S't and 0.60 as Beta parameters. In the process, starting from calculating the first to third smoothing, ensuring Constants, Slopes, and Parabolics, to completing the process by producing Forecasting, the results of the measurement of the margin error level with a margin of error of 0.94638% using data for the final 2021 period, which is between November - December on the Triple Exponential implementation simulation and on the implementation into the system that has been developed is 3.7249% using data from May 2022 to June 2022
Analysis of the Relationship between Facilities, Learning Motivation, and Parental Involvement in Students' Digital Literacy in Junior High School

This study aimed to (1) examine the relationship between facilities and students' digital literacy in junior high schools, (2) explore the association between learning motivation and students' digital literacy in junior high schools, (3) investigate the correlation between parental involvement and students' digital literacy in junior high schools, and (4) examine the relationship between facilities, motivation, parental involvement, and students' digital literacy in junior high schools. This research employed a quantitative descriptive approach with an ex post facto design. The subjects of this study were students of State Junior High School 4 Pakem (SMP Negeri 4 Pakem), Yogyakarta, Indonesia, in the seventh and eighth grades. The sampling used a random technique totaling 178 respondents. Data analysis involved correlation and multiple regression analyses. The results indicated the following: (1) there was a significant correlation between facilities and students' digital literacy in junior high schools, with a computed correlation coefficient of 0.407 and a significance value of 0.000 (p &lt; 0.05); (2) a significant correlation existed between students' learning motivation and their digital literacy in junior high schools, with a computed correlation coefficient of 0.449 and a significance value of 0.000 (p &lt; 0.05); (3) a significant correlation was found between parental involvement and students' digital literacy in junior high schools, with a computed correlation coefficient of 0.508 and a significance value of 0.000 (p &lt; 0.05); (4) there was a relationship between facilities, motivation, parental involvement, and students' digital literacy in junior high schools, as evidenced by the multiple regression analysis, which yielded a computed F-value of 29.693 and a significance value of 0.000 (p &lt; 0.05), with an R2 value of 0.339. This implies that facilities, learning motivation, and parental involvement collectively contribute to 33.9% of students' digital literacy in junior high schools.
RADIUS: Risk-Aware, Real-Time, Reachability-Based Motion Planning

Deterministic methods for motion planning guarantee safety amidst uncertainty in obstacle locations by trying to restrict the robot from operating in any possible location that an obstacle could be in.Unfortunately, this can result in overly conservative behavior.Chance-constrained optimization can be applied to improve the performance of motion planning algorithms by allowing for a user-specified amount of bounded constraint violation.However, state-of-the-art methods rely either on moment-based inequalities, which can be overly conservative, or make it difficult to satisfy assumptions about the class of probability distributions used to model uncertainty.To address these challenges, this work proposes a real-time, risk-aware reachability-based motion planning framework called RADIUS.The method first generates a reachable set of parameterized trajectories for the robot offline.At run time, RADIUS computes a closed-form over-approximation of the risk of a collision with an obstacle.This is done without restricting the probability distribution used to model uncertainty to a simple class (e.g., Gaussian).Then, RADIUS performs realtime optimization to construct a trajectory that can be followed by the robot in a manner that is certified to have a risk of collision that is less than or equal to a user-specified threshold.The proposed algorithm is compared to several state-of-the-art chanceconstrained and deterministic methods in simulation, and is shown to consistently outperform them in a variety of driving scenarios.A demonstration of the proposed framework on hardware is also provided.
Design Intervention to Teach Life Skills

In the history of education from the earliest times for which there are available records, the shift in emphasis from values to skills is perhaps one of the most remarkable developments. Briefly, it can be summarized as follows: Before the Industrial Revolution, education was a form of gaining knowledge for the holistic development of an individual; from the nineteenth century onward, education became a system and a means of learning and polishing new skills that would help the individual to contribute to the economy. This paper explores the evolution of education in India from the gurukul system to the New Education Policy 2020. It focuses on understanding the importance of life skills in the education system and in an individual’s life. User study suggests that students learn life skills through their family upbringing, interactions, and experiences with school, classmates, and teachers, “How-to” guides and self-help books, and online TED talks. Further, it apprehends the ecosystem of triggers and struggles that the students face in learning different life skills, as well as the skills needed to conquer them. The study suggests that there is a lack of self-awareness skills in the modern-day education system, which leads to mental health issues, stress, lack of empathy, and indecisiveness in the students’ life. The paper showcases a system design approach to address and educate students about life skills for their holistic development.
Digital transformation and post-Covid-19 education in South Africa: a review of literature

Little thought or speculation was given to the possibilities of digital transformation for basic education until the global Covid-19 pandemic acted as a catalyst for digital transformation in education. Given the global trends toward digital transformation of teaching and learning, the South African basic education system has not been spared. While South African education policy was put in place to drive digital transformation, challenges persist in its implementation. The aim of this study was to examine the challenges facing the South African basic education system in digital transformation and assess the strategies that can be used to mitigate these challenges. Although South Africa is attempting to address existing inequalities and the digital divide stemming from apartheid policies, the inequalities of the post-apartheid era have continued and worsened during the pandemic, resulting in a multi-layered digital divide that hinders quality and inclusive education. We adopted a narrative literature review in this study, focusing on previous studies that focused on ICT adoption, digital transformation, and inequality challenges in the South African education system. The findings make apparent the impact of the digital divide and former policies in perpetuating educational inequality. From the literature, strategies to mitigate the challenges are highlighted, including consultations.
New Trends in Artificial Intelligence for Recommender Systems and Collaborative Filtering

In recent times, recommender systems (RSs) have been attracting a lot of attention from the research community because of their groundbreaking applications [...]
The Role of HRM Practices on the Talent Management: Evidence from Jordanian Commercial Banks

This study aims to examine how human resource management (HRM) practices affect talent management in Jordanian commercial banks. Information was provided by 120 administrators and staff members working for Jordanian commercial banks. The questionnaire used in this study was developed based on a comprehensive review of relevant literature and underwent validity assessments by experts in the field. To ensure data quality, clear instructions were provided, and data collection staff were available for support. Steps were also taken to address common method bias, including participant anonymity, separate data collection points, and the inclusion of control variables in the analysis. These measures contribute to enhancing the validity and reliability of the study’s findings. The findings showed that administrative innovation is positively impacted by human resource management practices, while the study also showed that there is a positive, statistically significant impact of the dimensions of HRM practices (training and development, wages and incentives, performance appraisal) on administrative innovation in Jordanian commercial banks. By giving field indications on the nature of the interaction between these two variables in the workplace, the current research contributes to the development of the literature addressing the relationship between HRM practices and administrative creativity. Lastly, this research recommends the need for officials in Jordanian commercial banks to pay attention to human resource management practices as an important factor contributing to administrative creativity, and to focus on training practices as training is a strategic option for preparing creative human cadres.
PROFIT PREDICTION USING MULTIPLE LINEAR REGRESSION METHODS PYTHON PROGRAMMING LANGUAGE AT PT TRI ERDNOV REZEKI

PT. Tri Erdnov Rezeki is a national private company founded in 2016 and fully under the leadership and ownership of Indonesian entrepreneurs. PT. Tri Erdnov Rezeki is also engaged in Construction Development Planning and Repair and Maintenance of Steam Aircraft and Pressure Vessels, Supply of Technical Equipment, Industrial Work Equipment, Electrical Equipment, and Machinery, especially in the Palm Oil Plantation and Power Plant Sectors. In carrying out a project, the company does not only carry out technical design but also must carry out the economic design so that the company can determine the economic feasibility of a project. However, companies often experience cost calculation errors. Data science can be utilized to predict the value achieved in a period using previous data. Data science will analyze patterns related to data with other data to produce a reference or a formula that can be used as a value prediction in the future. So, the author will use the multiple linear regression method using the Python programming language, which functions to perform statistical analysis, namely predicting profits in a project. The analysis results in this study show that the profit variable is influenced by 99.7% by the variables material cost, labor cost, and utility cost. In comparison, other variables outside the study influence the other 0.3%. The material cost variable has the most significant influence, where the value is below 0 .05 compared to the variable labor cost and utility cost to the profit variable. The average percentage of Python prediction errors is 0.97%, where the average percentage of Python prediction errors is smaller than the average percentage of SPSS prediction errors which is 2.04%.&#x0D;
Improving Operational Efficiency through Quality 4.0 Tool: Blockchain Implementation and Subsequent Market Reaction

Purpose: This article aims to observe and measure how modern and innovative blockchain technology improves the data quality and transparency and thus affect the stock prices of publicly traded companies after announcing its implementation in their operations. Additionally, the objective is to compare the results with control group of non-adopters. Methodology/Approach: We selected 30 public companies across various sectors, obtained daily stock price data, identified peer companies, and employed an event study approach to examine the statistical impact of blockchain adoption announcements. Findings: A significant negative reaction (-0.4%) was observed in stock prices the day following a blockchain adoption announcement, but overall, the market response was unsystematic, indicating no consistent reaction in stock prices post-announcement. Research Limitation/Implication: The event study approach assumes that markets are always efficient. This methodology has some limitations because we live in a world that is not perfect, and stock prices do not necessarily fully reflect all available information. Originality/Value of paper: Blockchain implementation is a current and intriguing subject that has attracted limited scholarly research. Each new study contributes valuable insights to the understanding of how this innovative technology impacts corporate operations. Furthermore, this research endeavours to draw comparisons between companies that have announced their adoption of blockchain and their non-adopters counterparts.
Control of Linear Electric Actuator with Hybrid Fuzzy PID Controller

In this study, the actuator, which converts circular motion to linear motion, is controlled with a smart hybrid controller. The model includes the analysis of electrical and mechanical parts. The controller, on the other hand, has a design methodology that cleverly blends classical PID (Proportional Integral Derivative) and fuzzy controllers. In this design methodology, classical PID and fuzzy controller have an error parameter dependent blending mechanism. In order to compare the performance of the hybrid controller, the coefficients of the classical PI and PID controllers were obtained by tuning and the coefficients with the best response were used. For performance comparison of conventional controllers and hybrid controllers; rise time, settling time, maximum overshoot and common performance indices values are used. The hybrid controller showed higher performance in terms of maximum overshoot, settling time, rising time and performance indices. The potential benefits of using a hybrid controller for the control of linear electric actuators were demonstrated by the fact that it performed better than conventional PID controllers on the majority of evaluation criteria.
Integrating the Web in the English Language Teaching-Learning Process: A Case Study in Text Analysis, 2nd Course, English Branch

E-learning has changed the perception of the world and influenced many areas of human social&#x0D; activity. It offers many new pedagogic opportunities and challenges in the teaching-learning process in Higher Education. Based on that, the integration of websites in the English acquisition process is important in the variety of interactive activities for improving the understanding of the English language and the communication of students in different subjects. This article analyses the integration of websites in the English teaching-learning process and examines the extent that technology-enhanced teaching and learning and its integration with coursebooks, make students benefit from language acquisition. This paper is focused on a case study with a group of 12 English language students, at the University of Korça. It focuses on how the web can be interlaced with the Text Analysis coursebook, by integrating four language skills, to improve overall language comprehension. The empirical descriptive qualitative research is applied to offer a lesson observation and description of applied learning experiences, such as collaborative learning with technology and the use of technology in communication. To gain an in-depth result, quantitative research is applied based on a focus-group online questionnaire with the students to see how web integration develops cognitive learning and how it facilitates learning and memory through speaking, listening, reading, and writing new knowledge found on the web, at different time intervals. Based on students’ perceptions it is seen how the websites may be a means of entertainment and motivation in acquiring new concepts in the subject of Text Analysis.
Effect of Green Banking Practice on the Performance of Deposit Money Banks in Nigeria: An Electronic Banking System Approach

The study examined the effect of green banking practice on the performance of Deposit Money Banks in Nigeria. The study employed the historical data research design while the quarterly time series data spanning through the period of 2012 to 2021 were collated from the CBN Statistical Bulletin. The Johansen cointegration test, Parsimonious Error Correction model and the fully modified Least Square were used for the data analysis.The findings indicated evidence of long-run relationship between green banking and the performance of Deposit money banks. Thus, the study concludes that banks can enhance their performance and environmental protection by adopting and promoting socially responsible and environmentally sustainable investment through the vehicle of green banking. In view of the findings therefore, the researcher suggests that the Central Bank of Nigeria should formulate and implement relevant policies that will encourage the full adoption of green banking practices by banks. Finally, Deposit Money Banks should educate their customers as well as creating awareness regarding the benefit of utilizing the electronic banking products in order to enhance the adoption of green banking in Nigeria.
Soundsystem Rental Information System Design, Web-Based Band Equipment and Bands

The manual system at Dhira Entertainment results in customer information and transactions only recorded in books or receipts, price errors, data processing irregularities, delays, and misinformation related to reports required in ineffective and efficient data recording. One of the management companies that offers rental services is Dhira Entertainment. Building a web-based sound system rental information system, band equipment, and bands was the goal of this study. System development using waterfall method, direct observation and literature study are two data collection techniques used. Use case diagrams and class diagrams are used in the system design process. PHP is a programming language used to create and implement information systems, while MYSQL is the database. The development of a web-based band and band equipment rental information system is believed to improve information services and streamline the process of managing rentals, transactions, and reporting at Dhira Entertainment.
The Application of VR in Game Design

As VR has been applied into many fields, and in recent years, video game developers tried to use VR in game deign because they always looking for new technology that can give players a better experience. This paper introduces the reason of why developer choose VR including the evolution of hardware, game design principles, cross-platforms, and combination of video game and health/education. Specifically, this article focuses on how virtual reality has become a part of the gaming landscape through the history of video games. Then, this paper analyses the contribution of VR to game design and the application of VR in cross-platform is described. Finally, here are some examples of how VR games can help people in other fields. The application of VR still has many exist issues that need to be fixed, but its benefits are irreplaceable for new game style and performance. In the end, this paper summarizes the research content and prospects the future.
Image Detection and Segmentation using YOLO v5 for surveillance

Segmentation an advancement of object detection where bounding boxes are placed around object in object detection whereas segmentation is used to classify every pixel in the given image. In Deep Learning, Yolov5 algorithm can be used to perform segmentation on the given data. Using YOLOv5 algorithm objects are detected and classified by surrounding the objects with the bounding boxes. Compared to the existing algorithms for segmentation, YOLOv5 algorithm has improved time complexity and accuracy. In this paper YOLOv5 algorithm is compared with the existing CNN algorithm.
Inter-translation Between CT and MRI Brain Scans Based on Cycle Consistent Adversarial Networks

Since Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are often used together in diagnosing brain diseases, it is rather time-consuming and expensive for patients to obtain two scans simultaneously. In this paper, the author proposed a new idea for CT-MRI inter-translation, using dataset of human brain scans to achieve unpaired image-to-image translation between CT scans and MRI scans. More specifically, the author proposed using Cycle Consistent Adversarial Networks (CycleGAN) to realize the idea of style transfer between CT and MRI. Briefly, this paper had trained two sets of generator and discriminator to form a cycle. This model can retain the main characteristics of a scan while transferring the scans style. To keep this translation process cycle-consistent, the Loss_cyc is used to keep the main content. Furthermore, the Loss_GAN ensures that the generated images exhibit a close stylistic resemblance to the target domain and the Loss_identity guarantees that the hue of the generated images is retained during the translation process. In addition, the author has added weights to the Loss_cyc and the Loss_identity to help the model perform better. Finally, this paper visualize the training process by presenting the original images and generated images together. Experimental results indicates that CycleGAN achieves a competitive performance can hopefully be a good auxiliary in brain diseases diagnosis.