bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Consumer Data Privacy Protection Model Based on Non-Parametric Statistics for Dynamic Data Publishing in e-Commerce Platforms
Authors: Jia Jiao 
Published: June 2024

Objectives: Consumer data privacy on e-commerce platforms is increasingly crucial. This study aims to investigate privacy protection mechanisms, particularly focusing on personal and corporate secrets. It seeks to understand individual perspectives on privacy and preferences for data disclosure. The primary objective is to explore methods for safeguarding personal information while maintaining data integrity. Methods/Analysis: We employ non-parametric statistical techniques to analyze consumer behavior and preferences on e-commerce platforms. This involves examining patterns of data disclosure and identifying sensitive information shared by users. By studying communication dynamics and recording practices, we assess the efficacy of current privacy protection measures. Novelty/Improvement: This study contributes to the understanding of consumer privacy protection by emphasizing the importance of non-parametric statistical methods in e-commerce research. Our findings underscore the need for enhanced privacy measures. We advocate for further research and development of innovative privacy-enhancing technologies to address evolving privacy challenges in online commerce. Findings:Our research highlights the significance of personal privacy concerns in e-commerce settings. We identify a spectrum of privacy attitudes among users, ranging from strict confidentiality to selective disclosure. Furthermore, our analysis reveals potential vulnerabilities in current privacy safeguards, particularly regarding the collection and storage of sensitive data on e-commerce platforms. Doi: 10.28991/HIJ-2024-05-02-013 Full Text: PDF
The Measurement of Blockchain Technology in Financial Reports in Commercial Banks
Authors: Zaqeeba Nidal , Alqudah Hamza , Rawashdeh Badi S. , Lutfi Abdalwali , Alrawad Mahmaod , Almaiah Mohammed A. 
Published: June 2024

The objective of the present study is to measure the impact of blockchain technology on financial reports. The study utilizes a time series analysis covering eleven commercial banks listed on the Amman Stock Exchange from 2009 to 2019. Two key measures, namely other operating expenses and customer deposits are employed in the Return on Assets (ROA). The findings indicate that blockchain technology can be quantified by 0.038 of other operating expenses. However, there are no discernible indications of measuring blockchain technology through customer deposits. The study suggests that blockchain technology is a double-edged sword; when not utilized as required, it leads to increased expenses, and conversely, its effective exploitation can have cost-reducing effects. In other words, operational inefficiencies or heterogeneity are associated with elevated costs associated with implementing blockchain technology. Doi: 10.28991/HIJ-2024-05-02-014 Full Text: PDF
Social Media Data Privacy Related to Security Awareness and Student Trust Regarding Data on Instagram
Authors: Kurniawan Yohannes , Natalia Bella , Pratama Windy , Devi Ni Luh Gede Aninda Kesuma 
Published: June 2024

Instagram, as one of the most popular social media sites, has brought many new trends. Many people use Instagram to express themselves or share content through photos and videos. While social media data privacy is important, many people still share their daily activities and personal data. This causes a lot of personal information disclosure, which can lead to the potential for crime or misuse of the scattered data, considering that data is crucial today. Therefore, this research was conducted to determine people's social media data privacy and security awareness on Instagram, especially those with a data-related educational background. This research uses quantitative descriptive methods, distributing questionnaires through Google Forms in group chats, personal chats, or questionnaires to respondents directly. The population in this study is made up of students with a computing program background. It also used purposive sampling to determine the number of 153 samples. From the descriptive analysis, it is known that most respondents are aware of the vulnerability of social media data privacy on Instagram. This can be seen from respondents who know what data is used by Instagram, where they also monitor login activity. Respondents also secure their Instagram accounts by not using the same password as other social media accounts. However, in certain cases, some respondents still need to realize this awareness, so education is still needed regarding the importance of social media data privacy, especially on Instagram. Doi: 10.28991/HIJ-2024-05-02-015 Full Text: PDF
Optimizing Container Fill Rates for the Textile and Garment Industry Using a 3D Bin Packing Approach
Authors: Thi Xuan Hoa Nguyen 
Published: June 2024

The scarcity of empty containers presents a significant logistical challenge globally. To address this issue, this study proposes the application of the optimal box arrangement in a container with a 3D bin packing problem to enhance fill rates and accommodate the complex packing criteria of the textile and garment industry. The study’s objective is to optimize box stacking into containers by considering various factors such as multiple product types, diverse box sizes, varying container sizes, and prioritizing stacking according to purchase orders (PO). In tackling the NP-hard problem with the added constraint of PO-based stacking, this study advocates employing a genetic algorithm combined with a wall-building algorithm to address practical challenges. The genetic algorithm demonstrates optimal efficacy in solving large-scale optimization problems within specified timeframes, yielding high-quality results. In addition, normalization methods are applied to convert box sizes to pallet sizes, expediting problem-solving and facilitating the selection of appropriate container sizes, namely 20- or 40-feet. The research findings indicate that the proposed method achieved a container fill rate of up to 91.67% and minimized the number of containers used. Doi: 10.28991/HIJ-2024-05-02-017 Full Text: PDF
Analysis of Factors Influencing Online Learning Using the Decision Tree Method
Authors: Li Xiaojie , Tang Huili 
Published: June 2024

Objective: With the continuous development of online learning, the analysis of students' online learning has become increasingly important. Understanding which factors can influence students' engagement in online learning plays a crucial role in improving their learning performance. Methods: By utilizing web crawling techniques, students' online learning behavior data was collected from the Chinese University’s massive open online courses (MOOC) platform. To address the imbalance in the dataset, a synthetic minority oversampling technique (SMOTE) was used. Course progress was used to reflect students' online learning status, which was categorized into interruptions and completions. Furthermore, to tackle the issue of low computational efficiency in the C4.5 decision tree algorithm, its calculation formula was improved to develop an improved version of C4.5. Findings: Of the several factors analyzed, the number of course chapters had the greatest impact on students' online learning, followed by the number of course evaluations and overall course scores. The classification of students’ online learning situations based on an improved C4.5 algorithm revealed that the improved method achieved the highest accuracy rate of 0.942 and the shortest classification time of 0.165 s compared to methods such as the naive Bayesian and random forest algorithms. Novelty: This study designed an improved version of C4.5 to analyze the influencing factors in online learning, and its reliability was demonstrated through experiments, providing a new effective method for data analysis in online learning. Doi: 10.28991/HIJ-2024-05-02-018 Full Text: PDF
Evaluating Household Consumption Patterns: Comparative Analysis Using Ordinary Least Squares and Random Forest Regression Models
Authors: Lee En , Ong Thian Song , Lee Yvonne 
Published: June 2024

This research aims to decompose the contribution of socioeconomic factors towards household consumption expenditure using a regression approach, with log per capita expenditure as the dependent variable. Our study stands out as the first to utilise SHAP analysis and Machine Learning models to analyse household consumption expenditure. We select both OLS (linear) and Random Forest (nonlinear) models to compare how they estimate consumption expenditure differently. Both models explain about 85% of the variation in log per capita expenditure. The SHAP analysis reveals the nonlinear relationships inside the Random Forest model. Several insightful findings were suggested that can be integrated into current policy-making. The results are as follows: (1) Both models agree that income, household size, and educational level are major factors in the purchasing power of household heads. (2) The Random Forest model demonstrated a nonlinear contribution of age and household size towards log per capita expenditure, contrasting with previous studies that treated them as linear. (3) Household heads with a higher income and educational level tend to spend more. (4) Current policy should consider focusing on households with larger sizes and lower incomes, who tend to spend more despite earning less, primarily by assisting them with non-cash transfers and subsidies. Doi: 10.28991/HIJ-2024-05-02-019 Full Text: PDF
An Adaptive Differential Evolution with Multiple Crossover Strategies for Optimization Problems
Authors: Farda Irfan , Thammano Arit 
Published: June 2024

The efficiency of a Differential Evolution (DE) algorithm largely depends on the control parameters of the mutation strategy. However, fixed-value control parameters are not effective for all types of optimization problems. Furthermore, DE search capability is often restricted, leading to limited exploration and poor exploitation when relying on a single strategy. These limitations cause DE algorithms to potentially miss promising regions, converge slowly, and stagnate in local optima. To address these drawbacks, we proposed a new Adaptive Differential Evolution Algorithm with Multiple Crossover Strategy Scheme (ADEMCS). We introduced an adaptive mutation strategy that enabled DE to adapt to specific optimization problems. Additionally, we augmented DE with a powerful local search ability: a hunting coordination operator from the reptile search algorithm for faster convergence. To validate ADEMCS effectiveness, we ran extensive experiments using 32 benchmark functions from CEC2015 and CEC2016. Our new algorithm outperformed nine state-of-the-art DE variants in terms of solution quality. The integration of the adaptive mutation strategy and the hunting coordination operator significantly enhanced DE's global and local search capabilities. Overall, ADEMCS represented a promising approach for optimization, offering adaptability and improved performance over existing variants. Doi: 10.28991/HIJ-2024-05-02-02 Full Text: PDF
5G Opportunities in the South Pacific: Leveraging Low-Band Spectrum for Socio-Economic Development
Authors: Singh Satyanand , Singh Pragya , Rosak-Szyrocka Joanna , Vasa Laszlo 
Published: June 2024

This paper explores the potential for deployment of 5G communication in the South Pacific, with a particular focus on leveraging the low-band spectrum for socio-economic development. The purpose of this study is to assess the feasibility of deploying 5G infrastructure in the South Pacific region, analyze the socio-economic benefits it may bring, and propose strategies to maximize these benefits. The research methodology includes a comprehensive review of existing literature on 5G deployment strategies, the socio-economic impacts of telecommunications infrastructure, and case studies of similar initiatives in other regions. The findings show that the deployment of 5G technology using low-band spectrum has the potential to significantly improve connectivity, healthcare, education, and economic opportunities in the South Pacific. Additionally, the paper proposes innovative approaches to address challenges such as infrastructure development in remote areas and affordability for marginalized communities. This study contributes to existing literature by providing tailored recommendations for leveraging 5G technology to address socio-economic inequalities in the South Pacific, thereby contributing to the development of telecommunications infrastructure in the region. Provides a new perspective on the possibilities of structure. Doi: 10.28991/HIJ-2024-05-02-020 Full Text: PDF
Prediction of Dust Emissions in Highway Subgrade-Filling Construction Based on Deep Neural Network
Authors: Wang Zhibin , Feng Lei , Li Yanwei , Du Qunle , Zhao Lin , Wang Xingju 
Published: June 2024

Dust pollution can harm the urban environment and the health of citizens. Each stage in highway construction generates unorganized dust emissions to varying degrees, which complicates their quantification. To precisely forecast dust emissions during the construction of highway subgrades and reduce the associated pollution risks, this study introduces a predictive model based on a deep neural network (DNN) for dust emissions during highway subgrade-filling operations. Dust concentration is treated as a nonlinear multivariate problem, with predictive indicators encompassing particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), ground surface temperature, wind speed, air temperature, surface pressure, and relative humidity. Using a DNN model, this study forecasts the concentrations of PM2.5 and PM10 at highway construction sites. Based on a highway project in Hebei Province, this study predicts dust-emission concentrations via field monitoring conducted using self-developed equipment. The model’s predictions exhibit a small mean-absolute-percentage error and root-mean-square error compared with the actual values, and the model’s accuracy significantly surpasses that of conventional regression models. Accurate forecasting can facilitate the timely control of dust concentrations at construction sites, thus facilitating more environmentally friendly and efficient construction. Doi: 10.28991/HIJ-2024-05-02-03 Full Text: PDF
Analysis of Seasonal Wind Energy Potential on Zanzibar Coastal Island
Authors: Shame Buruhan Haji , Tjahjana Dominicus D. D. P. , Ubaidillah . , Aziz Mohammad , Mbumba Manala T. 
Published: June 2024

The main objectives of this research were to numerically analyze the potential for seasonal wind power (WP), assess wind direction, and select the most effective wind turbine (WT) for installation at the research site. Wind data were collected half-hourly from a branch of the Tanzania Meteorological Authority nearest to the research site. The collected data were analyzed using a double-parameter Weibull distribution (WD) model, where the standard deviation (SD) method was used to fit the WD. The results revealed that the site experienced strong winds within the range of 4.5–7 m/s between the hours of 05:00 - 20:00, with the most likely seasonal wind speed (WS) ranging from 5–7 m/s, while the mean seasonal WS was 9.07–12.14 m/s. The highest possible wind energy density (wED) of 23.3 GWh/m2 at a hub height of 10 m occurred during winter, followed by spring, autumn, and summer, with 6.39, 6.32, and 3.33 GWh/m2, respectively. The annual wED was > 13.52 GWh/m2, with a typical month-to-month energy of 1.13 GWh/m2. Finally, the study concluded that the recommended WT model (POLARIS P62-1000) was the best choice for installation at the study site due to its sustainable WS and WP potential. Based on the findings of this research, which show that the site has sustainable seasonal wind resources, it is suggested that future wind research be carried out to extend the dataset to ensure the long-term seasonal wind pattern at the site. Doi: 10.28991/HIJ-2024-05-02-08 Full Text: PDF
Application of Smart Model in the Analysis of Opera Heritage Archiving and Protection
Authors: Liu Xueying , Zhou Wei , Dong Yuting , Zhu Libing , Chen Naijia 
Published: June 2024

Objective: Opera Heritage in China is a rich and diverse cultural tradition passed down through generations. Today, Opera Heritage remains an essential part of Chinese culture and is celebrated through performances, festivals, and other cultural events. Efforts are being made to preserve and promote Opera Heritage through innovative technologies and approach such as digital archives, virtual reality, and community-based heritage management. Analysis: In this study, we suggested the SMART model that seeks to integrate these technologies and approaches into the preservation and promotion of Opera Heritage, ensuring that this rich cultural tradition can be enjoyed by future generations. We employed an ‘opera heritage’ using the Smart model in this study. In this research, "Smart Heritage" was defined as heritage experiences that used the word "Smart Heritage" or "similar terms" to describe the smart model. Findings: Opera Heritage analysis paid close attention to cutting-edge tools to record developments that showcase technical independence. Due to language barriers, this article could only interpret a clear convergence between SMART and opera heritage protection. For China's Opera Heritage to be properly archived and protected, a holistic and cooperative strategy that incorporates cutting-edge technologies and community-based heritage management practises are essential. Conclusion:Innovating technologies such as virtual reality and digital archives have been employed in efforts to promote and preserve China's rich Opera Heritage. This study emphasises the necessity for an extensive strategy for the efficient preservation and protection of Opera Heritage and suggests the SMART model to incorporate these methods. Doi: 10.28991/HIJ-2024-05-02-09 Full Text: PDF
Drop Size Distribution in Agitated Contactor: A Review
Authors: Hamed Marwa S. , Hasan Basim O. , Znad Hussein T. , Al-Zuraiji Sahir M. 
Published: June 2024

The breakage rate of liquid drops in the dispersed phase is a key way to improve the heat and mass transfer between the continuous/dispersed phases. This work includes a review of experimental results of liquid drop breakage in an agitated tank. The study highlighted the experimental conditions that were investigated as well as the important findings about the impact of operating conditions on some breakup parameters. The conflicts and discrepancies in the findings of those studies were identified and analyzed. The review found that many experimental parameters affect the drop breakage rate. The breakage probability (BP), number of fragments, and breakage time (BT) are direct functions of power input.
Laser Produced Hydrophilic and Hydrophobic Silicon Surfaces
Authors: Hatem A. A. , Rasheed B. G. , Ahmed Naser M. 
Published: June 2024

Two lasers were utilized for silicon processing using photoelectrochemical etching and laser texturing in order to produce nano/micro structures, respectively. Photoelectrochemical etching process utilizes a CW diode laser of 532 nm wavelength was used to support electrochemical etching for both n-type and p-type conductivity. While laser texturing process was employed using pulsed fiber laser of 1064 nm wavelength. Various characterization methods were devoted to examine silicon micro/nanostructures surfaces produced by lasers. These methods include AFM, SEM and Raman scattering to provide clear evidence about formation of micro/nanostructures abundant at silicon surfaces. Moreover, FTIR analysis for the laser produced silicon surfaces could emphasize whether the resultant silicon surface is hydrophilic or hydrophobic. Image analysis software adopted a side view micro image was used to measure the contact angle between the water droplet and silicon micro/nano-surfaces. It is found that the laser produced silicon nanostructure by photoelectrochemical etching creates a hydrophobic surface and even super hydrophobic with contact angle of 130 degrees for 50 nm average size. In addition, utilizing fiber laser of high repetition rate for laser texturing produces microstructures that are super hydrophilic with contact angle could reach 8 degrees for a surface dimension of 50 μm.
Penerapan Model Pembelajaran Mastery Learning (Belajar Tuntas) Dalam Meningkatkan Prestasi Belajar Akidah Akhlak
Authors: Syarifuddin Syarifuddin , Zubaidah Zubaidah , Khairiah Khairiah 
Published: June 2024

Abstract: Application of Mastery Learning Model (Complete Learning) in Improving The Learning Achievement of Akhlak Creed.Students have had difficulty improving morally advanced learning achievements because teachers cannot develop learning models. The purpose of this paper is to map the achievements of students learning. Using descriptive qualitative methods. The findings show (1) the form of student achievement has not been optimal because teachers are less able to apply the mastery learning model; (2) the relationship between applying the mastery learning model. The more effective thbetweenapplication of the learning model, the higher the achievements achieved by students; (3) the application of the mastery learning (complete learning) model affects the improve ement of student achievement in learning morals. Then it can be concluded that the application of the mastery learning model (complete learning) can improve the achievements of students learning moral beliefs. This can be recommended to the institution.Abstract: Penerapan Model Pembelajaran Mastery Learning (Belajar Tuntas) dalam Meningkatkan Prestasi Belajar Akidah Akhlak. Siswa telah mengalami kesulitan dalam meningkatkan prestasi belajar akidah akhlak dikarenakanguru guru tidak mampu mengembangkan model pembelajaran. Tujuan tulisan ini adalah untuk memetakan prestasi siswa belajar. Menggunakan metode kualitatif diskripstif. Temuan menunjukkan (1) bentuk prestasi siswa belum optimal disebabkan guru kurang mampu menerapkan model pembelajaran mastery learning; (2) penerapan model pembelajaran mastery learning. Semakin efektifpenerapan model pembelajaran, maka semakin tinggi prestasi yang dicapai siswa; (3) penerapan model pembelajaran mastery learning (belajar tuntas) dapat meningkatkan prestasi siswa belajar akidah akhlak. Kemudian dapat disimpulkan bahwa penerapan model pembelajaran mastery learning (belajar tuntas) dapat meningkatkan prestasi siswa belajar akidah akhlak. Dengan ini dapat disarankan kepada lembaga pendidikan untuk menerapkan model pembelajaran mstery learning untuk meningkatkan prestasi siswa.