bluuebunny/crossref_metadata_2025_split huggingface dataset:
EASE AND USEFULNESS OF ZAKAT E-PAYMENT: THE MEDIATING ROLE OF ATTITUDE TOWARDS INTENTION
Authors: Hamzah Muhammad Zilal , Rahim Hainnuraqma , Abdul Rasool Mohamed Saladin , Abdul Khir Mohamed Fairooz , Zakaria Nor Balkish 
Published: March 2024

Background and Purpose: Online payment is an important method of transaction widely practiced across the globe. Due to its flexibility and convenience, it has been a popular method of payments in recent times especially in important religious matters such as zakat, one of the pillars of Islam. Since it is an important religious obligation, the relevant authorities need to identify factors that would facilitate the payment of zakat from the perspective of zakat payers, especially in difficult times of the 2020-2021 pandemic situation. Thus, the aim of this paper is to identify factors that influence the intention of using electronic payment (e-payment) platforms to pay zakat. In addition, the mediating role of attitude will also be analysed in examining the relationships between perceived usefulness and perceived ease of use to zakat payment intention.

Methodology: The present study employed a survey method to assemble data pertaining to attitude, perceived usefulness and perceived ease of use as potential factors that determine user’s behavioural intention of e-payment zakat in Malaysia. 193 questionnaires were responded to and analysed via Partial Least Square (PLS) with the Smart-PLS 3.0 software.

Findings: Results showed that significant aspects such as perceived ease of use and perceived usefulness have positive bearings on attitude and intention to use zakat e-payment platform. The study also found that Islamic financial institutions (IFIs) are growing in popularity and the zakat authorities and fin-tech companies are establishing greater synergies tool.

Contributions: The findings put forward that Zakat institutions may need to improvise their e-payment platform to attract zakat payers. Besides, the findings also highlight the behavioural intention of zakat payers in response to technological advancement that the providers and users should acknowledge. Hence, it is expected that the collection of zakat would be increased in the future via e-payment platform.

Keywords: Zakat, e-payment, attitude, intention, online payment.

Cite as: Hamzah, M. Z., Rahim, H., Abdul Rasool, M. S., Abdul Khir, M. F., & Zakaria, N. B. (2023). Ease and usefulness of zakat e-payment: The mediating role of attitude towards intention. Journal of Nusantara Studies, 8(TI), 408-428. http://dx.doi.org/10.24200/jonus.vol8issTIpp408-428
ENHANCING ORGANISATIONAL ACCOUNTABILITY: THE ROLE OF HUMAN RESOURCE MANAGEMENT IN MALAYSIAN STATUTORY BODIES
Authors: Yahya Nurhidayah , Said Jamaliah , Zakaria Nor Balkish , Baltov Milen 
Published: March 2024

Background and Purpose: Using the Social Contract Theory underpinning, this research examines the relationship between human resource management (HRM) and accountability within Malaysian statutory bodies.

Methodology: A quantitative approach was employed to gather data from 195 online surveys distributed to CEOs of Malaysian statutory bodies. 186 usable responses were obtained for further analysis. Statistical techniques were applied to assess the relationship between HRM and accountability.

Findings: The study’s results reveal a positive and significant relationship between HRM practices and accountability within Malaysian statutory bodies. These findings highlight the critical role of HRM in promoting accountability and ensuring the successful fulfilment of socioeconomic obligations in emerging countries like Malaysia.

Contributions: This study contributes to the existing literature by exploring the association between HRM and accountability in Malaysian statutory bodies. Additionally, it incorporates the Social Contract Theory to provide a unique theoretical lens for understanding this relationship.

Keywords: Human resource management, accountability, Malaysian statutory bodies, social contract theory.
Cite as: Yahya, N., Said, J., Zakaria, N. B., & Baltov, M. (2023). Enhancing organisational accountability: The role of human resource management in Malaysian statutory bodies. Journal of Nusantara Studies, 8(TI), 453-479. http://dx.doi.org/10.24200/jonus.vol8issTIpp453-479
K-wire is more damaging than standard or acrylic drill bits when evaluating torsional properties of rabbit (Oryctolagus cuniculi) femurs
Authors: Massie Anna M. , Kapatkin Amy S. , Garcia Tanya C. , Marcellin-Little Denis J. , Guzman David Sanchez-Migallon , Chou Po-Yen , Stover Susan M. 
Published: March 2024

Abstract

OBJECTIVE
The objective of this study is to compare drilling variables and torsional mechanical properties of rabbit femora after bicortical drilling with a 1.5-mm standard surgical drill bit, acrylic drill bit, and K-wire.

SAMPLES
24 pairs of rabbit femora.

METHODS
After drilling under controlled axial displacement rate, each bone was biaxially loaded in compression followed by rapid external torsion to failure. Maximum axial thrust force, maximum drill torque, integral of force and displacement, change in temperature, maximum power spectral density of the torque signal, torque vibration, and torque and angle at the yield and failure points were collected. Pre- and postyield stiffness, yield and failure energies, and postyield energy were calculated.

RESULTS
The work required to drill through the cis- and transcortices (integral of force and displacement) was greater for the K-wire, followed by the acrylic and then standard drill bits, respectively. The K-wire demonstrated higher maximum torque than the drill bits at the ciscortex, and the force of drilling was significantly greater. The vibration data was greater with the acrylic and standard drill bits than the K-wire. There was no difference in torsional strength between drilling types.

CLINICAL RELEVANCE
Mechanical differences exist between different drill bits and K-wire and demonstrate that the K-wire is overall more damaging than the surgical drill bit.
Construction of Interactive Teaching Platform for College Language Courses Based on Speech Recognition Technology
Authors: Lu Xi , Jiang Kai 
Published: March 2024

Abstract
This study constructs an interactive teaching platform based on speech recognition technology for language courses in colleges and universities. The study begins with preprocessing speech signals, including sampling, enhancement, pre-emphasis and other steps. Subsequently, speech features are extracted using Improved Mel Falling Spectral Coefficients (IMFCC), and features are optimized by combining Principal Component Analysis (PCA). In addition, the study uses the Long Short-Term Memory (LSTM) network and Gated Recurrent Unit (GRU) to improve speech recognition’s accuracy and efficiency. The experimental results show that the method in this study achieves an average accuracy of 98% in classroom speech emotion recognition, which is a significant improvement over the traditional ADASYN method. This paper also provides an in-depth study of classroom interaction behavior by comprehensively analyzing the speech recognition results. The study shows that the platform can effectively promote the interaction between teachers and students and improve the quality of teaching. This study provides an efficient interactive tool for language teaching in colleges and universities, which helps to realize a personalized and dynamic teaching process.
A deep learning-based method for evaluating the quality of corporate brand packaging visual design
Authors: Ma Yanfei 
Published: March 2024

Abstract
With the development of deep learning technology, the quality evaluation of enterprise brand packaging visual design becomes more critical. The study first established a brand packaging design product color imagery dataset through color emotionalization, and used systematic clustering technology for imagery selection and evaluation. Subsequently, the brand packaging visual design was optimized based on user demand, combining perceptual engineering and user demand mapping model. Many samples were evaluated by GoogLeNet model, and the data were processed by K-mean clustering and semantic difference method. The results show that the proposed method can effectively distinguish the perceptual imagery of different brand packaging designs, such as traditional, modern, simple, and complex. Specifically, more than 90% of the samples in the experiment achieve high consistency in perceptual imagery evaluation. In addition, the study analyzed the classification effect and quality evaluation of corporate brand packaging visual design, proving the validity and reliability of the method. This study provides a new quality evaluation method for corporate brand packaging graphic design, which helps to improve design efficiency and quality.
A CiteSpace Analysis of Rural Accounting Research in the Perspective of Digital Rural Governance
Authors: Li Xiaohe 
Published: March 2024

Abstract
In digital rural governance, the effective integration of accounting and rural development is crucial for maximizing rural economic benefits. This paper uses CiteSpace software and LDA modeling to examine the current state and hot topics in rural accounting research from 2018 to 2022. The study was visualized by analyzing valid literature and using perplexity to determine the best effect of topic extraction. The results show that the number of annual publications in this field continues to grow, and the number of universities and institutions publishing relevant papers is also increasing yearly. Regarding research hotspots, the keyword “rural” appears most frequently, reaching 122 times, followed by “financial management” with a frequency of 106 times. The keyword with the highest centrality is “rural revitalization”, with a centrality as high as 0.38. The research keywords are mainly divided into rural revitalization and financial management, with the financial management group being the most dominant. However, the number of studies on rural revitalization has been increasing yearly, and the gap between them has been narrowing. The importance of accounting is growing in promoting rural revitalization and improving rural economic efficiency.
Predictive analysis of brain imaging data based on deep learning algorithms
Authors: Wang Xuan , Zhang Xiaotong , Zhang Yuchen 
Published: March 2024

Abstract
This paper analyzes the effectiveness of predictive analysis of brain imaging data based on deep learning algorithms, and improves the prediction accuracy and efficiency of brain imaging data through improved methods. The first step is to measure the local consistency of the brain imaging data using Kendall’s concordance coefficient (KCC), and to analyze the differences between the datasets using the two-sample t-test. Secondly, a batch normalized convolutional neural network (BN-CNN)-based prediction method for brain imaging data has been developed. This method extracts spatial and temporal features in two convolutional layers, followed by a fully connected layer for classification. Experimental results show that this method is helpful in predicting missing structural data in brain imaging. Secondly, a batch normalized convolutional neural network (BN-CNN) based brain imaging data prediction method is developed, which extracts spatial and temporal features in two convolutional layers. Then it connects to a fully connected layer for classification. The experimental results show that this method’s structural similarity index (SSIM) and feature similarity index (FSIM) in brain imaging data prediction of missing data reaches 0.9446 and 0.9465, respectively, which is significantly better than that of other GAN benchmarks. In applying the method to epilepsy and Parkinson’s cases, this algorithm is used to epilepsy and Parkinson’s cases, and a two-sample t-test analyzes the differences in the data sets. In the application of epilepsy and Parkinson’s cases, the algorithm in this paper has an average prediction accuracy of 93.37%, effectively reducing the rate of incorrect predictions. Deep learning algorithms are highly efficient and accurate in predicting brain imaging data, which is crucial for future clinical diagnosis and treatment.
Science, technology and innovation driving urban land use and urban planning development: policy and practice
Authors: Min Jianan , Liu Zicong 
Published: March 2024

Abstract
In an era where science, technology, and innovation are key drivers of urban transformation, this research addresses the critical influences of policy and practice on urban planning and land utilization, proposing efficacious planning strategies to navigate emerging challenges. The study offers a comprehensive examination of urban development trends by integrating methods such as fuzzy set urban planning models, multi-objective planning, fuzzy regression, and GIS-based land use analysis. Specifically, our analysis of Shenzhen’s expansion and agricultural land growth from 1998 to 2023 demonstrates the significant impacts of technological innovation on urban landscapes, notably in expanding built-up regions by 90.21 square kilometers and augmenting greenfield farmland by 17.83%, thereby markedly enhancing land designated for ecological purposes. These findings affirm the vital role of innovation in advancing environmental sustainability and sustainable urban planning practices.
Clinical Study of Shenhong Tongluo Recipe in Treating Carotid Atherosclerosis
Authors: Zhang Linlin , Wei Qian , Wang Meiling , Li Peize , Chen Ying 
Published: March 2024

Abstract
To observe the clinical effect of Shenhong Tongluo Recipe on carotid atherosclerosis. Method: 72 patients were randomly divided into a control group (36 cases) and an experimental group (36 cases). The control group received atorvastatin calcium, while the experimental group received the Shenhong Tongluo formula. The treatment program consisted of 24 weeks. Observe the thickness of the intima media and plaque area of the carotid artery; Hs CRP, MLR (mononuclear C/lymphoid C), NLR (neutrophil C/lymphoid C); Clinical efficacy of traditional Chinese medicine and TCM syndrome score; Measurement of blood lipid levels (TG, TC, HDL, LDL); Homocysteine and uric acid; Changes in safety indicators. The total effective rate of the experimental group was higher than that of the control group (P<0.05). After treatment, the carotid intima-media thickness and plaque area in the experimental group; Hs CRP, MLR (mononuclear C/lymphoid C), NLR (neutrophil C/lymphoid C); Clinical efficacy of traditional Chinese medicine and TCM syndrome score; Blood lipid levels (TG, TC, LDL); Homocysteine and uric acid levels decreased (P<0.05), and the traditional Chinese medicine syndrome score was lower than that of the control group (P<0.05). No significant adverse reactions were observed in the experimental group’s control group. Conclusion Shenhong Tongluo Recipe can safely and effectively regulate the level of inflammation in the circulation of patients with carotid atherosclerosis, improve lipid metabolism disorder, reduce inflammatory reaction, alleviate and stabilize plaque and resist atherosclerosis.
Casework intervention research on interpersonal communication disorders of unsupported children
Authors: Liu Zhaoxu 
Published: March 2024

Abstract
This study aimed to critically evaluate the effectiveness of casework intervention in addressing the interpersonal challenges encountered by de facto unsupported children. An in-depth analysis of casework practices revealed positive outcomes, with significant advancements observed in the children’s social interaction capabilities. Leveraging a psychosocial therapy framework, the intervention strategically provided emotional support and social skills development, crucial for bolstering self-esteem and improving communicative competences. The results of this study illuminate the substantial benefits of casework interventions, confirming their essential role in facilitating the holistic growth and interpersonal health of unsupported children.
Dynamic Design of 3D Structures in Indoor and Outdoor Spaces by Integrating Perceptual and Behavioral Correlation Methods
Authors: Zhao Rui , Han Shijiao 
Published: March 2024

Abstract
Redefining the intersection of user perception and spatial design, this research introduces a sophisticated design methodology that integrates quantitative visual perception analysis with user behavior insights to optimize spatial configurations. Conducted across 15 communities in City H, the study employs a mix of questionnaires and observational tactics to identify how design elements correlate with user engagement. Findings reveal that environmental qualities, such as tranquility and clear signage, alongside the density of fitness equipment, significantly affect residents’ activity patterns, with a notable correlation (R²=0.727) between equipment density and spontaneous activity levels. This method promises enhanced space efficiency and user satisfaction by weaving user feedback into the spatial design process, offering a novel paradigm for spatial design innovation.
Exploring the connection between landscape art and interior and exterior space design using gray correlation analysis
Authors: Han Shijiao , Zhao Rui 
Published: March 2024

Abstract
In-depth research on landscape art interrelating with interior and exterior space design is still relatively limited. In this paper, we use gray correlation analysis to investigate the connection between landscape art and indoor and outdoor space design to better understand and apply the potential of landscape art in design. In this paper, we investigate the application of landscape art in indoor and outdoor space design, including the Use of landscape gardening techniques and landscape formation types. The study constructed an evaluation index system, including 16 indicators for road landscape, site landscape, green landscape and other types of landscapes, which were screened and weighted according to systematicity, operability, participation, dynamism and the combination of qualitative and quantitative indicators. We used AHP to determine the indicators’ weights and gray correlation analysis to calculate comprehensive scores for different design solutions. The best indoor and outdoor design solutions were determined by comparing and ranking the evaluations of various design solutions through case studies and statistical analysis. The method facilitates the scientific assessment and selection of indoor and outdoor design solutions to enhance the quality of design and the comfort of the human environment.
Curriculum System Design and Teaching Mode Innovation for Specialized College English Platforms
Authors: Qi Ying 
Published: March 2024

Abstract
This study addresses the application of rough set theory in English hierarchical teaching and explores how to optimize the teaching mode and improve the teaching quality and learning effect through this theory. This paper adopts a literature analysis and questionnaire survey method to study rough set theory’s knowledge expression and systematic decision-making mechanism. It applies it to the design of the curriculum system and the innovation of the teaching mode in the English platform of special-purpose universities. The optimized English hierarchical teaching mode using rough set theory significantly improved students’ learning interest and learning effect, in which 87.53% of the students believed it could improve their mastery of knowledge. The average score of 90.3 was 23.4 points higher than that of the control group, which was statistically significant (P<0.05). This study also found that the level of teacher specialization, students’ study habits, and school policies are key factors that influence the implementation of the teaching model. The introduction of rough set theory in this study provides new perspectives and methods for English teaching, promoting innovation in teaching methods and improving students’ learning ability.
Personalized Recommendations of Online English Teaching Resources for Higher Vocational Education
Authors: Qiao Han 
Published: March 2024

Abstract
Facing the intricate challenges of English instruction in higher vocational colleges, this research innovatively employs online resources to elevate educational quality and learner efficiency. It critiques the ineffectiveness of “one-size-fits-all” educational models and proposes a cutting-edge personalized recommendation system. This system adeptly curates learning materials to align with individual students’ learning patterns and competencies. By pioneering the TDINA and CUPMF models, and synergizing them with convolutional neural network (CNN) technology, our study dives deep into the educational content, ensuring precise resource recommendations. The system’s prowess was demonstrated through the successful recommendation of 815 resources, identifying strengths in electronic wall charts and courseware, alongside areas for enhancement in microclass scripts and recordings. A specialized experiment in personalized exercise recommendations further underscored the system’s efficacy, accurately tailoring the exercise level and difficulty to students’ learning capacities. Significantly, the CUPMF model emerged as a robust tool in refining the accuracy of these personalized recommendations, heralding a new era of bespoke educational experiences for students.
Exploring the Decorative Innovation of Interactive Digital Art in Interior Design under the Guidance of Ecological Concepts
Authors: Ren Li 
Published: March 2024

Abstract
In this article, we study how interactive digital art is applied in interior design under the ecological concept, focusing on color innovation and image technology to enhance the aesthetics and functionality of interior decoration. The article studies the three elements of color design and their application in product design. The K-Means clustering method is used to classify color imagery words in interior design, and the GAN model is combined to generate interior design colors. The results show that the error qualification rate for the color design scheme coding combination serial number is 88.2%. The composition of interior image decoration systems, digitization processing, and image fusion technology are also a part of this. A method for analyzing the impact of indoor digital decoration based on the ecological concept was proposed after studying the application range of interior decorative colors using cluster analysis. A questionnaire survey was conducted to analyze the perceptual imagery of interior decoration design. Interactive digital art can effectively enhance the aesthetics and functionality of interior design while reaffirming the ecological concept.
Research on the Application of Digital Media Art in Film and Television Animation in Multimedia Perspective
Authors: Shen Danni , Dong Yu 
Published: March 2024

Abstract
The fusion of digital media art with film and television animation production ushers in a new artistic and technological synergy era. This form of art, merging visual, sound, and digital innovations, faces unparalleled growth opportunities and significant challenges. This paper investigates the impact of digital media art on animation, emphasizing its influence on creative expression and production processes. Through case study analysis, we demonstrate the efficiency gains and aesthetic enhancements afforded by digital media, including a 70% reduction in rendering time and a 40% increase in character animation realism. Incorporating Virtual Reality (V.R.) and Augmented Reality (A.R.) technologies also opens up novel avenues for immersive viewer experiences. Despite facing obstacles in technology adaptation and financial investment, the application of digital media art in animation represents a crucial driver of industry evolution.