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4th International Conference of science and information technology in Smart Administration, ICSINTESA 2024

作者： Lubis, Hasby Sahendri Nasution, Mahyuddin K.M. Amalia, Amalia Universitas Sumatera Utara Faculty of Computer Science and Information Technology Padang Bulan Medan20155 USU Indonesia

ISBN: (纸本)9798350376111

Term Frequency-Inverse Document Frequency (TF-IDF) is used to assess the importance of words in a document relative to the rest of the document set, while KMeans clusters documents based on content similarity. Utilizing a text dataset covering various government services, this study measures the effectiveness of these methods in identifying and clustering these services. Text pre-processing reduced the number of words from 30,753 to 15,783, indicating the elimination of irrelevant words. Visualization of the TF-IDF scatter plot shows a negative relationship between the frequency of occurrence of a word (TF) and its uniqueness (IDF). Clustering performance evaluation was performed using Silhouette Index (SI) and Davies Bouldin Index (DBI), which showed the consistency and good quality of the generated clusters. A stable SI value of about 0.62 and a consistent DBI value of about 0.552 indicate that the K-Means algorithm, both with the Euclidean and Manhattan approaches, is effective in grouping comments into clusters representing negative, neutral, and positive sentiments. The results of this research make a significant contribution to the development of information systems that are more efficient and responsive to public needs, as well as strengthening text data management in the context of government. © 2024 IEEE.

关键词： information management

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Enhancing Usability: A Grounded Theory Approach-based Scrum Framework for Mobile Application Design 19

Enhancing Usability: A Grounded Theory Approach-based Scrum ...

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19th International Conference on Future Networks and Communications, FNC 2024 / 21st International Conference on Mobile Systems and Pervasive Computing, MobiSPC 2024 / 14th International Conference on Sustainable Energy information technology, SEIT 2024

作者： Alnanih, Reem Department of Computer Science Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia

As technology becomes increasingly integrated into our daily lives, the role of software engineering in promoting healthy lifestyles has become increasingly important. Software applications have permeated our routines and well-being. Scrum, unlike traditional methodologies, offers an agile, iterative, and client-centric approach to software engineering. It emphasizes frequent client involvement, adaptability to changing requirements, and early risk mitigation, fostering a dynamic and responsive development environment. This approach is particularly crucial in the realm of mobile application design. Meanwhile, Grounded Theory can enhance the understanding of the alignment between developers and users' needs. This paper presents a comprehensive exploration of the development journey of a mobile application designed for promoting health, utilizing the Scrum framework and Grounded Theory. The iterative process, based on qualitative research, encompasses requirements gathering, database design, interface development, and usability testing. The author introduces concepts and styles to define and simplify sprints for improved clarity and comprehension. The usability testing for the proposed application-based Scrum framework was evaluated by two groups: an expert group familiar with the application's functionality and a participant group with no prior experience. The chi-square analysis revealed no significant differences between the two groups in their performance of the set of tasks, suggesting the application was evaluated similarly. Furthermore, the results of the post-test questionnaire, specifically the System Usability Scale (SUS) measure, indicate that over 83% of the participants scored the application above 82, placing it in the "A"grade range and reflecting an excellent level of user satisfaction. The analysis of the gathered data yields valuable insights with practical implications for organizations aiming to optimize the effectiveness of their Scrum teams. The

关键词： Application programs

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IRS-enabled NOMA communication systems:A network architecture primer with future trends and challenges

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Digital Communications and Networks 2024年第5期10卷 1503-1528页

作者： Haleema Sadia Ahmad Kamal Hassan Ziaul Haq Abbas Ghulam Abbas Muhammad Waqas Zhu Han Faculty of Electrical Engineering and Telecommunications and Networking(TeleCoN)Research Center Ghulam Ishaq Khan Institute of Engineering and Technology(GIKI)Topi 23640Pakistan Faculty of Computer Science and Engineering GIKITopi 23640Pakistan Department of Computer Engineering College of Information TechnologyUniversity of Bahrain32028Bahrain School of Engineering Edith Cowan UniversityPerth WA6027Australia Department of Electrical and Computer Engineering University of HoustonHoustonTX 77004USA Department of Computer Science and Engineering Kyung Hee UniversitySeoul 446-701South Korea

Non-Orthogonal Multiple Access(NOMA)has already proven to be an effective multiple access scheme for5th Generation(5G)wireless *** provides improved performance in terms of system throughput,spectral efficiency,fairness,and energy efficiency(EE).However,in conventional NOMA networks,performance degradation still exists because of the stochastic behavior of wireless *** combat this challenge,the concept of Intelligent Reflecting Surface(IRS)has risen to prominence as a low-cost intelligent solution for Beyond 5G(B5G)*** this paper,a modeling primer based on the integration of these two cutting-edge technologies,i.e.,IRS and NOMA,for B5G wireless networks is *** in-depth comparative analysis of IRS-assisted Power Domain(PD)-NOMA networks is provided through 3-fold ***,a primer is presented on the system architecture of IRS-enabled multiple-configuration PD-NOMA systems,and parallels are drawn with conventional network configurations,i.e.,conventional NOMA,Orthogonal Multiple Access(OMA),and IRS-assisted OMA *** by this,a comparative analysis of these network configurations is showcased in terms of significant performance metrics,namely,individual users'achievable rate,sum rate,ergodic rate,EE,and outage ***,for multi-antenna IRS-enabled NOMA networks,we exploit the active Beamforming(BF)technique by employing a greedy algorithm using a state-of-the-art branch-reduceand-bound(BRB)*** optimality of the BRB algorithm is presented by comparing it with benchmark BF techniques,i.e.,minimum-mean-square-error,zero-forcing-BF,and ***,we present an outlook on future envisioned NOMA networks,aided by IRSs,i.e.,with a variety of potential applications for 6G wireless *** work presents a generic performance assessment toolkit for wireless networks,focusing on IRS-assisted NOMA *** comparative analysis provides a solid foundation for the dev

关键词： Intelligent reflecting surface Non-orthogonal multiple access 6G Beamforming Sum rate Energy efficiency

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Exploring the Usage of Mobile Phones in the Assessment Process: A Case Study 47

Exploring the Usage of Mobile Phones in the Assessment Proce...

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47th ICT and Electronics Convention, MIPRO 2024

作者： Kovačević, Željko Bubnic, Bostjan Kosar, Tomaž Zagreb University Of Applied Sciences Department Of Computer Science And Information Technology Zagreb Croatia University Of Maribor Faculty Of Electrical Engineering And Computer Science Maribor Slovenia

ISBN: (纸本)9798350382495

technology is changing how students learn in the 21st century significantly. Integrating mobile devices in teaching, learning, and assessment processes has emerged as an important strategy for improving teaching methodologies and students' learning. However, adopting mobile devices presents several challenges, including understanding the students' performance, impact on time, and efficiency in the assessment process. This study explores this area with an empirical study of using mobile devices and compares the results to those using traditional desktop computers. In the educational environment, we investigated students' effective use while interacting with mobile and desktop versions of the Second Introductory programming summative assessment. Multinational/multi-institutional research involved a comparative analysis between two student groups undertaking identical tasks on mobile phones and desktop computers. Our results suggest that the students' results are not affected significantly by using the mobile version of the assessment application. These results highlight the usability of mobile devices as a flexible and effective tool for various educational applications, strengthening their role in the modern learning environment. © 2024 IEEE.

关键词： Object oriented programming

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Development of Student Face Recognition Attendance System 22

Development of Student Face Recognition Attendance System

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22nd IEEE Student Conference on Research and Development, SCOReD 2024

作者： Latif, Muhamad Aiman Bin Mohd. Aziz, Ruhaya Ab. Hafit, Hanayanti Universiti Tun Hussein Onn Malaysia Parit Raja Faculty of Computer Science & Information Technology Johor Malaysia

ISBN: (纸本)9798331510077

Face recognition technology, a subset of biometric technology, has emerged as a crucial and revolutionary tool in various industries, including identity verification, security, and surveillance. In this study, face recognition technology has been employed to enhance the student attendance system at the faculty of computer science and information technology (FSKTM). The current attendance recording method, which requires students to scan a QR code during teaching and learning sessions, presents several challenges. It is time-consuming, prone to inaccuracies, and susceptible to misuse, such as remote attendance recording and QR code sharing, which can lead to errors and class disruptions. To address these issues, the Student Face Recognition Attendance System was developed to ensure attendance is recorded accurately, efficiently, and with integrity. The system incorporates three user roles, which are administrator, students, and lecturer, and focuses on managing student attendance data within educational institutions. Prototyping software process model was adopted for this project, emphasizing iterative development through phases including requirement gathering, quick decision-making, building and refining a prototype, user evaluation, and final product development. The system was developed using a combination of OpenCV and software such as PyCharm and Firebase, with Python as the programming language. This system is expected to significantly reduce the time required for attendance recording while minimizing errors, thereby improving the overall efficiency and reliability of the attendance process. © 2024 IEEE.

关键词： Students

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Centralized Attention Modules for Hyperspectral Remote Sensing Image Classification 8

Centralized Attention Modules for Hyperspectral Remote Sensi...

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8th International Conference on Computational Intelligence and Applications, ICCIA 2023

作者： Li, Ningyang Wang, Zhaohui Cheikh, Faouzi Alaya Ullah, Mohib Hainan University Faculty of Computer Science and Technology Haikou China Norwegian University of Science and Technology Faculty of Information Technology and Electrical Engineering Gjovik Norway

ISBN: (纸本)9798350339741

Hyperspectral image classification based upon the spectral-spatial information is a research hotspot in the field of remote sensing. The popular deep learning technique, attention mechanism, is generally used to search the influential bands and pixels for hyperspectral image classification. However, the spectral and spatial attention inferred by the existing attention modules may be weakly related to the center pixel, which is harmful to realize better classification. Inspired by the recent centralization ideology designed exclusively for hyperspectral image, the core components of three popular attention modules, including the dot-product part of self-Attention module, the global semantic information of squeeze-And-excitation module, and the discovery of the relation between the global representation and crucial elements of convolutional block attention module, are improved. Therefore, the center pixel will be stimulated to make more contribution to the relevancy of attention. Experimental results on two classic data sets demonstrate the effectiveness of the centralized attention modules. © 2023 IEEE.

关键词： Pixels

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Automatic Speech Emotion Recognition: a Systematic Literature Review

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International Journal of Speech technology 2024年第1期27卷 267-285页

作者： Mustafa, Haidy H. Darwish, Nagy R. Hefny, Hesham A. Computer Science Department Faculty of Graduate Studies for Statistical Research Cairo University Giza12613 Egypt Information Systems and Technology Department Faculty of Graduate Studies for Statistical Research Cairo University Giza12613 Egypt

Automatic Speech Emotion Recognition (ASER) has recently garnered attention across various fields including artificial intelligence, pattern recognition, and human–computer interaction. However, ASER encounters numerous challenges such as a shortage of diverse datasets, appropriate feature selection, and suitable intelligent recognition techniques. To address these challenges, a systematic literature review (SLR) was conducted following established guidelines. A total of 60 primary research papers spanning from 2011 to 2023 were reviewed to investigate, interpret, and analyze the related literature by addressing five key research questions. Despite being an emerging area with applications in real-life scenarios, ASER still grapples with limitations in existing techniques. This SLR provides a comprehensive overview of existing techniques, datasets, and feature extraction tools in the ASER domain, shedding light on the weaknesses of current research studies. Additionally, it outlines a list of limitations for consideration in future work. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Speech recognition

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An Overview chatGPT in Higher Education in Indonesia and Malaysia

An Overview chatGPT in Higher Education in Indonesia and Mal...

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2023 International Conference on Informatics, Multimedia, Cyber and information Systems, ICIMCIS 2023

作者： Arista, Artika Shuib, Liyana Ismail, Maizatul Akmar Universitas Pembangunan Nasional Veteran Jakarta Information Systems Faculty of Computer Science Jakarta Indonesia Faculty of Computer Science and Information Technology Universiti Malaya Department of Information Systems Kuala Lumpur Malaysia

ISBN: (纸本)9798350307306

ChatGPT is a useful tool for teaching and learning in the context of education. Despite ChatGPT's growing popularity across several fields, little is known about how it is accepted and used, particularly in the context of higher education. ChatGPT holds a lot of potential to be a helpful tool for both students and lecturers. However, in higher education, the introduction of ChatGPT has raised serious questions about academic integrity. Thus, this research focuses on the overview of chatGPT in Higher Education in Indonesia and Malaysia. This study is conducted using the literature review method. According to this research result, this tool can help students and instructors with academic writing, language instruction, and learning in class in Higher Education in Indonesia. Higher Education in Malaysia is also raising optimism that this technology will speed up the transformation of higher education. Even though there are positive and negative effects of ChatGPT. Future research will need to conduct more case studies and interviews to obtain an in-depth comprehension of the application of ChatGPT in learning especially in higher education. © 2023 IEEE.

关键词： Students

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A Study of Cellular Neural Networks with Vertex-Edge Topological Descriptors

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computers, Materials & Continua 2022年第2期70卷 3433-3447页

作者： Sadia Husain Muhammad Imran Ali Ahmad Yasir Ahmad Kashif Elahi Country College of Computer Science&Information Technology Jazan UniversityJazanSaudi Arabia Department of Mathematical Sciences United Arab Emirates UniversityAl AinUnited Arab Emirates Deanship of E-learning and Information Technology Jazan UniversityJazanSaudi Arabia

The CellularNeuralNetwork(CNN)has various parallel processing applications,image processing,non-linear processing,geometric maps,highspeed *** is an analog paradigm,consists of an array of cells that are interconnected *** can be arranged in different *** cell has an input,a state,and an *** cellular neural network allows cells to communicate with the neighbor cells *** can be represented graphically;cells will represent by vertices and their interconnections will represent by *** chemical graph theory,topological descriptors are used to study graph structure and their biological *** is a single value that characterizes the whole *** this article,the vertex-edge topological descriptors have been calculated for cellular neural *** can be used for cellular neural network of any *** will enhance the applications of cellular neural network in image processing,solving partial differential equations,analyzing 3D surfaces,sensory-motor organs,and modeling biological vision.

关键词： Cellular neural networks degree topological indices

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Improving long-tail classification via decoupling and regularisation

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CAAI Transactions on Intelligence technology 2025年第1期10卷 62-71页

作者： Shuzheng Gao Chaozheng Wang Cuiyun Gao Wenjian Luo Peiyi Han Qing Liao Guandong Xu School of Computer Science and Technology Harbin Institute of TechnologyShenzhenChina Peng Cheng Laboratory ShenzhenChina Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies Harbin Institute of TechnologyShenzhenChina Faculty of Engineering and Information Technology University of Technology SydneySydneyNew South WalesAustralia

Real-world data always exhibit an imbalanced and long-tailed distribution,which leads to poor performance for neural network-based *** methods mainly tackle this problem by reweighting the loss function or rebalancing the ***,one crucial aspect overlooked by previous research studies is the imbalanced feature space problem caused by the imbalanced angle *** this paper,the authors shed light on the significance of the angle distribution in achieving a balanced feature space,which is essential for improving model performance under long-tailed ***,it is challenging to effectively balance both the classifier norms and angle distribution due to problems such as the low feature *** tackle these challenges,the authors first thoroughly analyse the classifier and feature space by decoupling the classification logits into three key components:classifier norm(*** magnitude of the classifier vector),feature norm(*** magnitude of the feature vector),and cosine similarity between the classifier vector and feature *** this way,the authors analyse the change of each component in the training process and reveal three critical problems that should be solved,that is,the imbalanced angle distribution,the lack of feature discrimination,and the low feature *** from this analysis,the authors propose a novel loss function that incorporates hyperspherical uniformity,additive angular margin,and feature norm *** component of the loss function addresses a specific problem and synergistically contributes to achieving a balanced classifier and feature *** authors conduct extensive experiments on three popular benchmark datasets including CIFAR-10/100-LT,ImageNet-LT,and iNaturalist *** experimental results demonstrate that the authors’loss function outperforms several previous state-of-the-art methods in addressing the challenges posed by imbalanced and longtailed datasets,t

关键词： computer vision image classification long-tailed data machine learning

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