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2024 IEEE/SICE International Symposium on System Integration, SII 2024

作者： Bozkurtlar, Mert Yen, Benjamin Itoyama, Katsutoshi Nakadai, Kazuhiro School of Engineering Tokyo Institute of Technology Department of Systems and Control Engineering 2-12-1 Ookayama Meguro-ku Tokyo152-8552 Japan Istanbul Technical University Faculty of Management Department of Industrial Engineering Maçka/Beşiktaş/Harbiye Istanbul34367 Turkey Istanbul Technical University Faculty of Computer and Informatics Engineering Department of Computer Engineering Sariyer/Ayazaga Istanbul34485 Turkey The Nakadai Lab Japan Honda Research Institute Japan Co. Ltd 8-1 Honcho Saitama Wako351-0188 Japan

ISBN: (纸本)9798350312072

This paper addresses the task of learning periodic information using deep neural networks to achieve real-time, environment-independent sound source localization. Previous papers showed phase data is the most significant cue in sound source localization tasks and the proposed vM-B DNN was validated to be able to handle such periodic information using on synthesized data. However, they haven't shown its effectiveness and robustness in realistic use cases. This paper introduces a more complex model based on residual networks and adapts vM-B activation function for convolutional layers for use cases that require real-time predictions in dynamically changing environments. © 2024 IEEE.

关键词： Deep neural networks

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The Impact of Social Media in Marketing on Brand Awareness and Customer Trust in Increasing Purchase Intention

The Impact of Social Media in Marketing on Brand Awareness a...

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2024 International Conference on Information Technology Research and Innovation, ICITRI 2024

作者： Fernando, Erick Prabowo, Yulius Denny Winanti Universitas Multimedia Nusantara Faculty of Engineering and Informatics Department of Information Systems Tangerang Indonesia Binus Online Learning Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Universitas Insan Pembangunan Department of Information Systems Indonesia

ISBN: (纸本)9798350376210

In the current digital era, marketing has developed using technology through media to reach consumers. One prominent feature is influencer marketing, where individuals with significant social media influence promote products or services to their audiences. This strategy has become dominant because of its potential to expand brand reach and boost sales. However, there are challenges in ensuring the effectiveness of influencer marketing, particularly in delivering content with sufficient information and entertainment value. Overcoming these challenges is critical to maximizing customer purchase intent. This research explores the influence of information value, entertainment value, brand awareness, and customer trust on customer purchase intentions in influencer marketing. This research used an online survey (google form) with 398 valid respondents used for analysis PLS-SEM with SMART PLS 3.0. The indicator test results are valid and reliable with loading value for each item with a value >0.5, AVE value ⩾ 0.50, Cronbach's alpha value ⩾ 0.70 and Composite Reliability (CR) value ⩾ 0.7. The findings show that these factors have a significant effect on purchase intention. In emphasizing the importance of influencers delivering educational and entertaining content to increase Brand Awareness in building customer trust, with the consistency of influencers. Overall, providing valuable insights for companies looking to optimize their influencer marketing strategy to increase brand awareness and customer trust, ultimately driving customer purchase intent. © 2024 IEEE.

关键词： Sales

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Evaluation of IT Governance with BAI Domain at Senior High School Using Cobit 5 8

Evaluation of IT Governance with BAI Domain at Senior High S...

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Prabowo, Yulius Denny Fernando, Erick Gate, Jullend Binus Online Learning Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Universitas Multimedia Nusantara Faculty of Engineering and Informatics Department of Information System Tangerang Indonesia Institut Teknologi Dan Bisnis Kalbis Faculty of Computer Science and Design Department of Information System Jakarta Indonesia

ISBN: (纸本)9798350326093

This study's objective is to evaluate the system's level of maturity by adopting the COBIT Framework 5. The COBIT Framework is one of the ISACA-issued frameworks that defines the concept of information technology governance. The BAI (Build, Acquire, and Implement) domain is the subject of this investigation. The BAI domain is one of the COBIT 5 Framework domains responsible for program and project management, description of needs, identification of solutions, building change availability and capacity, change acceptance and transition, knowledge, assets, and configuration. This study employs qualitative methods to perform literature reviews and question-and-answer sessions, and then collects quantitative analytical data through the formulation of statements or inquiries. There were 5 respondents who responded to the statement, and they implemented the system. The BAI domain of the CBT Examination System in Jakarta's Senior High School XYZ has been calculated and determined to be at level 4, indicating that the system is functioning appropriately. There are subdomains with a lower maturity level in BAI01, BAI02, BAI03, BAI04, BAI06, BAI07, and BAI08, specifically at a rate between 3.8 and 3.96. Additionally, BAI05, BAI09, and BAI10 contain subdomains with a higher level of maturity, with a value range of 4.07 to 4.15. All BAI subdomains culminate at level 4, the system's maturity level, with a value of 3.93. Level 4 indicates that the level of development for Managed and Measurable is fairly good. It can also provide recommendations for improvements, such as paying attention to project management methods before beginning implementation, being able to estimate the time required for the implementation process, and paying attention to the role of trained stakeholders. © 2023 IEEE.

关键词： Project management

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An Efficient Lightweight Authentication and Key Agreement Protocol for Patient Privacy

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computers, Materials & Continua 2021年第12期69卷 3495-3512页

作者： Seyed Amin Hosseini Seno Mahdi Nikooghadam Rahmat Budiarto Department of Computer Engineering Ferdowsi University of MashhadMashhad***Iran Department of Informatics Faculty of Science and TechnologyUniversitas Alazhar IndonesiaJakarta12110Indonesia

Tele-medical information system provides an efficient and convenient way to connect patients at home with medical personnel in clinical *** this system,service providers consider user authentication as a critical *** address this crucial requirement,various types of validation and key agreement protocols have been *** main problem with the two-way authentication of patients and medical servers is not built with thorough and comprehensive analysis that makes the protocol design yet has *** paper analyzes carefully all aspects of security requirements including the perfect forward secrecy in order to develop an efficient and robust lightweight authentication and key agreement *** secureness of the proposed protocol undergoes an informal analysis,whose findings show that different security features are provided,including perfect forward secrecy and a resistance to DoS ***,it is simulated and formally analyzed using Scyther *** results indicate the protocol’s robustness,both in perfect forward security and against various *** addition,the proposed protocol was compared with those of other related protocols in term of time complexity and communication *** time complexity of the proposed protocol only involves time of performing a hash function Th,i.e.,:O(12Th).Average time required for executing the authentication is 0.006 seconds;with number of bit exchange is 704,both values are the lowest among the other *** results of the comparison point to a superior performance by the proposed protocol.

关键词： Authentication key agreement protocol tele-medical Scyther perfect forward secrecy

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Identification of Acute Myeloid Leukemia (AML) Subtypes: M1, M2, M3 on White Blood Cells Using Microscopic Images 25

Identification of Acute Myeloid Leukemia (AML) Subtypes: M1,...

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25th International Electronics Symposium, IES 2023

作者： Azzahra, Soniya Jasmine Sigit, Riyanto Yuniarti, Heny Hernaningsih, Yetti Imannurohma, Ade Politeknik Elektronika Negeri Surabaya Departemen of Informatics and Computer Engineering Surabaya Indonesia Airlangga University Dr. Soetomo General Academic Hospital Faculty of Medicine Departemen of Clinical Pathology Surabaya Indonesia

ISBN: (纸本)9798350314731

Leukemia is a form of blood cancer characterized by an overproduction of abnormal white blood cells that invade the body's immune system. Leukemias are divided into four main groups based on cell type and growth rate. Acute Myeloid Leukemia (AML) is one of them, namely leukemia that occurs in the myeloid series. AML itself is divided into several subtypes, according to the French-American-British (FAB), namely M0-M7. AML subtypes M1, M2, and M3 are influenced by the same cell type, namely myeloblast cells, so a more detailed analysis is needed to classify them. Therefore we need a system that can identify the presence of AML in the blood, this identification is done by classifying white blood cells on microscopic images. To detect the presence of AML in microscopic images, multiple processes will be used, including preprocessing, segmentation, feature extraction, and classification stages by applying the K-NN method. This classification procedure will result in a diagnosis of M1, M2, or M3 blood cells. At the end of phase 1 of this final project, pre-processing and segmentation processes and graphical user interface (GUI) designs have been carried out. This final project resulted in an accuracy of 80% for the identification of subtype M1, 70% for the identification of subtype M2, and 80% for the identification of subtype M3. © 2023 IEEE.

关键词： Graphical user interfaces

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ClipArtGAN: An Application of Pix2Pix Generative Adversarial Network for Clip Art Generation

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Multimedia Tools and Applications 2025年 1-25页

作者： Elnabawy, Reham H. Abdennadher, Slim Hellwich, Olaf Eldawlatly, Seif Technische Universität Berlin Berlin Germany Computer Science and Engineering Department Faculty of Media Engineering and Technology German University in Cairo Cairo Egypt Computer Science Department Faculty of Informatics and Computer Science German International University New Administrative Capital Egypt Computer and Systems Engineering Department Faculty of Engineering Ain Shams University 1 El-sarayat st. Abbassia Cairo Egypt Computer Science and Engineering Department The American University in Cairo Cairo Egypt School of Information Technology New Giza University Giza Egypt

An image can convey a thousand words. This statement emphasizes the importance of illustrating ideas visually rather than writing them down. Although detailed image representation is typically instructive, there are several contexts where simplification of image representations may be more informative. One way to provide an abstract representation of an object is via clip art, which is a simple graphic illustration of an object that can be included in documents or presentations. Clip art representation can be utilized in graphic design for concepts expression and daily life objects illustration. Furthermore, clip art had shown remarkable advantages when compared to real images in terms of editing and manipulation since clip art geometry can be easily edited in addition to the feasibility of storing it in a resolution-independent manner. However, it can be difficult to automatically create clip arts that resemble any object. Here, we propose a novel deep learning model, named ClipArtGAN, that utilizes Generative Adversarial Networks (GANs) to convert a photo of an object to its corresponding clip art. To our knowledge, this is the first GAN model based on Pix2Pix architecture that is capable of automatically generating clip art for any arbitrary object. Three training datasets were collected to train and compare two GAN models based on Pix2Pix and CycleGAN architectures. Our results demonstrate that the mean accuracy obtained using ClipArtGAN utilizing Pix2Pix outperforms that of CycleGAN by 58% and that of Google Images-based search by 54%. These results indicate the efficacy of ClipArtGAN in generating representative clip art images. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Generative adversarial networks

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Chaotic binary reptile search algorithm and its feature selection applications

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Journal of Ambient Intelligence and Humanized Computing 2023年第10期14卷 13931-13947页

作者： Abualigah, Laith Diabat, Ali Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan Faculty of Information Technology Middle East University Amman11831 Jordan Division of Engineering New York University Abu Dhabi Saadiyat Island Abu Dhabi129188 United Arab Emirates Department of Civil and Urban Engineering Tandon School of Engineering New York University BrooklynNY11201 United States Faculty of Computer Sciences and Informatics Amman Arab University Amman11953 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang11800 Malaysia

Feature selection (FS) is known as the most challenging problem in the Machine Learning field. FS can be considered an optimization problem that requires an efficient method to prepare its optimal subset of relative features. This article introduces a new FS method-based wrapper scheme that mixes chaotic maps (CMs) and binary Reptile Search Algorithm (RSA) called CRSA, employed to address various FS problems. In this method, different chaotic maps are included with the main ideas of the RSA algorithm. The objective function is revealed to combine three objectives: maximizing the classification accuracy, the number of chosen features, and the complexity of produced wrapper models. To assess the achievement of the proposed methods, 20 UCI datasets are applied, and the results are compared with other well-known methods. The results showed the superiority of the introduced method in bettering other well-known techniques, particularly when applying binary RSA with Tent CM. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Feature Selection

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Generative AI, IoT, and blockchain in healthcare: application, issues, and solutions

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Discover Internet of Things 2025年第1期5卷 1-23页

作者： Mazhar, Tehseen khan, Sunawar Shahzad, Tariq khan, Muhammad Amir Saeed, Mamoon M. Awotunde, Joseph Bamidele Hamam, Habib School of Computer Science National College of Business Administration and Economics Lahore54000 Pakistan Department of Computer Science International Islamic University Islamabad44000 Pakistan Department of Computer Science COMSATS University Islamabad Sahiwal Campus Sahiwal57000 Pakistan School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia Sana’a Yemen Department of Computer Science Faculty of Communication and Information Sciences University of Ilorin Ilorin Nigeria Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Computer Science and Information Technology School Education Department Government of Punjab 31200 Layyah Pakistan School of Electrical Engineering University of Johannesburg Johannesburg2006 South Africa Av. Grandes Ecoles LibrevilleBP 1989 Gabon Bridges for Academic Excellence Spectrum Tunis Tunisia

This article discusses Blockchain and Generative AI in healthcare, including their uses, difficulties, and solutions. Blockchain technology improves EHR security, privacy, and interoperability, while smart contracts streamline supply chain management and administrative procedures. Blockchain verifies and secures IoT data, improving medical care and treatment, according to case studies. Generative AI systems like ChatGPT have transformed healthcare by personalizing therapy, diagnostics, and predictive analytics. AI systems can examine massive databases to diagnose diseases early, anticipate dangers, and personalize therapies. By providing timely information, boosting treatment adherence, and giving continuous support, AI-powered virtual health assistants have enhanced patient involvement. Generative AI has additionally enhanced medical research and drug development, cutting the time and expense of introducing new medicines. Generative AI and Blockchain provide safe patient data storage, high-quality AI training datasets, and efficient healthcare operations. Scalability, energy usage, and interoperability issues remain. Scalable Blockchain designs and standardized data integration and exchange protocols are suggested by this study. These technologies could improve medical research and therapy by making them safer, more effective, and more individualized. © The Author(s) 2025.

关键词： Electronic health record

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Multi-Robot Navigation Uses the Greedy Heuristic Algorithm Based on the ACO Algorithm

Multi-Robot Navigation Uses the Greedy Heuristic Algorithm B...

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International Conference on computer engineering, Network and Intelligent Multimedia (CENIM)

作者： Ahmad Zaini Muhtadin Hansen Ade Rioza Department of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350368802

ISBN: (纸本)9798350368819

Robot swarm navigation faces challenges in coordi-nation in dynamic environments with limited information, since each robot only has local access, making optimal paths difficult to achieve. Increasing the number of robots also increases the complexity of communication and decision-making, while energy efficiency remains a priority. The Ant Colony Optimization (ACO) algorithm mimics the behavior of ants through pheromone trails, allowing robots to leave virtual trails that guide other robots in forming optimal paths, allowing them to adapt to changing environments. In this paper, we propose an optimal multi-robot navigation system with ACO based on Greedy Heuristics to improve the efficiency of robots in dealing with static and dynamic obstacles, avoiding collisions, and preventing deadlocks. The test results obtained the shortest distance of 31.2132034 meters with alpha parameters of 3 points and beta of 4 points as the optimum parameter configuration according to the method used.

关键词： Meters Navigation Heuristic algorithms MIMICs System recovery Energy efficiency Collision avoidance Robots Optimization Faces

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Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma

arXiv

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arXiv 2025年

作者： Aydın, Ömer Karaarslan, Enis Erenay, Fatih Safa Džakula, Nebojša Bačanin Manisa Celal Bayar University Faculty of Engineering and Natural Sciences Department of Computer Sciences Manisa Turkey University of Waterloo Faculty of Engineering Management Science and Engineering Ontario Canada Mugla Sitki Kocman University Faculty of Engineering Department of Computer Engineering Mugla Turkey Singidunum University Faculty of Informatics and Computing Belgrade Serbia

Deepseek and Qwen LLMs became popular at the beginning of 2025 with their low-cost and open-access LLM solutions. A company based in Hangzhou, Zhejiang, China, announced its new LLM, DeepSeek v3, in December 2024. Then, Alibaba released its AI model, Qwen 2.5 Max, on January 29, 2025. These tools, which are free and open-source have made a significant impact on the world. Deepseek and Qwen also have the potential to be used by many researchers and individuals around the world in academic writing and content creation. Therefore, it is important to determine the capacity of these new LLMs to generate high-quality academic content. This study aims to evaluate the academic writing performance of both Qwen 2.5 Max and DeepSeek v3 by comparing these models with popular systems such as ChatGPT, Gemini, Llama, Mistral, and Gemma. In this research, 40 articles on the topics of Digital Twin and Healthcare were used. The method of this study involves using generative AI tools to generate texts based on posed questions and paraphrased abstracts of these 40 articles. Then, the generated texts were evaluated through the plagiarism tool, AI detection tools, word count comparisons, semantic similarity tools and readability assessments. It was observed that plagiarism test result rates were generally higher for the paraphrased abstract texts and lower for the answers generated to the questions, but both were above acceptable levels. In the evaluations made with the AI detection tool, it was determined with high accuracy that all the generated texts were detected as AI-generated. In terms of the generated word count comparison, it was evaluated that all chatbots generated satisfactory amount of content. Semantic similarity tests show that the generated texts have high semantic overlap with the original texts. The readability tests indicated that the generated texts were not sufficiently readable. © 2025, CC BY.

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