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2024 International Conference on Circuit, Systems and Communication, ICCSC 2024

作者： Elalaouy, Ouafae Aghoutane, Bilal El Ghzaoui, Mohammed Das, Sudipta Foshi, Jaouad El Faylali, Hanan University of Moulay Ismail Faculty of Sciences and Techniques Errachidia Errachidia Morocco Faculty of Sciences IbnTofail University Informatics Systems and Optimization Laboratory Department of Computer Science Kenitra Morocco Sidi Mohamed Ben Abdellah University Faculty of Sciences Dhar El Mahraz Fes Morocco Imps College of Engineering and Technology Department of Electronics and Communication Engineering W.B Malda India

ISBN: (纸本)9798350365306

In the contemporary era, harnessing millimeter-wave frequencies emerges as a compelling strategy to fulfill the swift data transfer requirements for 5G communications. Consequently, this study involves designing a metamaterial-based multiple-input multiple-output (MIMO) antenna with a focus on achieving high isolation and gain within the millimeter-wave spectrum. The suggested MIMO is printed on a Rogers RT5800 measuring 18 × 38 × 0.8 mm3. The single antenna element demonstrates a broad frequency coverage from 27.2 to 28.72GHz. To elevate the antenna's effectiveness, a two-port MIMO configuration is implemented by introducing a second antenna element parallel to benchmark antenna. However, the isolation between the two elements is deemed satisfactory. To address this, a 4 × 1 metamaterial unit cell is introduced, significantly enhancing isolation from 31 dB to 39 dB at 28 GHz. Furthermore, it improves the gain by 0.5 dBi at 28 GHz, elevating it from 8.5 to 9 dBi. The collective features of the suggested two ports MIMO antenna, encompassing its compactness and simplicity, position it as an excellent option for upcoming portable and shrink devices in Internet of Things uses. © 2024 IEEE.

关键词： Microwave antennas

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Manufacturing A Low-Cost Telegram and Optical Character Recognition-Based Indoor Air Quality Monitoring Data Logger 8

Manufacturing A Low-Cost Telegram and Optical Character Reco...

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

作者： Pramono, Andi Budiman, Satrio Arif Farchan, Muchammad Mappaturi, Andi Baso School of Design Bina Nusantara University Interior Design Department Jakarta11480 Indonesia Brawijaya University Information System Computer Science Faculty Malang65145 Indonesia Institut Teknologi Sepuluh Nopember Faculty of Intelligent Electrical and Informatics Technology Department of Electrical Engineering Surabaya60111 Indonesia Islamic State University of Maulana Malik Ibrahim Faculty of Science and Technology Architecture Department Malang Indonesia

ISBN: (纸本)9798350326093

Urban air is frequently contaminated with CO, CO2, VOC, HCHO, PM 2.5, and PM 10. Rural regions are at a lower risk than those near roads and industrial areas that produce emissions. Air pollutants negatively affect its inhabitants' health, particularly the respiratory system. Most people will spend more time indoors, requiring a method for monitoring indoor air quality (IAQ). Urban communities need IAQ monitoring instruments as an early warning system for their health. This research seeks to produce inexpensive IAQ that can be utilized by all levels of society, particularly urban communities. This research utilizes a qualitative, design-thinking-based methodology. The research diverged from Empatize, which asserts that urban communities require a method for determining the local air quality. Moreover, it is determined at the define stage that IAQ monitoring, which includes a data log feature, is still comparatively expensive, so a solution is developed at the ideate stage. Creating a prototype is the next step in realizing the specified solution. In this investigation, they decided to use IAQ monitoring, which is relatively inexpensive but lacks log data storage. The author uses the ESP32-cam microcontroller to capture the screen display device, and the resulting image is sent to a telegram and processed with optical character recognition (OCR) to generate a data log. The results of prototype testing are utilized for prototype development. © 2023 IEEE.

关键词： Industrial emissions

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Multi-objective VNF Placement Optimization with NSGA-III 1st

Multi-objective VNF Placement Optimization with NSGA-III

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1st International Conference on Advances in Computing Research, ACR’23

作者： Bekhit, Mahmoud Fathalla, Ahmed Eldesouky, Esraa Salah, Ahmad Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia Kent Institute Australia Melbourne Australia Department of Mathematics Faculty of Science Suez Canal University Ismailia Egypt Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia College of Computers and Informatics Zagazig University Zagazig Egypt College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman

ISBN: (纸本)9783031337420

With the rising acceptance of virtual network functions (VNFs) as a replacement for traditional network functions, the optimal placement of VNFs has become a crucial task for ensuring constant performance within constrained resources. This research investigates the challenge of mapping and scheduling VNFs as a multi-objective optimization problem. The state-of-the-art methods have focused on optimizing the mapping or scheduling of VNFs while considering one or two objectives continuously. In this study, we aim to optimize two objectives: minimizing the link capacity cost and maximizing the average resource utilization of each virtual machine. To address this problem, an adaptation of the NSGA-III optimization algorithm is proposed and thoroughly evaluated through a set of experiments. In terms of objective values, the results outlined that the proposed method outperformed the other methods of comparison by a significant margin. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mapping

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Multiobjective Branch-and-Cut Method with Shared Cutting Plane Information: A Case Study on Optimizing Garbage Collection

Multiobjective Branch-and-Cut Method with Shared Cutting Pla...

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International Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Tomoki Kaho Kazutoshi Sakakibara Mikiharu Arimura Shinya Watanabe The Graduate School of Engineering Muroran Institute of Technology Muroran Japan Department of Data Science Faculty of Information Engineering Toyama Prefectural University Toyama Japan Department of Engineering Muroran Institute of Technology Muroran Japan Department of Sciences and Informatics Muroran Institute of Technology Muroran Japan

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

This paper presents an application of the Multi-Objective Branch-and-Bound based on Decomposition (MOBB/D) method for Branch-and-Cut, combining branch-and-bound and cutting-plane methods. Traditionally, multi-objective branch-and-bound methods for multi-objective mixed-integer linear programming problems struggle with the large number of Pareto-optimal solutions. MOBB/D addresses this by decomposing multi-objective problems into single-objective subproblems using weight vectors and applying branch-and-bound to each, with information sharing between nearby subproblems. In this paper, we customize the MOBB/D method for Branch-and-Cut to achieve an efficient search by sharing cutting plane information in MOBB/D. We demonstrate our approach with a case study on garbage collection planning in Muroran City, Hokkaido, Japan. This case study combines facility location and route optimization within a multi-objective framework, balancing the burdens on residents and garbage collection workers. Numerical experiments compare execution times and solutions with and without cutting plane sharing, and visualize the impact of different objective balance preferences on route optimization. The results show substantial efficiency gains and provide practical insights for multi-objective optimization in urban planning.

关键词： Visualization Scalability Roads Urban planning Vectors Real-time systems Planning Mixed integer linear programming Computational efficiency Optimization

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A Bibliometric and Social Media Analysis of the Nexus Between Blockchain technology and Finance 2nd

A Bibliometric and Social Media Analysis of the Nexus Betwee...

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2nd International Conference on Intelligent Manufacturing and Robotics, ICIMR 2024

作者： Ayodele, Olamide Emmanuel Ajibade, Temiloluwa Iyanuoluwa Oyebode, Oluwadare Joshua Akintoye, Kayode Akinlekan Ajayi, Babatunde Adedotun Adediran, Anthonia Oluwatosin Ajibade, Samuel-Soma M. Majeed, Anwar P. P. Abdul Luo, Yang Department of Banking and Finance Ekiti State University Ekiti State Ado Ekiti Nigeria Department of Business Management Scholar School System Birmingham United Kingdom Civil and Environmental Engineering Afe Babalola University Ekiti State Ado Ekiti Nigeria Department of Computer Science The Federal Polytechnic Ekiti State Ado Ekiti Nigeria Department of Cyber Security Faculty of Computing and Informatics Ladoke Akintola University of Technology Ogbomoso Nigeria Department of Real Estate Faculty of Built Environment Universiti Malaya KL Kuala Lumpur Malaysia Department of Data Science and Artificial Intelligence Faculty of Engineering and Technology Sunway University Selangor Malaysia Department of Computer Engineering Istanbul Ticaret University Istanbul Turkey Suzhou Taicang215400 China

ISBN: (纸本)9789819639489

This study explores Blockchain technology in the global financial industry using trends analysis, bibliometric analysis, and a literature appraisal using Elsevier Scopus data from 2016 to 2023. The Blockchain in Finance (BCF) study produced 185 publications: 53.5% papers, 45.4% conference proceedings, and 1.1% reviews. Analysis of the subject area revealed three important Computer science, engineering, and Decision sciences articles. However, source title analysis showed that ACM International Conference Proceeding Series, Sustainability Switzerland, and E3S Web of Conferences publish BCF research most often. According to the stakeholders study, Jon M. Truby and Qatar University (Qatar) are the top BCFin researchers and affiliations with 4% and % publications, respectively. China produces the most research on the topic. Due to active support from funding sources like the Chinese National Natural science Foundation (NNSF), 18 publications have been funded. Co-occurrence of keywords The investigation indicated that BCFin’s top keywords include Blockchain, Finance, and Supply Chain Finance. Three clusters with 4–8 keywords, 132 linkages, and 866 TLS were found via cluster analysis. Keywords classify the clusters as Integrated Business Solutions (Cluster 1), Digital Commerce Infrastructure (Cluster 2), and Decentralized Financial Network (Cluster 3). The findings indicate that BCFin is a dynamic and influential multidisciplinary study field. BCFin has transformed the global financial sector by improving trust, transaction security, and communication. It still struggles with interoperability, system integration, and sustainability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Decentralized finance

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An Evaluation of Integrating ERP System to Develop a Strategy Business 8

An Evaluation of Integrating ERP System to Develop a Strateg...

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

作者： Wijaya, Santo Fernandi Wiratama, Jansen Kuswanto, Verri School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Universitas Multimedia Nusantara Faculty of Engineering and Informatics Information Systems Department Tangerang11480 Indonesia Buddhi Dharma University Faculty of Science and Technology Information Systems Department Tangerang11480 Indonesia

ISBN: (纸本)9798350326093

The digital changes business patterns that require companies by using an integrated system for strategic decision-making. ERP system is one technological innovation that enable to have a competitive advantage. But the fact is that only a few companies have succeeded in implementing the ERP system. The objective of this research is to integrate the ERP system with business strategy in implementing ERP systems. The research focuses on developing an ERP system integration model for implementing the SAP ERP success. The methodology is based on previous research for the ERP implementation. This research examines quantitative data to determine indicators using entropy and conducts case studies in the industry. The research results prove that the management support indicator is an essential factor in integrating ERP systems to develop the company's strategic business. The output research is the design of the integration model development of the ERP system. © 2023 IEEE.

关键词： Decision making

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A Lightweight and Robust Access Control Protocol for IoT-based e-Healthcare Network

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IEEE Transactions on Mobile Computing 2025年

作者： Ghaffar, Zahid Kuo, Wen-Chung Mahmood, Khalid Tariq, Tayyaba Shamshad, Salman Das, Ashok Kumar Alenazi, Mohammed J.F. National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Douliu64002 Taiwan National Yunlin University of Science and Technology Department of Computer Science and Information Engineering Douliu64002 Taiwan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University Department of Computer Science and Engineering College of Informatics 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh Saudi Arabia

Internet of Things (IoT) devices are crucial components in e-healthcare networks. It enables remote patient health monitoring and facilitates seamless communication among medical sensors, wearable devices, and healthcare providers through public communication channels. Despite these advantages, the use of public communication among medical sensors in e-healthcare networks introduces critical challenges, such as vulnerability to impersonation, physical capture, and ephemeral secret leakage, particularly in resource-constrained environments. In recent years, various access control protocols have been developed to mitigate these risks. However, these protocols often fail to ensure robust security while incurring significant communication and computation overhead. To overcome these limitations, we propose a lightweight and robust access control protocol for IoT-based e-healthcare networks using chaotic maps. We propose a novel protocol that integrates a PUF-based mechanism to mitigate the challenges of physical tampering and cloning attacks in e-healthcare networks. It leverages the inherent uniqueness of PUF and enhances security through the high-entropy properties of chaotic maps. We analyze the proposed protocol informally, which confirms that it significantly bolsters efficiency and security. We also validate the security using the Random or Real (RoR) model. Moreover, we verify the security of the proposed protocol using Scyther. These analyses highlight that the proposed protocol offers robust resistance to numerous attacks, such as impersonation, physical capture, and ephemeral secret leakage. Moreover, we also compare it with existing and relevant protocols. The comparative analysis showcases its superior performance. Notably, the proposed authentication protocol significantly reduces 46.84% computational overhead and decreases 31.30% communication overhead, underscoring its enhanced performance and resource efficiency. © 2002-2012 IEEE.

关键词： Authentication

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Classification of Medicinal Wild Plants Using Radial Basis Function Neural Network with Least Mean Square 2

Classification of Medicinal Wild Plants Using Radial Basis F...

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2nd International Conference on Electronic and Electrical engineering and Intelligent System, ICE3IS 2022

作者： Borman, Rohmat Indra Rossi, Farli Alamsyah, Dedy Nuraini, Rini Jusman, Yessi Fauziyah Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Universitas Muhammadiyah Tangerang Faculty of Engineering Tangerang Indonesia Universitas Nasional Jakarta Faculty of Communication Technology and Informatics Selatan Indonesia Universitas Muhammadiyah Yogyakarta Faculty of Engineering Department of Electrical Engineering Yogyakarta Indonesia University of Science and Technology Beijing Faculty of Engineering Beijing China

ISBN: (纸本)9781665465410

Wild plants are considered as plants whose growth interferes with other plants. However, in its development it turns out that wild plants contain ingredients for medicines. However, information and knowledge about wild plant species, especially plants with herbaceous vegetation, needs to be carried out with various technologies, including through digital image processing. This study aims to develop a classification model for medicinal plant species using color and texture extraction using the Radial Basis Function Neural Network (RBFNN) algorithm with a combination of the Least Mean Square (LMS) algorithm. Color feature extraction is obtained by calculating the RGB average value and texture feature extraction using a Gabor filter obtained from the mean, entropy, and variance parameters. The result of feature extraction becomes input for RBFNN with LMS. RBFNN has three layers that have feedforward properties that can assist in solving classification or pattern recognition problems. The LMS algorithm is used for learning or updating neural network weights. Based on the test results by calculating precision, recall, and accuracy, it gets a precision value of 92.50%, recall gets a value of 91.74, accuracy gets a value of 92.08. These results indicate that the developed model can classify wild plant species with medicinal properties well. © 2022 IEEE.

关键词： Gabor filters

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An Enhanced Residual Networks Based Framework for Early Alzheimer’s Disease Classification and Diagnosis 6th

An Enhanced Residual Networks Based Framework for Early Alzh...

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6th International Conference on Communication, Devices and Networking, ICCDN 2022

作者： Awotunde, Joseph Bamidele Sur, Nath Samarendra Imoize, Agbotiname Lucky Misra, Sanjay Gaber, Tarek Department of Computer Science Faculty of Information and Communication Sciences University of Ilorin Kwara State Ilorin240003 Nigeria Department of Electronics and Communication Engineering Sikkim Manipal Institute of Technology Sikkim Manipal University East Sikkim Rangpo Majitar737136 India Department of Electrical and Electronics Engineering Faculty of Engineering University of Lagos Akoka Lagos100213 Nigeria Department of Electrical Engineering and Information Technology Institute of Digital Communication Ruhr University Bochum44801 Germany Department of Applied Data Science Institute of Energy Technology Halden Norway Faculty of Computers and Informatics Suez Canal University Ismailia41522 Egypt School of Science Engineering and Environment University of Salford ManchesterM5 4WT United Kingdom

ISBN: (纸本)9789819919826

Alzheimer's disease (AD) is a long-lasting, degenerative brain illness for which there is now no successful treatment. However, there are medications that can delay its growth and stop its tracks. Therefore, stopping and regulating the progression of AD depends greatly on its early diagnosis. Computer-aided diagnosis (CAD) in health care has become more and more dependent on deep learning technologies. This has help in early diagnosis and detection of various disease in health care. New techniques for the early diagnosis of neurocognitive abnormalities are now possible thanks to advancements in medical imaging and computational capacity in an effort to stop or slow down cognitive aging. Therefore, this study proposes a residual network (ResNet) type 50 for early diagnosis of AD. Convolutional neural networks (CNNs) are first used in the study for features extraction and then make the ultimate diagnosis using the ResNet-50. To create a better architecture, the problem of AD diagnosis will be addressed by utilizing and incorporating ResNet-50, which improves the current categorization problem's accuracy to its maximum. With a 98.8% accuracy rate, the proposed model using ResNet-50 produces encouraging findings for AD prediction. The study reveals that the model can effectively circumvent CNNs for the diagnostic issue with AD. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computer aided diagnosis

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PAVLM: Advancing Point Cloud based Affordance Understanding Via Vision-Language Model

arXiv

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arXiv 2024年

作者： Liu, Shang-Ching Tran, Van Nhiem Chen, Wenkai Cheng, Wei-Lun Huang, Yen-Lin Liao, I-Bin Li, Yung-Hui Zhang, Jianwei Department of Informatics University of Hamburg Germany Taiwan Department of Electrical Engineering National Taiwan University Taiwan Department of Computer Science and Technology National Tsinghua University Taiwan

Affordance understanding, the task of identifying actionable regions on 3D objects, plays a vital role in allowing robotic systems to engage with and operate within the physical world. Although Visual Language Models (VLMs) have excelled in high-level reasoning and long-horizon planning for robotic manipulation, they still fall short in grasping the nuanced physical properties required for effective human-robot interaction. In this paper, we introduce PAVLM (Point cloud Affordance Vision-Language Model), an innovative framework that utilizes the extensive multimodal knowledge embedded in pre-trained language models to enhance 3D affordance understanding of point cloud. PAVLM integrates a geometric-guided propagation module with hidden embeddings from large language models (LLMs) to enrich visual semantics. On the language side, we prompt Llama-3.1 models to generate refined context-aware text, augmenting the instructional input with deeper semantic cues. Experimental results on the 3D-AffordanceNet benchmark demonstrate that PAVLM outperforms baseline methods for both full and partial point clouds, particularly excelling in its generalization to novel open-world affordance tasks of 3D objects. For more information, visit our project site: ***. © 2024, CC BY-NC-ND.

关键词： Human robot interaction

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