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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Guslendra Yuhandri Sarjon Defit Department of Information System Computer Science Faculty Universitas Putra Indonesia YPTK Padang Indonesia Department of Information Technology Computer Science Faculty Universitas Putra Indonesia YPTK Padang Indonesia

CT-Scan is a computer-based imaging technology, but it presents certain weaknesses, including interpretation challenges, lengthy analysis times, and visualization limitations. The progress in digital image processing science empowers computers to identify objects through recognizing distinctive features. To facilitate further data processing, an image cropping method is essential to narrow down the area of interest, as not all parts of an object require processing. However, using a rectangular cropping method can lead to a reduction in image size, potentially compromising image quality and causing blurring when displayed on the same axes. To uphold image quality and avert blurring, maintaining the cropped image’s size becomes crucial. The developed rectangular cropping method successfully preserves the cropped image’s size by adjusting the intensity values of pixels surrounding the cutting point. Coordinate points within the cropping rectangle delineate the region where pixel intensity values are modified. In this study, input images were sourced from CT-scan images of M. Djamil Hospital, Padang, West Sumatra, in jpg format. The developed algorithm underwent testing using the Matlab program, employing the rectangle method for image cropping to ensure the image size remained constant. The study’s outcomes reveal no disparity in the number of pixels obtained when employing the developed rectangular cropping method. Based on the experiments carried out in this study using 8 input images that were successfully maintained, the size of the image from the cropped image was 8 images and 0 images were unsuccessful, so the accuracy obtained in this study was 100%.

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Research on emotional space for movie and TV drama videos

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The Journal of China Universities of Posts and Telecommunications 2022年第5期29卷 73-82页

作者： Li Yujie Zhang Jingjing Jiang Wei Wang Chunxiao Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijing 100024China Beijing Key Laboratory of Modern Entertainment Technology Communication University of ChinaBeijing 100024China School of Information and Communication Engineering Communication University of ChinaBeijing 100024China School of Computer and Cyber Sciences Communication University of ChinaBeijing 100024China

Emotional space refers to a multi-dimensional emotional model that describes a group of subjective feelings or emotions. Since the existing discrete emotional space is mainly aimed at human’s primary emotions, it cannot describe the complex emotions evoked when watching movies. In order to solve this problem, an emotional fusion space for videos was constructed by selecting movies and TV dramas with rich emotional semantics as the research objects. Firstly, emotional words based on movie and TV drama videos are acquired and analyzed by using subjective evaluation and semantic analysis methods. Then, the emotional word vectors obtained from the above analysis are fused, reduced dimension by t-distributed stochastic neighbor embedding(t-SNE) algorithm, and clustered by bisecting K-means clustering algorithm to get a discrete emotional space for movie and TV drama videos. This emotional fusion space can obtain different categories by changing the value of the emotion classification number without re-labeling and calculation.

关键词： emotional space movie and TV drama videos subjective evaluation words semantic analysis fusion space

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CC-Net: Consistency Learning Combined with Contrastive Learning for Kidney Ultrasound Segmentation

CC-Net: Consistency Learning Combined with Contrastive Learn...

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IEEE International Conference on systems, Man and Cybernetics

作者： Yang Luo Jun Liu Mengqian Ding School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Due to the scarcity of medical images with labels and the fact that medical image data is not easily accessible. Kidney ultrasound (KUS) images have speckle noise, low image quality, acoustic shadows, and other reasons, which pose significant challenges to the kidney ultrasound image segmentation task. To solve the above two problems, a novel consistency learning and contrastive learning-based kidney ultrasound image segmentation method (CC-Net) has been proposed. Specifically, the student-teacher model was adopted as the semi-supervised learning framework and uncertainty estimation was introduced. The Consensus Uncertainty Map (CUM) strategy was proposed to generate segmentation results for the teacher model when calculating uncertainty. To solve the problems of acoustic shadows and low image quality in kidney ultrasound images, a kidney ultrasound image data augmentation method (KUS-AUG) and a convolutional block (KUS-CONV) tailored to the characteristics of kidney ultrasound images were proposed. In addition, contrastive learning was implemented to enhance the encoder's ability to learn more semantic information, due to its inherent advantage in learning data distribution. Finally, a series of experiments were conducted on the ultrasound image dataset and the method achieved the best performance.

关键词： Image quality Image segmentation Ultrasonic imaging Uncertainty Noise Contrastive learning Semisupervised learning Acoustics Kidney Biomedical imaging

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Robust Dynamic Broadcasting for Multi-Hop Wireless Networks Under Time-Varying Connectivity and Dynamic SINR

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IEEE Transactions on Mobile Computing 2025年

作者： Tian, Xiang Yu, Jiguo Luo, Chuanwen Yu, Dongxiao Wang, Guijuan Feng, Bin Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250353 China University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu610054 China Qilu University of Technology Big Data Institute Jinan250353 China Beijing Forestry University School of Information Science and Technology Beijing100083 China Shandong University School of Computer Science and Technology Shandong Qingdao266237 China Taishan University School of Information Science and Technology 271000 China

Throughput-optimal dynamic broadcasting is an essential cornerstone for the efficient operation of Multi-hop Wireless Networks (MWNs). Most existing algorithms for this problem were developed assuming static interference environments and network connectivity. However, wireless interference environments and network connectivity are inherently time-varying in real-world scenarios, primarily due to uncontrollable interference sources and unreliable links. Such time-varying characteristics make these existing algorithms less robust. In this paper, we study the robust throughput-optimal dynamic broadcasting for MWNs with multi-dimensional time-varying characteristics in terms of interference environments, network connectivity, and data arrival. We model the time-varying link existence states using a random process and characterize the time-varying interference environments through a dynamic variant of the classical Signal-to-Interference-plus-Noise-Ratio (SINR) model. In this variant, the SINR model parameters are dynamically adjusted over time by an adversary. Based on this, we first design a Robust Throughput-optimal Dynamic Broadcast (RTDB) algorithm which makes efficient slot-based max-weight link scheduling, power allocation, and data forwarding decisions in each time slot. We then prove its throughput-optimality in time-varying acyclic directed MWNs under the dynamic SINR model. The effectiveness of RTDB is validated via numerous simulations. © 2002-2012 IEEE.

关键词： Signal to noise ratio

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Corporate Reputation Risk in Social Media 2

Corporate Reputation Risk in Social Media

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2nd International Conference on computer Science and Engineering, IC2SE 2021

作者： Hamidi, Saidatul Rahah Akmar Ismail, Maizatul Shuhidan, Shuhaida Mohamed Faculty of Computer Science and Information Technology Department of Information System Kuala Lumpur50 603 Malaysia Faculty of Computer and Mathematical Sciences Department of Computer Science Shah Alam Selangor40450 Malaysia

ISBN: (纸本)9781665400459

In today's world, digital platforms such as social media have become one of the most influential media sources. This may give an impact on company reputation due to massive user-generated content. However, due to its vast volume and unstructured nature, manual classification of these digital contents is difficult. Previous studies, evaluate corporate reputation using machine learning-focused mostly on positive, neutral, and negative aspects and lacking the multidimensional nature of corporate reputation. Therefore, this paper aimed to explore the integration of the domain ontology approach with machine learning approaches to achieve multi-dimensional classification for online corporate reputation. Overall research route to measure corporate reputation in social media is discussed. The proposed research route starts from retrieving corporate content from digital media for selected domain, next preprocessing data before topics and bag-of-words generated from the extracted data and mapping according to corporate reputation dimensions. The proposed approach is expected to produce a framework for an online corporate reputation that can be used across multiple business domains. © 2021 IEEE.

关键词： Sentiment analysis

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Advances in Noble Metal-Decorated Metal Oxide Nanomaterials for Chemiresistive Gas Sensors:Overview

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Nano-Micro Letters 2023年第6期15卷 353-427页

作者： Li‑Yuan Zhu Lang‑Xi Ou Li‑Wen Mao Xue‑Yan Wu Yi‑Ping Liu Hong‑Liang Lu State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics and SystemsSchool of MicroelectronicsFudan UniversityShanghai 200433People’s Republic of China School of Opto‑Electronic Information and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093People’s Republic of China State Key Laboratory of Metal Matrix Composites School of Material Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China

Highly sensitive gas sensors with remarkably low detection limits are attractive for diverse practical application fields including real-time environmental monitoring,exhaled breath diagnosis,and food freshness *** various chemiresistive sensing materials,noble metal-decorated semiconducting metal oxides(SMOs)have currently aroused extensive attention by virtue of the unique electronic and catalytic properties of noble *** review highlights the research progress on the designs and applications of different noble metal-decorated SMOs with diverse nanostructures(e.g.,nanoparticles,nanowires,nanorods,nanosheets,nanoflowers,and microspheres)for high-performance gas sensors with higher response,faster response/recovery speed,lower operating temperature,and ultra-low detection *** key topics include Pt,Pd,Au,other noble metals(e.g.,Ag,Ru,and Rh.),and bimetals-decorated SMOs containing ZnO,SnO_(2),WO_(3),other SMOs(e.g.,In_(2)O_(3),Fe_(2)O_(3),and CuO),and heterostructured *** addition to conventional devices,the innovative applications like photo-assisted room temperature gas sensors and mechanically flexible smart wearable devices are also ***,the relevant mechanisms for the sensing performance improvement caused by noble metal decoration,including the electronic sensitization effect and the chemical sensitization effect,have also been summarized in ***,major challenges and future perspectives towards noble metal-decorated SMOs-based chemiresistive gas sensors are proposed.

关键词： Noble metal Bimetal Semiconducting metal oxide Chemiresistive gas sensor Electronic sensitization Chemical sensitization

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A Survey of information Security Roles and Trends in the Quranic Perspective

A Survey of Information Security Roles and Trends in the Qur...

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Cyber Security and Computing (CyberComp), International Conference on

作者： Mohd Amin Mohd Yunus Nurul Hidayah Ab Rahman Isredza Rahmi A. Hamid Applied Information System Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit Raja Malaysia Centre of Information Security Research Universiti Tun Hussein Onn Malaysia Parit Raja Malaysia

ISBN: (数字)9798350387728

ISBN: (纸本)9798350387735

In this study, we surveyed the existing information security literature related to the Quran to contribute to the knowledge gap(s) in seeking the role of information security in the Quran research area. Materials published in English were located between January 2019 and February 2024 by searching various academic databases, including Google Scholar, IEEEXplore, ACM Digital Library, Springer and ScienceDirect. Thirty-two publications were collected and classified into ten domains of information security Common Body of Knowledge to identify the research trends. The results show that Domain 3 (Cryptography and Digital Watermarking) is the most studied area, followed by Domain 2 (Ethical and Legal Issues) with eight publications and Domain 5 (Access Control) with three publications. Other domains consist of only 1 or 2 publications each. Our observation also showed that three recurring themes of studies that are the implementation of information security techniques to preserve digital Quran authenticity, the association of Quran verses in supporting information security approaches; and the development of information security techniques from the Quran epistemology. Overall, exploring the research trends and interconnected areas could lead to advancements in information security practices and Quranic studies, fostering how traditional wisdom influences modern technologies.

关键词： Surveys Ethics Law Databases information security Watermarking Market research Libraries Internet Cryptography

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MAML MOT: Multiple Object Tracking Based on Meta-Learning

MAML MOT: Multiple Object Tracking Based on Meta-Learning

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IEEE International Conference on systems, Man and Cybernetics

作者： Jiayi Chen Chunhua Deng School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

With the advancement of video analysis technology, the multi-object tracking (MOT) problem in complex scenes involving pedestrians is gaining increasing importance. This challenge primarily involves two key tasks: pedestrian detection and re-identification. While significant progress has been achieved in pedestrian detection tasks in recent years, enhancing the effectiveness of re-identification tasks remains a persistent challenge. This difficulty arises from the large total number of pedestrian samples in multi-object tracking datasets and the scarcity of individual instance samples. Motivated by recent rapid advancements in meta-learning techniques, we introduce MAML MOT, a meta-learning-based training approach for multi-object tracking. This approach leverages the rapid learning capability of meta-learning to tackle the issue of sample scarcity in pedestrian re-identification tasks, aiming to improve the model's generalization performance and robustness. Experimental results demonstrate that the proposed method achieves high accuracy on mainstream datasets in the MOT Challenge. This offers new perspectives and solutions for research in the field of pedestrian multi-object tracking.

关键词： Metalearning Training Pedestrians Accuracy Robustness Object tracking Optimization Cybernetics

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The Automated Future: How AI and Automation Are Revolutionizing Online Services

The Automated Future: How AI and Automation Are Revolutioniz...

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IEEE International Conference on Engineering Technologies and Applied Sciences (ICETAS)

作者： Abdulla Jaafar Desmal Mohamed Alsaeed Suraya Hamid Ali Hussain Zulait College of Computer Studies University of Technology Bahrain Salmabad Bahrain Department of Information System Universiti Malaya Kuala Lumpur Malaysia College of Information Technology University of Bahrain Sakhair Bahrain

Artificial intelligence (AI) and automation are rapidly transforming the landscape of online services. From intelligent chatbots to hyper-personalized recommendations, AI-driven technologies are enabling online providers to deliver more customized, streamlined, and human-like digital experiences. This paper examines the growing role and impacts of AI and automation across a range of online industries, products, and interactions. It analyzes key applications like natural language processing, computer vision, predictive analytics, and robotic process automation that are automating everything from customer service to supply chain logistics. The benefits of these technologies, including 24/7 availability, scalability, and cost savings, are discussed along with challenges around data privacy, transparency, and workforce impacts. The paper underscores how AI and automation will shape the future of how companies engage and serve digital consumers. As online providers continue to collect more data and refine predictive algorithms, they edge closer to delivering truly individualized services tailored to customers' ever-evolving preferences and needs. However, realizing the promise of AI will require addressing critical issues around bias, ethics, and accountability. This paper provides a comprehensive look at the current landscape and future trajectory of AI and automation in online services.

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Feedback for Excellence: Improving mGovernment Services Through User Insights

Feedback for Excellence: Improving mGovernment Services Thro...

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Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT), International Conference o

作者： Abdulla Jaafar Desmal Mohamed Alsaeed Ali Hussein Zolait Suraya Hamid College of Computer Studies University of Technology Bahrain Salmabad Bahrain College of Information Technology University of Bahrain Sakhair Bahrain Department of Information System Universiti Malaya Kuala Lumpur Malaysia

User feedback is an approach for users to review the service process and plays a critical role in reviewing service approaches. One of these is Mobile Government (eGovernment) services, which aim to facilitate government services for public use. As mobile government (mGovernment) services gain prominence in public service delivery, understanding user insights and feedback is paramount for ensuring service excellence. Using a systematic Literature Review (SLR), the authors gathered and analyzed qualitative studies that explored user perspectives, experiences, and expectations related to the role of users' feedback on online services. This review highlights critical areas for service improvement, including user interface design, accessibility, responsiveness, and information accuracy. By synthesizing and integrating user insights, this study recommends optimizing mGovernment services and creating more user-centric platforms. The findings contribute to the existing body of knowledge on mGovernment service quality and offer practical implications for policymakers and service providers. By prioritizing user feedback and incorporating it into service design and development, mGovernment platforms can be tailored to meet users’ needs, ultimately enhancing their overall experience and engagement with public services.

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