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检索条件"任意字段=International Conference on Advances in Information Communication Technology and Computing"

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Transformating trigonometric function to apply in software reliability modeling 3rd

Transformating trigonometric function to apply in software r...

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3rd international conference on advances in information and communication technology, ICTA 2024

作者： Hung-Cuong, Nguyen Quyet-Thang, Huynh Trung-Nghia, Phung Dai-Nghia, Vy Hung Vuong University Phu Thọ Viet Nam Hanoi University of Science and Technology Ha Noi Viet Nam Thai Nguyen University University of Information and Communication Technology Thai Nguyen city Viet Nam

ISBN: (纸本)9783031809422

There are three types of S-shaped functions in non-homogeneous Poisson process Software reliability models. The advantages of this shape in this area are demonstrated when many models are proposed based on those functions. This paper evaluates the applicability of the 4th type S-shaped function, the trigonometric functions. However, those functions should be transformed to adapt to the real conditions. The mathematic calculations show that there is a possibility to use the trigonometric functions to introduce a new software reliability model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Software reliability

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Classification of nuclei in whole slide imaging based on ensemble deep learning

Classification of nuclei in whole slide imaging based on ens...

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international conference on Innovation and Technological advances for Sustainability, ITAS 2023

作者： Al-Thelaya, Khaled Alzubaidi, Mahmood Majeed, Fahad Ullah, Gilal Nauman Agus, Marco Schneider, Jens Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar

ISBN: (纸本)9781032803722

Recently, several innovative digital imaging technologies led to the development of several medical imaging data representations. Whole slide imaging (WSI) refers to capturing and storing tissue glass slides and biopsy samples in a digital form. This newly emerging modality is increasingly gaining huge interest in pathology departments worldwide due to the unique advantages introduced by this medical imaging modality for diagnostic, educational, and research purposes. This work provides a comparative analysis of multiple classification approaches of nuclei in WSI where multiple nuclei context-aware manipulation strategies are evaluated by our nuclei classification experiments. We propose a contextaware deep ensemble approach based on ResNet deep architecture using different forms of input images pre-processed using multiple manual feature extraction techniques. Results show that our approach attains higher accuracy performance compared to traditional context-ware strategies in the literature. © 2025 The Author(s).

关键词： Medical imaging

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Development Framework for Virtual Reality and UAV Technologies for the Adoption of Sustainable Heritage and Cultural Virtual Tourism in Melaka, Malaysia 5th

Development Framework for Virtual Reality and UAV Technologi...

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5th international conference on advances in information communication technology and computing, AICTC 2024

作者： Mubin, Siti Azreena Perumal, Ravindra Kumar Seelan, Amogha Asia Pacific University of Technology and Innovation Technology Park Malaysia Bukit Jalil Kuala Lumpur57000 Malaysia

ISBN: (纸本)9789819761050

The travel and tourism industry has been severely impacted by worldwide tragedies and disasters. Previous observations showed that most of these crises only had a limited, clearly defined impact on tourism during their specified timeframes, albeit not long-lasting. Unmanned aerial vehicles (UAVs), sometimes referred to as drones, and virtual reality (VR) are only a couple of the numerous ways that technology influences tourists’ cognitive and educational experiences. This study centers on the Malaysian cultural heritage site in Melaka, which is popular among tourists. Research indicates that virtual reality (VR) offers a more inventive and dynamic means of delivering enhanced information to users. Thus, the difficulties stakeholders have in marketing and publicizing Malaysia's cultural heritage sites as travel destinations are covered in this article. Additionally, it discussed how VR and UAVs could be two technical instruments that Melaka could use to boost tourism and that as a first step, a development framework has been created. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Drones

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Construction technology of 5G special test network for flight test 4

Construction technology of 5G special test network for fligh...

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4th international conference on Network communication and information Security, ICNCIS 2024

作者： Huo, Zhaohui Qu, Youyang Chai, Yingnan Chinese Flight Test Establishment China

ISBN: (数字)9781510688261

ISBN: (纸本)9781510688254

With the continuous deepening of the application of 5G technology in various industries, the aviation industry's flight test business is also accelerating the rapid transformation and upgrading of the 5G aviation test support model: deploying safe and reliable 5G networks in scattered test fields and laboratories, connecting test objects, basic test facilities, special test equipment, test engineers and management personnel, and information systems, effectively solving the new challenges encountered by existing test modes, Fully integrate 5G technology into cross factory and institute collaborative sharing of test data, and comprehensively break through barriers to data sharing and business collaboration between testing and flight testing. This paper focuses on aviation equipment flight test application, carries out research on the top-level architecture of 5G dedicated test and test network, proposes a 5G dedicated test and test network architecture for flight test, and introduces the wireless network, transmission network, core network architecture and edge computing scheme of dedicated 5G network in detail. Realize remote test monitoring and command collaboration in different locations, intelligent control of test sites, and rapid download of airborne collected flight test data;Establish a 5G network ecosystem for data sharing throughout the entire experimental process, support and optimize major business activities such as product design and development, production trial production, experimental verification, comprehensive support, and resource management. The 5G based testing and testing network is the first proposed in the domestic aviation testing field and also at a leading level in international testing system applications, which can be promoted and applied to other military testing fields. © 2025 SPIE.

关键词： 5G mobile communication systems

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Detection of Malicious Interpreted Code using ML to Optimize Parameters for Minimizing Prediction Errors

Detection of Malicious Interpreted Code using ML to Optimize...

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2025 international conference on computing for Sustainability and Intelligent Future, COMP-SIF 2025

作者： Dhawan, Manoj Kuril, Devendra Panadiwal, Himanshu Rawat, Hitesh Rawat, Anjali Rawat, Romil School of Engineering Avantika University Ujjain India Shri Vaishnav Vidyapeeth Vishwavidyalaya Department of Information Technology Indore India University of Extremadura Department of Business Management and Economics Badajoz Spain University of Extremadura Department of Computer and Communication Technology Badajoz Spain LabGeoInf-Research LABoratory in GEOmatics and INFormation systems Rome Italy

ISBN: (纸本)9798331538538

Mobile devices face growing cybersecurity threats, including malware, data breaches, malicious applications, and social engineering attacks. Cybercriminals exploit these vulnerabilities to gain unauthorized access, disrupt communication, and compromise sensitive information. Conventional malware detection methods, such as signature-based and heuristic techniques, often struggle to identify evolving threats due to their reliance on predefined patterns. This study presents an advanced malware detection framework that integrates a Reservoir Network with a Deep Learning Approach (DLA) to enhance detection accuracy and minimize prediction errors. The proposed method utilizes two static features-API call permissions and alert signals- to improve detection efficiency. Experimental evaluation, conducted using the Drebin malware dataset, demonstrates that the proposed model achieves an accuracy of 99.7 %, reduces the false positive rate to below 1 %, and ensures optimal processing speed with a batch size of 64 and a learning rate of 0.001. Compared to traditional approaches, this framework exhibits superior adaptability to obfuscated malware while enabling real-time threat detection. The findings emphasize the effectiveness of machine learning (ML)-driven security mechanisms in addressing emerging cybersecurity threats. © 2025 IEEE.

关键词： Computer viruses

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Research on Garbled Circuits-Based Identity Authentication and Ciphertext Hidden Access Control in Vehicular Networks 24

Research on Garbled Circuits-Based Identity Authentication a...

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9th international conference on Cloud computing and Internet of Things, CCIOT 2024

作者： Jiao, Zhilong Bai, Fenhua Zhang, Chi Zhang, Xiaohui Gong, Bei Faculty of Information Engineering and Automation Kunming University of Science and Technology China Kunming China Department of Computing Beijing University of Technology China Beijing China

ISBN: (纸本)9798400717161

Since most communications in vehicular networks rely on wireless transmissions, information broadcast by vehicles is highly susceptible to interception and eavesdropping by third parties, making it vulnerable to various attacks. This can result in communication messages being tampered with and the leakage of vehicle locations and identity privacy. From a security perspective, this paper introduces Yao's garbled circuit mechanism, combining random bytes with the solutions of linear equations as identity information assigned to vehicle nodes. By employing dual authentication, the proposed approach addresses issues such as privacy protection, anonymity, replay attacks, and collusion attacks in vehicular networks, thereby enhancing security. Moreover, considering the post-authentication access control scenario, this paper proposes a novel LSSS matrix transformation algorithm for ciphertext hidden access control strategy. It realizes a partially hidden policy, which makes matrix generation more efficient by supporting both AND and OR gates, thus improving the access control efficiency while ensuring security. Performance analysis indicates that in terms of identity authentication, the scheme reduces computational costs by an average of 96.25%, and in access control, the scheme reduces key generation time by an average of 80%. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Ciphertext

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Load Balancing in Cloud computing based on Ant Colony Optimization and Crow Search Algorithm 27

Load Balancing in Cloud Computing based on Ant Colony Optimi...

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27th international conference on Advanced communications technology, ICACT 2025

作者： Alsheavi, Amar N. Wang, Xingfu Zhao, Wei Hawbani, Ammar Alhusaini, Naji Ahmed, Ibrahim Abdulrab Ismail, A.S. School of Computer Science and Technology University of Science and Technology of China Anhui Hefei230027 China School of Computer Science and Technology Anhui University of Technology Anhui China School of Computer Science Shenyang Aerospace University Shenyang110136 China School of Computer and Information Engineering Chuzhou University Anhui Chuzhou239000 China Computer Department Applied College Najran University Najran66462 Saudi Arabia College of Life Sciences and Oceanography Shenzhen University Shenzhen518060 China Faculty of Science Zagazig University Zagazig44519 Egypt

ISBN: (纸本)9791188428137

With the rapid increase in cloud services and the increasing shift toward them, balancing the cloud load has become a critical research issue. The increasing demand from customers for technology services worldwide is largely due to its direct impact on performance quality. Therefore, to provide better service quality, it is essential to consider reducing response time and cost in load balancing. This paper addresses the load-balancing problem by optimizing response time and computing cost in cloud computing systems. Specifically, we first formulated the load balancing problem in cloud computing mathematically by designing an objective function that optimizes response time and cost, including constraints to ensure task assignment to a single virtual machine (VM) and resource limits are not exceeded. To solve this optimization problem, we proposed a hybrid algorithm, ACOCSA, that combines Ant Colony Optimization (ACO) and Crow Search Algorithm (CSA). We implemented the ACOCSA algorithm, evaluated the response time, cost, and load balancing metrics, and found that our algorithm performed better in terms of response time and computational cost, and showed good fairness among VMs. © 2025 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Ant colony optimization

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Diabetic Foot Ulcer Classification Using Deep Learning Approach 8th

Diabetic Foot Ulcer Classification Using Deep Learning Appro...

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8th IFIP TC 12 international conference on Computer, communication and Signal Processing, ICCCSP 2024

作者： Sivakamasundari, P. Niranjana, G. Department of Computer Science and Engineering SRM Institute of Science and Technology Tamil Nadu Kattankulathur India Department of Computing Technologies SRM Institute of Science and Technology Tamil Nadu Kattankulathur India

ISBN: (纸本)9783031736162

Podiatrist diagnosis and lesion localization are used as current testing approaches for Diabetic Foot ulcers (DFU). Current systems for automation concentrate on either categorization or division. One of the most common metabolic conditions, Diabetes (also called diabetes mellitus), is brought on by the pancreas incapacity to generate sufficient anti hyper-glycemic hormone to control glycemia levels. It may cause "Diabetic Peripheral Neuropathy," a collection of nerve diseases that can develop if the blood glucose level is left uncontrolled and unmanaged. Blood glucose levels may be efficiently maintained by recognising diabetes initially through constant surveillance and screenings. Using image processing methods such as data stretching with Deep Learning, image reduction and improvement, image division, and feature extraction, this paper offers a thorough approach for analysing thermal scans of the diabetic foot. By using these techniques, doctors may assess and track a patient's condition with fewer examinations. In this work, EfficientNetB3 architecture is compared with other Deep Learning models for accuracy in DFU identification. To create a powerful deep learning model, we gathered an extensive collection of 1,775 DFU photos. The basis of belief for this data gathering was created by two medical experts using annotator software to define the DFU region of interest. It took 48 ms to figure out a single image and 57.2 MB to validate the model. EfficientnetB3 got an average mean accuracy of 93%. This work demonstrates the effectiveness of Deep Learning for DFU localization in real-time, which could have improved with the use of a larger data set. © IFIP international Federation for information Processing 2025.

关键词： Diagnosis

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A Hybrid Deep Learning Models: Optimization for Forecasting Wireless 6G IoT Network 1

A Hybrid Deep Learning Models: Optimization for Forecasting ...

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1st international conference on advances in Computer Science, Electrical, Electronics, and communication Technologies, CE2CT 2025

作者： Singh, B.P. Venkadeshwaran, Kuthalingam Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Mechanical Engineering Karnataka Ramnagar District India

ISBN: (纸本)9798331518578

New specifications for 6G mobile networks will surpass the performance targets of 5G networks. As more 5G networks are deployed, their limits become obvious, encouraging the exploration of networks using 6G as the future solution. This paper covers 6G technology's core privacy and security concerns. Monitoring real-time structures need secured wireless sensor networks (WSNs). Denial of service (DoS) outbreaks increase secure risks for WSNs and potentially undermine the whole system. This study presents a new approach to control and optimize the security of 6G wireless networks based on blockchain technology by means of a machine learning method. Utilizing a blockchain users datagram transit protocol in conjunction with reinforcement projection regression, this research manages security of organized 6G wireless sensor net. The network is then optimized via artificially democratized cuckoo glowworm remora optimizations. Numerous network characteristics pertaining to accuracy, end-to-end latency, packet delivery ratio, energy efficiency, and throughput have formed the basis of the simulation findings. Reduced network traffic may be achieved by figuring out which node and route are best for data transfer. 98% of Throughput, energy effectiveness of 96%, 97% accuracy, end to end latency of 51%, and packet delivery ratio of 95% were all achieved by the suggested method. © 2025 IEEE.

关键词： 5G mobile communication systems

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Evaluating the Contribution of AI-Powered Knowledge and Digital Literacy to the Improvement of Fintech Operations in the Electronics Sector 1

Evaluating the Contribution of AI-Powered Knowledge and Digi...

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1st international conference on advances in Computer Science, Electrical, Electronics, and communication Technologies, CE2CT 2025

作者： Choudhari, Amey Adinath Moholkar, Nilambari Hanmant Ghadage, Avinash Bhoite, Dashrath Kumari, Sujata Patil, Mangalgouri S JSPM's Rajashi Shahu College of Engineering Pune India Dr. D.Y. Patil Institute of Technology Pimpri Pune India D.Y. Patil Vidyapeeth's Global Business School and Research Centre Pune India International School of Management and Research Pune India Shri Balaji University Pune India Pune India

ISBN: (纸本)9798331518578

The financial services sector is undergoing a change because to artificial intelligence (AI) particularly in the field of financial technology (FinTech). FinTech's incorporation of artificial intelligence (AI) has fundamentally altered traditional financial services by increasing security, accuracy, and efficiency. Artificial intelligence (AI) technology, financial organizations can benefit from technologies like ML algorithms, natural language processing (NLP), including predictive analytics in making better decisions, streamlining operations, and offering customized customer experiences. While cutting edge capability and advanced education enables both staff and purchasers to capably connect with fintech courses of action, recreated insight-controlled data helps associations with overhauling heading, further foster client experiences, and limit money related risks. Since technology has made it easier to share information and lower transaction costs, financial services production could be broken down. Because specialized players offer unbundled financial services, customers can locate and put together the product suites that they want. This study sees how cutting-edge capability and man-made brainpower-controlled data could chip away at financial undertakings, advance safe trades, and addition proficiency in the contraptions business. This study assesses how these advances add to the augmentation and goodness of fintech applications in equipment by dissecting context-oriented examinations, ongoing crazes, and inconveniences. © 2025 IEEE.

关键词： Sales

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