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Decision Aid Sciences and Application (DASA), International Conference on

作者： Jovencio Merin Alvin Sarraga Alon Joel Pinkihan Ricky C. Sandil Michael Angelo Delos Santos Ligayo Ryan Flores Arago Rovenson Sevilla Christopher Cunanan Dept. of Electrical Engineering Technological University of the Philippines Manila Philippines Department of Trade and Industry Center for AI Research Makati City Philippines College of Computing Sciences Ifugao State University Ifugao Philippines College Preparatory Program Kingdom of Saudi Arabia Saudi Arabia College of Engineering Quezon City University Quezon City Philippines Department of Electrical Engineering Technological University of the Philippines Manila Philippines Christopher Franco Cunanan Computer Engineering Department Bulacan State University Bulacan Philippines

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

This paper introduces a novel approach for power system inspection using Mask-RCNN, an advanced model for instance segmentation. The accuracy of our model in identifying and diagnosing damaged low- to medium-voltage insulators is exceptional, as evidenced by its Mean Average Precision (mAP) score of 98.7 % • Throughout the training process, the model exhibited minimal loss metrics, indicating its proficiency in predicting bounding boxes precisely, segmenting, classifying, and aligning masks. The model exhibited consistent reliability in distinguishing between undamaged and damaged components during the inference process, as seen by its consistently high detection rates for both “normal intact” and “damaged broken” insulators. The results demonstrate the practical usefulness of the model and offer promising prospects for enhancing power system maintenance and inspection protocols. The model's consistent and accurate identification of damaged insulators has the potential to significantly enhance the safety and efficiency of power systems, thereby revolutionizing the industry.

关键词： Measurement Training Accuracy Medium voltage Inspection Predictive models Insulators Maintenance Power system reliability Safety

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CIPM: Common identification process model for database forensics field 2

CIPM: Common identification process model for database foren...

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2nd International Conference on Smart computing and Electronic Enterprise, ICSCEE 2021

作者： Alfadli, Ibrahim M Ghabban, Fahad M Ameerbakhsh, Omair Abuali, Amer Nizar Al-Dhaqm, Arafat Al-Khasawneh, Mahmoud Ahmad Taibah University College of Computer Science and Engineering Information System Department Madinah Saudi Arabia University Technology Malaysia Faculty of Engineering School of Computing Johor Malaysia Al-Madinah International University Faculty of Computer and Information Technology Shah Alam Malaysia

ISBN: (纸本)9781665432221

Database Forensics (DBF) domain is a branch of digital forensics, concerned with the identification, collection, reconstruction, analysis, and documentation of database crimes. Different researchers have introduced several identification models to handle database crimes. Majority of proposed models are not specific and are redundant, which makes these models a problem because of the multidimensional nature and high diversity of database systems. Accordingly, using the metamodeling approach, the current study is aimed at proposing a unified identification model applicable to the database forensic field. The model integrates and harmonizes all exiting identification processes into a single abstract model, called Common Identification Process Model (CIPM). The model comprises six phases: 1) notifying an incident, 2) responding to the incident, 3) identification of the incident source, 4) verification of the incident, 5) isolation of the database server and 6) provision of an investigation environment. CIMP was found capable of helping the practitioners and newcomers to the forensics domain to control database crimes. © 2021 IEEE.

关键词： Digital forensics

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Integrating Local and Global Attention Mechanisms for Enhanced Oral Cancer Detection and Explainability

SSRN

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SSRN 2024年

作者： Shah, Syed Jawad Albishri, Ahmed Wang, Rong Lee, Yugyung School of Science and Engineering University of Missouri-Kansas City Kansas City United States College of Computing and Informatics Saudi Electronic University Riyadh Saudi Arabia Department of Oral and Craniofacial Sciences School of Dentistry University of Missouri - Kansas City Kansas City United States

Accurate detection of oral cancer is essential for improving patient outcomes, yet challenges such as the limited application of deep learning-based segmentation and the scarcity of annotated data persist. Our study introduces OCANet, a U-Net-based architecture designed to detect oral cancer in hematoxylin and eosin (H&E) stained images. OCANet employs a hybrid attention model, integrating advanced modules like the Channel and Spatial Attention Fusion (CSAF) module, which enhances the detection of critical regions in H&E images by leveraging contextual information. Additionally, OCANet incorporates Squeeze-and-Excitation (SE) attention modules, Atrous Spatial Pyramid Pooling (ASPP), residual blocks, and multi-scale fusion to capture intricate patterns and context, leading to superior performance in oral cancer segmentation across various datasets. Comprehensive evaluation shows that OCANet excels in identifying cancer cells in H&E images from the OCDC and ORCA datasets, outperforming existing segmentation methods, including transformer-based models. OCANet also leverages large language models (LLMs) like GPT-4 to enhance explainability, providing precise insights into the model’s decision-making process and improving interpretability for clinical applications. This integration improves the transparency of OCANet’s segmentation outcomes, helping clinicians understand and verify the results. OCANet is established as a state-of-the-art solution for oral cancer detection, offering a reliable and interpretable tool for clinical settings. © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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Like an Ophthalmologist: Dynamic Selection Driven Multi-View Learning for Diabetic Retinopathy Grading 39

Like an Ophthalmologist: Dynamic Selection Driven Multi-View...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Luo, Xiaoling Xu, Qihao Wu, Huisi Liu, Chengliang Lai, Zhihui Shen, Linlin Computer Vision Institute College of Computer Science and Software Engineering Shenzhen University Shenzhen China Shenzhen Key Laboratory of Visual Object Detection and Recognition Harbin Institute of Technology Shenzhen China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Guangdong Provincial Key Laboratory of Intelligent Information Processing China

ISBN: (纸本)157735897X

Diabetic retinopathy (DR), with its large patient population, has become a formidable threat to human visual health. In the clinical diagnosis of DR, multi-view fundus images are considered to be more suitable for DR diagnosis because of the wide coverage of the field of view. Therefore, different from the previous single-view DR grading methods, we design a dynamic selection-driven multi-view DR grading method to fit clinical scenarios better. Since lesion information plays a key role in DR diagnosis, previous methods usually boost the model performance by enhancing the lesion feature. However, during the actual diagnosis, ophthalmologists not only focus on the crucial parts, but also exclude irrelevant features to ensure the accuracy of judgment. To this end, we introduce the idea of dynamic selection and design a series of selection mechanisms from fine granularity to coarse granularity. In this work, we first introduce an Ophthalmic Image Reader (OIR) agent to provide the model with pixel-level prompts of suspected lesion areas. Moreover, we design a Multi-View Token Selection Module (MVTSM) that prunes redundant feature tokens and dynamically selects key information. In the final decision stage, we dynamically fuse multi-view features through the novel Multi-View Mixture of Experts Module (MVMoEM), to enhance key views and reduce the impact of conflicting views. Extensive experiments on a large multi-view fundus image dataset with 34,452 images prove that our method performs favorably against state-of-the-art models. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Ophthalmology

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Dynamic Packet Content Construction and Processing for End-to-End Streaming in 6G

Dynamic Packet Content Construction and Processing for End-t...

引用

IEEE International Workshop on computer-Aided Modeling, Analysis, and Design of Communication Links and Networks, CAMAD

作者： Stuart Clayman Emre Karakıș Mustafa Tüker Elif Ak Berk Canberk Müge Sayıt Dept. of Electronic Engineering University College London London UK International Computer Institute Ege University Izmir Turkey Department of Engineering Istanbul Technical University Turkey School of Computing Engineering The Built Environment Edinburgh Napier University UK

In the context of 6G, the use of drones/UAVs and satellite is a high priority. One of the main issues is that there is limited and varying bandwidth in these environments, so the question arises: how do we provide high Quality of Experience (QoE) to the users. BPP is a recent protocol which is effective when used with Scalable Video Coding (SVC) streams and limited bandwidth environments. We present an end-to-end architecture, with a drone sending video, utilizing functions for dynamically constructing the content of packets, and then dynamically processing those packets during their transmission across a network, all managed by a multi-domain orchestrator. These functions are implemented as virtualized network elements, as in our previous work. In this current work, we investigate how different packing strategies for filling packets impact different QoE parameters, when evaluated using a number of different bandwidths. These insights can be utilized for choosing the best QoE, and will be especially useful in 5G / 6G environments.

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Joint Power and Spectrum Orchestration for D2D Semantic Communication Underlying Energy-Efficient Cellular Networks

arXiv

引用

arXiv 2025年

作者： Xia, Le Sun, Yao Sun, Haijian Hu, Rose Qingyang Niyato, Dusit Imran, Muhammad Ali James Watt School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom School of Electrical and Computer Engineering University of Georgia AthensGA30602 United States Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24061 United States College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore

Semantic communication (SemCom) has been recently deemed a promising next-generation wireless technique to enable efficient spectrum savings and information exchanges, thus naturally introducing a novel and practical network paradigm where cellular and device-to-device (D2D) SemCom approaches coexist. Nevertheless, the involved wireless resource management becomes complicated and challenging due to the unique semantic performance measurements and energy-consuming semantic coding mechanism. To this end, this paper jointly investigates power control and spectrum reuse problems for energy-efficient D2D SemCom cellular networks. Concretely, we first model the user preference-aware semantic triplet transmission and leverage a novel metric of semantic value to identify the semantic information importance conveyed in SemCom. Then, we define the additional power consumption from semantic encoding in conjunction with basic power amplifier dissipation to derive the overall system energy efficiency (semantics/Joule). Next, we formulate an energy efficiency maximization problem for joint power and spectrum allocation subject to several SemCom-related and practical constraints. Afterward, we propose an optimal resource management solution by employing the fractional-to-subtractive problem transformation and decomposition while developing a three-stage method with theoretical analysis of its optimality guarantee and computational complexity. Numerical results demonstrate the adequate performance superiority of our proposed solution compared with different benchmarks. Copyright © 2025, The Authors. All rights reserved.

关键词： Energy utilization

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Assistive Technical Communication of Montenegrin eServices: a Case Study 27

Assistive Technical Communication of Montenegrin eServices: ...

引用

27th International Conference on Information Technology, IT 2023

作者： Simon, Aniko Lakovic, Luka Kovacevic, Pavle Kara, Peter A. Ognjanovic, Ivana Sendelj, Ramo Reich, Christoph Roganovic, Milovan Mantas, John Bokor, Laszlo Sigma Technology Budapest1093 Hungary University of Donja Gorica Faculty for Information Systems and Technologies Podgorica81000 Montenegro Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Networked Systems and Services Budapest1111 Hungary Kingston University Wireless Multimedia and Networking Research Group Department of Computer Science School of Computer Science and Mathematics Faculty of Science Engineering and Computing LondonKT1 2EE United Kingdom University of Donja Gorica Humanistic Studies Podgorica81000 Montenegro Furtwangen University Institute of Data Science Cloud Computing and It Security Furtwangen78120 Germany Clinical Centre of Montenegro Clinic for Neurology Podgorica81000 Montenegro National and Kapodistrian University of Athens Faculty of Nursing School of Health Sciences Goudi 11527 Greece

ISBN: (纸本)9798350397512

With the advancement of information technology in the recent decades, digital and online services have become essential components of everyday life in Europe. Montenegro is no different in this regard. However, as digital literacy in the country is still in a developing phase in comparison with most countries of the EU, a higher portion of its citizens may rely on assistive technical communication. In this paper, we provide a case study on the assistive technical communication of Montenegrin eServices. The work addresses the sectors of online banking, healthcare services, higher education, national administrative services, and utilities. Our findings highlight the diversity in terms of implemented assistive technical communication, and distinguish usage contexts on the level of adequacy. Yet as the functionalities of Montenegrin eServices are expected to gradually expand in the upcoming years, assistive technical communication must aim to handle the higher extents of service complexity. © 2023 IEEE.

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Guaranteeing Control Requirements via Reward Shaping in Reinforcement Learning

arXiv

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arXiv 2023年

作者： De Lellis, Francesco Coraggio, Marco Russo, Giovanni Musolesi, Mirco Bernardo, Mario di The Department of Electrical Engineering and Information Technology University of Naples Federico II Naples Italy The Scuola Superiore Meridionale School for Advanced Studies Naples Italy The Department of Computer and Electrical Engineering & Applied Mathematics University of Salerno DIEM Salerno Italy The Department of Computer Science University College London United Kingdom The Department of Informatics - Science and Engineering University of Bologna Bologna Italy

In addressing control problems such as regulation and tracking through reinforcement learning, it is often required to guarantee that the acquired policy meets essential performance and stability criteria such as a desired settling time and steady-state error prior to deployment. Motivated by this necessity, we present a set of results and a systematic reward shaping procedure that (i) ensures the optimal policy generates trajectories that align with specified control requirements and (ii) allows to assess whether any given policy satisfies them. We validate our approach through comprehensive numerical experiments conducted in two representative environments from OpenAI Gym: the Inverted Pendulum swing-up problem and the Lunar Lander. Utilizing both tabular and deep reinforcement learning methods, our experiments consistently affirm the efficacy of our proposed framework, highlighting its effectiveness in ensuring policy adherence to the prescribed control requirements. © 2023, CC BY-NC-SA.

关键词： Reinforcement learning

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Precoding Optimization for Rate Splitting Enabled Internet of Underwater Things over Optical Wireless Underwater Turbulent Channels

引用

IEEE Internet of Things Journal 2025年

作者： Xing, Fangyuan Tong, Fei Liu, Xiaonan Wang, Zhenduo Leung, Victor C. M. Southeast University School of Cyber Science and Engineering Nanjing211189 China School of Natural and Computing Science University of Aberdeen AberdeenAB24 3FX United Kingdom Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Shenzhen MSU-BIT University Artificial Intelligence Research Institute Shenzhen518172 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T1Z4 Canada

With the booming development of the underwater Internet of Things, underwater devices and data volume are explosively increasing. Thanks to the advantages of high efficiency and low complexity, the emerging rate splitting multiple access (RSMA) can be integrated with underwater optical wireless communication (UOWC), which can help improve resource utilization and system performance. However, the oceanic characteristics are distinctive and pose great challenges for RSMA-enabled UOWC networks. Precoding design is crucial for benefitting from RSMA-enabled systems, and thus, we explore the precoding optimization for RSMA-enabled UOWC networks over underwater turbulent channels. Specifically, the RSMA-enabled UOWC network is modeled, where a combined turbulent channel involving the effects of absorption, scattering, and underwater turbulence is considered, and a message transmission scheme with rate splitting design is analyzed. A precoding problem is formulated to maximize the ergodic sum rate (ESR) under the constraint of total transmitted power. Since the accurate expression of ESR is a non-closed form and intractable, we first propose a consecutive Fenton-Wilkinson (CFW)-based ergodic rate approximation approach to solve this formulation problem. Fenton-Wilkinson moment matching is consecutively employed to achieve a closed-form and low-complexity expression of the ergodic rate, as only Fenton-Wilkinson moment matching method can offer closed-form solutions for underlying parameters of the approximating log-normal distributions. For further solving the non-convex precoding problem, the successive convex approximation (SCA) approach is adopted, which is particularly applicable for resource-limited underwater environments. The effectiveness of the proposed CFW approach and precoding strategy is evaluated by extensive simulation results for various user deployments and different network loads. © 2025 IEEE.

关键词： Normal distribution

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Development of Structure For Reliability Kind of Assessment Through Artificial Intelligence

Development of Structure For Reliability Kind of Assessment ...

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Advance computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： Padmaja Kadiri A. Brahmareddy Narayanasamy S Alankrita Aggarwal Ahmed Jalal Fakher Aqeel Al-Hilali Department of AIML School of Computing Mohan Babu University Tirupati Andhra Pradesh India Department of Computer Science and Engineering Marri Laxman Reddy Institute of Technology and Management (MLRITM) (A UGC Autonomous Institute) Hyderabad Telangana India J.J College of Engineering and Technology Trichy Tamilnadu India Computer Science and Engineering Apex Institute of Technology Chandigarh University Mohali Punjab India College of Technical Engineering National University of Science and Technology Dhi Qar Iraq Al-Farahidi university Baghdad Iraq

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

The transformative potential of AI raises serious moral questions for companies and calls into question the need for trust. To address this, several ethical frameworks are commonly proposed, if only in theory. AI is also necessary for workers to appropriately measure trust. There aren’t many studies that address how an ethical framework may help employees calibrate their practical trust. To ensure trust calibration and reduce this gap, research is being done on an ethical framework that centres on AI safety and reliability. Finally, an assessment of the efficacy of the deployed framework is conducted through interviews conducted at a multinational automotive supplier. This ethical foundation thus led to a significant rise in trust. This is a groundbreaking finding: workers are willing to tolerate a lesser level of AI safety as long as AI reliability is preserved.

关键词： Ethics Companies Reliability theory Reliability engineering Safety Calibration Artificial intelligence

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