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Revisiting the Curvature-aided IAG: Improved Theory and Reduced Complexity

IFAC-PapersOnLine 2023年第2期56卷 5221-5226页

作者： Erik Berglund Sarit Khirirat Xuyang Wu Sindri Magnússon Mikael Johansson School of Electrical Engineering and Computer Science KTH Royal Institute of Technology SE 100 44 Stockholm Sweden Department of Machine Learning Mohamed bin Zayed University of Artificial Intelligence Abu Dhabi UAE Department of Computer and System Science Stockholm University Stockholm Sweden

The curvature-aided IAG (CIAG) algorithm is an efficient asynchronous optimization method that accelerates IAG using a delay compensation technique. However, existing step-size rules for CIAG are conservative and hard to implement, and the Hessian computation in CIAG is often computationally expensive. To alleviate these issues, we first provide an easy-to-implement and less conservative step-size rule for CIAG. Next, we propose a modified CIAG algorithm that reduces the computational complexity by approximating the Hessian with a constant matrix. Convergence results are derived for each algorithm on both convex and strongly convex problems, and numerical experiments on logistic regression demonstrate their effectiveness in practice.

关键词： asynchronous optimization delay compensation incremental aggregated gradient

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DDPS: Dynamic Differential Pricing-Based Edge Offloading system With Energy Harvesting Devices

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IEEE Transactions on Network science and engineering 2025年

作者： Xue, Hai Xia, Yun Xiong, Neal N. Zhang, Di Pei, Songwen University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China Sul Ross State University Department of Computer Science and Mathematics AlpineTX79830 United States Zhengzhou University School of Electrical and Information Engineering Zhengzhou450001 China Zhengzhou University Henan International Joint Laboratory of Intelligent Health Information System Zhengzhou450001 China Zhengzhou University National Engineering Laboratory for Internet Medical Systems and Applications Zhengzhou450001 China

Mobile edge computing (MEC) mitigates the energy and computation burdens on mobile users (MUs) by offloading tasks to the network edge. To optimize MEC server utilization through effective resource allocation, a well-designed pricing strategy is indispensable. In this paper, we propose a dynamic differential pricing scheme (DDPS) for an edge offloading scenario with energy harvesting devices, which determines prices based on computing resource usage to enhance edge server (ES) utilization. First, an offloading decision algorithm is proposed to balance harvested and consumed energy, determining whether and how much data to offload. Second, a Stackelberg game-based differential pricing algorithm is proposed to optimize computing resource allocation for MUs and reallocate surplus resources to delay-sensitive devices. Extensive simulations are conducted to demonstrate the effectiveness of the proposed DDPS scheme. Specifically, in comparison to the existing best-performing pricing scheme, for different task arrival rates, DDPS can achieve a 5.3% decrease in average execution delay, a 1.7% increase in ES utility (Userver, which represents the payment from MUs minus penalties for discarded tasks), and a 2.1% increase in the average ratio of service for MUs. In addition, DDPS also improves 2.8% Userver on average with different ES computation capacities. © 2025 IEEE. All rights reserved.

关键词： Mobile edge computing

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Make 3D Cable Model from Single RGB Image 10

Make 3D Cable Model from Single RGB Image

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10th International Congress on Advanced Applied Informatics, IIAI-AAI 2021

作者： Fan, Zheming Ohashi, Takeshi Hayashi, Toyohiro Graduate School of Computer Science and System Engineering Kyushu Institute of Technology Fukuoka Japan Kyushu Institute of Technology Information Science and Technology Center Fukuoka Japan

ISBN: (纸本)9781665424202

Along with the electrification, there are many electrical equipment are used in our daily life. Using those equipment we need cables to charge and connect them. But, sometimes cables will become problems, like when we clean the room the cables will be annoying. We think if we can resolve this problem with robot, it will save lots of time for people. But, unfortunately, there is no system which can manipulate cables with robot. The key point is cable can deform it's shape. Because of this, we can't recognize and record cables position correctly from picture. And if we want to manipulate cables with robot, the 3D information of cables is far batter than 2D information. Therefore, in this paper, we made a system which can build a 3D voxels model base on 2D image as a beforehand for use robot to manipulate cables. In our system, we cut input image into a series of small pictures and make 3D model based on each pictures then we assemble those 3D model together. So we can get a complete 3D model(output of this system) which is made base on input image and can represent the 3D cables position. Our method can transfer 2D data to 3D data, this let us can get 3D information from image and we think this is useful in robot science. © 2021 IEEE.

关键词： Cables

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Critical Factors of Immersive Learning in Higher Education: A systematic Literature Review

Critical Factors of Immersive Learning in Higher Education: ...

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International Conference on ICT For Smart Society (ICISS)

作者： Sunardi Meyliana Arief Ramadhan Yusep Rosmansyah Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Information System Departement School of information system Bina Nusantara University Jakarta Indonesia School of Computing Telkom University Bandung Indonesia School of electrical engineering and informatics Bandung Institute of Technology Bandung Indonesia

Immersive learning has gained significant attention with the rising trend of spatial computing, particularly in the after-pandemic era. Numerous research has explored the potential of immersive learning in higher education, primarily on the educational sector. However, prior research has frequently focused too narrowly on the effects of technology and neglected to address the crucial element influencing successful immersive learning in higher education. This study seeks to pinpoint the crucial element contributing to the development of immersive learning experiences. The methodology uses a systematic literature review (SLR) from 2018 up to 2023 to investigate the critical factors of immersive Learning in Higher Education. From the 728 papers initially retrieved, 274 were considered potential candidates, and ultimately, 86 articles were selected based on their relevance to the research question. The results reveal that the critical factors include learning design, technology, immersion, engagement, interactivity, and usability. Academic interests will benefit from this SLR's consequences as institutions create models for designing suitable immersive learning, especially within the context of higher education.

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Retinal Image Pre-Processing Using Equalization and thResholding (RIPPER) 23

Retinal Image Pre-Processing Using Equalization and thReshol...

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Proceedings of the 2023 10th International Conference on Bioinformatics Research and Applications

作者： Nnamdi Nwanze Chukwuemeka C. Nwanze Abumere Akinwale Larry Baitch Computer Science & Engineering North Central College USA School of Optometry Mass. Coll. of Pharm & Health Sciences USA Department of Ophthalmology Veterans Healthcare System USA

ISBN: (纸本)9798400708152

The eye is the only location on the human body that enables non-invasive evaluation of blood vessels. Clinicians can correlate the presence of systemic diseases, such as hypertension and diabetes, with the appearance of the ocular blood vessels. As such, there has been significant interest in accurate retinal vessel segmentation and classification. Traditionally, segmentation and classification methods first pre-process an image, then apply a vessel identifying technique. The results of this process is then compared to a gold-standard–typically an image that has been manually segmented by a human domain expert. In this paper, we propose RIPPER (Retinal Image Pre-Processing using Equalization And thResholding) a highly effective retinal image pre-processing technique for use in both manual and automated vessel segmentation systems. We apply RIPPER to two publicly available retinal image databases, DRIVE and HRF, which contain gold standard segmentations for each image. Our results show that using RIPPER can increase the accuracy of the gold standard images by up to 20% thereby allowing for increased performance in retinal vessel segmentation and classification systems.

关键词： convolutional neural networks datasets deep learning fundus images image pre-processing image processing machine learning retinal blood vessel segmentation retinal blood vessels classification retinal vessels vessel segmentation

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(θ,θ∗)-Operator-Driven Intuitionistic Fuzzy Matrix Composite Operation and Its Optimal Application in Medical Diagnosis 11th

(θ,θ∗)-Operator-Driven Intuitionistic Fuzzy Matrix Compos...

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11th International Joint Conference on Rough Sets, IJCRS 2025

作者： Kang, Yuqi Feng, Huarong Zhang, Xianyong Yang, Jilin Liang, Qian School of Mathematical Sciences Sichuan Normal University Chengdu610066 China National-Local Joint Engineering Laboratory of System Credibility Automatic Verification Research Center of Sichuan Normal University Chengdu610066 China College of Science Xihua University Chengdu610039 China College of Computer Science Sichuan Normal University Chengdu610066 China

ISBN: (纸本)9783031927430

Intuitionistic fuzzy sets (IFSs) extend fuzzy sets, and they provide a more accurate representation of uncertainty in realistic scenarios. Fuzzy implication operators play a crucial role in fuzzy reasoning. Accordingly, this paper introduces fuzzy implication operators θ and θ∗ to IFSs, and it correspondingly proposes two types of intuitionistic fuzzy matrix composite operations, where the (θ, θ∗) induction is comparatively accompanied with a direct formulation from (∧,∨). Firstly, we investigate concrete properties of fuzzy implication operators θ,θ∗. Then, two IFSs matrix composite operations are proposed, respectively from (∧,∨) and (θ, θ∗). Finally, the two composite operations of IFSs matrices are applied to medical diagnosis, and their application feasibility is verified through a practical medical example;by comparative analyses, the (θ,θ∗)-driven operation better provides right diagnosis results in contrast to previous studies. This study resorts to specific fuzzy implication operators to enrich theoretical research and practical applications of IFSs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Fuzzy rules

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Automating smart Internet of Things devices in modern homes using context-based fuzzy logic

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Computational Intelligence 2024年第1期40卷 e12370-e12370页

作者： Ming, Chen Kadry, Seifedine Dasel, A. Antony Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle Hubei University of Arts and Science Xiangyang China School of Automotive and Traffic Engineering Hubei University of Arts and Science Xiangyang China Department of Mathematics and Computer Science Beirut Arab University Beirut Lebanon Department of Mechanical Engineering VIT University Vellore India

Internet of Things (IoT) is mainly used to connect different embedded objects over the internet to make communication between them possible. With the help of IoT, devices find a way to interact, work together, and study from each other's experiences just like humans do. IoT finds its way in applications such as smart home, smart city, healthcare, agriculture, and so on. The name smart home arises due to the automation of the normal home appliances to make it smart. When the devices of the normal smart home are connected via the internet, they become a part of the IoT. The smart home should ensure the following characteristics such as security, comfort, convenience, and energy saving. The article presents a technique for IoT controlled devices in a smart home using context-based fuzzy logic. Fuzzy logic is mainly used to monitor and analyze the real-time data collected from the sensors in the smart homes from various environments. Context-based fuzzy logic uses a multivalued logic principle which differs from the normal Boolean logic, where the truth value lies between only zero and one (ie, true or false). The proposed smart home is implemented in a real case scenario where it yields an accuracy of 90.5%, response time of 6.41 milliseconds, and an F-measure of 97%. © 2020 Wiley Periodicals LLC.

关键词： Internet of things

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GCD-Sampling: A General Cross-scale Decoupled Sampling for Point Cloud 39

GCD-Sampling: A General Cross-scale Decoupled Sampling for P...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Dai, Tao Wang, Yanzi Xiong, Jianyu Zha, Yaohua Xia, Shu-Tao Zhu, Zexuan College of Computer Science and Software Engineering Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Tsinghua Shenzhen International Graduate School Tsinghua University China Shenzhen City Key Laboratory of Embedded System Design Shenzhen China

ISBN: (纸本)157735897X

Sampling strategy (e.g., fixed farthest point sampling) of point cloud has been an essential step for developing practical solutions in 3D computer vision tasks. Previous fixed sampling is simple, but suffer from suboptimal performance for downstream tasks. To adapt to target networks properly, adaptive sampling methods with trainable parameters have been recently developed to enhance the performance. However, existing adaptive sampling methods still suffer from the over-coupling problem of target network, and thus become model-specific, which limits their practical applications. To address this issue, we propose a novel general cross-scale decoupled sampling method (GCD-sampling) for point cloud, which consists of original feature cache, cross-scale feature fusion and convex combination learning for better feature extraction. To reduce the coupling relationship with the target task network, our method only utilizes the point cloud coordinates as the input and output of itself. Besides, we introduce an arbitrary scale structure to enable parameter sharing across multi-scale sampling in point cloud networks. Extensive experiments on different architectures demonstrate the effectiveness of our method over other existing adaptive sampling methods. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Feature extraction

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Why Does Little Robustness Help? A Further Step Towards Understanding Adversarial Transferability

arXiv

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arXiv 2023年

作者： Zhang, Yechao Hu, Shengshan Zhang, Leo Yu Shi, Junyu Li, Minghui Liu, Xiaogeng Wan, Wei Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia School of Computer Science and Technology Huazhong University of Science and Technology China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security China Hubei Engineering Research Center on Big Data Security China Cluster and Grid Computing Lab

Adversarial examples for deep neural networks (DNNs) have been shown to be transferable: examples that successfully fool one white-box surrogate model can also deceive other black-box models with different architectures. Although a bunch of empirical studies have provided guidance on generating highly transferable adversarial examples, many of these findings fail to be well explained and even lead to confusing or inconsistent advice for practical use. In this paper, we take a further step towards understanding adversarial transferability, with a particular focus on surrogate aspects. Starting from the intriguing "little robustness" phenomenon, where models adversarially trained with mildly perturbed adversarial samples can serve as better surrogates for transfer attacks, we attribute it to a trade-off between two dominant factors: model smoothness and gradient similarity. Our research focuses on their joint effects on transferability, rather than demonstrating the separate relationships alone. Through a combination of theoretical and empirical analyses, we hypothesize that the data distribution shift induced by off-manifold samples in adversarial training is the reason that impairs gradient similarity. Building on these insights, we further explore the impacts of prevalent data augmentation and gradient regularization on transferability and analyze how the trade-off manifest in various training methods, thus building a comprehensive blueprint for the regulation mechanisms behind transferability. Finally, we provide a general route for constructing superior surrogates to boost transferability, which optimizes both model smoothness and gradient similarity simultaneously, e.g., the combination of input gradient regularization and sharpness-aware minimization (SAM), validated by extensive experiments. In summary, we call for attention to the united impacts of these two factors for launching effective transfer attacks, rather than optimizing one while ignoring the other,

关键词： Deep neural networks

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Hotel Information system Management Audit Using COBIT 2019 - APO12

Hotel Information System Management Audit Using COBIT 2019 -...

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Innovation in Technology (INOCON), IEEE International Conference for

作者： Joy Nashar Utamajaya Suhono Harso Supangat Ford Lumban Gaol Benny Ranti BINUS Graduate Program School of Information System BINUS University Jakarta Indonesia School of Electrical Engineering and Informatic Bandung Institute of Technology Bandung Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Faculty of Computer Science University of Indonesia Depok Indonesia

In general, public or private organizations or companies have used information-based technology as a support to improve business performance to be more effective and efficient in order to achieve a company’s business goals. Given the large contribution of information technology in the application of hotel applications as a supporting information system, it is a vital system that must avoid risks that can hinder and cause harm to the hotel management business processes. Therefore, it is necessary to carry out risk management using the COBIT 5 framework to manage possible risks that may occur based on the APO12 (Manage Risk) domain. From the evaluation results of the data obtained through observation and interviews as well as the calculation of the results of the questionnaire based on 6 APO12 subdomains, the results of the risk management level capability assessment in hotel applications are still at level 3 or have reached the level of established process with the target to be achieved at level 4 resulting in a gap of 1 level. Based on the results obtained, it is necessary to propose recommendations that can be used by hotels in improving the application of information technology risk management so that in the future it can achieve the expected target level so that the APO12 level of capability can increase and become more optimal.

关键词： Technological innovation Companies Risk management Information technology Interviews Information systems

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