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A computationally efficient skull scraping approach for brain mr image

Recent Advances in computer science and Communications 2020年第5期13卷 833-844页

作者： Naga Srinivasu, P. Srinivasa Rao, T. Srinivas, G. Prasad Reddy, P.V.G.D. Department of Computer Science and Systems Engineering GIT GITAM University Rushikonda VisakhapatnamAP530045 India Department of Computer Science and Systems Engineering AUCOE Andhra University Visakha-patnamAP530003 India

Background: In the process of volumetric evaluation of the damaged region in the human brain from a MR image it is very crucial to remove the non-brain tissue from the acquainted image. At times there is a chance during the process of assessing the damaged region through automated approaches might misinterpret the non-brain tissues like skull as damaged region due to their similar in-tensity features. So in order to address such issues all such artefacts. Objective: In order to mechanize an efficient approach that can effectively address the issue of remov-ing the non-brain tissues with minimal computation effort and precise accuracy. It is very essential to keep the computational time to be as minimal as possible because the processes of skull removal is used in conjunction with segmentation algorithm, and if the skull scrapping approach has consumed a considerable amount of time, they it would impact the over segmentation and volume assessment time which is not advisable. Method: In this paper a completely novel approach named Structural Augmentation has been proposed, that could efficiently remove the skull region from the MR image. The proposed approach has several phases that include applying of Hybridized Contra harmonic and Otsu AWBF filtering for noise removal and threshold approximation through Otsu based approach and constructing the bit map based on the approximated threshold. Morphological close operation followed by morphological open operation with reference to a structural element through the generated bitmap image. Results: The experiment are carry forwarded on a real time MR images of the patient at KGH hospital, Visakhapatnam and the images from open sources repositories like fmri. The experiment is conducted on the images of varied noise variance that are tabulated in the results and implementation section of the article. The accuracy of the proposed method has been evaluated through metrics like Accuracy, Sensitivity, Specificity through true pos

关键词： Morphology

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IvyCross: a Privacy-Preserving and Concurrency Control Framework for Blockchain Interoperability

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IEEE Transactions on Mobile Computing 2025年

作者： Li, Ming Weng, Jian Weng, Jiasi Li, Yi Wu, Yongdong Li, Dingcheng Xu, Guowen Deng, Robert Singapore Management University School of Computing and Information Systems 178902 Singapore Jinan University College of Cyber Security Guangzhou510632 China Nanyang Technological University School of Computer Science and Engineering Singapore

Interoperability is a fundamental challenge for longenvisioned blockchain applications. A mainstream approach is using Trusted Execution Environment (TEE) to support interoperable off-chain execution. However, this incurs multiple TEE configured with non-trivial storage capabilities running on fragile concurrent processing environments, rendering current strategies based on TEE far from being practical. This paper aims to fill this gap and design a practical interoperability mechanism with simplified TEE as the underlying architecture. Specifically, we present IvyCross, a TEE-based framework that achieves lowcost, privacy-preserving, and race-free blockchain interoperability. IvyCross allows running arbitrary smart contracts across heterogeneous blockchains atop two distributed TEE-powered hosts. We design an incentive scheme based on smart contracts to stimulate the honest behavior of two hosts, bypassing the requirement of the number of TEE and large memory need. We examine the conditions to guarantee the uniqueness of Nash Equilibrium via Game Theory. Furthermore, an extended optimistic concurrency control protocol is designed to ensure the correctness of concurrent contracts execution. We formally prove the security of IvyCross in the Universal Composability (UC) framework and implement a prototype atop Bitcoin, Ethereum, and FISCO BOCS. Extensive experimental results on end-to-end performance and concurrency control demonstrate the efficiency and practicality of IvyCross. © 2002-2012 IEEE.

关键词： Blockchain

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Semi-ECNet: Edge-Consistency Based Semi-Supervised Retinal Vessel Segmentation Network

Semi-ECNet: Edge-Consistency Based Semi-Supervised Retinal V...

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IEEE International Symposium on Biomedical Imaging

作者： Yilun Qiu Zhongxi Qiu Yan Hu Mingyang Bi Yubo Wang Jianwen Chen Yitian Zhao Heng Li Jiang Liu Department of Computer Science and Engineering Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Southern University of Science and Technology Hospital Shenzhen China Institute of Biomedical Engineering Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo China

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Blood vessel segmentation plays an important role in the diagnosis and treatment of retinal diseases. The performance of supervised deep-learning-based segmentation methods is dependent on the training labels, which brings a great burden to surgeons. Semi-supervised methods can solve the problem partly, but recently proposed algorithms hardly consider the complexity of the tree structures in retinal images, especially fine peripheral bronchi. Thus, we propose a novel edge-consistency based semi-supervised retinal vessel segmentation algorithm, named Semi-ECNet. Specifically, Semi-ECNet first generates two kinds of vessel maps, including an edge constraint map and a pixel-wise probability map in the model-prediction stage. Then for the loss-consistency stage, we adopt the Sobel operator and propose a novel loss strategy for the consistency constraints among these maps and the ground truth. Extensive experiments on a publicly available dataset demonstrate that our Semi-ECNet effectively leverages unlabeled data, and outperforms other state-of-the-art semi-supervised segmentation methods by introducing this innovative edge-consistency strategy.

关键词： Training Image segmentation Image edge detection Supervised learning Surgery Blood vessels Retinal vessels

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Equilibrium-Independent Control of Continuous-Time Nonlinear systems via the LPV Framework - Extended Version

arXiv

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arXiv 2023年

作者： Koelewijn, Patrick J.W. Weiland, Siep Tóth, Roland The Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands The Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

In this paper, we consider the analysis and control of continuous-time nonlinear systems to ensure universal shifted stability and performance, i.e., stability and performance w.r.t. each forced equilibrium point of the system. This "equilibrium-free" concept is especially beneficial for control problems that require the tracking of setpoints and rejection of persistent disturbances, such as input loads. In this paper, we show how the velocity form, i.e., the time-differentiated dynamics of the system, plays a crucial role in characterizing these properties and how the analysis of it can be solved by the application of Linear Parameter-Varying (LPV) methods in a computationally efficient manner. Furthermore, by leveraging the properties of the velocity form and the LPV framework, a novel controller synthesis method is presented which ensures closed-loop universal shifted stability and performance. The proposed controller design is verified in a simulation study and also experimentally on a real system. Additionally, we compare the proposed method to a standard LPV control design, demonstrating the improved stability and performance guarantees of the new approach. Copyright © 2023, The Authors. All rights reserved.

关键词： Controllers

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Digital Twin-Driven Intrusion Detection for IoT and Cyber-Physical System

Digital Twin-Driven Intrusion Detection for IoT and Cyber-Ph...

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2024 International Conference on Intelligent Algorithms for Computational Intelligence systems, IACIS 2024

作者： Ramamoorthy, Saravanan Kandaneri Sindhu, L. Valarmathi, K. Gobinath, C. Umaeswari, P. College of Non-Medicine University: Texila American University Guyana Sona College of Technology Department of Information Technology Salem India S. A. Engineering College Department of Information Technology Chennai India Reva University School of Computing and Information Technology Bengaluru India R.M.K. Engineering College Department of Computer Science and Business Systems Kavaraipettai India

ISBN: (纸本)9798350360660

From smart homes to industrial automation, the efficiency and connectivity of many applications have been greatly improved by the fast expansion of the Internet of Things (IoT) and Cyber-Physical systems (CPS). Sophisticated cyberattacks are becoming more common in this networked ecosystem, thus strong security measures are needed. In order to protect CPS and IoT settings, this study presents a new intrusion detection method that makes use of Digital Twin technology. To build an adaptable and dynamic Intrusion Detection System (IDS), our suggested architecture combines Digital Twins with state-of-the-art machine learning methods. In order to accurately detect and categorize any threats, the IDS constantly learns from data in both the past and the present. When tested on benchmark datasets and in real-world Internet of Things (IoT) settings, the framework outperforms conventional intrusion detection system (IDS) solutions in terms of detection accuracy and false alarm rate reduction. To protect IoT and CPS infrastructures from ever-changing cyber threats, this scalable and resilient security solution is offered by this IDS that is powered by digital twins. We present ICNN-FCID, an Integrated Convolutional Neural Network for Fog Computing Environment, a hybrid deep learning intrusion detection model for fog computing environments. © 2024 IEEE.

关键词： Network intrusion

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Sensitivity Decouple Learning for Image Compression Artifacts Reduction

arXiv

引用

arXiv 2024年

作者： Ma, Li Zhao, Yifan Peng, Peixi Tian, Yonghong Huawei Technologies Company Ltd Shenzhen518129 China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China School of Electronics and Computer Engineering School of Computer Science Peking University Beijing100871 China PengCheng Laboratory Shenzhen518055 China

With the benefit of deep learning techniques, recent researches have made significant progress in image compression artifacts reduction. Despite their improved performances, prevailing methods only focus on learning a mapping from the compressed image to the original one but ignore the intrinsic attributes of the given compressed images, which greatly harms the performance of downstream parsing tasks. Different from these methods, we propose to decouple the intrinsic attributes into two complementary features for artifacts reduction, i.e., the compression-insensitive features to regularize the high-level semantic representations during training and the compressionsensitive features to be aware of the compression degree. To achieve this, we first employ adversarial training to regularize the compressed and original encoded features for retaining high-level semantics, and we then develop the compression quality-aware feature encoder for compression-sensitive features. Based on these dual complementary features, we propose a Dual Awareness Guidance Network (DAGN) to utilize these awareness features as transformation guidance during the decoding phase. In our proposed DAGN, we develop a cross-feature fusion module to maintain the consistency of compression-insensitive features by fusing compression-insensitive features into the artifacts reduction baseline. Our method achieves an average 2.06 dB PSNR gains on BSD500, outperforming state-of-the-art methods, and only requires 29.7 ms to process one image on BSD500. Besides, the experimental results on LIVE1 and LIU4K also demonstrate the efficiency, effectiveness, and superiority of the proposed method in terms of quantitative metrics, visual quality, and downstream machine vision tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep learning

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Enhanced Capuchin Search Algorithm Using Cooperative Island Model with Application of Evolutionary Feedforward Neural Networks

Enhanced Capuchin Search Algorithm Using Cooperative Island ...

引用

Intelligent Computing, Communication, Networking and Services (ICCNS), International Conference on

作者： Thaer Thaher Mohammed Awad Alaa Sheta Mohammed Aldasht Department of Computer Systems Engineering Arab American University Jenin Palestine Computer Science Department Southern Connecticut State University CT 06515 USA Department of Computer Engineering Palestine Polytechnic University Hebron Palestine

This paper introduces an enhanced version of the Capuchin Search Algorithm (CapSA) called ECapSA. CapSA draws inspiration from the collective intelligence of Capuchin monkeys and has shown success in solving real-world problems. However, it may encounter challenges handling complex optimization tasks, such as premature convergence or being trapped in local optima. ECapSA employs a local escaping mechanism operating the abandonment limit concept to exploit potential solutions and introduce diversification trends. Additionally, the ECapSA algorithm is improved by integrating the principles of the cooperative island model, resulting in the iECapSA. This modification enables better management of population diversity and a more optimal balance between exploration and exploitation. The efficiency of iECapSA is validated through a series of experiments, including the IEEE-CEC2014 benchmark functions and training the feedforward neural network (FNN) on seven biomedical datasets. The performance of iECapSA is compared to other metaheuristic techniques, namely differential evolution (DE), sine cosine algorithm (SCA), and whale optimization algorithm (WOA). The results of the comparative study demonstrate that iECapSA is a strong contender and surpasses other training algorithms in most datasets, particularly in terms of its ability to avoid local optima and its improved convergence speed.

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Prompt Learning on Temporal Interaction Graphs

arXiv

引用

arXiv 2024年

作者： Chen, Xi Zhang, Siwei Xiong, Yun Wu, Xixi Zhang, Jiawei Sun, Xiangguo Zhang, Yao Zhao, Feng Kang, Yulin Shanghai Key Laboratory of Data Science School of Computer Science Fudan University Shanghai China IFM Lab Department of Computer Science University of California DavisCA United States Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong Ant Group Shanghai Hangzhou China

Temporal Interaction Graphs (TIGs) are widely utilized to represent real-world systems, such as e-commerce and social networks. To facilitate representation learning on TIGs, researchers have proposed a series of TIG models. However, these models are still facing two tough gaps between the pre-training and downstream predictions in their "pre-train, predict" training paradigm. First, there is a temporal gap that exhibits limited accommodation ability to their timely predictions. This shortcoming severely undermines their applicability in distant future predictions on the dynamically evolving TIG data. Second, there is a semantic gap due to the lack of versatility in these pre-trained models to effectively cater to diverse downstream tasks. This hinders their practical applications, as they struggle to align with their learning and prediction capabilities across various application scenarios. Recently, the "pre-train, prompt" paradigm has emerged as a lightweight mechanism for model generalization. Therefore, applying this paradigm within TIGs is a potential solution to solve the aforementioned challenges. However, the adaptation of this paradigm to TIGs is not straightforward. The prevalent application of prompting in static graph contexts falls short in temporal settings due to a lack of consideration for time-sensitive dynamics and a deficiency in expressive power. To address this issue, we introduce Temporal Interaction Graph Prompting (TIGPrompt), a versatile framework that seamlessly integrates with existing TIG models, bridging both the temporal and semantic gaps mentioned above. In detail, we propose a temporal prompt generator to offer temporally-aware prompts for different tasks. These prompts stand out for their minimalistic design, relying solely on the fine-tuning of the prompt generator with very little supervision data, which is extremely efficient. To cater to varying computational resource demands, we propose an extended "pre-train, prompt-based fine

关键词： Forecasting

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Modeling of Energy Flows in Microgrids 31

Modeling of Energy Flows in Microgrids

引用

2023 31st National Conference with International Participation, TELECOM 2023

作者： Stanchev, Plamen Vacheva, Gergana Hinov, Nikolay Klimenta, Dardan Technical University of Sofia Faculty of Computer Systems and Technologies Departement of Information Techonology in Industry Sofia Bulgaria Technical University of Sofia Faculty of Electronic Engineering and Technologies Departement of Power Electronics Sofia Bulgaria University of Priština in Kosovska Chair of Power Engineering Faculty of Technical Science Kosovska Mitrovica Mitrovica Serbia

ISBN: (纸本)9798350303292

In this article, a microgrid model with the possibility of adding renewable energy sources is considered. The considered grid is radial and in it the dues of the lines between the individual nodes have been added and the values of the loads have been set. According to a certain methodology, the necessary cross-sections and type of wires are calculated and designed. Different energy sources and energy storage elements can be easily connected to the implemented scheme. For this reason, it is suitable for study by students and doctoral students for a better presentation of the basic principles in the distribution of energy flows in low voltage grids. © 2023 IEEE.

关键词： Renewable energy

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LED there be DoS: Exploiting variable bitrate IP cameras for network DoS

arXiv

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arXiv 2025年

作者： Goldberg, Emmanuel Brodt, Oleg Elyashar, Aviad Puzis, Rami Department of Software and Information Systems Engineering Ben-Gurion University of the Negev Israel Cyber Labs@BGU Ben-Gurion University of the Negev Israel Department of Computer Science Shamoon College of Engineering Israel

Variable-bitrate video streaming is ubiquitous in video surveillance and CCTV, enabling high-quality video streaming while conserving network bandwidth. However, as the name suggests, variable-bitrate IP cameras can generate sharp traffic spikes depending on the dynamics of the visual input. In this paper, we show that the effectiveness of video compression can be reduced by up to 6× using a simple laser LED pointing at a variable-bitrate IP camera, forcing the camera to generate excessive network traffic. Experiments with IP cameras connected to wired and wireless networks indicate that a laser attack on a single camera can cause significant packet loss in systems sharing the network with the camera and reduce the available bandwidth of a shared network link by 90%. This attack represents a new class of cyber-physical attacks that manipulate variable bitrate devices through changes in the physical environment without a digital presence on the device or on the network. We also analyze the broader view of multidimensional cyberattacks that involve both the physical and digital realms and present a taxonomy that categorizes attacks based on their direction of influence (physical-to-digital or digital-to-physical) and their method of operation (environment-driven or device-driven), highlighting multiple areas for future research. © 2025, CC BY-NC-ND.

关键词： Video streaming

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