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5th International Conference on Advancements in Computing, ICAC 2023

作者： Wijerathna, Udari Dissanayake, Nimavi Nimasha, Dinithi Senarathne, Udara Weerasinghe, Lokeesha Kahandawaarachchi, Chathurangika Sri Lanka Institute of Information Technology Faculty of Computing Dept of Computer System Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Dept of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Dept of Computer System Network Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

Abnormal formation of cells in a layer. The brain is known as the brain cancer complex, and a brain cancer detection system is needed to detect cancer in its early stages Phase. As a result, the primary goal of this initiative is to assist existing doctors in their training for the early identification o f brain cancer by utilizing magnetic resonance imaging (MRI), which is the most effective approach to identifying brain cancer. This system is done through four components, and it has made it easier to detect brain tumors. These techniques with different image processing techniques include noise removal, segmentation, classification, a nd u se o fa nalysis segments f or detection. Pre-processing techniques prepare the image for further processing by removing image noise. During segmentation, the brain tumor system determines the size of the brain tumor and estimates its size. Specialists should examine them and classify brain tumors as meningiomas, gliomas, and pituitary tumors. In analysis, this component is expected to be designed so that users or medical experts can know the future through a dashboard. We explored the methodology of using generative adversarial networks (GANs) implemented in TensorFlow to denominate brain tumor images. Analyses the outcomes of various types of established deep learning models on the brain tumor MR image datasets, such as classification methods ResNet-50, VGG 16, CNN, and Inception V3. The validation precision, AUC, recall, and validation loss for CNN are 95.3%, 99.43%, 92.1 %, and 0.360 adjustments respectively. © 2023 IEEE.

关键词： Magnetic resonance imaging

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Brain Tumor Detection Using Image Processing

Brain Tumor Detection Using Image Processing

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Advancements in Computing (ICAC), International Conference on

作者： Udari Wijerathna Nimavi Dissanayake Dinithi Nimasha Udara Senarathne Lokeesha Weerasinghe Chathurangika Kahandawaarachchi Dept of Computer System Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Dept of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Dept of Computer System Network Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

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Increasing Hosting Capacity of Uncontrollable Distributed Energy Resources in Isolated Power systems

Increasing Hosting Capacity of Uncontrollable Distributed En...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Phivos Therapontos Andreas Stavrou Petros Aristidou Distribution System Operator Electricity Authority of Cyprus Nicosia Cyprus Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Transmission Network Owner Electricity Authority of Cyprus Nicosia Cyprus Dept. of Electrical & Computer Engineering & Informatics Cyprus University of Technology Limassol Cyprus

Due to the push for more sustainable generation, small-scale distributed energy resources (DERs) penetration has increased significantly. Most countries have no remote monitoring and control requirements for DERs below a certain size. Therefore, they can be labeled as uncontrollable DERs (UDERs). In isolated systems, the UDERs hosting capacity is limited due to frequency stability concerns, as it is impossible to modify or curtail their generation in a centralized manner. In this paper, we propose the utilization of the active power over-frequency reduction curve for increasing the hosting capacity of UDERs in isolated power systems. Cyprus’s power system has been used to evaluate the proposed solution’s performance. The optimal settings of the curve have been identified, and it was found that UDERs hosting capacity can be increased significantly with the proposed methodology.

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Application and Assessment of Click Modular Firewall vs POX Firewall in SDN/NFV Framework

Application and Assessment of Click Modular Firewall vs POX ...

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2020 IEEE Region 10 Conference, TENCON 2020

作者： Monir, Md Fahad Pan, Dan Independent University Dept. of Computer Science and Engineering Dhaka Bangladesh Telenor Sverige AB Dept. of Network Development System Stockholm Sweden

ISBN: (纸本)9781728184555

The evolution of Software Defined networks (SDN) and network Function Virtualization (NFV) introduced a revolutionary development in network architecture. SDN together with NFV provides users a platform to design flexible virtual networks (VNs) on a shared computer infrastructure. However, network administrators have specific requirements to secure this network. There are new security demands for VN such as flexible network function migrations and user-focused security system, which may not be supported by traditional firewalls. In our work we have implemented SDN and NFV based firewalls on an open source platform mininet. POX module and Click Modular Router are used to develop our firewall modules. Then we evaluated the performance of both firewalls with packet loss and throughput measurement. © 2020 IEEE.

关键词： network function virtualization

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Improving the Noise Estimation of Latent Neural Stochastic Differential Equations

arXiv

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arXiv 2024年

作者： Heck, Linus Gelbrecht, M. Schaub, M. Boers, N. Institute for Computing and Information Sciences Radboud University Nijmegen Netherlands Earth System Modelling School of Engineering and Design TU Munich Germany Computational Network Science Dept of Computer Science RWTH Aachen University Germany Department of Computer Science RWTH Aachen University Germany Complexity Science Potsdam Institute for Climate Impact Research Potsdam Germany Department of Mathematics and Statistics University of Exeter Exeter United Kingdom

Latent neural stochastic differential equations (SDEs) have recently emerged as a promising approach for learning generative models from stochastic time series data. However, they systematically underestimate the noise level inherent in such data, limiting their ability to capture stochastic dynamics accurately. We investigate this underestimation in detail and propose a straightforward solution: by including an explicit additional noise regularization in the loss function, we are able to learn a model that accurately captures the diffusion component of the data. We demonstrate our results on a conceptual model system that highlights the improved latent neural SDE’s capability to model stochastic bistable dynamics. © 2024, CC BY-NC-ND.

关键词： Stochastic models

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Lightweight Task-Oriented Semantic Communication Empowered by Large-Scale AI Models

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IEEE Transactions on Vehicular Technology 2025年

作者： Liu, Chuanhong Guo, Caili Yang, Yang Chen, Mingzhe Quek, Tony Q. S. Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL United States Singapore University of Technology and Design Dept. of Information Systems Technology and Design 487372 Singapore

Recent studies have focused on leveraging large-scale artificial intelligence (LAI) models to improve semantic representation and compression capabilities. However, the substantial computational demands of LAI models pose significant challenges for real-time communication scenarios. To address this, this paper proposes utilizing knowledge distillation (KD) techniques to extract and condense knowledge from LAI models, effectively reducing model complexity and computation latency. Nevertheless, the inherent complexity of LAI models leads to prolonged inference times during distillation, while their lack of channel awareness compromises the distillation performance. These limitations make standard KD methods unsuitable for task-oriented semantic communication scenarios. To address these issues, we propose a fast distillation method featuring a pre-stored compression mechanism that eliminates the need for repetitive inference, significantly improving efficiency. Furthermore, a channel adaptive module is incorporated to dynamically adjust the transmitted semantic information based on varying channel conditions, enhancing communication reliability and adaptability. In addition, an information bottleneck-based loss function is derived to guide the fast distillation process. Simulation results verify that the proposed scheme outperform baselines in term of task accuracy, model size, computation latency, and training data requirements. © 1967-2012 IEEE.

关键词： NP-hard

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Random graph modeling of foliage influence on millimeter-wave propagation channels 23

Random graph modeling of foliage influence on millimeter-wav...

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23rd International ITG Workshop on Smart Antennas, WSA 2019

作者： Yang, Lin Yin, Xuefeng Rodríguez-Piñeiro, José Wang, Nanxin Yu, Ziming School of Electronics and Information Engineering Tongji University Shanghai China National Computer and Information Technology Practical Education Demonstration Center Tongji University Shanghai China Wireless Network System Research Dept. II WN Huawei Technologies Corporation Chengdu China

ISBN: (纸本)9783800749409

In this paper, we propose a novel graph modeling method for analyzing the impact of foliage on propagation channels by utilizing spherically distributed scatters to characterize trees influence. Traditional graph modelling always uses rectangular or squared surfaces to simulate the real world objects, hence it fails to reflect foliage scattering structures accurately. By introducing the sphere, the original shape of environmental elements can be better modeled, resulting in a better explanation of the foliage influence on millimeter-waves (mm-waves) propagation. By comparing simulation results with measurements, we appreciated slight mismatches. With the aim of minimizing the mismatches found in our first approach, the proposed graph model is improved by using multilayer nested spheres, and the results obtained are more consistent with the measurement ones. The evaluation of the proposed method is conducted by comparing the simulated foliage loss characteristics and the real-environment measured data in directional domain. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach

关键词： Wave propagation

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Fish-Eye Lenses-Based Camera Calibration and Panoramic Image Stitching 5

Fish-Eye Lenses-Based Camera Calibration and Panoramic Image...

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5th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2018

作者： Hsu, Chao-Yung Chang, Chih-Ming Kang, Li-Wei Kang Fu, Ru-Hong Chen, Duan-Yu Weng, Ming-Fang Automation Instrumentation System Development Sec. China Steel Corporation Kaohsiung Taiwan New Smart Technology Co. LTD. Taipei Taiwan Graduate School of Engineering Science and Technology Dept. Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan Department of Electrical Engineering Yuan Ze University Taoyuan Taiwan Institute for Information Industry Smart Network System Institute Taiwan

ISBN: (纸本)9781538663011

Fish-eye lenses are common in several computer vision applications, such as four-camera surround view driver assistance, where a very wide angle (e.g., 180 degrees) of view is available. Nevertheless, their applicability is usually limited by the lack of an accurate and easy-to-use calibration procedure. In this paper, we present a camera calibration method for fish-eye lenses and a panoramic image stitching framework for calibrated surround images. To achieve the calibration of fish-eye captured images, it only requires to observe a reference planar pattern (e.g., chessboard), followed by offline estimating extrinsic and intrinsic parameters and save the related parameters. Each fish-eye distorted image can then be efficiently online corrected. Then, each calibrated image is transformed to its top-down view (or bird's-eye view) via the perspective transformation based on the estimated homography matrix. As a result, these surround bird'seye view images can be stitched to generate the final panoramic image. It is expected that the proposed framework would be applicable to AVM (around view monitoring) system or ADAS (advanced driver assistance system) of vehicles in the future. © 2018 IEEE.

关键词： Calibration

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Abstracts

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JOURNAL OF SPINAL CORD MEDICINE 2021年第SUPPL 1期44卷 S278-S324页

作者： [Anonymous] Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto Toronto ON CA KITE - Toronto Rehabilitation Institute University Health Network Toronto ON CA Institute for Health Policy Management and Evaluation University of Toronto Toronto ON CA Rehabilitation Sciences Institute University of Toronto Toronto ON CA Institute of Medical Sciences University of Toronto Toronto ON CA. Rehabilitation Sciences Institute University of Toronto ON CA KITE Research Institute-Toronto Rehab-University Health Network Toronto ON CA Physical Therapy Department University of Toronto ON CA Praxis Spinal Cord Institute Vancouver BC Université de Montréal (École de réadaptation) Montreal QC CA Institut de réadaptation Gingras-Linsay-de-Montréal Montreal QC CA Division of Physical Medicine & Rehabilitation Department of Medicine Faculty of Medicine & Dentistry University of Alberta Edmonton AB CA University of Calgary Calgary AB CA Alberta Health Services Centre for Family Medicine Kitchener ON CA McMaster University Department of Family Medicine Hamilton ON CA Dept. of Physical Therapy University of Toronto Toronto ON CA KITE-University Health Network Toronto ON CA Praxis Spinal Cord Institute Vancouver BC CA Center for Interdisciplinary Research in Rehabilitation and Social Integration (CIRRIS) Quebec City QC CA Dept. of Rehabilitation Laval University Quebec City QC CA Institute of Health Policy Management and Evaluation University of Toronto Toronto ON CA School of Rehabilitation Science University of Saskatchewan Saskatoon SK CA Ontario Neurotrauma Foundation Toronto ON CA Canadian Spinal Research Organization Toronto ON CA CIUSSS du Centre-Sud-de-l ‘Île-de-Montréal (Installation Gingras-Lindsay) Montréal QC CA École de réadaptation Université de Montréal Montréal QC CA First Steps Wellness Centre Regina SK CA Stan Cassidy Centre for Rehabilitation Horizon Health Network Fredericton NB CA Departmen

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Learning Space Conceptual Model for Computing Games Developers

Learning Space Conceptual Model for Computing Games Develope...

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International computer Sciences and Information Technologies (CSIT)

作者： Andrii Biloshchytskyi Alexander Kuchansky Yurii Andrashko Olena Bielova Department of network and Internet technologies KNU Kyiv Ukraine Dept. of cybersecurity and computer engineering KNUCA Kyiv Ukraine Dept. of system analysis and optimization theory UzhNU Uzhhorod Ukraine Dept. of business admin. and project management KROK University Kyiv Ukraine

The article is devoted to the construction of learning space conceptual model for preparation of GameHub computer game developers in higher education institutions. The concept consists of three main components: a methodological or pedagogical component, a technological component, an information component. The article describes processes scheme for developing of learning space infrastructure and reflects the interactions between GameHub participants. The article presents an example of such a scheme for magistracy students, bachelor's degree students and free listeners from one of the Ukrainian universities. An approach to the student knowledge diagnosis is described on the basis of writing and testing analysis. Highlighted results in this paper are useful as a guide for step-by-step organization and for supporting the functioning of game educational hubs in higher education institutions. The described concept includes basic tools that are necessary for effective student training organizing on the principles of computer game development. Learning space conceptual model can serve as foundation for the formation of professionals training implementation roadmap in gaming industry. The concept is proposed for implementation by universities and private IT companies interested in Serious Games industry development.

关键词： Training Games Industries Laboratories Task analysis Software

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