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Brain Tumor Diagnosis Using Sparrow Search Algorithm Based Deep Learning Model

Computer systems science & engineering 2023年第2期44卷 1793-1806页

作者： G.Ignisha Rajathi R.Ramesh Kumar D.Ravikumar T.Joel Seifedine Kadry Chang-Won Jeong Yunyoung Nam Department of Computer Science and Business Systems Sri Krishna College of Engineering and TechnologyCoimbatore641008India Department of Information Technology Sri Krishna College of TechnologyCoimbatore641008India Department of Electronics and Communication Engineering Kings Engineering CollegeChennai602117India Department of Electronics and Communication Engineering R.M.K.Engineering CollegeChennai601206India Deparmtent of Applied Data Science Noroff University CollegeKristiansandNorway Medical Convergence Research Center Wonkwang UniversityIksanKorea Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Recently,Internet of Medical Things(IoMT)has gained considerable attention to provide improved healthcare services to *** earlier diag-nosis of brain tumor(BT)using medical imaging becomes an essential task,auto-mated IoMT and cloud enabled BT diagnosis model can be devised using recent deep learning *** this motivation,this paper introduces a novel IoMT and cloud enabled BT diagnosis model,named *** IoMTC-HDBT model comprises the data acquisition process by the use of IoMT devices which captures the magnetic resonance imaging(MRI)brain images and transmit them to the cloud ***,adaptive windowﬁltering(AWF)based image preprocessing is used to remove *** addition,the cloud server executes the disease diagnosis model which includes the sparrow search algorithm(SSA)with GoogleNet(SSA-GN)*** IoMTC-HDBT model applies functional link neural network(FLNN),which has the ability to detect and classify the MRI brain images as normal or ***ﬁnds useful to generate the reports instantly for patients located in remote *** validation of the IoMTC-HDBT model takes place against BRATS2015 Challenge dataset and the experimental analysis is car-ried out interms of sensitivity,accuracy,and speciﬁ*** experimentation out-come pointed out the betterment of the proposed model with the accuracy of 0.984.

关键词： Internet of medical things healthcare brain tumor disease classiﬁcation deep learning metaheuristics

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Performance Analysis of MIMO CR Multihop Relaying with Imperfect CSI in Short-Packet URLLCs 14

Performance Analysis of MIMO CR Multihop Relaying with Imper...

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14th International Conference on information and Communication Technology Convergence, ICTC 2023

作者： Tu, Ngo Hoang Trong Dai, Hoang Lee, Kyungchun University of Technology Sydney School of Electrical and Data Engineering UltimoNSW2007 Australia Seoul National University of Science and Technology Department of Electrical and Information Engineering Seoul01811 Korea Republic of Seoul National University of Science and Technology Research Center for Electrical and Information Technology Seoul01811 Korea Republic of

ISBN: (纸本)9798350313277

This paper evaluates the multiple-input multiple-output underlay cognitive multihop relay networks with short-packet communications, where general and practical scenarios are considered with multiple primary users and imperfect channel state information of the interference channels. For performance evaluation, the closed-form expressions of the end-to-end (E2E) block error rate for the considered systems are derived under consideration of quasi-static Rayleigh fading channels and the finite-blocklength (FBL) regime, from which the E2E throughput, energy efficiency (EE), latency, and reliability are also studied. Based on the analytical results, we adopt a machine learning-aided estimator, i.e., extreme gradient boosting (XGB), to predict the E2E throughput, EE, latency, and reliability for real-time configurations. The XGB-based evaluation achieves equivalent performance while significantly reducing the execution time compared to conventional analytical and simulation methods, which makes XGB an efficient tool to estimate the system performance in real-time applications. © 2023 IEEE.

关键词： and machine learning multihop relaying multiple-input multiple-output (MIMO) Short-packet communication (SPC) underlay cognitive radio (CR)

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Enhancing Wireless Sensor Network data Collection through Aerial Unmanned Vehicles

Enhancing Wireless Sensor Network Data Collection through Ae...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Ali Alheeti, Khattab M. Najim, Ali Hamza Satar, Nurhizam Safie Mohd Aliesawi, Salah A. Hashim, Aisha Hassan Abdallah Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia College of Computer and Information Technology Department of Computer Networking Systems University of Anbar Anbar Iraq Faculty of Engineering Department of Electrical and Computer Engineering International Islamic University Malaysia Selangor Malaysia

ISBN: (纸本)9798350369106

This study addresses the critical aspect of data collection within Wireless Sensor Networks (WSNs), which consist of autonomous, compact sensor devices deployed to monitor environmental conditions. These networks have limited processing capacity, storage, short-range communication capabilities, and constrained battery power. A primary challenge in WSN s revolves around data gathering, particularly when employing static sinks, leading to premature energy depletion in nodes near these sinks. Integrating mobile collectors introduces the potential for energy conservation by shortening data routes. This article introduces three distinct algorithms for optimizing data collection in WSN s. Our approach involves an in-depth analysis of diverse strategies to mitigate packet collisions and facilitate the retransmission of lost packets. Our findings underscore the considerable impact that packet collisions can exert on the overall network performance during data gathering within wireless sensor networks. Through empirical exploration and analysis, we highlight the significance of these algorithms in enhancing the efficiency, energy conservation, and reliability of data collection processes within WSNs. This research sheds light on these algorithms' vital role in addressing the pressing challenges of data gathering and network performance optimization in wireless sensor networks. © 2024 IEEE.

关键词： Aircraft accidents

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Extending Partial Differential Private Mechanisms via Linear Programming

Extending Partial Differential Private Mechanisms via Linear...

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Iran Workshop on Communication and information Theory (IWCIT)

作者： Javad B. Ebrahimi Alireza Tofighi Mohammadi Department of Mathematical Sciences Sharif University of Technology Center for Information Systems and Data Science Institute for Convergence Science Technology Institute for Researches in Fundamental Science (IPM)

ISBN: (数字)9798350387094

ISBN: (纸本)9798350387100

An (ε,δ)-DP mechanism is a mapping defined as follows. The domain of the mechanism is a finite set of objects, (also called the data points) such that a symmetric neighborhood relation over the data points is defined. The range of the mechanism at each data point is a distribution over another set. Further more, neighboring data points must be mapped to two distributions that are not far away. The parametric notion of distance of two distribution in terms of the parameters (ε,δ) in the context of privacy theory, is first introduced by Dwork and her *** this paper, we study the following problem. Given a finite set $\mathcal{D}$ of data points, the neighboring relation, the parameters ε,δ, and a partial mechanism that is defined over a subset ${\mathcal{D}^\prime } \subseteq \mathcal{D}$, is there an extension of the mechanism defined over the entire set $\mathcal{D}$ that is identical to the partial mechanism on D ′ and also, is (ε,δ)-differential private. We show that there exists an algorithm to answer this question and it runs in time that is polynomial in the input variables. Our result generalizes a result of Medard et al. about optimum mechanism extension with respect to preferential query ordering.

关键词： Differential privacy Privacy Shape Input variables Conferences Linear programming Polynomials

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Water color from Sentinel-2 MSI data for monitoring large rivers:Yangtze and Danube

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地球空间信息科学学报（英文版） 2024年第3期27卷 854-869页

作者： Shenglei Wang Xuezhu Jiang Evangelos Spyrakos Junsheng Li Conor McGlinchey Adriana Maria Constantinescu Andrew N.Tyler International Research Center of Big Data for Sustainable Development Goals BeijingChina Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina International Research Center of Big Data for Sustainable Development Goals BeijingChina Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina College of Resources and Environment University of Chinese Academy of SciencesBeijingChina Earth and Planetary Observation Sciences(EPOS) Department of Biological and Environmental StudiesFaculty of Environmental SciencesUniversity of StirlingStirlingUK International Research Center of Big Data for Sustainable Development Goals BeijingChina Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijingChina National Institute of Marine Geology and GeoEcology-GeoEcoMar BucharestRomania

Rivers provide key ecosystem services that are inherently engineered and optimized to meet the strategic and economic needs of countries around the ***,limited water quality records of a full river continuum hindered the understanding of how river systems response to the multiple stressors acting on *** study highlights the use of Sentinel-2 Multi-Spectral Imager(MSI)data to monitor changes in water color in two optically complex river systems:the Yangtze and Danube using the Forel-Ule Index(FUI).FUI divides water color into 21 classes from dark blue to yellowish brown stemming from the historical Forel-Ule water color scale and has been promoted as a useful indicator showing water turbidity variations in water *** results revealed contrasting water color patterns in the two rivers on both spatial and seasonal ***,the FUI of the Yangtze River gradually increased from the upper reaches to the lower reaches,while the FUI of the Danube River declined in the lower reaches,which is possibly due to the sediment sink effect of the Iron Gate *** regional FUI peaks and valleys observed in the two river systems have also been shown to be related to the dams and hydropower stations along ***,the variations of FUI in both systems can be attributed to climate seasonality,especially precipitation in the basin and the water ***,land cover within the river basin was possibly a significant determinant of water color,as higher levels of vegetation in the Danube basin were associated with lower FUI values,whereas higher FUI values and lower levels of vegetation were observed in the Yangtze *** study furthers our knowledge of using Sentinel-2 MSI to monitor and understand the spatial-temporal variations of river systems and highlights the capabilities of the FUI in an optically complex environment.

关键词： Forel-Ule Index(FUI) water color water quality rivers Sentinel-2 MSI Yangtze Danube

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Performance Analysis of Energy and Secure Efficient Routing for Wireless Sensor Networks

Performance Analysis of Energy and Secure Efficient Routing ...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Hussein, Zainab Mohammed Najim, Ali Hamza Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisha Hassan Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

Wireless Sensor Networks (WSNs) are essential for various applications, but their architecture makes them vulnerable to attacks. While traditional security methods like authentication and encryption offer some protection, they often fall short against specific node attacks. This paper introduces the Secure Energy Aware Routing (SEAR) strategy, which uses trust-based assessments to exclude malicious nodes while optimizing energy consumption. SEAR factors in node trust, hop time, and residual energy to ensure reliable data transmission through trustworthy nodes. MATLAB simulations on networks of varying sizes (100-500) compare SEAR with existing methods (EAD and EASER), demonstrating SEAR's superior performance. Results show significant improvements in packet delivery ratio (13-16%), network throughput (19-24 %), energy consumption (32-36%), packet loss (16-190/0), and end-to-end latency (21-26%), proving SEAR's effectiveness in enhancing WSN security, energy efficiency, and performance. © 2024 IEEE.

关键词： MATLAB

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Harris Hawks Optimizer with Graph Convolutional Network Based Weed Detection in Precision Agriculture

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Computer systems science & engineering 2023年第8期46卷 1533-1547页

作者： Saud Yonbawi Sultan Alahmari T.Satyanarayana Murthy Padmakar Maddala E.Laxmi Lydia Seifedine Kadry Jungeun Kim Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia King Abdul Aziz City for Science and Technology RiyadhKingdom of Saudi Arabia Chaitanya Bharathi Institute of Technology HyderabadTelanganaIndia Department of Civil Engineering Vignan’s Institute of Information and Technology(A)DuvvadaVisakhapatnamAP530049India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea

Precision agriculture includes the optimum and adequate use of resources depending on several variables that govern crop *** agriculture offers a novel solution utilizing a systematic technique for current agricultural problems like balancing production and environmental *** control has become one of the significant problems in the agricultural *** traditional weed control,the entire field is treated uniformly by spraying the soil,a single herbicide dose,weed,and crops in the same *** more precise farming,robots could accomplish targeted weed treatment if they could specifically find the location of the dispensable plant and identify the weed *** may lessen by large margin utilization of agrochemicals on agricultural fields and favour sustainable *** study presents a Harris Hawks Optimizer with Graph Convolutional Network based Weed Detection(HHOGCN-WD)technique for Precision *** HHOGCN-WD technique mainly focuses on identifying and classifying weeds for precision *** image pre-processing,the HHOGCN-WD model utilizes a bilateral normal filter(BNF)for noise *** addition,coupled convolutional neural network(CCNet)model is utilized to derive a set of feature *** detect and classify weed,the GCN model is utilized with the HHO algorithm as a hyperparameter optimizer to improve the detection *** experimental results of the HHOGCN-WD technique are investigated under the benchmark *** results indicate the promising performance of the presented HHOGCN-WD model over other recent approaches,with increased accuracy of 99.13%.

关键词： Weed detection precision agriculture graph convolutional network harris hawks optimizer hyperparameter tuning

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DC Voltage Prediction based on CNN with Physics information Embedding for MVDC Distribution systems 10

DC Voltage Prediction based on CNN with Physics Information ...

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10th IEEE International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia

作者： Sun, Pingyang Wu, Rongcheng Wang, Hongyi Shen, Zhiwei Li, Gen Khalid, Muhammad Konstantinou, Georgios Unsw School of Electrical Engineering and Telecommunications Sydney Australia University of Technology Data Science Institute Sydney Australia Alborg University Department of Aau Energy Denmark Dtu Department of Engineering Technology and Didactics Electric Energy Denmark King Fahd University of Petroleum and Minerals Electrical Engineering Department & Interdisciplinary Research Center for Sustainable Energy Systems Saudi Arabia

ISBN: (纸本)9798350351330

Conventional neural networks (NNs), though efficient in rapid dc voltage calculations for medium-voltage direct current (MVDC) distribution systems with diverse converter control schemes, face accuracy challenges with untrained system parameter distributions and topology structures. This paper proposes a physics-embedded convolutional NN (PECNN) to address this issue. The PECNN is enhanced with two additional layers, including a multi-channel combination layer and a physics operation layer. The former channel combination layer strengthens the model feature extraction capability by converting all input channels constituted by initial data matrix into dc voltage, current and line conductance matrix channels. The latter physics operation layer reformulates the combined input channels by physical connections in MVDC systems. The new layers enhance the prediction accuracy and allow generalization of the model. Three MVDC distribution networks with different dc voltage levels and network layouts are used to verify the superiority of proposed PECNN compared to other NNs in different topologies. © 2024 IEEE.

关键词： Convolution

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Improving VANET Localization Performance with data Verification: Challenges and Solutions

Improving VANET Localization Performance with Data Verificat...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Kadhim, Aqeel Kamil Najim, Ali Hamza Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisa Hassan Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

In VANETs, the important and effective applications of vehicle localization include safety and communication applications. Thus, it is difficult to get very accurate localization in the dynamic and often very fluctuating environment of VANET. This research responds to this challenge with a keen thrust on improving vehicle localization using the Mobility data Verification process. The primary goal of this work is to achieve high accuracy of vehicle positioning within VANET by checking the coherence of mobility data of moving vehicles. Hence, we present a concept that builds upon Mobility data Verification to provide real-time location details from vehicles. Both GPS and onboard sensors feed this method, which uses a multi-level verification to flag out or eliminate the errors of deliberately spoofed data points. We use simulations to evaluate and validate the effectiveness of the proposed verification approach. As the proposed system, our previously developed and fine-tuned weighted localization (OWL) strategy does so. The performance evaluation results suggest that our proposed solution is feasible to distinguish automobiles that are not trustworthy and improve the performance of the localization algorithm. © 2024 IEEE.

关键词： Vane pumps

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Evaluation Method of Motor Coordination Ability in Children Based on Machine Vision

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Tsinghua science and Technology 2025年第2期30卷 633-649页

作者： Yi Lei Dawei Shu Miao Yu Donglin Shi Jianqiang Li Yanjie Chen Faculty of Information Technology Beijing University of TechnologyBeijing 100124China Department of Automation Tsinghua UniversityBeijing 100084China Pharmacovigilance Research Center for information technology and Data Science Cross-strait Tsinghua Research InstituteXiamen 361000China Institute of Systems Engineering Dalian University of TechnologyDalian 116024China Physical Education Department Hebei Sports UniversityShijiazhuang 050049China Department of Children’s Health Care Center Beijing Children’s HospitalCapital Medical UniversityNational Center for Children’s HealthBeijing 100045China

Motor coordination is crucial for preschoolers’development and is a key factor in assessing childhood *** diagnostic methods often rely on subjective manual *** paper presents a machine vision-based approach aimed at improving the objectivity and adaptability of *** method proposed involves the extraction of key points from the human skeleton through the utilization of a lightweight pose estimation network,thereby transforming video assessments into evaluations of keypoint *** study uses different methods to handle static and dynamic actions,including regularization and Dynamic Time Warping(DTW)for spatial alignment and temporal discrepancies.A penalty-adjusted single-frame pose similarity method is used to evaluate *** lightweight pose estimation model reduces parameters by 85%,uses only 6.6%of the original computational load,and has an average detection missing rate of less than 1%.The average error for static actions is 0.071 with a correlation coefficient of 0.766,and for dynamic actions it is 0.145 with a correlation coefficient of *** results confirm the proposed method’s effectiveness,which includes customized visual components like motion waveform graphs to improve accuracy in pediatric healthcare diagnoses.

关键词： developmental coordination disorder action quality assessment pose estimation dynamic time warping decision support system

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