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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Rajkumar, K. Ragupathi, T. Karthikeyan, S. School of Computing Srm Institute of Science and Technology Department of Data Science and Business Systems Tamil Nadu Kattankulathur India Department of Computer Science and Engineering Bangalore562112 India

ISBN: (纸本)9798350371055

The main objective of this project is to create a user-friendly intelligent chatbot for Medical guidance and support. This application has been classified into two different modes based on user preference, those are Online and Offline modes of interaction. In the Online mode of interaction, there is no need for any automation, there will be a real person at the other end answering user queries. Users can even ask for untrained data and will receive instant replies. This application is similar to a normal chat application, but the main disadvantage is that a real person is needed at the other end at all times. In the Offline mode of conversation which is entirely automated the user will be performing an interaction with the chatbot itself. The chatbot must consist of data sets and trained data collection, in this process there is no need for any real person, the chatbot itself will reply instantly based on the trained data. The chatbot will be more accurate when a large number of data is trained. This application is compatible with working in various browsers and varied networks. The Admin of the application plays a significant role. Admin can access all the given functions and is responsible for data training. Data training plays a vital role in this application, the trained data will be used by the chatbot while answering user queries i.e. Offline mode. This chatbot application can be accessed by several users at the same time, where IP address plays the main role. The main function of this application is that user can post their corresponding queries and the application will be providing relevant information based on queries. The Latest Modern chatbots are used in applications where simple interaction is needed, for example, service and marketing technology to provide answers such as products, services, and consultancy. If the customer's queries don't match with the trained data sets, the customer will be escalated to manual interaction i.e. Online mode. © 2024 IE

关键词： Automated Intelligent Chat IP Address Offline mode Online mode Trained Data

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Machine Learning Based Diagnosis for Diabetic Retinopathy for SKPD-PSC

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Intelligent Automation & Soft Computing 2023年第5期36卷 1767-1782页

作者： M.P.Thiruvenkatasuresh Surbhi Bhatia Shakila Basheer Pankaj Dadheech Department of Computer Science and Engineering Erode Sengunthar Engineering CollegePerunduraiErode638057Tamil NaduIndia Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityAl HasaSaudi Arabia Department of Information Systems College of Computer and Information SciencePrincess Nourah bint Abdulrahman UniversityP.O.BOX 84428Riyadh11671Saudi Arabia Department of Computer Science&Engineering Swami Keshvanand Institute of TechnologyManagement&Gramothan(SKIT)Jaipur302017RajasthanIndia Corresponding

The study aimed to apply to Machine Learning(ML)researchers working in image processing and biomedical analysis who play an extensive role in compre-hending and performing on complex medical data,eventually improving patient *** a novel ML algorithm speciﬁc to Diabetic Retinopathy(DR)is a chal-lenge and need of the *** images include several challenges,including relevant feature selection,class variations,and robust classiﬁ*** the cur-rent research in DR has yielded favourable results,several research issues need to be *** is a requirement to look at novel pre-processing methods to discard irrelevant features,balance the obtained relevant features,and obtain a robust classi-ﬁ*** is performed using the Steerable Kernalized Partial Derivative and Platt Scale Classiﬁer(SKPD-PSC)*** novelty of this method relies on the appropriate non-linear classiﬁcation of exclusive image processing models in har-mony with the Platt Scale Classiﬁer(PSC)to improve the accuracy of DR ***,a Steerable Filter Kernel Pre-processing(SFKP)model is applied to the Retinal Images(RI)to remove irrelevant and redundant features and extract more meaningful pathological features through Directional Derivatives of Gaussians(DDG).Next,the Partial Derivative Image Localization(PDIL)model is applied to the extracted fea-tures to localize candidate features and suppress the background ***,a Platt Scale Classiﬁer(PSC)is applied to the localized features for robust classiﬁ*** the experiments,we used the publicly available DR detection database provided by Standard Diabetic Retinopathy(SDR),called DIARETDB0.A database of 130 image samples has been collected to train and test the ML-based classiﬁ*** results show that the proposed method that combines the image processing and ML models can attain good detection performance with a high DR detection accu-racy rate with minimum time and complexity compared to

关键词： Diabetic retinopathy retinal images machine learning image localization Platt Scale classiﬁer accuracy

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Accelerating Gradient Tracking with Periodic Global Averaging 63

Accelerating Gradient Tracking with Periodic Global Averagin...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Feng, Shujing Jiang, Xin Lehigh University Department of Computer Science and Engineering BethlehemPA United States Lehigh Univeristy Department of Industrial and Systems Engineering BethlehemPA United States

ISBN: (纸本)9798350316339

Decentralized optimization algorithms have recently attracted increasing attention due to its wide applications in all areas of science and engineering. In these algorithms, a collection of agents collaborate to minimize the average of a set of heterogeneous cost functions in a decentralized manner. State-of-the-art decentralized algorithms like Gradient Tracking (GT) and Exact Diffusion (ED) involve communication at each iteration. Yet, communication between agents is often expensive, resource intensive, and can be very slow. To this end, several strategies have been developed to balance between communication overhead and convergence rate of decentralized methods. In this paper, we introduce GT-PGA, which incorporates GT with periodic global averaging. With the additional PGA, the influence of poor network connectivity in the GT algorithm can be compensated or controlled by a careful selection of the global averaging period. Under the stochastic, nonconvex setup, our analysis quantifies the crucial trade-off between the connectivity of network topology and the PGA period. Thus, with a suitable design of the PGA period, GT-PGA improves the convergence rate of vanilla GT. Numerical experiments are conducted to support our theory, and simulation results reveal that the proposed GT-PGA accelerates practical convergence, especially when the network is sparse. © 2024 IEEE.

关键词： Cost functions

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Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space

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computers, Materials & Continua 2023年第11期77卷 2031-2047页

作者： Mudassir Khalil Muhammad Imran Sharif Ahmed Naeem Muhammad Umar Chaudhry Hafiz Tayyab Rauf Adham E.Ragab Department of Computer Engineering Bahauddin Zakariya UniversityMultan60000Pakistan Department of Computer Science Kansas State UniversityManhattanKS66506USA Department of Computer Science University of Management and TechnologyLahore54000Pakistan Centre for Smart Systems AI and CybersecurityStaffordshire UniversityStoke-on-TrentST42DEUK Industrial Engineering Department Collage of EngineeringKing Saud UniversityPO Box 800Riyadh11421Saudi Arabia

Early detection of brain tumors is critical for effective treatment *** tumors in their nascent stages can significantly enhance the chances of patient *** there are various types of brain tumors,each with unique characteristics and treatment protocols,tumors are often minuscule during their initial stages,making manual diagnosis challenging,time-consuming,and potentially *** techniques predominantly used in hospitals involve manual detection via MRI scans,which can be costly,error-prone,and *** automated system for detecting brain tumors could be pivotal in identifying the disease in its earliest *** research applies several data augmentation techniques to enhance the dataset for diagnosis,including rotations of 90 and 180 degrees and inverting along vertical and horizontal *** CIELAB color space is employed for tumor image selection and ROI *** deep learning models,such as DarkNet-53 and AlexNet,are applied to extract features from the fully connected layers,following the feature selection using entropy-coded Particle Swarm Optimization(PSO).The selected features are further processed through multiple SVM kernels for *** study furthers medical imaging with its automated approach to brain tumor detection,significantly minimizing the time and cost of a manual *** method heightens the possibilities of an earlier tumor identification,creating an avenue for more successful treatment planning and better overall patient outcomes.

关键词： Brain tumor deep learning feature extraction feature selection feature fusion transfer learning

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Analytical results for the quantum alternating operator ansatz with Grover mixer

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Physical Review A 2024年第5期110卷 052409页

作者： Guilherme Adamatti Bridi Franklin de Lima Marquezino Department of Computer Science and Systems Engineering Duque de Caxias Campus Centre for Quantum Computer Science

The Grover mixer operator is a variational version of Grover's diffusion operator, introduced as a mixing operator for the quantum alternating operator ansatz (QAOA) and used in a variant known as Grover mixer QAOA (GM-QAOA). An important property of the QAOA with Grover mixer is that its expectation value is invariant over any permutation of states. As a consequence, the algorithm is independent of the structure of the problem. If, on the one hand, this characteristic raises serious doubts about the capacity of the algorithm to overcome the bound of the unstructured search problem, on the other hand, it can pave the way to its analytical study. In this sense, a prior work introduced a statistical approach to analyze GM-QAOA that results in an analytical expression for the expectation value depending on the probability distribution associated with the problem Hamiltonian spectrum. Although the method provides surprising simplifications in calculations, the expression depends exponentially on the number of layers, which makes direct analytical treatment unfeasible. In this work, we extend the analysis to the more simple context of Grover mixer threshold QAOA, a variant that replaces the phase separation operator of GM-QAOA to encode a threshold function. As a result, we obtain an expression for the expectation value independent of the number of layers and, with it, we provide bounds for different performance metrics. Furthermore, we extend the analysis to a more general context of QAOA with Grover mixer, which we called Grover-based QAOA. In that framework, which allows the phase separation operator to encode any compilation of the cost function, we generalize all the bounds by using an argument by contradiction with the optimality of Grover's algorithm on the unstructured search problem. As a result, we get the main contribution of this work, an asymptotic lower bound on the quantile achieved by the expectation value that formalizes the notion that the Grover mixer,

关键词： Quantum algorithms & computation

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A Game-Theoretic Approach to Safe Crowd Evacuation in Emergencies

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computers, Materials & Continua 2024年第4期79卷 1631-1657页

作者： Maria Gul Imran Ali Khan Gohar Zaman Atta Rahman Jamaluddin Mir Sardar Asad Ali Biabani May IssaAldossary Mustafa Youldash Ashraf Saadeldeen Maqsood Mahmud Asiya Abdus Salam Dania Alkhulaifi Abdullah AlTurkey31Department of Computer Science COMSATS University IslamabadAbbottabad CampusAbbottabad22010Pakistan Department of Computer Science Abbottabad University of Science and TechnologyAbbottabad22010Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Science and Technology Unit Umm Al-Qura UniversityMakkah21955Saudi Arabia Deanship of Scientific Research Umm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Information Systems College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer Engineering College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer Science Faculty of Computer Science and Information TechnologyOmdurman Islamic UniversityOmdurman14415Sudan Business Analytic Program Department of Management and MarketingCollege of Business AdministrationUniversity of BahrainSakhir32038Bahrain

Obstacle removal in crowd evacuation is critical to safety and the evacuation system efficiency. Recently, manyresearchers proposed game theoreticmodels to avoid and remove obstacles for crowd evacuation. Game theoreticalmodels aim to study and analyze the strategic behaviors of individuals within a crowd and their interactionsduring the evacuation. Game theoretical models have some limitations in the context of crowd evacuation. Thesemodels consider a group of individuals as homogeneous objects with the same goals, involve complex mathematicalformulation, and cannot model real-world scenarios such as panic, environmental information, crowds that movedynamically, etc. The proposed work presents a game theoretic model integrating an agent-based model to removethe obstacles from exits. The proposed model considered the parameters named: (1) obstacle size, length, andwidth, (2) removal time, (3) evacuation time, (4) crowd density, (5) obstacle identification, and (6) route *** proposed work conducts various experiments considering different conditions, such as obstacle types, obstacleremoval, and several obstacles. Evaluation results show the proposed model’s effectiveness compared with existingliterature in reducing the overall evacuation time, cell selection, and obstacle removal. The study is potentially usefulfor public safety situations such as emergency evacuations during disasters and calamities.

关键词： Safe crowd evacuation public safety emergency transition probability cooperation

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Track Damage And Obstacle Detection Using Multi Sensor Fusion Framework 15

Track Damage And Obstacle Detection Using Multi Sensor Fusio...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Priya, S.Padma Abarna, P.S. Devi, C.Manjula Hammed, S. Shahul Karthikeyan, M.P. Saravanan, K.Muthu Psna College of Engineering and Technology Department of Computer Science and Business Systems Dindigul India Velammal college of Engineering and Technology Department of Information Technology Madurai India

ISBN: (纸本)9798350370249

The integration of Internet of Things (IoT) technology into railway track monitoring systems marks a pivotal advancement in ensuring the safety and efficiency of railway operations. Through strategic deployment of sensors along the tracks, this innovative system offers real-time detection of obstacles, furnishing vital data for timely intervention to avert potential accidents. This capability not only elevates passenger and crew safety but also bolsters the reliability of railway transportation systems as a whole. The system constantly scans the track ahead of the train for any anomalies using sensors positioned toward the front of the vehicle. The system immediately notifies the application faults it detects, enabling prompt action. Additionally, it updates the status of an IoT platform and displays it for personnel on board via an LCD panel. An audio alarm is generated in the event of critical sensor readings to ensure prompt attention. By lowering potential risks and responding quickly to track problems, This IoT-based solution holds the promise of revolutionizing railway operations by furnishing augmented safety, efficiency, and reliability, thereby addressing the burgeoning demands of contemporary transportation infrastructure. © 2024 IEEE.

关键词： InfraRed Sensor Railway safety reliability track monitoring Ultrasonic Sensor

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Computational Investigation of Multiband EMNZ Metamaterial Absorber for Terahertz Applications

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computers, Materials & Continua 2022年第5期71卷 3905-3920页

作者： Ismail Hossain Md Samsuzzaman Mohd Hafiz Baharuddin Norsuzlin Binti Mohd Sahar Mandeep Singh Jit Singh Mohammad Tariqul Islam Space Science Center Universiti Kebangsaan Malaysia43600UKM BangiSelangorMalaysia Department of Computer and Communication Engineering Faculty of Computer Science and EngineeringPatuakhali Science and Technology UniversityBangladesh Department of Electrical Electronic and Systems EngineeringFaculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaMalaysia

This study presents an Epsilon Mu near-zero(EMNZ)nanostructured metamaterial absorber(NMMA)for visible regime *** resonator and dielectric layers are made of tungsten(W)and quartz(fused),where the working band is expanded by changing the resonator layer’s *** to perfect impedance matching with plasmonic resonance characteristics,the proposed NMMA structure is achieved an excellent absorption of 99.99%at 571 THz,99.50%at 488.26 THz,and 99.32%at 598 THz *** absorption mechanism is demonstrated by the theory of impedance,electric field,and power loss density distributions,*** geometric parameters are explored and analyzed to show the structure’s performance,and a near-field pattern is used to explain the absorption mechanism at the resonance frequency *** numerical analysis method describes that the proposed structure exhibited more than 80%absorbability between 550 and 900 *** computer Simulation Technology(CST Microwave Studio 2019)software is used to design the proposed ***,CSTHFSS interference is validated by the simulation data with the help of the finite element method(FEM).The proposed NMMA structure is also exhibits glucose concentration sensing capability as *** the proposed broadband absorber may have a potential application in THz sensing,imaging(MRI,thermal,color),solar energy harvesting,light modulators,and optoelectronic devices.

关键词： Metamaterial absorber terahertz applications multiband EM near zero nanostructured visible regime applications

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Intelligent Aquila Optimization Algorithm-Based Node Localization Scheme for Wireless Sensor Networks

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computers, Materials & Continua 2023年第1期74卷 141-152页

作者： Nidhi Agarwal M.Gokilavani S.Nagarajan S.Saranya Hadeel Alsolai Sami Dhahbi Amira Sayed Abdelaziz Department of Information Technology KIET Group of InstitutionsDelhi201206India Department of Computer Science and Engineering Indira Gandhi Delhi Technical University for WomenNew DelhiDelhi110006India Department of Computer Science and Engineering KL UniversityVaddeswaramAndhra Pradesh522502India Department of Electronics&Communication Engineering Saveetha Engineering CollegeChennai602105India Department of Computer Science and Engineering K.Ramakrishnan College of EngineeringTiruchirapalli621112India Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

In recent times,wireless sensor network(WSN)finds their suitability in several application areas,ranging from military to commercial *** nodes in WSN are placed arbitrarily in the target field,node localization(NL)becomes essential where the positioning of the nodes can be determined by the aid of anchor *** goal of any NL scheme is to improve the localization accuracy and reduce the localization error *** this motivation,this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme(IAOAB-NLS)for *** presented IAOAB-NLS model makes use of anchor nodes to determine proper positioning of the *** addition,the IAOAB-NLS model is stimulated by the behaviour of *** IAOAB-NLS model has the ability to accomplish proper coordinate points of the nodes in the *** guaranteeing the proficient NL process of the IAOAB-NLS model,widespread experimentation takes place to assure the betterment of the IAOAB-NLS *** resultant values reported the effectual outcome of the IAOAB-NLS model irrespective of changing parameters in the network.

关键词： Aquila optimizer node localization WSN intelligent models unknown nodes anchor nodes

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Reinforcement learning-based unknown reference tracking control of HMASs with nonidentical communication delays

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science China(Information sciences) 2023年第7期66卷 46-57页

作者： Yong XU Zheng-Guang WU Wei-Wei CHE Deyuan MENG School of Automation Beijing Institute of Technology Institute of Cyber-Systems and Control Zhejiang University College of Mathematics and Computer Science Zhejiang Normal University Department of Automation Qingdao University School of Automation Science and Electrical Engineering Beihang University(BUAA)

This paper focuses on the optimal output synchronization control problem of heterogeneous multiagent systems(HMASs) subject to nonidentical communication delays by a reinforcement learning *** with existing studies assuming that the precise model of the leader is globally or distributively accessible to all or some of the followers, the leader's precise dynamical model is entirely inaccessible to all the followers in this paper. A data-based learning algorithm is first proposed to reconstruct the leader's unknown system matrix online. A distributed predictor subject to communication delays is further devised to estimate the leader's state, where interaction delays are allowed to be nonidentical. Then, a learning-based local controller, together with a discounted performance function, is projected to reach the optimal output synchronization. Bellman equations and game algebraic Riccati equations are constructed to learn the optimal solution by developing a model-based reinforcement learning(RL) algorithm online without solving regulator equations, which is followed by a model-free off-policy RL algorithm to relax the requirement of all agents' dynamics faced by the model-based RL algorithm. The optimal tracking control of HMASs subject to unknown leader dynamics and communication delays is shown to be solvable under the proposed RL algorithms. Finally, the effectiveness of theoretical analysis is verified by numerical simulations.

关键词： heterogeneous multiagent systems HMAS reinforcement learning RL optimal output synchronization communication delays

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