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Stage Wise Classification and prediction of Alzheimer disease using Hybrid Appraoch 4

Stage Wise Classification and prediction of Alzheimer diseas...

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4th international conference on Intelligent Technologies, CONIT 2024

作者： Prabagaran, A. Dwivedi, Vinay Neelam Rani, Jyoti Angelin Blessy, J. Padmanabhan, P. Gupshup Technology India Pvt Ltd Bengaluru India Galgotias University School of Computer Science and Engineering Uttar Pradesh Greater Noida India Noida Institute of Engineering & Technology Department of Computer Science and Engineering Uttar Pradesh Greater Noida India Galgotias Univeristy School of Computing Science and Engineering Dept of Computer Application India Greater Noida Institute of Technology Department of Computer Science and Engineering Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350349900

Alzheimer's, the most prevalent cause of dementia, leads to a continuous decline in cognitive functions, social skills, and behavior, affecting individuals' independent functioning. As per survey 2010 in India around 3.7 million affected by dementia, and this data is expected to twofold by 2030. The associated cost of care is projected to triple, necessitating ongoing support. This issue is a significant societal concern that warrants careful consideration. Prediction and classification of Alzheimer's disease (AD) are crucial for identifying and addressing it at earlier stages. The disease is typically classified into three stages: early-stage dementia, middle-stage, and late-stage. However, several challenges exist, including limited awareness, diagnostic difficulties, insufficient technologies and treatments, unpredictable progression across stages, and a lack of comprehensive stage-by-stage predictions. This work proposes a hybrid model for predicting, classifying, and stage-wise classifying Alzheimer's disease. The hybrid model aims to address the challenges associated with the disease, utilizing different features for prediction and classification. The hybrid model used a Random forest, convolutional neural network (CNN), kernel density algorithm (KDA) with hyperparameter tuning for accurate prediction and classification. The proposed hybrid method used Random forest used for basic classification, CNN and kernel density for stage wise classification. The proposed hybrid method achieved an impressive 95.6% accuracy in stage wise classification and prediction of AD. © 2024 IEEE.

关键词： Convolutional neural networks

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Research on FDTD-PML Algorithm for Magnetic Anomaly Analysis and Length Detection of Rebar 3

Research on FDTD-PML Algorithm for Magnetic Anomaly Analysis...

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3rd international conference on Artificial Intelligence and computer Information technology, AICIT 2024

作者： Yang, Fan Huang, Lei School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan China

ISBN: (纸本)9798350365443

Pile foundation mainly provides support and bearing function for buildings, deeply buried underground belongs to hidden engineering, non-destructive detection of reinforcement length within the pile foundation has become a research hotspot. The research theoretically explains the method and principle of magnetic anomaly detection of rebar burial depth, and develops the pile length detection equipment. The FDTD-PML algorithm is used to calculate the magnetic field strength on the surface of rebar, combined with MATLAB and ANSYS-MAXWELL software simulation to analyze the electromagnetic wave propagation on the surface of rebar in the ground, and the pile length detection equipment is developed, combined with the actual testing of the Za vertical magnetic component curve of the south side and the north side of the drilled pile on the site. The experimental results show that, using the developed magnetic anomaly detection equipment based on the depth of rebar, the changes in the magnetic curve of 'two peaks clamped by a valley' correspond to the length of the pile foundation, and when the pile hole spacing is increased to 1.5 meters, the measurement error is only 0.3 meters, which is of good performance and high practical application value. © 2024 IEEE.

关键词： MATLAB

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Research on The Application of American College Classroom Experience Evaluation System Based on computer Virtual Reality technology

Research on The Application of American College Classroom Ex...

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2022 international conference on Mathematics, Modeling, and computer Science, MMCS 2022

作者： Lei, Chenwenxuan Kuai, Xiao Rossier School of Education University of Southern California Los AngelesCA90007 United States Viterbi School of Engineering University of Southern California Los AngelesCA90007 United States

ISBN: (纸本)9781510664593

With the continuous development of computer virtual reality technology, in recent years, Chinese foreign students can learn more knowledge and multi-dimensional and multi-stage online open courses in the process of classroom experience in American universities. The traditional video playing system has been unable to meet the process of new college classroom learning. With the progress of computer virtual reality technology, Many college classroom learning processes can be reconstructed using computer modeling technology, so as to mine the student behavior data available in the teaching management system, and extract the key factors affecting students' academic performance. This computer system uses the method of machine learning virtual reality to analyze the meaning and predict the final score of students' courses. The experimental simulation shows that the system realizes the substantial equivalence of online and offline teaching, and promotes the good development of online teaching. © 2023 SPIE.

关键词： Students

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Enhancing Efficiency in Drain Cleaning Operations Using K-Nearest Neighbors Algorithm with IoT-Enabled Robots 1

Enhancing Efficiency in Drain Cleaning Operations Using K-Ne...

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1st international conference on Innovations in Communications, Electrical and computer engineering, ICICEC 2024

作者： Ranganathan, Chitra Sabapathy Vijayalakshmi, Kuppan Kalaichelvi, S. Sivanantham, E. Ganeshbabu, T.R. Murugan, S. Mphasis Corporation Tamil Nadu Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tami Nadu Chennai India Pg and Research Department of Computer Science and Applications Tamil Nadu Namakkal India Rajalakshmi Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Department of Electronics and Communication Namakkal India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350376517

Maximizing efficiency in drain cleaning operations is crucial for maintaining municipal infrastructure and the prevention of possible risks like floods and pollution. Conventional approaches often need human examination and approval, which may consume a significant amount of time and require substantial effort. This research proposes a new method to improve the effectiveness of drain cleaning operations by combining Internet of Things (IoT)-enabled robots with the K-Nearest Neighbors (KNN) algorithm. The robots enabled by the IoT are fitted with sensors to gather real-time data, such as detecting blockages, measuring debris levels, and assessing the status of drains. The KNN algorithm analyzes this data to forecast the most effective cleaning procedures by comparing them to comparable prior situations. The system can adjust and enhance cleaning routes and processes using machine learning techniques, resulting in improved efficiency and effectiveness in drain maintenance. This novel methodology not only decreases human involvement and expenses related to labor but also mitigates the possibility of harm to infrastructure and enhances the overall efficiency of the drainage system. The experimental findings provide evidence of the efficacy of the proposed technique in improving the efficiency and dependability of drain cleaning operations. © 2024 IEEE.

关键词： Nearest neighbor search

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Four LG modes MDM based hybrid FSO-fiber link for high capacity PON 4

Four LG modes MDM based hybrid FSO-fiber link for high capac...

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4th international conference on Innovative Practices in technology and Management, ICIPTM 2024

作者： Kumari, Meet Sharma, Neha Chauhan, Rahul Joshi, Kireet Kumar, Amit Sunil, G. Uie Chandigarh University Dept. of Ece Mohali140413 India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India Graphic Era Deemed to Be University Computer Science & Engineering Uttarakhand Dehradun248002 India Sr University School of Computer Science & Artificial Intelligence Warangal India

ISBN: (纸本)9798350307757

The trend in development of hybrid fiber-wireless optical systems is towards high transmission rate communication systems with high capabilities, high bandwidths as well as operational frequencies. A 24×50Gbps integrated mode division multiplexing -passive optical network system incorporating fiber-free space optics (FSO) link is reported under diverse climate conditions. Results indicate that proposed design allows maximum FSO range of 10-110km along with 1000m fibr range at 50Gbps/channel rate under air as well as mode 0. Higher split ratio of 64 can be realized using the proposed work. Compared to other designs, this designed offers best performance. © 2024 IEEE.

关键词： Passive optical networks

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Multi-sequence exposure image fusion method based on weight function 5

Multi-sequence exposure image fusion method based on weight ...

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5th international conference on computer Vision and Data Mining, ICCVDM 2024

作者： Yang, Xu Zheng, Zhixin School of Electronic Information Engineering Changchun University of Science and Technology Changchun China

ISBN: (纸本)9781510682863

Aiming at the existing multi-exposure image fusion method based on weight function, the fused image obtained tends to introduce halo artifacts, loss of details, unclear edges and other problems. A multi-exposure image fusion method with improved weight function is proposed. First, the luminance weights reflecting the importance of each pixel of the image to the global luminance and neighboring exposure images are determined, and the gradient weights reflecting the importance of the local gradient of each pixel in the whole sequence of the image are determined, and the contrast weights are used to improve the clarity and detail information of the integration results;finally, the fused images are obtained according to the weights. According to the experimental results that the image fusion effect of the method proposed in this paper is clear and natural, and the average multi-exposure fusion structural similarity (MEF-SSIM) reaches 0.981, and the average running time is 0.725s. © 2024 SPIE.

关键词： Pixels

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Research on Direction Finding Algorithm Based on Bluetooth AOA Measurement 5

Research on Direction Finding Algorithm Based on Bluetooth A...

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5th international conference on Advances in Electrical engineering and computer Applications, AEECA 2024

作者： Luo, Kaifan Wuhan University of Technology Wuhan China

ISBN: (纸本)9798350355253

With the broad deployment of Bluetooth in IoT devices, the Bluetooth SIG has incorporated a measurement-based AOA direction finding algorithm specification into the Bluetooth protocol to facilitate location-based services. In this study, we found that these errors in AOA measurements originate from phase noise and multipath effects. In order to solve these problems, we employ the MUSIC algorithm to enhance the accuracy of AOA measurements, incorporating phase noise into the measurement process, and introduce an improved MUSIC algorithm aimed at mitigating phase noise. Furthermore, we propose an AOA correction algorithm utilizing mean-value optimization to counter the fluctuations in angle measurements induced by multipath effects. Simulation experiments demonstrate that, relative to the mean phase difference algorithm and the original MUSIC algorithm, the improved AOA direction finding algorithm significantly reduces measurement errors by 47% and 28%. Moreover, the likelihood of achieving a measurement error of less than 5° reaches to 97%, signifying a substantial enhancement in positioning accuracy. © 2024 IEEE.

关键词： Bluetooth

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Analysis of the Effectiveness of Large Language Model Feature in Source Code Defect Detection 3

Analysis of the Effectiveness of Large Language Model Featur...

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3rd international conference on Artificial Intelligence and computer Information technology, AICIT 2024

作者： He, Tao Yang, Meini Hu, Wei Chen, Yun Naval University of Engineering Department of Information Security Hubei Wuhan China

ISBN: (纸本)9798350365443

The defects in software source code threaten the usage of software. With the increase in the quantity and complexity of software, traditional methods of source code defect detection are unable to meet the needs of software security testing, leading to the emergence of machine learning-based source code defect detection methods. The effectiveness of machine learning-based method is closely related to the input features. This paper investigates the impact of using outputs from large language model as input features for machine learning models on the task of source code defect detection. Experimental results demonstrate that adding feature from large language model to machine learning models can enhance the effectiveness of source code defect detection. Furthermore, among different strategies for constructing prompt words, few-shot prompting shows relatively better performance. © 2024 IEEE.

关键词： Adversarial machine learning

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Web-Based Patient Health Management System with Doctor Recommendations and Medicine Alternatives using Machine Learning

Web-Based Patient Health Management System with Doctor Recom...

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2024 international conference on Smart Systems for Electrical, Electronics, Communication and computer engineering, ICSSEEC 2024

作者： Hemkiran, S. War, Mohammad Mudasir Aadhithiyan, K.S. Kabilan, K. PSG Institute of Technology and Applied Research Department of Cse Coimbatore India

ISBN: (纸本)9798350378177

Web-Based Patient Health Management System with Doctor Recommendations and Medicine Alternatives depicts a novel doctor appointment system that unites simplicity with sophisticated technology, featuring a Random Forest Classifier model to boost healthcare services. Another advantageous component is the inclusion of a specific pharmacy area, enabling efficient drug administration tracking. Confirmation emails are sent upon successful appointment bookings, keeping individuals updated on upcoming visits. The platform also encompasses a multifaceted disease prediction mechanism powered by the Random Forest Classifier's predictive capabilities, assisting physicians in delivering accurate diagnoses and targeted therapy recommendations[15]. Integrating of these elements results in a comprehensive strategy for managing patient health. By emphasizing user-friendliness and advanced technology, the system aims to elevate both patient satisfaction and healthcare provider productivity. Employing machine learning techniques within medical settings can lead to enhanced appointment scheduling efficiency and diagnostic precision, ultimately benefiting patients through improved care outcomes. © 2024 IEEE.

关键词： Electronic health record

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A Motion Compensation Method for a One-Transmitter Multiple-Receiver Mobile Radar System 6

A Motion Compensation Method for a One-Transmitter Multiple-...

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6th international conference on Communications, Information System and computer engineering, CISCE 2024

作者： Lian, Qijun Da, Kai Song, Zhiyong Wang, Ping National University of Defense Technology College of Electronic Science and Technology Changsha China

ISBN: (纸本)9798350353174

The mobile radar platform will lead to defocusing of the range-Doppler spectra of the echo signal, which will reduce the effect of multi-pulse coherent accumulation and target detection performance. In the one-transmitter multiple-receiver mode, the influencing factors of defocusing phenomenon are more complicated. In this paper, the influence of the complex motion of the radar platform on the multi-pulse coherent accumulation of the echo signal is studied based on the one-transmitter multiple-receiver mobile radar system. Combined with the principle of Radon-Fourier transform, a motion compensation method suitable for the one-transmitter multiple-receiver mobile radar system is proposed. Theoretical derivation and simulation results show that the proposed method can effectively compensate the phase shift between pulses caused by radar platform motion and achieve better energy accumulation effect in low SNR environment. © 2024 IEEE.

关键词： Radar transmitters

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