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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Bhambu, Pawan Haripriya Yadav, Dhyan Chandra Vivekananda Global University Department of Computer Science and Engineering Jaipur India Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350383348

Introduces a estimation based totally on time series evaluation. among ladies, and it's far more critical to stumble on and deal with it in the early ranges. However, due to time consumption within the analysis method and its cost, there's a need to increase pc-aided structures to automate the analysis. It proposes a time series evaluation method based on machine mastering for detecting and estimating breast most cancers degree (early or past due) at the preliminary ranges of prognosis. The proposed device is predicated on the type of records amassed in an early stage of breast most cancers analysis, along with age, tumor size, lymph node involvement, and other laboratory values, which includes estrogen and progesterone receptor degrees. The proposed machine changed into tested using a dataset of patients with breast cancers. The device's performance was evaluated using the region under the curve and F1 rating. a unique method estimating possibility of diagnosis through time series evaluation. The proposed method applies a sparse illustration model for pre-processing, observed via the utility of a random wooded area classifier to evaluate the chance of breast cancer. public dataset of 961 female sufferers with breast cancer from the UCI machine studying repository. The proposed approach is faster and more correct than the associated methods. The concept of using time collection evaluation for estimating breast cancers is, for this reason promising as it could be deployed in medical exercise to offer reliable detection of breast cancer. © 2024 IEEE.

关键词： Time series analysis

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Novel Three-Phase PLL with Per Phase Grid Angle Tracking Capability for Shunt-Connected Solar Microinverter

Novel Three-Phase PLL with Per Phase Grid Angle Tracking Cap...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Varadharajan, Roshan Dornala, Avinash Lee, Kangbeen Lee, Woongkul Michigan State University Department of Electrical and Computer Engineering East LansingMI United States Purdue University Elmore Family School of Electrical and Computer Engineering West LafayetteIN United States

ISBN: (纸本)9798350376067

A shunt-connected solar microinverter can effectively mitigate the high starting current of induction motors and seamlessly redirect the energy source back to the power grid with grid synchronization. However, external disturbances in the power grid can influence the motor starting operation, and it becomes a predominant issue for grid-connected systems to act independently of these scenarios. The frequent grid faults, voltage sags, and swells can negatively affect the durability of the motor. This paper proposes a novel three-phase phase-locked loop (PLL) that can track the grid angle of each phase independently in faulty grid conditions. The existing DQ-PLL is modified with the proposed PLL structure for the microinverter application. This can help the line-connected IM system tackle the unbalanced grid scenario and run the induction motor efficiently with minimal impact from the grid faults. © 2024 IEEE.

关键词： Phase locked loops

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Enhancement of High Angular Resolution Diffusion-Weighted Imaging Through Parallel Imaging and Motion Correction 5th

Enhancement of High Angular Resolution Diffusion-Weighted Im...

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5th International Conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Sandhya, Prajapati Sreejith, V. Alam, Intekhab Haripriya Department of Electrical Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Manduwala Dehradun Navgaon India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India

ISBN: (纸本)9789819780426

Excessive Angular decision Diffusion-Weighted Imaging (HARDI) is an effective imaging modality that produces high decision pictures of fiber tracts within the brain. Reconstruction of those pictures calls for a huge quantity of computational power and reminiscence, because it acquires appreciably extra diffusion weighted photographs than the conventional diffusion-weighted imaging (DWI) strategies. It makes use of multiple receiver coils in parallel, with every coil measuring the same records set. MC improves the accuracy of HARDI reconstruction by using correcting for motion artifacts. The application of PI and MC along with HARDI allows high-decision reconstruction of fiber tracts inside the mind, with stepped forward sign-to-noise ratio and decreased test instances. When used together, PI and MC also can improve the accuracy of HARDI tractography, providing extra designated records on fiber tract micros. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： measuring movement reconstruction

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Drowsiness Detection A Blink-Based Approach Using computer Vision Techniques

Drowsiness Detection A Blink-Based Approach Using Computer V...

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2024 International Conference on Information Technology Systems and Innovation, ICITSI 2024

作者： Gunawan, Rudy Azwar, Ade Geovania Gunawan, Aditya Zufar Mahendra Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia Bandung Institute of Technology Department of Industrial Engineering Bandung Indonesia FITB Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9798331511470

Real-time detection of drowsiness is an important need in efforts to improve safety, especially in the transportation sector. This research focuses on the development of a non-invasive system to detect drowsiness based on eye blink analysis. This system utilizes computer vision technology to measure blink frequency and duration as the main parameters. With an Eye Aspect Ratio (EAR)-based algorithm implemented, the system can detect changes in eye blink patterns accurately. The data obtained is used to identify signs of drowsiness such as increased blink duration or decreased frequency. The study evaluates hardware performance for real-time image processing in detecting drowsiness through blink dynamics. The results reveal that an AMD A9 laptop performs significantly better, achieving a sampling rate of 16 Hz, compared to the Raspberry Pi 3B+, which operates at 1.6 Hz, approximately 10 times slower. Additionally, the experiment establishes two drowsiness detection criteria: the duration of a single blink and the frequency of blinks within a set timeframe. The latter requires additional program functionality to store and analyze blink data over time. These findings underscore the need for robust hardware and software optimization to ensure reliable, real-time drowsiness detection. Experimental results show a high level of accuracy in detecting drowsiness, making it a reliable solution to improve user safety in various sectors. © 2024 IEEE.

关键词： Digital storage

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High-precision nonisothermal transient wellbore drift flow model suitable for the full flow pattern domain and full dip range

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Petroleum Science 2023年第1期20卷 424-446页

作者： Wen-Qiang Lou Da-Lin Sun Xiao-Hui Sun Peng-Fei Li Ya-Xin Liu Li-Chen Guan Bao-Jiang Sun Zhi-Yuan Wang Offshore Petroleum Engineering Research Center School of Petroleum EngineeringChina University of Petroleum(East China)Qingdao266580ShandongChina School of Petroleum Engineering Yangtze UniversityWuhan430199HubeiChina Hubei Key Laboratory of Oil and Gas Drilling and Production Engineering(Yangtze University) Wuhan430199HubeiChina College of Computer Science and Technology China University of Petroleum(East China)Qingdao266580ShandongChina Department of Petroleum Engineering University of TulsaTulsaUnited States

A reliable multiphase flow simulator is an important tool to improve wellbore integrity and production *** develop a multiphase flow model with high adaptability and high accuracy,we first build a multiphase flow database with 3561 groups of data and developed a drift closure relationship with stable continuity and high ***,a high-order numerical scheme with strong fault capture ability is constructed by effectively combining MUSCL technology,van Albada slope limiter and AUSMV numerical ***,the energy equation is coupled into the AUSMV numerical scheme of the drift flow model in the form of finite difference.A transient non-isothermal wellbore multiphase flow model with wide applicability is formed by integrating the three technologies,and the effects of various factors on the calculation accuracy are *** accuracy of the simulator is verified by comparing the measurement results with the blowout experiment of a full-scale experimental well.

关键词： Drift closure relation Non-isothermal model High-precision Multiphase flow solver Wellbore pressure control

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Multi-Dimensional Recurrent Neural Networks Hyperspectral Image Classification 2

Multi-Dimensional Recurrent Neural Networks Hyperspectral Im...

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2nd IEEE International Conference on Data Science and Network Security, ICDSNS 2024

作者： Ramkumar, K. Al-Jawahry, Hassan M. Shilpa, N. Shalini, G. Arun, M. Rajalakshmi Institute of Technology Department of Computer Science and Engineering Chennai India College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq School of Engineering Sr University Department of Ece Warangal India Nitte Meenakshi Institute of Technology Department of Civil Engineering Bengaluru India Panimalar Engineering College Department of Ece Chennai India

ISBN: (纸本)9798350373110

The classification of Hyperspectral Images (HSI) has gained popularity in the remote sensing community. Machine Learning (ML) techniques often find it difficult to accurately classify hyperspectral data due to its complicated properties. Therefore, the Multi-Dimensional Recurrent Neural Network (MDRNN) is suggested in this research for the categorization of HSI images. The dataset from the University of Pavia is initially utilized to gather the data. Then, the Min-max normalization, a preprocessing technique, improves the HSI image by lowering noise. The characteristics are then extracted using a spatial attention-based feature extraction technique. Lastly, middle-level visual patterns are learned using the suggested MDRNN, and the spatial relationships between them enhance the HSI classification. Hence, the proposed model is used to improve the performances by utilizing the various performances in image classification. The results showed that the proposed method performed better than the existing models, which include ALFA-SCNN, CNN, and DCNN, in terms of accuracy of (99.75%), precision of (99.56%), F1-measure of (90.43%), and recall of (99.58%) respectively. © 2024 IEEE.

关键词： Recurrent neural networks

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Systematic Literature Review on Sentiment Analysis in Airline Industry

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SN computer Science 2025年第1期6卷 1-26页

作者： Hasib, Khan Md Naseem, Usman Keya, Ashfia Jannat Maitra, Shithi Mithu, Kamruzzaman Alam, Md. Golam Rabiul Department of Computer Science and Engineering Brac University Mohakhali Dhaka 1212 Bangladesh Department of Computer Science and Engineering Bangladesh University of Business and Technology Mirpur Dhaka 1216 Bangladesh School of Computing Macquarie University Sydney 2109 NSW Australia Unilever BD Ltd. Shanta Forum Dhaka 1208 Bangladesh Department of Computer Science and Engineering United International University United City Dhaka 1212 Bangladesh

The significance of sentiment analysis lies in its ability to identify key areas of customer satisfaction and dissatisfaction, revealing patterns that can guide enhancements in airline services and strategic decision-making. Additionally, the identification of topics within airline passengers’ opinions across various flight classes is crucial, achieved through topic modeling. By analyzing these opinions, we can discern passengers’ priorities and expectations, which are essential for delivering superior service. This survey converges the sparse implications and provides a dense, comprehensive understanding of the state of the art through a Systematic Literature Review (SLR). Our SLR breaks down the research process into three distinct phases: Planning (defining research questions and protocol), Conducting (identifying and assessing relevant studies), and Document Review (synthesizing findings). We analyze 60 papers on sentiment analysis and topic modeling to examine the application and effectiveness of machine learning and deep learning methods in the airline industry. Our study highlights critical tasks in airline sentiment analysis, including multilingual sentiment analysis, and provides an overview of popular datasets, their fundamental properties, and the machine learning and deep learning models applied to them. The existing literature is critically examined to uncover both strengths and weaknesses, yielding additional insights into the prevailing research paradigms. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Airline industries Customer feedback analysis Machine learning Sentiment analysis Systematic literature review Topic modeling

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Intelligent Energy Management Energy Storage Systems Using Machine Learning

Intelligent Energy Management Energy Storage Systems Using M...

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2024 International Conference on Intelligent Systems for Cybersecurity, ISCS 2024

作者： Govindasamy, Chinnaraj Dayana, T.R Nisha Adkar, Siddhika Dilip Prakash, D. Shyam Gupta, A. Shilpa Trivedi, Sanjeev Kumar Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamilnadu Chennai602105 India Vels Institute of Science Technology and Advance Studies Department of Computer Science Chennai India School of Computer Science Engineering and Applications D y Patil International University Akurdi India Department of Computer Science and Business Systems Sri Eshwar College of Engineering Coimbatore India Department of Electrical and Electronics Engineering Aurora's Technological Research Institute Uppal Hyderabad India Khwaja Moinuddin Chishti Language University Faculty of Engineering and Technology Department of Electronics Lucknow India

ISBN: (纸本)9798350375237

A nevertheless-emerging generation called cloud computing permits customers to pay for services on a usage-based foundation. Internet-primarily based IT offerings are supplied through cloud computing, at the same time as virtualization enables the availability of PC sources. The muse of cloud computing is the information center, which is made up of networked computers, cables, electricity components, and different components that host and shop corporate records. With cloud facts centers, high overall performance has continually been the most critical concern, yet it compromises strength utilization. The key hassle is to lessen power consumption at the same time as preserving provider nice and performance a good way to stability device performance and strength intake. A detailed grasp of strength use styles within the cloud environment is needed for our suggested technique. We look at power consumption tendencies and reveal how, through the use of the right optimization standards based on our strength intake models, we can keep more strength in cloud records facilities. All through the prediction section, tablet optimization, which has a 97 percent accuracy rate, permits this era to provide extra correct future price forecasts. © 2024 IEEE.

关键词： Machine learning

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Exploring the Use of Transfer Learning for Automated Brain Tumor Segmentation 5th

Exploring the Use of Transfer Learning for Automated Brain T...

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5th International Conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Savita Jaison, Feon Nautiyal, Kshitij Sunitha, B.J. Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bengaluru India Department of Electrical Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India

ISBN: (纸本)9789819780426

Switch getting to know has become increasingly famous in many aspects of pc vision, including picture segmentation. This paper explores switch-gaining knowledge for automated brain tumor segmentation using a deep getting-to-know structure known as U-net. U-internet is a convolution neural community version that has been used efficiently to ramify scientific image segmentation obligations in the beyond. This work utilizes a U-internet model skilled on a huge-scale brain tumor segmentation dataset. The version plays nicely at the utility of brain tumor segmentation, achieving an average cube coefficient of zero. Ninety-three on check scans. Moreover, qualitative consequences display that the U-net version produces segmentation masks with few false-nice mistakes. These consequences reveal the capability of switch getting to know for automatic mind tumor segmentation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image segmentation

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3D Modeling of Automated Robot for Seeding and Transplantation of Rice and Wheat Crops 1

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4th International Conference on Communication and Intelligent Systems, ICCIS 2022

作者： Krishna, G. Venkata Sai Amitasree, Palanki Manitha, P.V. Rajesh, M. Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9789819923229

ISBN: (纸本)9789819923212

The most important sector of Indian economy which is identified as the backbone is agriculture. The major part of agriculture lies in paddy cultivation. In earlier days, agriculture was the major sector where most people were employed but nowadays, due to industrial growth and IT revolution, the employment in agriculture has become too less. The major part of economy which is vital for India’s economic growth is now facing serious issues due to the manpower shortage, lack of advancement in technological usage. This proposes a solution to meet out this issue by bringing in automation in the agriculture domain. Agricultural processes are chains of systematic, repetitive and time-dependent tasks. It requires lot of manual labor and accurate placement and managing of seeds and saplings. It’s a case where a human error is highly possible. In this work, an attempt is made to automate the process of distributing the seeds and once they are grown big enough to get transplanted, the robotic solution will transplant these plants. The automated solution will distribute the seeds in an organized and optimized way. The robotic platform will pluck the plants and replant them in an organized way. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Three dimensional computer graphics

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