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7th International Conference on Mechanical Manufacturing and Industrial engineering, MMIE 2024

作者： Tsui, Zhe-Luen Chou, Ywh-Leh Yuan, Cadmus Feng Chia University Department of Industrial Engineering and System Management Taiwan Feng Chia University Department of Mechanical and Computer-Aided Engineering Taiwan

ISBN: (数字)9781510683297

ISBN: (纸本)9781510683280

This research responds to the complex challenges of mass customization and multi-objective parameter optimization. Leveraging the Call-Auction Matching proposed by Cadmus Yuan, Zhe-Luen Tsui, and Ywh-Leh Chou[1], we improved a Production Date Prediction Call-Auction Matching (PDP-CAM) scheduling algorithm. Our numerical analysis validated the ability of algorithm to implement a partial rescheduling mechanism and generate scheduling results in the face of mass customization scenarios. Importantly, the effectiveness of the PDP-CAM scheduling algorithm in minimizing instance rescheduling was demonstrated, thereby enhancing the computational efficiency of the algorithm. © 2024 SPIE.

关键词： Cleaning

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Performance Analysis of Disruptive Instances in Cloud Environment 16

Performance Analysis of Disruptive Instances in Cloud Enviro...

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16th International Conference on COMmunication systems and NETworkS, COMSNETS 2024

作者： Nandy, Pranab Saha, Rounak Satpathy, Anurag Chakraborty, Sandip Addya, Sourav Kanti National Institute of Technology Karnataka Cloud and Smart System Services Lab Department of Computer Science and Engineering Surathkal India Missouri University of Science and Technology Cloud and Smart System Services Lab Department of Computer Science and Engineering United States Indian Institute of Technology Kharagpur Cloud and Smart System Services Lab Department of Computer Science and Engineering India

ISBN: (纸本)9798350383119

Virtualization enables the service providers (SPs) to logically partition the resources into virtual machines (VM) instances. Real-world SPs such as Amazon, Google, Microsoft Azure, IBM, and Oracle provide different flavors of VM instances, such as on-demand, reserved, and low-cost or spot, depending on the type of application hosted. The on-demand instances are short-term and typically incur a higher cost than reserved instances that are provisioned for a longer duration at a discounted rate. Low-cost or spot instances are cost-effective compared to on-demand but are reclaimable by the SPs. The SPs often claim that the on-demand and spot instances achieve similar performance, but it is far from that. This paper studies the performance of spot instances via rigorous experimentation over commercial SPs such as Amazon AWS and Microsoft Azure. Real-world evaluations affirm that spot instances perform poorly compared to their on-demand counterpart concerning memory, CPU, disk read, and write operations. We identify such instances as disruptive and name them so because it does not fulfill the performance, durability, and flexibility expectations like an on-demand instance having the same configuration. We also perform hypothesis testing over the experimental data obtained to corroborate our claim further. © 2024 IEEE.

关键词： Cloud Computing Disruptive Instance On-demand Spot Instance

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Use of Euclidean Distance to Improve Fingerprint Matching Accuracy 4th

Use of Euclidean Distance to Improve Fingerprint Matching Ac...

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4th International Conference on Innovations in Computational Intelligence and computer Vision, ICICV 2024

作者： Bhargava, Neeraj Yadav, Rajendra Choudhary, Usha Department of Computer Science School of Engineering System Sciences MDS University Rajasthan Ajmer India Department of Computer and Communication Engineering Manipal University Jaipur Rajasthan Jaipur India

ISBN: (纸本)9789819769919

Fingerprint authentication is the most sophisticated method of all biometric techniques and has been thoroughly verified through various applications. Fingerprint matching has been done using several fingerprint recognition techniques. The methods for matching fingerprints have changed significantly over time, but Euclidean distance is still widely used since it is efficient and straightforward. Euclidean distance is still used in minutiae-based fingerprint matching to produce accurate results. The computational geometry, image processing, and patter recognition fields all make substantial use of Euclidean distance, a fundamental distance matching approach. The purpose of this work is to highlight the importance of normalization in improving contrast, particularly in noisy fingerprint photographs where accuracy is critical. We analyzed how to make fingerprint matching more robots against a reference template by utilizing Euclidean distance between small spots. We also analyzed algorithm’s effectiveness in producing dependable and accurate fingerprint matching results using MATLAB. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Computational geometry

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Design an Optimal Augmented PID Controller for Electric Vehicle Speed Control 23th

Design an Optimal Augmented PID Controller for Electric Vehi...

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23rd International Conference on Intelligent systems Design and Applications, ISDA 2023

作者： Abood, Layla H. Ali, Inaam I. Abood, May H. Control and System Engineering Department University of Technology Baghdad Iraq Electrical Engineering Department University of Technology Baghdad Iraq Computer Engineering Department University of Al Iraqia Baghdad Iraq

ISBN: (纸本)9783031648465

The prominence growth of the Electric Vehicle (EV) industry requests from researcher to adopts effective controlling techniques for marinating different issues. In this paper an augmented PID controller is suggested for controlling speed in EV based using sigmoid function relation and the smart and unique Gray wolf Optimization (GWO) algorithm to achieve a satisfied and robust system desired value, a comparison is utilized with PID controllers (Optimal PID, Normal PID) to evaluate its behavior then a robustness analysis is applied by varying system desired speed in multiple periods, the controller track the desired value perfectly and force the system to an efficient response with robust system behavior. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Electric vehicles

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A Scalable Open-Set ECG Identification system Based on Compressed CNNs

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IEEE Transactions on Neural Networks and Learning systems 2023年第8期34卷 4966-4980页

作者： Wu, Shun-Chi Wei, Shih-Ying Chang, Chun-Shun Swindlehurst, A. Lee Chiu, Jui-Kun National Tsing Hua University Department of Engineering and System Science Hsinchu30013 Taiwan University of California at Irvine Department of Electrical Engineering and Computer Science IrvineCA92697 United States

Deep learning (DL) is known for its excellence in feature learning and its ability to deliver high-accuracy results. Its application to ECG biometric recognition has received increasing interest but is also accompanied by several deficiencies. In this study, we focus on applying DL, especially convolutional neural networks (CNNs), to ECG biometric identification to address these deficiencies. Using prestored user-specific feature vectors, the proposed scheme can exclude unregistered subjects to realize 'open-set' identification. With the help of its scalable structure and 'transfer learning,' new subjects can be enrolled in an existing system without the need for storing the ECGs of those previously enrolled. Finally, schemes based on the quantum evolutionary algorithm (QEA) are presented to prune unnecessary filters in the proposed CNN model. The performance of the proposed scheme was evaluated using the ECGs of 285 subjects from the PTB dataset. The experimental results demonstrate an identification rate of more than 99% in closed-set identification. Although incorporating the proposed method for unregistered subject exclusion degraded the identification performance slightly, the ability of the approach to resist a dictionary attack was evident. Finally, using the QEA-based filter pruning method and its two-stage extension reduced the number of floating-point operations required to complete one identity recognition to 1.20% and 0.22% of the original value without significantly impacting the identification accuracy. © 2012 IEEE.

关键词： Biometrics

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Sagittarius: Floating Self Navigating Robot for Monitor the Water Quality of Rural Reservoirs 6

Sagittarius: Floating Self Navigating Robot for Monitor the ...

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6th International Conference on Advancements in Computing, ICAC 2024

作者： Pedige, Nishan Ilandara Abeywarna, Thaveesha Amarasinge, Randheera Bandara, Menuka Nawarathna Javakody, Anuradha Gamage, Narmada Sri Lanka Institute of Information Technology Department of Computer System Engineering Malabe Sri Lanka

ISBN: (纸本)9798331517878

This paper proposes an optimal solution for monitoring water quality in Sri Lanka, where reservoirs are essential for daily life and agriculture, especially in rural areas. Despite its importance, 3.6 million communities are affected by severe water quality problems, contributing to a high incidence of chronic kidney diseases. While water purification plants are the only solution, high salinity and hardness often make these sources unsuitable. Many rural reservoirs remain unpurified but could potentially provide safe water if properly monitored and maintained. Yet water sources are frequently contaminated by chemical waste and activities associated with agricultural business but effective solutions for continuous water quality monitoring are lacking. This study introduces an autonomous robot equipped with advanced sensors to monitor critical water quality parameters in real-time. By integrating machine learning for data analysis and prediction, Sagittarius enables continuous assessment of reservoir water quality, providing timely insights for public health protection. Field tests demonstrate a prediction accuracy exceeding 98.5%, supporting proactive water management and monitoring. This system has shown potential to aid in early detection of contamination, informing authorities promptly for preventive actions, and enabling sustainable water usage. This solution can significantly contribute to public health protection and informed water resource management decisions. © 2024 IEEE.

关键词： Reservoirs (water)

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Automated Colonic Polyp Detection and Classification Enabled Northern Goshawk Optimization with Deep Learning

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computers, Materials & Continua 2023年第5期75卷 3677-3693页

作者： Mohammed Jasim Mohammed Jasim Bzar Khidir Hussan Subhi R.M.Zeebaree Zainab Salih Ageed Engineering College Al-Kitab UniversityKirkukIraq Information System Engineering Department Erbil Technical Engineering CollegeErbil Polytechnic UniversityErbilIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq

The major mortality factor relevant to the intestinal tract is the growth of tumorous cells(polyps)in various *** specifically,colonic polyps have a high rate and are recognized as a precursor of colon cancer *** is the conventional technique for detecting colon polyps,and considerable research has proved that automated diagnosis of image regions that might have polyps within the colon might be used to help experts for decreasing the polyp miss *** automated diagnosis of polyps in a computer-aided diagnosis(CAD)method is implemented using statistical ***,Deep Learning,particularly throughConvolution Neural networks(CNN),is broadly employed to allowthe extraction of representative *** manuscript devises a new Northern Goshawk Optimization with Transfer Learning Model for Colonic Polyp Detection and Classification(NGOTL-CPDC)*** NGOTL-CPDC technique aims to investigate endoscopic images for automated colonic polyp *** accomplish this,the NGOTL-CPDC technique comprises of adaptive bilateral filtering(ABF)technique as a noise removal process and image pre-processing ***,the NGOTL-CPDC model applies the Faster SqueezeNet model for feature extraction purposes in which the hyperparameter tuning process is performed using the NGO ***,the fuzzy Hopfield neural network(FHNN)method can be employed for colonic poly detection and classification.A widespread simulation analysis is carried out to ensure the improved outcomes of the NGOTL-CPDC *** comparison study demonstrates the enhancements of the NGOTL-CPDC model on the colonic polyp classification process on medical test images.

关键词： Biomedical imaging artificial intelligence colonic polyp classification medical image classification computer-aided diagnosis

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Enhancing Medical Information Retrieval with a Language Model 1

Enhancing Medical Information Retrieval with a Language Mode...

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1st IEEE International Conference on Cognitive Robotics and Intelligent systems, ICC - ROBINS 2024

作者： Natarajan, Yuvaraj Sri Preethaa, K.R. Pandian, Sasikumar Geetha, Shruti Umapathi Senthilkumar, Sujadharshini Kpr Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Kyungpook National University Department of Robot and Smart System Engineering Daegu41566 Korea Republic of

ISBN: (纸本)9798350372748

In this ever-evolving healthcare landscape, with the integration of cutting-edge technology, this study has exemplified a medical chatbot by harnessing the advanced Llama2 model. This chatbot places significant emphasis on instance training by changing and adding the meta, which enables it to continuously adapt and stay updated with the latest medical developments. Its adaptability also encompasses capabilities such as question-answering and mining knowledge from an extensive meta dataset. By leveraging its extensive ability to learn medical terminology, the chatbot provides precise and real-time responses to medical inquiries by establishing itself as a reliable information source. Access to a specially collected meta dataset further enhances its ability to deliver comprehensive medical insights while self-supervised learning techniques enhance the model efficacy. Consequently, this chatbot reshapes the way individuals access precise medical information by enabling a new era of advanced digital healthcare assistants in the digital age. © 2024 IEEE.

关键词： Supervised learning

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Review of National Cybersecurity Policies: A Case Study on Asian Countries 1

Review of National Cybersecurity Policies: A Case Study on A...

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1st IEEE Karachi Section Humanitarian Technology Conference, Khi-HTC 2024

作者： Noor, Hera Seelro, Dodo Khan Ali, Syed Abbas NED University of Engineering & Technology Department of Computer Information System Engineering Karachi Pakistan Thar Institute of Engineering Science & Technology NED University of Engineering & Technology Karachi Pakistan

ISBN: (纸本)9798350373042

Accelerating the economic advantages of ICT is one of the finest methods for any nation to boost its economy. Due to the unique topography, governing laws, and cultural traditions of each nation, these colossal challenges must be confronted in each country. This comparative analysis aims to examine these aspects in further detail. To achieve the objectives of this study, research was conducted by collecting and analysing data from publicly accessible sources. This research compares Pakistan and other Asian countries' cybersecurity legislation, regulations, CERTs (national computer emergency response teams), CIIPs (computer intrusion prevention programs), and cyber security training and awareness. Among forty-eight Asian countries, the study focus on comparative analysis of major neighboring (developed or developing) countries of Pakistan such as Japan, China, Turkey, Iraq, Saudi Arabia, UAE, Nepal, Iran, Malaysia, Jordan, India, and Bangladesh. Cyber security has not been a major concern in Pakistan for a very long time, perhaps due to the way the government operates and how slowly it adapts to new technology. Many Asian countries have only ever released one version of their national cyber security plan, whilst Pakistan has never released anything;some other Asian countries are also added in this group. © 2024 IEEE.

关键词： Cybersecurity

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One Day International Cricket Match Score Prediction Using Machine Learning Approaches 1

One Day International Cricket Match Score Prediction Using M...

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1st IEEE International Conference on Smart Power Control and Renewable Energy, ICSPCRE 2024

作者： Hossain, Md. Sabbir Rumpa, Ummay Khadiza Hossain, Md. Shakil Shovon, Sazzadul Islam Huque, Md. Tahmidul Hasan, Mahamudul East West University Department of Computer Science and Engineering Dhaka Bangladesh Central Michigan University Department of Information System MI United States Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350377002

Cricket is the game that binds Bangladeshis to-gether. The datasets were split into different parts based on the time of the cricket matches to experiment with the results. We have used Random Forest Regression and Linear Regression to experiment with the results. We have worked on different sets of independent variables while working with different datasets but runs and wickets were constant features. The linear Regression technique gave 0.58 of r-squared metric and its MAE: 32.857046003557706, MSE: 1793.4360657965133, RMSE: 42.34897951304746 values indicate that the regression model is making predictions that are reasonably close to the actual ob-served values. However, there is still some room for improvement. The r-squared metric of 0.787 was derived from a relatively brief dataset, MAE: 20.48880467759807, MSE: 690.1167559064677, RMSE: 26.270073389818837 metrics indicate that the regression model is making predictions that are very close to the actual observed values. Random Forest Regression's r-squared metric resulted in 0.807 but the learning curve pointed out an overfit model. Thus, linear regression contained the best result. We have applied the regularisation technique to achieve a better result. The dataset was collected from Github and Kaggle, sizes are (350899, 15) and (4037, 9) respectively. © 2024 IEEE.

关键词： Prediction models

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