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Heart Disease Classification Using Supervised Machine Learning Algorithms 2

Heart Disease Classification Using Supervised Machine Learni...

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2nd international conference on Computer science, engineering and Applications, ICCSEA 2022

作者： Saraswathi, R. Shobarani, G. Veerma Devi, S. Sreenivasa Institute of Technology and Management Studies Computer Science Engineering Andhra Pradesh Chittoor India K.M.G College of Arts&Science Pg & Research Department of Computer Science Tamil Nadu Gudiyatham Vellore India Department of Computer Science Tamil Nadu Palacode India

ISBN: (数字)9781665458344

ISBN: (纸本)9781665458344

Heart disease cases are increasing at a rapid rate, and it's critical and concerning to predict any such infections ahead of time. This is a difficult job since it must be completed accurately and efficiently. This researchpaper focuses on which patients are more likely to develop a coronary artery disease based on several clinical criteria. Anaccurateforecast of coronary artery disease can stop life-threatening complications, whereas an inappropriateforecast can be fatal at the similar time. The outcomes and examination of the UCI Machine Learning Heart Disease dataset are considered and examined in this work using various AI computations and profound learning. In this paper we use the dataset covers 14 main features that remained used to carry out the research. Using the exactness and disorder framework, several promising outcomes are achieved and authorised. This system forecasts the future of cardiovascular illness. The consequences of this framework indicate the likelihood of coronary illness happening at a certain rate. Clinical borders are defined in the datasets that were used. Using an information mining grouping strategy, this framework evaluates such boundaries. Two main Machine Learning Algorithms are used to manage the datasets in Python programming. © 2022 IEEE.

关键词： Heart

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Enhanced Resource Control in Cloud Environment using Optimized VM Allocation in Data Centers 2

Enhanced Resource Control in Cloud Environment using Optimiz...

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2nd IEEE international conference on Advanced Technologies in Intelligent Control, Environment, Computing and Communication engineering, ICATIECE 2022

作者： Sharma, Vikrant Bhardwaj, Shambhu Jaipur National University Department of Engineering and Technology Jaipur India Teerthanker Mahaveer University Department of Computing Science and IT Moradabad India

ISBN: (纸本)9781665493963

Cloud computing is the most revolutionary technology of the last decade since it makes a new generation of computer resources accessible to consumers via IaaS, PaaS, and SaaS administrations. Infrastructure as a service (IaaS) allows a VM to be deployed, launched, and managed over a cluster of servers. Efficient VM assignment is often regarded as one of the most challenging issues for CPs to conquer because to the inherent tension between the goals of improving customer demand fulfilment while cutting costs and maximising asset efficiency. The purpose of this work is to provide a novel approach to allocating virtual machines to meet the needs of individual customers by using the modified emperor penguin optimization method algorithm. Relying on established optimization methods for efficient VM allocation further demonstrates the value of the suggested approach. This application was built using the Java programming language and deployed to the Netbeans IDE 12.4. © 2022 IEEE.

关键词： Infrastructure as a service (IaaS)

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Optimization of Ordering and Forwarding Solutions for Manufacturing Enterprises Based on Decision Model 2

Optimization of Ordering and Forwarding Solutions for Manufa...

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2nd international conference on artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2022

作者： Yu, Xiao School of Computer Engineering and Science Shanghai University Shanghai200444 China

ISBN: (纸本)9781510657717

This paper establishes a multi-objective integer programming model considering economic and safety aspects. The time series model predicts the loss of goods by forwarders for the forwarding decision, and dynamic planning is used to solve the forwarding solution with the lowest loss of goods. Firstly, the data are preprocessed by ADF test and quadratic isolated forest algorithm, raw material preference weights are set according to Friedman test and transaction mean, and decision tree model classifies suppliers, and finally, 50 most important suppliers are selected by ranking through structural entropy weight -Topsis comprehensive evaluation method;based on the marginal decreasing effect, a strategic-large supplier interaction function is established, and the minimum number of suppliers is solved to be 35, and the corresponding number of A, B and C suppliers are selected according to the ranking and quota allocation. Then, the minimum number of suppliers to meet the production demand of the enterprise is determined by the ordering scheme decision model based on multiobjective integer planning. © 2022 SPIE. All rights reserved.

关键词： Decision trees

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A Computational Analysis of Optimization Techniques to Solve Assignment Problem

A Computational Analysis of Optimization Techniques to Solve...

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Advances in Computation, Communication and Information Technology (ICAICCIT), international conference on

作者： Yash Kuma Ramesh Ch. Sahoo Prashant Dixit Dept.of Computer Science & Engineering Manav Rachna International Institute of Research and Studies Faridabad Haryana India Dept. of Computer Science & Engineering Galgotias University Greater Noida Uttar Pradesh India

ISBN: (数字)9798331541217

ISBN: (纸本)9798331541224

In the field of combinatorial optimization, numerous methods have been developed to address complex problems, including assignment, scheduling, and resource allocation. This paper presents a comparative analysis of seven prominent optimization techniques: Hungarian Algorithm, Greedy Algorithm, Auction Algorithm, Linear programming, Genetic Algorithm, Simulated Annealing, and Constraint programming. We evaluate these methods on computational efficiency, scalability, and practical applicability, focusing on assignment problems. The analysis reveals that Hungarian Algorithm, Linear programming, and Constraint programming consistently deliver high accuracy across all matrix sizes, making them ideal for scenarios where solution precision is paramount. Conversely, the Greedy Algorithm excels in speed on smaller matrices but suffers from significant time and accuracy issues as matrix size increases. Additionally, while both Constraint programming and Genetic Algorithm achieve high accuracy, their execution times rise considerably with matrix size, especially for Genetic Algorithm, which becomes impractical for large-scale problems. Thus, Hungarian Algorithm, Linear programming, and Constraint programming are optimal for accuracy-focused tasks, while Greedy Algorithm is preferable for smaller, speed-critical cases.

关键词： Constraint handling Greedy algorithms Accuracy Processor scheduling Scalability Simulated annealing Linear programming Resource management Optimization Genetic algorithms

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Design Modelling for Commercial/Pilot-Scale Circulating Fluidized Bed Combustion (CFBC) Boiler 2nd

Design Modelling for Commercial/Pilot-Scale Circulating Flui...

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2nd international conference on Advances in Mechanical engineering and Material science, ICAMEMS 2023

作者： Naga Kishore, S. Venkateswara Rao, T. Deva Kumar, M.L.S. Department of ME JNT University College of Engineering Anantapur India Department of ME DBS Institute of Technology Kavali India

ISBN: (纸本)9789819956128

Two biggest problems in present Indian pulverized coal combustion (PCC) power plants are that large capacity of PCC plants has reached retirement due to age limit and huge coal import from outside countries. Increasing the utilization of circulating fluidized bed combustion (CFBC) technology in India is the best solution for renovating old PCC boilers to extend their life to 20–25 years and reducing coal import by increasing the utilization of local low-grade coals in effective manner. Even though CFBC technology is economically sound, technically feasible and environmentally friendly than PCC technology, CFBC technology utilization in India is still in the nascent stage. To increase the utilization of CFBC technology in India, more design models are needed to come out on Indian low-grade fuels such as Indian lignite and high ash coal for predicting thermal and environmental performance, analysing design and optimizing processes in operation at wider range of operating parameters. In this paper, a CFBC boiler design modelling which is developed by programming code of visual basics for applications (VBA) software is explained. To check the accuracy, the design methodology is applied to validate the practical data of different CFBC units on various aspects such as thermal performance model (boiler efficiency, flow rates), hydrodynamic model (solids volume fraction), heat transfer model (water wall heat transfer coefficient) and sulphur capture model (SO2 emissions). The design procedure which is applied for validation process gives satisfactory results on different aspects, and the qualitative agreement is found between predicted values and actual measurements. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Design

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Buffer Reduction for Congestion Control during Timing Optimization 2

Buffer Reduction for Congestion Control during Timing Optimi...

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2nd IEEE international conference on Power, Electronics and Computer Applications, ICPECA 2022

作者： Song, Yitong Li, Peng Liu, Zhili Xi, Wei Yao, Hao Zheng, Dandan Huang, Kai Zhejiang University College of Information Science and Electronic Engineering Hangzhou China Digital Grid Research Institute CSG Guangzhou China Hangzhou Sec-chip Technology Co. Ltd. Hangzhou China Zhejiang University School of Micro-Nano Electronics Hangzhou China

ISBN: (纸本)9781665442763

In very-large-scale-integrated (VLSI) circuit design, Performance, Power and Area (PPA) are three very important indicators. Especially in the process of power-related chip design, possible trade-offs between these three indicators must be considered. In this work, we have developed two algorithms, respectively applying the greedy algorithm and the tree dynamic programming algorithm for redundant buffer reduction, in order to solve the local congestion problem of the chip. Redundant hold buffers are found and deleted during the timing optimization iteration, without making timing results worse. Through this method, the local cell area is reduced by 9.1%. It leaves room for other timing optimization, and reduces local utilization, routing congestion and short circuits. © 2022 IEEE.

关键词： Timing circuits

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Stochastic Optimal Scheduling of Electric-Thermal-Hydrogen Integrated Energy System Based on Seagull Optimization Algorithm 2

Stochastic Optimal Scheduling of Electric-Thermal-Hydrogen I...

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2nd international conference on Electrical engineering and Control science, IC2ECS 2022

作者： Jin, Zhenhua Wang, Xiaopei Hu, Ziping Hua, Yuwei Jia, Shiduo Hou, Anxiang Tsinghua University School of Vehicle and Mobility Beijing China Xi'An Jiaotong University Shaanxi Key Laboratory of Smart Grid Xi'An Jiaotong University Xi'an China School of Electrical Engineering Shandong University Jinan China

ISBN: (纸本)9798350399165

Uncertainties in the integrated energy system will bring challenges to its stable operation, hence a stochastic optimal scheduling model of electric-Thermal-hydrogen integrated energy system (ETH-IES) with the goal of minimizing operation cost is established. In addition, Proton exchange membrane fuel cell (PEMFC), hydrogen storage tank and electrolyzer are introduced to the ETH-IES, so that its flexibility and economy can be improved. Furthermore, seagull optimization algorithm (SOA) is used to solve the proposed mixed integer nonlinear programming (MINLP) model. To verify the availability of the proposed strategy, simulation analysis is performed for a typical ETH-IES case and the results are compared with those of other algorithms. The results indicate that the proposed algorithm has better global convergence performance and the cost solved is lower than other algorithms, which verifies the benefits of SOA algorithm. © 2022 IEEE.

关键词： Stochastic systems

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Data Augmentation for Brain Tumor Segmentation using MONAI Framework 2

Data Augmentation for Brain Tumor Segmentation using MONAI F...

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2nd IEEE international conference on Intelligent Technologies, CONIT 2022

作者： Sharma, Suraj Prakash Sampath, Nalini Amrita School of Engineering Bangalore Amrita Vishwa Vidyapeetham Department of Computer Science & Engineering India

ISBN: (数字)9781665484077

ISBN: (纸本)9781665484077

In 2020, worldwide 308,102 brain and nervous system cancer cases were reported out of which 251,329 deaths were registered i.e. ≈ 82.0 % fatality rate [1] and glioma was found to be one of most occurring brain tumors in the world, and it can be both benign or metastatic, and because of the high heterogeneity present in the occurrence of the lesion in terms of size, location and histology combined with the limitation of expert annotated dataset and programming frameworks for the development of automatic segmentation systems using deep learning presents a need of having an efficient and robust data augmentation pipeline to significantly boost the generalization capabilities of automatic segmentation systems based on deep neural network models. In this work, the main focus was on the development of a data augmentation pipeline, and a design is proposed using MONAI open-source domain specialized python framework, which can later be leveraged to train various U-Net based architectures in the context of the BraTS-2020 dataset without using any external multi-modal brain MRI dataset. © 2022 IEEE.

关键词： Magnetic resonance imaging

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MOLECULAR DYNAMICS STUDY ON DIFFUSION WELDING TECHNOLOGY OF PCHE 9

MOLECULAR DYNAMICS STUDY ON DIFFUSION WELDING TECHNOLOGY OF ...

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9th international conference on New Energy and Future Energy Systems, NEFES 2024

作者： Chen, Kai Huang, Chonghai Qi, Xiao Ke, Hanbing Zhao, Zhenxing Wuhan 2nd Ship Design and Research Institute State Key Laboratory of Marine Thermal Energy and Power Wuhan China

ISBN: (纸本)9781837241880

The titanium alloy diffusion bonding structure is widely used in aviation manufacturing because of its good welding quality and small stress deformation. The diffusion bonding process parameters determine the diffusion bonding quality of the titanium alloy, which determines the mechanical properties of the diffusion joint. In this paper, molecular dynamics simulation is used to study the diffusion bonding process of titanium alloy, the random replacement method was used to obtain the initial configuration of the corresponding atomic percentage. The Nose-Hoover temperature control method and Parrinello-Rahman pressure control method were applied to simulate the diffusion bonding process of titanium alloy under different conditions. The atom concentration distribution under various conditions was obtained using Matlab programming. The change rule of diffusion connection width with process parameters was also analyzed. Finally, the tensile deformation behavior of titanium alloy diffusion joint was simulated to obtain the stress-strain curves under different technological parameters. The results show that the holding temperature, holding time, and welding pressure influence the quality of diffusion welding. The higher the holding temperature;the larger the width of the welding diffusion layer. The longer the holding time, the greater the thickness of the welding diffusion layer. The greater the welding pressure, the wider the diffusion welding layer. The tensile tests on the welded joints and the base material show that the tensile mechanical properties of the diffusion joint can be comparable to the base material under the appropriate welding process parameters. © The Institution of engineering & Technology 2024.

关键词： Titanium alloys

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Design and performance study of a BMI-based hand-assisted robot 2

Design and performance study of a BMI-based hand-assisted ro...

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2nd IEEE international conference on Data science and Computer Application, ICDSCA 2022

作者： Cai, Jiayi Cai, Jialiang Macau University of Science and Technology Faculty of Humanities and Arts China Macao Institute of Materials Science and Engineering Macau University of Science and Technology China

ISBN: (数字)9781665472005

ISBN: (纸本)9781665472005

Forty-six percent of stroke patients, of whom 80 percent are not treated in a timely manner, have hand paralysis syndrome that lasts a lifetime. The integration and control of external rehabilitation devices based on EEG signal collection is gaining more attention and research, and this type of research has a wide range of directions to improve the quality of life for users. The research aims to study the design and performance of BMI-based hand-assisted robots. Existing robotics and equipment are relatively expensive, and the programmed procedures are not well adapted to different stroke users. Through experimental development and research of innovative BMI brain-computer interface devices, customized programming of experimental protocols, situational awareness of assistive robotics system data processing, brain-computer driven device testing and human-computer interaction methods, and finally after 510 practical tests concluded that patients can get significant rehabilitation process, especially for in the clinical state. The innovative system-on-a-chip research and ergonomic design confirmed that it meets the standards of rehabilitation practice and can significantly improve the patient's cognitive abilities during learning and rehabilitation and more efficiently facilitate the patient's recovery. © 2022 IEEE.

关键词： Machine design

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