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Enhancing Drug Recommendations: A Modified LSTM Approach in Intelligent Deep Learning Systems 5

Enhancing Drug Recommendations: A Modified LSTM Approach in ...

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5th international conference on Innovative Data Communication Technologies and Application, ICIDCA 2024

作者： Siji Rani, S. Shilpa, P. Menon, Aswin G. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri690525 India

The overwhelming burden on the healthcare system has resulted in increased mortality rates as individuals struggle to receive appropriate medical attention. Machine learning has demonstrated its efficacy across diverse applications, fueling a growing trend in the realm of innovative automation. This is particularly facilitated by drug recommendation systems, which possess the capability to significantly reduce the dependence on specialized assistance. Faced with limited access to medical expertise, a considerable number of individuals have turned to self-medication, often worsening their health conditions. In response to this critical scenario, this paper introduces an inventive drug recommendation system which helps to lessen the strain healthcare professionals. Here, we present the development of a medication recommendation system based on LSTM, utilizing user-provided symptoms and the model's evaluations of past drug recommendations. The results of the comparison between Random Forest, SVM, and LSTM indicated that the modified LSTM-based recommendation system outperforms the other two models, achieving a 94% accuracy rate. © 2024 The Authors. Published by Elsevier B.V.

关键词： Support vector machines

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Research on the Relationship between Vibration Noise and Magnetic Saturation of Magnetic Saturated Controllable Reactor Based on COMSOL 3

Research on the Relationship between Vibration Noise and Mag...

引用

2023 3rd international conference on Electrical engineering and computer Technology, ICEECT 2023

作者： Zhang, Yuzhu Tian, Mingxing School of Automation & Electrical Engineering Lanzhou Jiaotong University Gansu Province Lanzhou730070 China

This article is based on a 2.2 kVar small magnetically saturated controllable reactor (MSCR) prototype and builds a three-dimensional three-field coupling model of its electromagnetic structure acoustics in the finite element simulation software COMSOL. The time-domain sound field distribution of MSCR under electromagnetic force and magnetostrictive effect is obtained through simulation, and DC bias is linearly added. The trend of changes in magnetic saturation and MSCR maximum sound pressure level are obtained, and finally, the relationship curve between MSCR maximum sound pressure level and its magnetic saturation is analyzed, which is similar to the magnetization curve. Taking the half-load working state as the knee point, this study provides a research idea for the design and monitoring of reactors based on the relationship between MSCR acoustics and the working state. © Published under licence by IOP Publishing Ltd.

关键词： Saturation magnetization

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Sensitivity of radiomics features to region volume: A CT phantom study

Sensitivity of radiomics features to region volume: A CT pha...

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2024 international conference on Control, automation and Diagnosis, ICCAD 2024

作者： Khan, Muhammad Usama Bianconi, Francesco Fravolini, Mario Luca Palumbo, Barbara Università Degli Studi Di Perugia Department of Engineering Via Goffredo Duranti 93 Perugia06125 Italy Università Degli Studi Di Perugia Department of Medicine and Surgery Piazzale Settimio Gambuli 1 Perugia06129 Italy

ISBN: (纸本)9798350361025

The extraction of quantitative parameters (features) from medical images to build prediction models for computer-assisted clinical decision making (radiomics) has attracted a lot of research attention in recent years. Radiomics features may be influenced by the size of the region of interest (ROI) and it is recommended to employ volume-independent features to reduce the risk of biased prediction models. Despite being a crucial factor, the influence of ROI volume on radiomics features has been largely overlooked in the literature, with only few studies addressing this aspect. In this work we investigated the sensitivity to ROI volume of 103 conventional radiomics features from seven classes under absolute and relative signal resampling. The analysis was carried out on a set of 90 lesion-agnostic ROIs from a CT phantom. We identified a total of 45 and 54 features significantly correlated with volume under absolute and relative signal resampling, respectively. We also determined that signal resampling had an influence on the direction of the relationship, with relative resampling leading to a significant rise in the number of features negatively correlated with volume. © 2024 IEEE.

关键词： Textures

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Melanoma Skin Cancer Detection Using Deep Learning Techniques 7

Melanoma Skin Cancer Detection Using Deep Learning Technique...

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7th international conference on Contemporary Computing and Informatics, IC3I 2024

作者： Kashikar, Arya Maurya, Sudhanshu Pant, Himanshu Gupta, Parbhat Asudani, Deepak Suresh Yadav, Ajay Kumar Symbiosis Institute of Technology Nagpur Campus Pune India Graphic Era Hill University Bhimtal Campus Uttarakhand India Srm Institute of Science and Technology Department of Computer Science and Engineering Delhi NCR Campus Ghaziabad India United Institute of Management Department of Computer Application Prayagraj India

ISBN: (纸本)9798350350067

Skin cancer, known as melanoma, is very dangerous in case of when it is not diagnosed at an early stage and has a positive prognosis when it is treated within the time frame. This work goes deep into the field of deep learning techniques to enhance the automation of melanoma detection. Using a dataset including 735 dermatoscopic pictures and two profound deep learning models were put to the test: A CNN model with ResNet-50 as the backbone and a Faster R-CNN model with MobileNet v3 as the backbone. The ResNet-50-powered CNN brought a precision rate of 85.06%, which proves that it is viable for accurately differentiating melanoma sores. To take identification accuracy to a higher level, the Faster R-CNN model was introduced, combining sore characterization with bounding inside the pictures. Finally, this integrated approach produced a quite impressive accuracy of 90 percent. This is good for clinical applications, as indicated by its 03% rating. From the disclosures made in the review, it is possible to infer that deep learning models, particularly those that have been augmented with district-based methods, hold the potential for early identification of melanoma. These mechanical headways can enhance patient results by integrating with adequate diagnosis and treatment, potentially saving lives and enhancing the quality of patient care in dermatology and oncology practices. © 2024 IEEE.

关键词： Lung cancer

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Facial Expression Recognition with CNN-SVM for Emotional State Classification 7

Facial Expression Recognition with CNN-SVM for Emotional Sta...

引用

2023 7th international conference On Computing, Communication, Control And automation, ICCUBEA 2023

作者： Rishu Kukreja, Vinay Kumar, Abhinav Chitkara University Institute of Engineering and Technology Chitkara University Punjab Punjab India

ISBN: (纸本)9798350304268

Facial expression recognition is useful for many things, including human-computer interaction and emotion analysis. For the purpose of recognizing different facial expressions, we present a Convolutional Neural Network (CNN) and a Support Vector Machine (SVM) classifier in this research. Using a large-scale dataset, experiments confirm that the proposed system is effective at using the CNN-SVM model for recognizing seven distinct facial emotions (neutral, angry, surprise, fear, sorrow, disgust, and happy). The experimental findings were very reliable, with high F1 scores and excellent precision across a variety of memory and precision metrics. All classes of facial expressions are accurately interpreted by the algorithm, although the 'Angry,' 'Fear,' and 'Happy' classes do very well. The CNN-SVM model demonstrated its viability in real-world settings by achieving an overall accuracy of 98.06%. With an F1 score of over 97.80 percent, it's clear that the system can recognize a broad variety of emotions. Emotion identification in HCI, sentiment analysis, and content recommendation systems are just few of the areas where these findings highlight the value of the CNN-SVM paradigm. © 2023 IEEE.

关键词： Convolutional Neural Network (CNN) Facial Expression Recognition 2013(FER2013) Facial Expressions Support Vector Machine (SVM)

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Research and Optimization of the Development Process of Control Programs for CNC Systems Using a Specialized Postprocessor

Research and Optimization of the Development Process of Cont...

引用

2023 international Russian automation conference, RusAutoCon 2023

作者： Nezhmetdinova, Ramilya Chervonnova, Nadezhda Plaksin, Alexander Mstu "STANKIN" Department of Computer Control Systems Moscow Russia V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9798350345551

The article presents the results of modeling the processing of a workpiece using the trochoidal and high-speed milling approach. A methodology aimed at optimizing the strategy of mechanical high-speed metalworking during the development of control programs is also discussed. The correct utilization of the trochoidal and high-speed milling approach enables the clean machining of pockets in the workpiece without significantly reducing the quality of the finished surface or increasing the impact loads. The high demand for CNC machines is attributed to several advantages such as high production efficiency coupled with the ability to reconfigure, multi-surface processing, and the availability of multiple interchangeable tools for material processing. Emphasis is placed on improving efficiency, increasing production capacity, and maintaining the specified accuracy of the machining process. To achieve these objectives, the selection of the correct strategy in the development process of control programs is crucial. © 2023 IEEE.

关键词： Production efficiency

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An Electronic Circuit Principle and Test Platform for Negative Group Delay and Superluminal Propagation 5

An Electronic Circuit Principle and Test Platform for Negati...

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5th international conference on computer Network, Electronic and automation, ICCNEA 2022

作者： Wang, Zhongsheng Shen, Han Xi'an Technological University School of Computer Science and Engineering Xi'an710021 China

ISBN: (数字)9781665491099

ISBN: (纸本)9781665491099

Group velocity superluminal phenomenon, also known as negative group delay or negative group velocity phenomenon, refers to a group of envelope signals at the output end of the medium before the input, on the time axis, is the envelope on leaving the medium before entering the medium, but this does not violate causality. Based on the waveguide theory of negative group delay, this paper uses the transfer function, amplitude response and phase shift response of the electronic circuit to achieve the regulation of group velocity. The actual electronic circuit is made and the testing platform and method are built. The phenomenon of negative group delay is preliminarily realized, which lays a foundation for the subsequent research. As an envelope that can carry and transmit information, the study of negative group velocity is of great significance to the improvement of signal transmission efficiency. © 2022 IEEE.

关键词： Group delay

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Robustness Analysis of Multi-sink Placement in Wireless Sensor Networks 4

Robustness Analysis of Multi-sink Placement in Wireless Sens...

引用

4th international conference on Artificial Intelligence and Electromechanical automation, AIEA 2023

作者： Sheng, Dan Ding, Lin School of Computer University of South China Hengyang421001 China

ISBN: (纸本)9781510666412

Multi-sink wireless sensor networks are widely used because of their prominent advantages in extending network life and balancing energy. However, the current research on cascading failures of wireless sensor networks mainly focuses on the impacts of network topologies or routing schemes, and rarely involves the impacts of multi-sink placement. Therefore, this paper proposes a realistic multisink-oriented cascading model, in which a multi-oriented betweenness is designed to describe the load distribution of sensor nodes and wireless links considering sink nodes, and the overload dynamics of nodes and links are considered at the same time. On this basis, several topological metrics are considered to quantify the placement properties of sink nodes, and then how they affect the cascading robustness under node attacks and link attacks is investigated. Experimental results show that node attacks are more likely to trigger cascade failures. More importantly, no matter what kind of attack the network suffers, if sink nodes are placed as hubs, and these nodes are decentralized, the networks can better resist cascading failures. © 2023 SPIE.

关键词： Sensor nodes

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An Adaptive Multi-Stage Evolution Algorithm for High-Dimensional Expensive Problems

An Adaptive Multi-Stage Evolution Algorithm for High-Dimensi...

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2024 IEEE international conference on Systems, Man, and Cybernetics, SMC 2024

作者： Zhang, Boyuan Lai, Rui Gong, Guanghong Yuan, Haitao Yang, Jinhong Zhang, Jia School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Cssc Systems Engineering Research Institute Beijing China Southern Methodist University Dept. of Computer Science DallasTX75275 United States

ISBN: (纸本)9781665410205

Recently, many studies have used evolutionary algorithms (EAs) to optimize complex problems across various fields, including mechanical structure design, robotics, and cloud computing. EAs simulate the process of evolution to improve solutions to a given problem iteratively. However, EAs encounter significant challenges when dealing with high-dimensional expensive problems (HEPs). The large solution space and high computing cost of fitness evaluations (FEs) make optimization with limited FEs particularly difficult. To tackle this problem, an Adaptive Multi-stage Evolution Algorithm named AMEA is proposed. In AMEA, an adaptively enhanced teaching-learning-based optimization algorithm is adopted to explore the search space and find potential areas quickly. Then, in the next stage, the Gaussian process surrogate model and a genetic learning particle swarm optimization algorithm are adopted for further exploitation. Besides, this work proposes an adaptive stage switching criterion and an individual screening mechanism to enhance the optimization ability. AMEA demonstrates strong optimization performance when applied to HEPs. We compare AMEA with several state-of-the-art HEP optimization algorithms through seven benchmark functions, and the results show that it performs competitively with other algorithms. Finally, we also validate AMEA's effectiveness with a real-world computation offloading problem. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Human-Machine Interaction Systems for Training Industrial Robots

Human-Machine Interaction Systems for Training Industrial Ro...

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2024 OPJU international Technology conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Kumar, S Vinod Mishra, Dinesh Reddy, Uma Nagpal, Amandeep Kumar, Ashwani Al-Asadi, Zahraa Saad Institute of Aeronautical Engineering Hyderabad Dundigal India Cse Department M.P. Jabalpur India New Horizon College of Engineering Department of Artificial Intelligence and Machine Learning Bangalore India Lovely Professional University Phagwara India Lloyd Institute of Engineering & Technology Knowledge Park II Uttar Pradesh Greater Noida201306 India National University of Science and Technology College of Health and Medical Technology Dhi Qar64001 Iraq

ISBN: (纸本)9798350373783

Workplace robot processing speed and efficiency depend on human-machine interaction. This study investigated RLIL, ViTREX, and NLCCF, three innovative HMI approaches. The purpose is to improve workplace robot setup and use. RLIL uses copying and reinforcement learning to improve robot behaviour in real time. Workshops and assembly lines benefit from this flexible and precise solution. computer vision lets ViTREX robots adapt to new environments. This makes moving and transport simpler. In circumstances where people need to utilize conventional language to lead robots, NLCCF makes it easier for people and robots to communicate. We assessed these methods' F1 accuracy, precision, and high score. RLIL was accurate and precise, making it suitable for precise outcomes. ViTREX balanced precision with memory, making it ideal for users who had to choose. The NLCCF was versatile and outperformed in every way. These cutting-edge HMI technologies provide more alternatives, faster decision-making, and greater communication, making them valuable in current workplaces. Considering memory, precision, and balance, the procedure should be suited to the application. These technologies might improve robot-human collaboration in manufacturing, enabling more efficient, flexible, and natural automation. © 2024 IEEE.

关键词： Collaborative robots

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