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Hybrid Layered Classification Model for Heart Disease Diagnosis 3

Hybrid Layered Classification Model for Heart Disease Diagno...

引用

3rd International Conference on Intelligent engineering and Management, ICIEM 2022

作者： Jain, Archika Somwanshi, Devendra Singh, Rajesh Singh, Ghanshyam Poornima College of Engineering Dept. of Computer Engineering Jaipur India Uttaranchal University Uttaranchal Institute of Technology Dept. of Electronics and Communication Dehradun India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

Over past few decades due to hectic schedule and careless behavior of human much of disease has arises in form of life killer. Among several Heart diseases is one of the most leading destroyer diseases around the globe. Only a precise and timely forecast of this disease can aid in its prevention. Although many ways have been presented to assist professionals, each algorithm has its own set of obstacles. To improve the prognosis accuracy with low false alarms a new ensemble algorithm has proposed in this paper. To show the effectiveness of proposed approach it has simulated with the traditional and modern algorithm. The results indicates that proposed approach has improve prediction accuracy significantly. © 2022 IEEE.

关键词： Diseases

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Investigating the Advantages of AI-driven Predictive Analysis in Healthcare 3

Investigating the Advantages of AI-driven Predictive Analysi...

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3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024

作者： Mohammed, Murtuza Ali Mohammed, Vazeer Ali Ganesh, Ashween Kiruthiga, T. Lewis University Dept. of Computer & Information System IL United States Fresenius Medical Care North America Research and Development ConcordCA94520 United States Vetri Vinayaha College of Engineering and Technology Dept. of Ece Trichy India

ISBN: (纸本)9798350384598

AI-pushed predictive evaluation can revolutionize healthcare. With the usage of superior predictive models and machine algorithms, AI can discover styles and appropriately expect consequences for clinical treatments and remedies. It may assist clinicians in making more informed decisions and ensuring certain affected persons' safety. In this summary, we assess the benefits of imposing AI-driven predictive analysis in healthcare AI-driven predictive evaluation permits the usage of state-of-the-art fashions that can correctly predict medical outcomes. It allows doctors and healthcare carriers to limit risks and discover ability problems earlier than they grow to be intricate. By way of leveraging available information, such as scientific records, genomic information, and more, AI can accurately generate insights and guidelines for remedy and prognosis. Moreover, AI-pushed predictive evaluation is incredibly capable of figuring out destructive drug reactions and different interactions among drugs, in addition to providing perception into drug interactions among illnesses and other conditions. AI-driven predictive evaluation has numerous packages in healthcare and may be used to pick out capacity mistakes before they occur. AI can analyze a large variety of records and generate reports on the consequences. It will assist healthcare providers in making the proper decisions in relation to imparting top-quality care for sufferers. Moreover, AI can be used to expand customized treatment plans, which are custom-designed to every patient's unique state of affairs. It may be extraordinary. © 2024 IEEE.

关键词： Drug interactions

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Deep Learning for Wireless Network Distribution (5G/LTE)

Deep Learning for Wireless Network Distribution (5G/LTE)

引用

2023 IEEE International Conference on communications, Information, Electronic and Energy systems, CIEES 2023

作者： Al-Dulaimi, Mohammed Khodayer Hassan Al-Dulaimi, Omer Mohammed Khodayer Al-Dulaimi, Aymen Mohammed Khodayer Alexandra, Maiduc Osiceanu Jihad, Nidal Al-Rafidain University of College Dept. Computer Engineering Baghdad Iraq University Politehnica of Bucharest Dept. of Telecommunication Engineering Bucharest Romania Al- Farahidi University College Dept. of Technical Communication Engineering Baghdad Iraq University Politehnica of Bucharest Dept. of Director for Management of Scientific Research Bucharest Romania Dept. of Iraqi Prime Ministers' Council Baghdad Iraq

ISBN: (纸本)9798350336917

As a result of using machine learning and deep learning in the network, we were able to more efficiently manage the allocation of network resources and the availability of the network overall. Key performance indicators are used to analyze incoming traffic and make predictions to allocate network resources to unknown devices. High load balancing and efficient use of available resources on current network portions are made possible with intelligent resource allocation. The underlying model is smart enough to determine which piece of the network is most suited for the challenge at present. 5G mobile networks, mobile communications, and the latency of modern and future wireless networks are affected by strict regulations about how long it takes for data transmission to reach its destination, dependability, how much data can be transmitted without a problem, capacity, how much data can be transmitted securely, and speed of user connection. Mobile providers are always looking for new ways to make it possible for multiple, autonomous users to share a single network. Slicing is a method that uses network fragmentation to share the same physical infrastructure among multiple networks that have competing needs. Future communication networks will need to make decisions based on data in order to keep up with the exponential rise in traffic. © 2023 IEEE.

关键词： Wireless networks

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Analysis of Routing Protocol for Low Power and Lossy Networks Attack Behavior on the Internet of Things

Analysis of Routing Protocol for Low Power and Lossy Network...

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2022 International Conference on Artificial Intelligence and Data engineering, AIDE 2022

作者： Pai, Vasudeva Rao, Abhishek S. Krishna Prasad, D.S. Devidas Karthik Pai, B.H. Karnataka Nitte574110 India Dept. of Computer & Communication Engineering Karnataka Nitte574110 India

ISBN: (纸本)9781665493048

Routing Protocol for Low-Power and Lossy Networks (RPL) is the IPv6 routing protocol suitable for the Internet of Things (IoT) and Wireless Sensor Network (WSN). Despite being a lightweight protocol with enhanced routing characteristics, RPL lacks basic security measures. Protecting IoT networks is challenging due to their varied existence and access to unprotected internet. In-dept. analysis of RPL attacks such as Black Hole /Gray Hole, Hello Flood, and version numbers are provided in this research. In this study, we use the COOJA Simulator to simulate an RPL network with and without malicious nodes present and create a Packet Capture (PCAP) file on the Contiki operating system. To determine whether a network attack is taking place, we have evaluated the PCAP file by counting the number of different packets. Later, we discussed various techniques and proposed an algorithm for identifying malicious network nodes. The study will also cover open research issues and possible work that must be done to assure RPL for the IoT, as well as a complete analysis of the network's behavior in various attack scenarios. © 2022 IEEE.

关键词： Routing protocols

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Dementia Detection Using Machine Learning in Males and Females

Dementia Detection Using Machine Learning in Males and Femal...

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2024 International Conference on Artificial Intelligence and Emerging Technology, Global AI Summit 2024

作者： Iyer, Aishwarya Hariharan Vekkot, Susmitha Gupta, Deepa Gopalakrishnan, E.A. School of Computing National University of Singapore Singapore Amrita School of Engineering Amrita Vishwa Vidyapeetham Dept. of Electronics and Communication Engineering Bangalore India Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering Bangalore India Amrita School of Artificial Intelligence Amrita Vishwa Vidyapeetham Bangalore India

ISBN: (纸本)9798350379716

In this study, we train different Machine Learning classifiers on male and female samples from The ADReSS Challenge dataset. After testing them on data consisting of both male and female samples as well as on data with samples of only the corresponding sex, we use SHapley Additive exPlanations on the models to identify the most important features. Then, we present the results of training the models with only the most important features identified. Finally, we present a comparative analysis based on the observations and insights gathered through these experiments. © 2024 IEEE.

关键词： Adversarial machine learning

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Design and Hardware Realization of 32-Bit Multipliers Based on FPGAs

Design and Hardware Realization of 32-Bit Multipliers Based ...

引用

2022 International Conference on Electrical engineering and Informatics, ICELTICs 2022

作者： Zulhelmi, Zulhelmi Ali, Sawal Hamid Md. Nasaruddin, Nasaruddin Universitas Syiah Kuala Dept. of Electrical and Computer Engineering Banda Aceh Indonesia Universiti Kebangsaan Malaysia Dept. of Electrical Electronics and System Engineering Bangi Malaysia Universiti Kebangsaan Malaysia Dept. Name of Organization Dept. of Electrical Electronics and System Engineering Bangi Malaysia

ISBN: (数字)9781665487665

ISBN: (纸本)9781665487665

A new approach for optimized multipliers based on the Vedic mathematics principle is introduced. The design aims to meet current Field-Programmable Gate Arrays (FPGAs) requirements. However, the need for high-speed multipliers in Digital Signal Processing (DSP) has become a challenge for researchers to propose and find new multiplier designs that meet the DSP requirement. This paper presents a new 32-bit multiplier suitable for being employed on DSP systems. The multiplier employs the Vedic mathematics principle to produce partial products using fundamental 4x4 multipliers developed by utilizing 6-input LUTs and multiplexers in the same slices yielding a drastic decrease in the area when implemented FPGAs. The use of Carry Ripple/Chain Adder is to get final products. Moreover, the multiplier is developed in a non-pipeline multiplier schema, which is designed without a clock signal in its operation. This structure is the same as combinatorial circuitry. The proposed multiplier has a maximum delay of 14.529 ns, less than other similar multiplier designs. © 2022 IEEE.

关键词： Application specific integrated circuits

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Comparative Study of Inductive Graph Neural Network Models for Text Classification

Comparative Study of Inductive Graph Neural Network Models f...

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2022 International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2022

作者： Pandian, Saran Chaurasia, Uttkarsh Ranjan, Shudhanshu Saxena, Shefali Daiict Data Science Gandhinagar India Nit Dept. of Computer Science and Engineering Hamirpur India Presidency University Dept. of Computer Science and Engineering Banglore India Nit Dept. of Electronics and Communication Hamirpur India

ISBN: (纸本)9781665461092

Graph neural networks(GNN) are a special variant of neural networks which help in dealing with unstructured data such as graph data. The advent of the GNN has helped in dealing with problems in different domains, especially in the domain of Natural Language Processing(NLP). In NLP, GNNs are used to implement tasks such as text classification which has a wide variety of applications. There are two ways to represent the text data using GNN namely, Inductive and transductive. In this paper, we apply the approach of the inductive model using different variants of GNN. We observed that the GAT variant gave better performance compared to other variants. Moreover, we observed that the complexity of the model and the dataset size influences the entropy of the output. © 2022 IEEE.

关键词： Entropy

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Hand Gesture Recognition using OpenCV 10

Hand Gesture Recognition using OpenCV

引用

17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Gupta, Rohan Singh, Akashdeep University Institute of Engineering Chandigarh University Deptt. of Electronics and Communication Engineering Punjab Mohali India University Institute of Engineering Chandigarh University Dept. of Computer Science Engineering Punjab Mohali India

ISBN: (纸本)9789380544472

For regulating the gestures the module which is mainly employed is Opencv. To regulate the structure the hand gesture will act as input. A hand gesture recognition technology allows us to communicate nonverbally in a natural, groundbreaking, and ultramodern way. The goal of the program is to spread a revolutionary gesture reputation strategy based on the discovery of a few form grounded traits. One digital digicam is included in the arrangement to capture the stoner's gesture and use it as an entry point into the device. One of the most important aspects of this program is to provide a device that can recognize particular physical motions and send information for tools operation. For example, a user can control a computer by performing a particular action next to a videotape digital digicam connected to a computer. Using the OpenCV module, we can extend the range of a hand gesture device in this arrangement. The device can then be controlled with hand gestures rather than using a physical component. The system utilizes high definition cameras for identifying the gestures. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Palmprint recognition

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Optimization of Quality Power Distribution system using Artificial Intelligence 5

Optimization of Quality Power Distribution System using Arti...

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5th International Conference on Smart systems and Inventive Technology, ICSSIT 2023

作者： Awasthi, Satya Prakash Singh, Sanjay Pilania, Urmila Kumar, Manoj Sindhu, A.S. Sarika, A.S. Poornima University Faculty of Computer Engineering Ramchandraoura Jaipur India Manav Rachna University Dept. of Computer Science and Technology Faridabad India Rajas Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu India Amrita College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu India

ISBN: (纸本)9781665474672

A maximum power point tracker is used in this study to determine incremental conductance (INC) (MPPT). Artificial Intelligence (AD based analysis and simulation of a solar photovoltaic module and associated electric circuit is presented, along with an examination of the effects of various environmental conditions on the behavior of the PV module. To fully appreciate the operating parameters of a PV module, basic PV cell attributes are addressed. A block diagram model of a PV module was made in Simulink and used to illustrate the curves. The results of simulations using a solar module demonstrate that the suggested method is quick and precise. This model is effectively used utilizing steady conductance in light of most maximum power point tracking methodologies for testing the behavior of the suggested system and forestall this output in the simulation via MATLAB. Controller can be implemented using a number of different techniques and algorithms. Power Point is liked here and is likewise reasonable for business purposes due to the minimal oscillations while establishing the Maximum. © 2023 IEEE.

关键词： Maximum power point trackers

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Identification of Black Fungus Diseases Using CNN and Transfer-Learning Approach 22

Identification of Black Fungus Diseases Using CNN and Transf...

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2nd International Conference on Computing Advancements: Age of Computing and Augmented Life, ICCA 2022

作者： Hasan, Md Imran Mahbub, Nosin Ibna Sarkar, Bappa Dept. of Computer Science and Engineering Islamic University Kushtia Bangladesh Dept. of Information and Communication Technology Islamic University Kushtia Bangladesh

ISBN: (纸本)9781450397346

Black Fungus is a dangerous fungal illness, commonly referred to as 'mucormycosis', usually infecting uncompromising people. Mucormycosis is generally rare, affecting less than two individuals per million each year, but it is currently 80 times more frequent in India. People of all ages, including prematurity infants, may be impacted. To minimize the time and effort required by medical experts to investigate black fungus disease and enhance the consistency of image identification of black fungus infections, we suggested a transfer learning based CNN model as the dataset for the black fungal disease is limited. The experimental outcomes of several different architectures, including VGG16, InceptionV3, and Xception, are compared and analyzed in this study, and it is observed that Xception has the best performance, with 97.92% training accuracy and 95.60% testing accuracy. © 2022 ACM.

关键词： Image enhancement

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