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4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： sangeetha, M. Ruchitha, v. subasni, K.M. vaishnavi, D. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350364729

Parkinson's disease (PD) is a growing neurodegenerative disorder that exhibits abnormal shifts and a sort of added dispassionate exhibitions. Achieving an exact diagnosis of PD can explain the expected intimidating task on account of the correspondence of signs and symptoms, specifically in the beginning stages, to those of alternative healing environments or the open declining process. The main focus of this study is to improve the PD demonstrative process through the exercise of a convolutional neural network, Random Forest, and support vector Machine - all forms of Machine Learning proposed at the distinctive middle from two points things outside PD and those with the ailment. This method centers on recognizing departures in subjects' changes using illustration responsibilities. Furthermore, this research investigates the approximate influence of two illustration tasks, namely the cable dies and the spiral five of something, in the bias process. Demonstrating veracity of 93.5%, our convolutional classifier, prepared on images from the five-of-something illustration task and engaging improving methods, can serve as an unprejudiced method for critical betwixt PD cases and athletic individuals. Our sleek model has the potential to develop into an offline evident-occasion robotic diagnostic finish for sole-task requests, surely implementable in a dispassionate environment. © 2024 IEEE.

关键词： Convolutional neural networks

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smart Airbag Wearables Revolutionizing Fall Protection with IoT Integration 2

Smart Airbag Wearables Revolutionizing Fall Protection with ...

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： balasubramani, M. Kavinkumar, s. Karthik, P. sekar, K.M. Gowtham, b. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (数字)9798350368109

ISBN: (纸本)9798350368109

Internet of Things and smart airbag methodology together are enabling revolution in fall injury prevention. The device measures body temperature instantly and provides timely interfere. Temperature and other physiological parameters are monitored by embedded sensors and promptly analyzed using the IoT platform. When a fall is detected, the airbags are deployed quickly and the risk of injury is reduced, thanks to the fall detection feature. Alerts are quickly sent to individuals or emergency services via the IoT network. The partnership is set on enhancement of safety and delivery of value and quality within the partnership and is set on safety improvement;It also offers the highest guarantee of safety to people where previously they had been at risk of loss. © 2024 IEEE.

关键词： Physiological models

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Identifying Gestures through Convolutional Neural Networks: An Innovative Methodology 2

Identifying Gestures through Convolutional Neural Networks: ...

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Anbumani, P. Arun, L. Arunkumar, v. Anish, v. Gokula Hariharan, N. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (数字)9798350368109

ISBN: (纸本)9798350368109

Recognizing hand gestures holds significant importance in computer vision, influencing fields such as sign language interpretation, gaming, and human-computer interaction. While Convolutional Neural Networks (CNNs) have become a prominent solution for various computer vision tasks, including hand gesture recognition, our research diverges by proposing an alternative method. We introduce a novel approach to hand gesture recognition that employs a CNN architecture. Initial preprocessing enhances hand photo quality by refining borders and eliminating background noise. Following this, our CNN architecture, which includes multiple convolutional and fully connected layers, extracts unique features from hand images. Training on a substantial dataset and evaluating on a separate test set, our method surpasses alternative techniques in accuracy for hand gesture recognition. These results underscore the effectiveness of our approach and suggest its practical utility. Hand gestures, as a prevalent form of communication in modern society, hold significant potential for creating intuitive user interfaces across diverse applications. While previous approaches often struggled with reliable gesture classification across individuals, our proposed method, utilizing four CNNs, achieves real-time recognition of hand gestures. Achieving an average accuracy of 98.76% on a dataset covering nine hand motions, our CNN-based approach demonstrates promising results for real-world applications. © 2024 IEEE.

关键词： Convolutional neural networks

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Hue spectrum visualizer using python with OpenCv 2

Hue Spectrum visualizer using python with OpenCV

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Raajyavardhini, A. Gowthaman, T. Krishnamoorthy, R. Dhanush, s. Harish, s. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350368109

Color analysis is a significant source in many image processing processes consisting of automotive vehicle navigation, protest detection, traffic sign recognition, skin color analysis, and object tracking. The approach adopted in this study mainly relies on the ability to locate the color name right at the center of the camera frame and determine the objects of red, green, and blue colors using the bounding box property. by rating the amount of red, green and blue of each pixel's outfits, the colors of these pixel are revealed. Next, all objects of interest that fall within the video segment of interest are detected and located using rectangular boundary boxes based on the Hsv color model. The process used in this process entails the use of a dataset that has a tabular form with data on color names and its values to arrive at the best match. The values of Red, blue, and Green (RGb) as well as color names of each pixel are extracted, providing the means to track the three separate colors in the video stream. When a color is not detected in the reference data but observed in the real-time stream, a box surrounds the mentioned color: the color name is written above the box. It enhances the approaches to recognition of color and also provides significant improvements in the field of robotics. The application of these techniques generally involves the use of the OPENCv software library together with the PYTHON programming language. © 2024 IEEE.

关键词： Python

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AI-Driven Alert systems for an Intuitive Animal Monitoring system 4

AI-Driven Alert Systems for an Intuitive Animal Monitoring S...

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4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： Latha, P. Diana Inba Malar, Y. Hemavarthini, C.s. Manjuparkavi, v. sneha, s. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350364729

All animals that can sight, including humans, do so in a way that appears instinctive and natural. Creatures use their vision system early in life often even from birth to traverse their surroundings, recognize and communicate with other creatures, and learn about their surroundings. because of this, an animal's vision system is continuously being educated and modified to enable it to do a variety of activities. In humans, for instance, this system works by way of the optic nerve, which transmits light data from the eye to the brain for interpretation and processing. This sophisticated vision system enables us to focus on objects and see the world in three dimensions, all while being able to autonomously adjust to changing light conditions. It is possible to think of computer vision, digital image processing, and digital image analysis as a combination of phrases that are frequently used to refer to related operations. The main reason for this misconception is that they are related fields that arose with the advancement of digital picture capture. Thus, it's important to comprehend how these fields relate to one another, how a digital image is created, and how the various sensors that are available each best suited for a particular application differ. since the introduction of charge- coupled devices, which signaled the beginning of digital imaging, the field has developed very quickly. In this project, a camera that records the surroundings all day long will be used to periodically monitor the entire farm. We can identify when an animal is entering with the aid of a deep learning model, and then we play the right sounds to eject the animal. © 2024 IEEE.

关键词： CCD cameras

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AI Method for Improving Crop Yield Prediction Accuracy Using ANN

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computer systems science & engineering 2023年第10期47卷 153-170页

作者： T.sivaranjani s.P.vimal Department of Electrical and Electronics Engineering V.S.B College of Engineering Technical CampusCoimbatore642109India Department of Electronics and Communication Engineering Sri Ramakrishna Engineering CollegeCoimbatore641022India

Crop Yield Prediction(CYP)is critical to world food *** safety is a top priority for *** rely on reliable CYP to make import and export decisions that must be fulfilled before launching an agricultural *** Yield(CY)is a complex variable influenced by multiple factors,including genotype,environment,and their *** is a significant agrarian ***,CYP is the main task due to many composite factors,such as climatic conditions and soil *** Learning(ML)is a powerful tool for supporting CYP decisions,including decision support on which crops to grow in a specific ***,Artificial Neural Networks(ANN)are usually used to predict the behaviour of complex non-linear *** a result,this research paper attempts to determine the correlations between climatic variables,soil nutrients,and CYwith the available ***,threemethods,Levenberg-Marquardt(LM),bayesian regularisation(bR),and scaled conjugate gradient(sCG),are used to train the neural network(NN)model and then compared to determine prediction *** performance measures of the training,as declared above,such as Mean squared Error(MsE)and correlation coefficient(R),were determined to assess the ANN models that had been *** experimental study proves that LM training algorithms are better,while bR and sCG have minimal performance.

关键词： Crop prediction accuracy ANN precision agriculture crop yield

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Message authentication and wormhole detection mechanism in wireless sensor network

Message authentication and wormhole detection mechanism in w...

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International Conference on (IsCO) Intelligent systems and Control

作者： s. subha U.Gowri sankar Computer Science And Engineering V.S.B Engineering College Karur

One of the most effective way to prevent unauthorized and corrupted message being forwarded in wireless sensor network. but there is high computational and communication overhead in addition to lack of scalability and resilience to node compromise attacks. so to address these issues, a polynomial-based scheme was recently introduced. However, this scheme and its extensions all have the weakness of a built-in threshold determined by the degree of the polynomial. when the number of messages transmitted is larger than this threshold, the adversary can fully recover the polynomial. In the existing system, an unconditionally secure and efficient source anonymous message authentication (sAMA) scheme is presented which is based on the optimal modified Elgamal signature (MEs) scheme on elliptic curves. This MEs scheme is secure against adaptive chosen-message attacks in the random oracle model. This scheme enables the intermediate nodes to authenticate the message so that all corrupted message can be detected and dropped to conserve the sensor power. While achieving compromise resiliency, flexible-time authentication and source identity protection, this scheme does not have the threshold problem. While enabling intermediate nodes authentication, this scheme allows any node to transmit an unlimited number of messages without suffering the threshold problem. but by using this method the black hole and gray hole attacks are detected but wormhole attack is doesn't detect. because the wormhole attack is one of the harmful attacks which degrade the network performance. so, in the proposed system, one innovative technique is introduced which is called an efficient wormhole detection mechanism in the wireless sensor networks. In this method, considers the RTT between two successive nodes and those nodes' neighbor number which is needed to compare those values of other successive nodes. The identification of wormhole attacks is based on the two faces. The first consideration is that

关键词： Cryptography scalability Computational modeling Terminology

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An algorithm for heterogeneous wireless network connections for user preferences and services

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scientific Reports 2025年第1期15卷 1-15页

作者： Krishnan, s. Dinesh Daniel, A. Ayyasamy, s. balusamy, balamurugan selvarajan, shitharth Al-shehari, Taher Alsadhan, Nasser A. B V Raju Institute of Technology Telangana Narsapur India Amity University Madhya Pradesh Gwalior India Vellore Institute of Technology Vellore Campus Tamil Nadu Vellore India Associate Dean-Student Engagement Shiv Nadar University Gautam Buddha Nagar India Department of Computer Science Kebri Dehar University Kebri Dehar 250 Ethiopia Computer Skills Department of Self-Development Skill Common First Year Deanship King Saud University Riyadh 11362 Saudi Arabia Computer Science Department College of Computer and Information Sciences King Saud University Riyadh 12372 Saudi Arabia School of Built Environment Engineering and Computing Leeds Beckett University Leeds United Kingdom Department of Computer Science and Engineering Chennai Institute of Technology Chennai India Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura 140401 India

Heterogeneous wireless networks (HWNs) present a challenge in selecting the optimal network for user devices due to the overlapping availability of multiple networks. In order to help users choose the best HWN connection, this research is trying to build a decision-making framework that takes user preferences and network performance characteristics into account. Using a multi-attribute decision-making (MADM) method that incorporates fuzzy logic and the Fuzzy Analytic Hierarchy Process (FAHP), our goal is to improve the decision-making process for network selection. The suggested system takes into account a number of network metrics, including latency, jitter, bandwidth, and cost, and uses user preferences to determine the relative importance of each to guarantee a tailored and adaptable recommendation. Our results demonstrate that the algorithm greatly enhances the efficiency of network selection and the level of user happiness, with UMTs being the best option for conversational services, WiMAX being the best for streaming, and LTE being the best for interactive services. Through the incorporation of user-centric decision-making into the network selection process, this research enhances adaptive wireless communication systems, leading to better user experience and network efficiency. © The Author(s) 2025.

关键词： Fuzzy analysis hierarchy process Fuzzy logic Heterogeneous wireless networks Machine learning Multi-attribute decision-making approach

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IoT based-Enhancing banking security with Multi-CNN Face Recognition and sMs verification 2

IoT Based-Enhancing Banking Security with Multi-CNN Face Rec...

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Geetha, s. Nivetha, s. Preethi, s. Priyanka, R. Priyanka, v. V.S.B. Engineering College Department of Computer Science and Engineering Tamil Nadu Karur India

ISBN: (纸本)9798350368109

Integrating facial verification with an sMs system and IoT (Internet of Things) for accessing bank lockers can improve security and convenience. banking locker systems must be extremely secure in order to protect customer's expensive items. Traditional access methods sometimes rely on keys or passcodes, which are prone to theft or unauthorized usage. To address these problems, this article introduces an enhanced security feature using the banking locker system which incorporates such sophisticated features as customer registration or a procedure when a customer is captivated by facial recognition. The data is also collected, processed, and kept in a format that cannot be easily accessible by other people. If the customer wants to be served they have to go through a certain order when needing to access their locker conduct facial verification using the developed biometric data decide to select an IoT device to be integrated with the locker system to induce the unlocking process, which is an important step mobile number to be reached for updating through sMs is as follows. This is the customer's registered mobile phone number which, when used with the above requests, would yield information relating to the attempted access. After the validation stage, the locker is opened to allow the personnel measures of safety to be sensitive, and fundamental measures are applied when hackers are prevented from accessing the account in the face recognition system whenever they are not supposed to the security and safety of messages are kept protected and encrypted, and any attempts at verification lead to security alerts on the network system leading to suspension of their account or provision of certain procedures. © 2024 IEEE.

关键词： sales

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UX design to promote undergraduate projects to products: Case study 4

UX design to promote undergraduate projects to products: Cas...

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4th IEEE International Conference on MOOCs, Innovation and Technology in Education, MITE 2016

作者： Patil, Mahesh s. Desai, Padmashree vijayalakshmi, M. Raikar, Meenaxi M. battur, shivalingappa Parikshit, H. Joshi, G.H. Department of Computer Science and Engineering B v B College of Engineering and Technology Hubballi India

ISBN: (纸本)9781509010622

User experience design is all about making a product by understanding its users and enables user to use a product easily. UX design is part of current industry standards which can be started along with requirement phase. Undergraduate students build products in project courses. such courses include software Life Cycle phases like Requirement gathering/analysis, Design, Implementation and Testing but not UX design. Thus best of the project fail to generate a product that is usable. This paper presents a case study of minor project course which incorporated UX design in building mobile apps. UX is new technology and little known to instructors at colleges. so students were instructed to learn UX from MOOC on 'UX Design for Mobile Developer's', hosted by Udacity. Also, a workshop by industry expert in UX was conducted. The UX activities specified by MOOC were included as part course assessments. Through the UX design, students identified 3 to 4 user/mobile device requirements and incorporated them in the implementation. The weightage of marks for UX design is 24%, which increased Design phase weightage to 30%. Finally students were able to launch product, 'KLE Tech sTUDio' mobile-app. Attainment of design phase, UX, activities specified by MOOC, implementations are 7.2, 7.82, 6.8 and 7.5 respectively on the scale of 10. Further UX design can be included as part of software engineering course. Also, UX design can be tailored to any project course depending on the product being developed. © 2016 IEEE.

关键词： software testing

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