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检索条件"机构=School of Computer Science Engineering and Information Systems Vellore Institute of Technology"

共 31076 条记录，以下是4861-4870 订阅

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Efficient Layouts of Complete t-Partite and Complete Networks into 3-Ary n-Cubes for Optimized Parallel Processing in Multiprocessing systems

Efficient Layouts of Complete t-Partite and Complete Network...

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IEEE International Conference on Signal Processing, Informatics, Communication and Energy systems (SPICES)

作者： S Rajeshwari M Rajesh C Sowmiya Department of Mathematics Easwari Engineering College Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (数字)9798350376135

ISBN: (纸本)9798350376142

Embedding problems has received a lot of attention in the last decades by various research dealt with many inter-connection networks. Through embedding the existing parallel algorithm of an interconnection network can be used for the embedded network, thus it plays a vital role in manipulating the parallel algorithms of interconnection network in multiprocessing systems. A variation of the k -ary n-cube, notable for its adaptive network structure created to provide efficient parallel processing on multicomputers, is the 3-ary n-cube. In this study, complete t-partite graphs and complete graphs are embedded into 3-ary n-cubes with the least wirelengths.

关键词： Wiring Program processors Multiprocessor interconnection Scalability Layout Signal processing Throughput SPICE Parallel algorithms Multiprocessing systems

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Plant Disease Detection and Classification Using Transfer Learning

Plant Disease Detection and Classification Using Transfer Le...

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2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Karthigaiveni, S. Madhubala, C. Avinash, G. Saranya, E. Rohini, P. Yogapriya, G. Chennai Institute of Technology Department of Electronics and Communication Engineering Chennai India Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Information Technology Avadi Tamilnadu Chennai India School of Environment and Architecture Design Srm Institute of Science and Technology Tamilnadu Chennai India Sri Eshwar College of Engineering Department of Computer Science Engineering Chennai India Saranathan College of Engineering Department of Computer Science and Engineering Tamilnadu Trichy India Chettinad School of Architecture Chettinad Academy of Research and Education Tamilnadu Chennai India

ISBN: (纸本)9798331543617

Agriculture is a fundamental component of human civilization. It contributes to the economy while also providing sustenance. Plant foliage or crops are susceptible to many illnesses during agricultural agriculture. The illnesses impede the development of their respective species. Timely and accurate identification and categorization of illnesses may mitigate the risk of further harm to the plants. The identification and categorization of these disorders have emerged as significant challenges. The conventional methods used by farmers to forecast and identify plant leaf diseases may be tedious and inaccurate. Challenges may occur while endeavoring to manually forecast illness kinds. The failure to promptly identify and categorize plant diseases may lead to the devastation of crops, causing a substantial reduction in yield. Farmers using automated image processing techniques in their fields may mitigate losses and enhance productivity. This study proposes using a deep learning framework utilizing the latest convolutional neural network model EfficientNet to identify tomato illnesses based on 18,161 plain and segmented photos of tomato leaves. The efficacy of two segmentation theories, namely U-net and Modified U-net, for leaf segmentation is shown. The proposed methodology for plant disease identification is straightforward and computationally efficient, necessitating less time for predictions compared to previous deep learning methodologies. This document presents the computed accuracies for several plant and leaf diseases. © 2024 IEEE.

关键词： Convolutional neural networks

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Drought prediction using artificial neural network 2

Drought prediction using artificial neural network

引用

2nd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2022

作者： Metta, Pardha Saradhi Chintamaneni, Anish Kumar, Ashish Yadav, Jatin Kumar, Vishesh Bhaskar, Bharath Vellore Institute of Technology Department of Computer Science and Engineering Tamil Nadu Vellore India Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Tamil Nadu Coimbatore India Netaji Subhas University of Technology Dwarka Department of Information Technology Delhi India Karunya Institute of Technology and Sciences Department of Instrumentation and Technology Tamil Nadu Coimbatore India SRM Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Kattankulathur India Pes University Department of Electronics and Communications Karnataka Bangalore India

ISBN: (纸本)9781665437899

Drought has been one of the most frightening natural calamity that is being faced by the humans., and it is generally faced by the farmers all around the world. It can occur anywhere in the world and is also known as one of the slow disaster as it stays for a very longer time period and maybe even more if it wants to be harsher. Drought not only impacts the human life but also the agriculture, world economies and energy that had been infiltrated by the farmers. Everything goes on stakes during this calamity and the basic needs such as food are not easy to get during these times and the inflammation is at peak due to supply and demand instability. There are many ways which can be done to avoid the drought, which include drip irrigation to save water during the times of drought, rainwater harvesting can also be a saviour, crop engineering, desalination of water and many more things. The main solution for this would be to analyse the weather and the future outcomes of it which would help in preparing for the worse situation and also the soil prediction can help a lot when it comes to predicting this situation. The paper aims to take the data of weather and soil together to predict how droughts can be avoided. Deep learning techniques will help to get a great idea if the drought is going to happen or not. © 2022 IEEE.

关键词： Drought

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IoT based Smart Shoes for Blind people 3

IoT based Smart Shoes for Blind people

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3rd International Conference on Electronics and Sustainable Communication systems, ICESC 2022

作者： Darney, P. Ebby A.E., Muthu K., Jeyakumar R.S., Krishnan K.L., Narayanan Y.H., Robinson Rajarajeswari College of Engineering Department of Electrical and Electronics Engineering Bangalore India Scad College of Engineering and Technology Department of Computer Science and Engineering Tirunelveli India Scad College of Engineering and Technology Department of Mechanical Engineering Tirunelveli India Scad College of Engineering and Technology Department of Electronics & Communication Engineering Tirunelveli India Vellore Institute of Technology School of Information Technology and Engineering Tamilnadu Vellore India

ISBN: (数字)9781665479714

ISBN: (纸本)9781665479714

India stands third among the world's blind people population. They cannot see what is happening around them. They are facing numerous problems while moving from one place to another. Due to loss of eyesight, they hurt themselves while travelling to many places. Sometimes they even find it difficult to trace the route back to their home. Hence a novel system is required to facilitate them while travelling and to help them to find their way to home when they lost their route to home. To deal with this, the proposed study has designed a novel system called IoT based Smart Shoes for blind people. This can solve aforementioned problems and facilitate blind people to a huge extent. © 2022 IEEE.

关键词： Communication systems Sociology Blindness Footwear Statistics

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Model of Visualization and Analytics for Open Data (Case: Election Voters & Kids Disability Category) 1

Model of Visualization and Analytics for Open Data (Case: El...

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1st International Conference in Advanced Innovation on Smart City, ICAISC 2023

作者： Wibowo, Ripto Mukti Fakieh, Bahjat Ramzan, Muhammad Sher Alzahrani, Ahmed Saeed Siddiqui, Muazzam Alzahrani, Bander King Abdulaziz University Faculty of Computing and Information Technology Department of Information Systems Saudi Arabia King Abdulaziz University Faculty of Computing and Information Technology Department of Computer Science Saudi Arabia Indiana University Luddy School of Informatics Computing and Engineering Bloomington United States

ISBN: (纸本)9781665472753

Several regional head elections had to be postponed due to the pandemic, including in Indonesia because of the COVID-19 pandemic. Several big cities in Indonesia are of concern because of their large population and GDP. This study conducts analysis and testing of datasets taken from Open Data in a city in Indonesia. In addition to conducting research on regional head elections, we also present information on voters from the category of kids with disabilities. The steps used in this research are using regional mapping data of the city of Surabaya in the Election of the Regional Head. Download the data or dataset for the Regional Head Election ampersand Categories of kids with disabilities. Based on the dataset voters from the category of children with disabilities are more than 5 *** this research, we use Python to process our datasets & Big Data technology. Data cleaning or cleansing, Exploratory Data Analysis, and Empirical Cumulative Distribution Functions (ECDF) in python are also needed. Result from ECDF chart with steady increase (increment of 0.1). The highest variance value is in Electoral District 5 = 6.090 and the lowest value is in Electoral District 4 = 0.90. The result of Open Data is graphical data visualization and candidate scores to help as an alternative for the 2024 Regional Head Election and the Category of kids with disabilities. © 2023 IEEE.

关键词： Open Data

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Proposed Framework for Modifications to Artificial Intelligence/Machine Learning (Ai/Ml)-Based Software as A Medical Device (SAMD) 7

Proposed Framework for Modifications to Artificial Intellige...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Shrivastava, Anurag Jain, Upma Al-Farouni, Mohammed Kumar, Yogendra Anandhi, R.J. Bhavana, Munugapati Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Tamilnadu Chennai India Graphic Era Deemed to be University Department of Computer Science & Engineering Dehradun India The Islamic university College of technical engineering Department of computers Techniques engineering Najaf Iraq Gla University Department of Electrical Engineering Mathura India New Horizon College of Engineering Department of Information Science Engineering Bangalore India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India

ISBN: (纸本)9798350350067

The rapid adoption of software as a medical device (SAMD) driven by artificial intelligence and machine learning has brought about a fundamental shift in the medical industry. This shift has the potential to greatly improve clinical outcomes and the quality of care provided to patients. This shift has been responsible for a number of key achievements made in recent times. When seen in this context, the proposed legal framework for revisions to the AI/ML-SAMD appears as an essential response to the malleability of these technologies. To successfully navigate the tough process of modifying AI/ML-SAMD with the assistance of this framework. It does this by taking into consideration the need for rapid regulatory scrutiny and making an attempt to combine the promotion of innovation with the simultaneous preservation of patient safety. In other words, it ensures that patient safety is protected while also encouraging innovation. This abstract provides a summary of the fundamental components of the framework, as well as a discussion of the significance of those components with regard to fostering the development of moral AI/ML-SAMD within the context of the healthcare ecosystem. The healthcare sector is undergoing a change as a direct result of artificial intelligence and machine learning, which are improving patient outcomes, diagnostic accuracy, and treatment options. The research emphasizes the significance of specific AI and ML applications as well as the sector's embrace of this paradigm-shifting technology. In addition, the regulatory framework that has been presented is an important step towards guaranteeing the safe use of AI and ML in the medical field. © 2024 IEEE.

关键词： Artificial Intelligence Compliance Guidelines Healthcare Innovation Machine Learning Modifications Patient Safety Regulatory Framework Software as a Medical Device

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Estimating Challenges Of Atificial Inteligence (ML): information Extraction Perspective

Estimating Challenges Of Atificial Inteligence (ML): Informa...

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2023 International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023

作者： Siddiqui, Ahmad Tasnim Goyal, Nidhi Ahmed, Mohammad Nadeem Sandip University School of Computer Science & Engineering Maharashtra Nashik India Amity University Lucknow Campus Amity Institute of Information Technology India King Khalid University Department of Computer Science Abha61421 Saudi Arabia

ISBN: (纸本)9798350317060

The advancement of 'quantifiable artificial intelligence (ML)' ways of thinking served to re-advocate the field following the past 'Man-made awareness (computerized reasoning) winter.' The new and impending progressions in computer based intelligence and AI are the essential focal point of this short piece on mechanical turn of events. A growing interest in artificial intelligence (AI) is being expressed by academics as well as the general public. This interest includes gains that can be measured from massive amounts of data. Considering present day speculations, the basic and rotational seasons of mirrored information are making at a bewildering rate. The production of a bound together European man-made understanding exploration place has been moved by two or three social events, and the European Connection has essentially expanded supporting for PC based information research. schools are coordinating recreated insight and artificial intelligence into their instructive projects and long stretch goals. Even though the current methods appear to be working well, there are still significant issues that need to be resolved: Because of their indistinctness, the models that produce the best outcomes are alluded to as 'secret components.' It is endeavoring to utilize such 'black box' headway thinking about open and by and large in security, confirmation, control, and security. This study analyzed discretionary data assortment techniques for managing top notch research considering the examination objective. These headways offer stimulating, cutting edge deals with any consequences regarding testing genuine issues for planners and producers. Obviously, man-made scholarly ability (repeated understanding) has a huge number of purposes. The accessibility of various speculations, calculations, and techniques makes it conceivable. Choosing the ideal artificial intelligence technique for the fitting assembling or designing strategy and settings is testing. Furthermore, significant

关键词： Human computer interaction

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Bridging Automated Reasoning and Machine Learning for information Analysis 2

Bridging Automated Reasoning and Machine Learning for Inform...

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2nd IEEE International Conference on Futuristic Technologies, INCOFT 2023

作者： Joshi, Sarita Murugan, R. Balaji, N.V. Chandrakala, P. Deshmukh, Gopal B. Mathur, Mala Maharishi School of Business Management Maharishi University of Information Technology Uttar Pradesh India Bangalore Department of Computer Science and Information Technology Karnataka India Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electrical and Electronics Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Vivekananda Global University Department of Civil Engineering Jaipur India

ISBN: (纸本)9798350308846

Recent advances in automated reasoning and system studying have appreciably impacted the automation of statistics evaluation. These technologies facilitate understanding the increasingly more complicated volumes of facts in a ramification of approaches. Automatic reasoning helps decide valid solutions based on structured good judgment, while machines can pick out patterns and developments in massive datasets. Bridging those two technologies improves accuracy and efficiency in automated facts evaluation. This paper will overview present-day research on bridging automated reasoning and device-gaining knowledge for such purposes and gift novel approaches to combining the two technologies for more effective data evaluation. Discussion subjects will encompass integrating neural networks and reasoning engines, methods for addressing records incompleteness and uncertainty, and enhancement of reasoning-driven context-conscious systems. Furthermore, the paper will discover the capacity benefits that can be performed via leveraging the strengths of each automated reasoning and gadget gaining knowledge of to optimize answers for a selection of software scenarios. © 2023 IEEE.

关键词： Gaining Optimize Reasoning Selection Uncertainty

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Automatic Adjustment of HPA Parameters and Attack Prevention in Kubernetes Using Random Forests 24

Automatic Adjustment of HPA Parameters and Attack Prevention...

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9th International Conference on Cloud Computing and Internet of Things, CCIOT 2024

作者： Chan, Huah Yong Zhou, Hanlin Ni, Jingfei Wu, Mengchun Deng, Qing School of Computer Sciences Universiti Sains Malaysia Pulau Pinang Malaysia Xiamen Institute of Software Technology Xiamen China Department of Manzhouli Customs Manzhouli China College of Information Science and Engineering Jimei University Xiamen China

ISBN: (纸本)9798400717161

In this paper, HTTP status codes are used as custom metrics within the HPA as the experimental scenario. By integrating the Random Forest classification algorithm from machine learning, attacks are assessed and predicted, dynamically adjusting the maximum pod parameter in the HPA to manage attack traffic. This approach enables the adjustment of HPA parameters using machine learning scripts in targeted attack scenarios while effectively managing attack traffic. All access from attacking IPs is redirected to honeypot pods, achieving a lower incidence of 5XX status codes through HPA pod adjustments under high load conditions. This method also ensures effective isolation of attack traffic, preventing excessive HPA expansion due to attacks. Additionally, experiments conducted under various conditions demonstrate the importance of setting appropriate thresholds for HPA adjustments. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Random forests

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Collaborative MAC Protocol Design for Enhanced Network Lifetime in Mobile Ad Hoc Networks 6

Collaborative MAC Protocol Design for Enhanced Network Lifet...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Verma, Sanjeev Kumar Singh, Digvijay Raghav, Yogita Yashveer Hemelatha, S. Kannimuthu, S. Banchhor, Chitrakant O. Invertis University Department of Applied Sciences Bareilly India School of Engineering and Computer Dev Bhoomi Uttarakhand University Uttarakhand India K. R. Mangalam University Department of Computer Science & Engineering Gurugram India Karpagam College of Engineering Department of Computer Science Engineering Coimbatore India Karpagam College of Engineering Department of Information Technology Coimbatore India Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9798350304480

Cdma has a huge opportunity to boost the transmission within mobile devices by using surrounding stations to description method that was overheard in order to obtain place a priority. An effective Competitive Middle Authorization (Colloidal carrier) strategy is required to handle the complex data transmission dynamics brought on by transmitting and to capitalize on the advantages of such collaboration. In this article, we present the De las technique, a unique inter Distributing Fuel Position CMAC etiquette for Cellular Advertisements (MANETs). Enhancing MANET functionality in terms of networking longevity and clean energy is the design goal of Donde. The electricity generation of the receive amplification and transmission hardware is taken into consideration in this article using an actual energy usage model. The optimal relay is chosen using a dispersed power best relay technique known that considers young and motivated individual and gps data. Additionally, a cutting-edge benefit for the organization vector configuration is offered to adapt to the changing transmitted strength of the supply and relayed stations with the aim of increasing routing. By using a thorough dynamic simulation, we demonstrate how the planned De su significantly increases networks lifespan in a variety of situations, including those with high electrical energy demand. © 2023 IEEE.

关键词： CC CD-MAC CMAC DCF GPS and PDA MAC Protocol Designs MANET Utility-Based Best Relay Selection WMN

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