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检索条件"机构=Institute of Engineering and Computer Systems"

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Machine Learning based Crop Yield Prediction in Agriculture: A Survey in Vellore

Machine Learning based Crop Yield Prediction in Agriculture:...

引用

2023 Innovations in Power and Advanced Computing Technologies, i-PACT 2023

作者： Durai Raj Vincent, P.M. Elavarasan, Dhivya School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350325188

Agriculture is the backbone of any country as it feeds its population. Since the global population keeps increasing, it is necessary to give utmost importance to the field of agriculture. State-of-the-art techniques should be introduced to boost agricultural production multifold. On the other hand, machine learning brings new life to the computing field, which would solve many complex problems in every other field. Machine learning in agriculture based crop yield prediction is the focus of this paper, where significant works are to be explored in this work to understand the commendable outcomes. For this survey, the research articles that have been published in the last five years where vellore a southern Indian district based works are selected and the various aspects of the underlying research and its applications are listed as the outcome of this for the benefit of future budding researchers who would be working in this field of agriculture. © 2023 IEEE.

关键词： climatic conditions crop yield prediction Machine Learning rainfall data Reinforcement Learning

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Privacy-aware Deep Learning based Localization of Spectrum Violators 20

Privacy-aware Deep Learning based Localization of Spectrum V...

引用

20th IEEE International Conference on Mobile Ad Hoc and Smart systems, MASS 2023

作者： Ezemaduka, Chibuikem Abouzeid, Alhussein A. Rensselaer Polytechnic Institute Electrical Computer and Systems Engineering TroyNY United States

ISBN: (纸本)9798350324334

In spectrum sharing environments such as the Citizens Broadband Radio Service (CBRS), spectrum "violators"are secondary users that transmit without permission from the spectrum manager and could therefore cause harmful interference to the primary user, such as a radar, through their illegal transmissions. In such systems, it is desirable to detect the geographic locations of such violators without revealing the location, i.e. privacy, of the primary user. In this paper we propose a privacy-aware violator localization algorithm based on deep learning. In this approach, data collected at sensors are processed in a privacy-aware manner using a Generative Adversarial Network (GAN) based algorithm, and relayed to the centralized spectrum manager, e.g., the Spectrum Access System (SAS). The spectrum manager then detects and geographically localizes the violators based on the received data, using an encoder-decoder Convolutional Neural Network (CNN). We evaluate the proposed solution for a CBRS setting and show that it is able to achieve localization error of only 14 meters when using the GAN processed data for localization. Results also show that it achieves reconstruction error of at most 20% at very low Signal-to-Noise (SNR) ratio of 10 dB at a sensor. © 2023 IEEE.

关键词： Deep learning

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Agile Framework for Systematic Reviews of Literature in Formative Research 13

Agile Framework for Systematic Reviews of Literature in Form...

引用

13th International Conference on Virtual Campus, JICV 2023

作者： Ocampo-Pazos, Willian Javier Gonzalez-Gonzalez, Carina Soledad University of La Laguna Doctorate in Industrial Computer and Enviromental Engineering Systems Engineering and Automatic Tenerife Spain Women Studies Institute University of La Laguna Department of Computer Engineering and Systems Tenerife Spain

ISBN: (纸本)9798350343441

Currently, it is important to note that formative research can be used as a strategy in the teaching process [1], and it is possible to avoid 'the parceling of content into minimum units [1]' in class subjects. In parallel, systematic literature reviews [2] can be integrated into the teaching-learning process in all areas of knowledge, such as engineering, education [2] and others, combining them as a pedagogical strategy [1] in the learning process formative research in the classroom [1]. Also, it is necessary to highlight that the agile framework was applied, which is composed of 3 main events [3], [4]: planning, development and review, in a case study to elaborate the state of the art on topics related to the 'disorder of the autism spectrum (ASD)' and 'machine learning' (ML). © 2023 IEEE.

关键词： Learning systems

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MuSe4ASD - An Interactive Music Station for Children with ASD 6

MuSe4ASD - An Interactive Music Station for Children with AS...

引用

6th Experiment at International Conference, exp.at 2023

作者： Lagos, Beatriz Menezes, Paulo University of Coimbra Institute of Systems and Robotics Electrical and Computer Engineering Department Coimbra Portugal

ISBN: (纸本)9798350314403

This article explores the topic involving children with autism, referencing what this condition is about, as well as the hypotheses for approaching the problem based on the literature reviewed. The proposed approach involves the creation of an adequate space with an immersive interactive system based on musical stimuli, and physical exercise to improve their communication, memory, visual and motor capabilities, and eventually potentiate the development of artistic skills. The development of this interactive system includes the development of an avatar that will be animated using Motion Capture technology, so it can interact with the child and accompany him/her while doing the exercises with fluid movements. © 2023 IEEE.

关键词： Music

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Revolutionizing Malware Detection: Feature-Based Approach for Targeting Diverse Malware Categories 56

Revolutionizing Malware Detection: Feature-Based Approach fo...

引用

56th International Carnahan Conference on Security Technology, ICCST 2023

作者： Jain, Sanyam Thaseen, Sumaiya School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350315875

In today's digital landscape, the task of identifying various types of malicious files has become progressively challenging. Modern malware exhibits increasing sophistication, often evading conventional anti-malware solutions. The scarcity of data on distinct and novel malware strains further complicates effective detection. In response, this research presents an innovative approach to malware detection, specifically targeting multiple distinct categories of malicious software. In the initial stage, Principal Component Analysis (PCA) is performed and achieved a remarkable accuracy rate of 95.39%. Our methodology revolves around leveraging features commonly accessible from user-uploaded files, aligning with the contextual behavior of typical users seeking to identify malignancy. This underscores the efficacy of the unique feature-based detection strategy and its potential to enhance contemporary malware identification methodologies. The outcomes achieved attest to the significance of addressing emerging malware threats through inventive analytical paradigms. © 2023 IEEE.

关键词： Malware

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A Web-Based Vaccine Distribution System for Covid-19 Using Vaxallot 4th

A Web-Based Vaccine Distribution System for Covid-19 Using V...

引用

4th EAI International Conference on Cognitive Computing and Cyber Physical systems, IC4S 2023

作者： Valarmathi, B. Srinivasa Gupta, N. Prakash, G. BarathyKolappan, A. Padmavathy, N. Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore India Department of Manufacturing Engineering School of Mechanical Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Database Systems School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Systems Engineer Tata Consultancy Services Tamil Nadu Chennai India Department of Electronics and Communication Engineering Vishnu Institute of Technology Andhra Pradesh Bhimavaram India

ISBN: (纸本)9783031488900

Vaxallot seeks to implement a system to distribute vaccines across high-risk groups accounting for various parameters and prove to be superior to what conventional systems are capable of today. It is a Python flask-based tool backed by infrastructure and data resources from the Covid India central repository;all it needs is a single channel input and a single parameter of the value produced, and the algorithm will take care of the rest. Since it’s Python-based and has an active integration with google sheets, live value updating could be possible for the real-time output of the distribution. The novelty of the proposed mechanism is the unique priority index, a score that accounts for an array of factors associated with the pandemic and is computed for regions in question here;this makes way for better distribution of vaccines. The application has an exclusive segment centered on handling excess units, if any. Moreover, since the application is developed to suit the needs of dynamic demographics, any region can roll out this application for purposes they desire to serve the masses. Since it isn’t bound by a coronavirus, it can be used by the healthcare industry as they deem fit. © 2024, ICST institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Coronavirus

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TOPMG: Trust-Based Crowdsourcing through Multilateral Bargaining Game Theory

TOPMG: Trust-Based Crowdsourcing through Multilateral Bargai...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Charatsaris, Panagiotis Adesokan, Adedamola Rahman, Aisha B Tsiropoulou, Eirini Eleni Papavassiliou, Symeon National Technical University of Athens Institute of Communication and Computer Systems School of Electrical and Computer Engineering Athens Greece University of New Mexico Dept. of Electrical and Computer Engineering AlbuquerqueNM United States

ISBN: (纸本)9798350351255

Crowdsourcing plays a critical role in modern information gathering and task execution, yet it faces challenges regarding the task selection and equitable monetary incentives distribution. In this paper, we introduce the TOPMG framework, which addresses these challenges by enabling the workers to select tasks based on their historically experienced monetary incentives and the platforms' trustworthiness. Specifically, the TOPMG framework utilizes a reinforcement learning approach based on the principles of Optimistic Q-learning with Upper Confidence Bound (OQ-UCB) algorithm, guiding the platform selection process by considering the workers' monetary incentives, profit, and the platforms' trustworthiness. Also, the proposed framework introduces a multilateral bargaining game to allocate the platforms' monetary incentives to the workers by prioritizing their information contribution, fairness, and the platforms' reputation. Simulation results demonstrate TOPMG's operational dynamics, scalability, and efficacy, as well as its superiority over existing methodologies. © 2024 IEEE.

关键词： Reinforcement learning

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Exploring Player's Body as a Game Controller for Fitness Activity Promotion 6

Exploring Player's Body as a Game Controller for Fitness Act...

引用

6th Experiment at International Conference, exp.at 2023

作者： Simoes, Diogo Menezes, Paulo University of Coimbra Institute of Systems and Robotics Electrical and Computer Engineering Department Coimbra Portugal

ISBN: (纸本)9798350314403

In recent years, there has been a tendency for people to resort to a more sedentary lifestyle, which has only been aggravated by the COVID-19 pandemic and the evermore common remote work policies. This lack of physical activity brings negative health outcomes and can generally be difficult to overcome due to how challenging it can be for a person to find the motivation to adopt a more physically active routine. To address this issue, we propose the use of serious games as an engaging, fun, and highly motivational tool that can aid people in their quest for a healthier lifestyle. We focus on three problem areas: motor control improvement and rehabilitation, post-stroke rehabilitation, and physical activity for general health. There exist multiple solutions for these problems which often require specific equipment that may not be available to the common user. Therefore, we propose a different approach requiring solely a laptop equipped with a camera, thus making it more practical and accessible to the wider public. © 2023 IEEE.

关键词： Serious games

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A Review of Modern Authentication Methods in Digital systems

A Review of Modern Authentication Methods in Digital Systems

引用

2023 Annual International Conference on Emerging Research Areas: International Conference on Intelligent systems, AICERA/ICIS 2023

作者： Midhuna Jyothi, R. Jeyanthi, N. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350303452

In today's world, the traditional way of password based authentication is having limitations in addressing the security concerns of the digital users. There is a strong movement in favour of passwordless authentication to secure our cyber identities and digital assets. In the recent years, a lot of research outputs have been published in the field of authentication with techniques like multifactor authentication, passwordless authentication, adaptive authentication and continuous authentication. Not only the user, but also the device, the application etc. must be authenticated to access the resources, facilities and services. Even though the passwords face some serious security issues, they enjoy considerable user acceptance and hence some schemes termed as semi-passwordless authentication are also prevalent. This paper goes through existing authentication schemes, their security issues, attacks and the next step ahead. © 2023 IEEE.

关键词： Authentication

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TRUSTCACHE: Trust-based Content Caching in Information-Centric Networks

TRUSTCACHE: Trust-based Content Caching in Information-Centr...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Tsikteris, Sean Rahman, Aisha B. Siraj, Md Sadman Charatsaris, Panagiotis Tsiropoulou, Eirini Eleni Papavassiliou, Symeon National Technical University of Athens Institute of Communication and Computer Systems School of Electrical and Computer Engineering Athens Greece University of New Mexico Dept. of Electrical and Computer Engineering AlbuquerqueNM United States

ISBN: (纸本)9798350351255

The Information-Centric Networking (ICN) paradigm has reshaped the modern network architectures and promises efficient content delivery to the end-users. This paper introduces TRUSTCACHE, a novel framework enabling the content caching within ICNs and focusing on the trust-based ICN selection and optimal cache memory allocation to the Content Providers (CPs). The TRUSTCACHE framework incorporates the Optimistic Q-learning with Upper Confidence Bound reinforcement learning algorithm that enables the CPs to autonomously select ICNs based on their cache memory availability and trust levels. Also, TRUSTCACHE enables the CPs to jointly consider the reliability of the ICNs and their cache memory availability by integrating a novel trust model. Furthermore, TRUSTCACHE leverages the multilateral bargaining principles in order to ensure the optimal cache memory allocation among the CPs, in terms of aligning with their profit margin characteristics. Simulation-based experiments validate TRUSTCACHE's operational efficiency across diverse CP profit margin profiles and highlight its superiority over alternative models lacking trust-based ICN selection or employing proportional fairness strategies for cache memory allocation. © 2024 IEEE.

关键词： Reinforcement learning

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