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2023 Intelligent Com.uting and Control for engineering and Business System., ICCEBS 2023

作者： Rajesh, G. Kalaivani, K. Priya Hem.latha, D. Prabhu, V. Siva Ram. Lingham. N. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India Jeppiaar Engineering College Department of Computer Science and Engineering Chennai India R.M.K Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350394580

Social networking sites attract several users from.varied parts around the world. Som. of the popular sites containing a huge volum. of users are Twitter, Facebook, and so on. All these sites poses a significant im.act am.ng its users and som.tim.s undesirable for a standard of living. Considering the huge num.er of users, these online platform. are targeted by the spam.ers as a threat to the user's privacy as well as a harm.ul effect to the site itself. One am.ng those sites is the Twitter, which in short tim. has attracted huge am.unt of users and in turn has lead forward to itself to the online spam.ers. These spam.ers act as authorized users and send fake users. Consequently, Twitter has becom. a typical analysis space in today's online social networks (OSN). In addition, a classified taxonom. of the Twitter spam.detection m.vem.nt is presented, categorizing the techniques supported in their detection: (i) fake content, (ii) spam.ed computer addresses, (iii) The bestowed options, structure options, and tim. options or inform.tion in the social m.dia platform. Those inform.tion m.st of the tim. are found to be m.sleading or otherwise m.y affect the sentim.ntal behavior of other valid users also. In this way, harm.ul content is widely spread, techniques are com.ared with m.ny supported options, such as user settings content settings, the diagram.triggers others to send unwanted tweets or m.sidentify other valid users am.ng the network platform. and som.tim.s even m.kes users be. They needed to be m.re effectively provided with resources. To protect the users from.this kind of spam.ers, recently, a m.thodology has used to detect and identify. © 2023 IEEE.

关键词： Client Side Error Detection Fake Users Online Social Networks Server Side Spam.Detection Trending Topics Twitter

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Enhancing Food Supply Chain Transparency and Agricultural Practices through Blockchain technology 5

Enhancing Food Supply Chain Transparency and Agricultural Pr...

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5th IEEE Global Conference for Advancem.nt in technology, GCAT 2024

作者： Dinesh Kum.r, K. Vennila, G. m.noj Kum.r, D.S. Jasm.ne, J. Jeno Govindharaj, I. Balam.rugan, S. Vel Tech University Department of Computer Science and Engineering Chennai India Mohan Babu University Department of Aiml Chennai India Chennai India R.M.K Engineering College Department of Computer Science and Engineering Chennai India School of Computing and It Bengaluru India

ISBN: (数字)9798350376685

ISBN: (纸本)9798350376685

Blockchain technology em.rged to be one of the sm.rt solutions to ease the functionality of m.ny real tim. applications due to its decentralized nature, high security and distributed decentralized ledger. m.ny people have started questioning about the production process of food product that will ultim.tely be sold at m.rket and retail shops. Blockchain provides viable solution to track the com.lete process of crop production from.harvesting to food products. Therefore, agro business are increasingly searching for supply chain m.nagem.nt application that m.y help to im.rove the standard of safe food handling, quality and traceability through the agricultural supply chains. Im.lem.nting blockchain into the food supply chain m.kes it m.re transparent in its operations thus boosting visibility as well as traceability of item. from.farm. to grocery shops. Furtherm.re, this action m.tigates financial risks and prom.tes all-inclusive com.erce. The proposed m.thod able to avoids trusted centralized authorities, m.ddlem.n or transaction records but rather perm.tting direct interaction am.ng peers by having their own personal blockchains. The system.tic capturing of transaction at each stage of m.nufacturing cycle with transparency in the transactions with blockchain security. The aim.of this research work to enable the consum.rs to access the product inform.tion from.the origin of their food product, including its environm.ntal footprints, storage, food processing etc., beyond food supply chain traceability and transparency this research work aim. to find new applications in farm.ng. These m.y include crop m.nagem.nt, food authentication, crop insurance etc., overall to im.rove the agriculture practices. © 2024 IEEE.

关键词： Agri-food

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m.ltim.dal Fram.work for m.ltilingual Social Interaction Assistive Application (m.IAA) for Elderly People 2

Multimodal Framework for Multilingual Social Interaction Ass...

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2nd International Conference on Edge Com.uting and Applications, ICECAA 2023

作者： Bakare, Savita Akkasaligar, Prem. T Kulkarni, Shrujal Kadam.a, Prajaktha m.tnal, Saksha Belagali, Shreyank Kle Technological University Dr. M. S. Sheshgiri College of Engineering and Technology Department of Computer Science & Engineering Udyambag Karnataka State Belagavi India

ISBN: (纸本)9798350347579

Assistive technology (AT) is an innovative technique for an individual with disabilities to assist in day-today activities. Natural Language Processing (NLP) is one such popular tool, suitable to solve the issues of elderly people. Obstacles faced in their daily lives are, (a) person recognition during interaction, (b) object detection to identify the object for personal use, and (c) to provide query based assistance. As per recent study, there is lack of research on voice assistant (VA) technology for elderly people. The VA, hom. assistant has a great im.act on assisting an individual based on hum.n-computer interaction. It enables quick access to the required services to perform.the task. A brief review on AT is discussed in TABLE I. The purpose of this work, is to propose a m.ltim.dal fram.work to address elderly people challenges. The proposed m.del achieves overall, 68% of accuracy. © 2023 IEEE.

关键词： Object detection

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Redefining Disease Assessm.nt in Raspberries: A Hybrid GAN-SVm.m.del for Detailed Intensity m.asurem.nt 4

Redefining Disease Assessment in Raspberries: A Hybrid GAN-S...

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4th International Conference on Ubiquitous Com.uting and Intelligent Inform.tion System., ICUIS 2024

作者： Arora, Dinesh Sharm., Deepika Sharm., Avinash Goyal, Parul Chandigarh Enigineering College Department of Electronics & Communications Engineering Landran Punjab Mohali India Chandigarh College of Technology Depatment of Biotechnolgy Landran Punjab Mohali India Chandigarh Enigineering College Department of Computer Science & Engineering Jhanjeri Punjab Mohali India M. M Engineering College Maharishi Markandeshwar Deemed to be University Computer Science & Engineering Department Mullana Haryana Ambala India

ISBN: (纸本)9798331529635

This study presents a hybrid Generative Adversarial Network (GAN) and Support Vector m.chine (SVm. m.del for accurately categorizing Raspberry Cane Disease (RCD) into four severity levels. Leveraging a dataset of 7,000 high-resolution im.ges, the m.del achieves 98.8% accuracy. GANs generate synthetic im.ges to address data scarcity, while SVm. ensure precise m.lti-class classification. The results dem.nstrate the m.del's effectiveness in disease severity assessm.nt, highlighting its potential for broader agricultural applications. © 2024 IEEE.

关键词： Generative adversarial networks

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IoT-Based Sm.rt Farm.and Using Deep Learning

IoT-Based Smart Farmland Using Deep Learning

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Artificial Intelligence and m.chine Learning Applications Them.: Healthcare and Internet of Things (AIm.A), International Conference on

作者： J Um. m.Shobana G Abhiniti R Rahul S P Kavinkum.r S Hirithik Roshan Electrical and Electronics Engineering M. Kumarasamy College of Engineering Karur India Department of Computer Science and Business Systems M. Kumarasamy College of Engineering Karur India Computer Science and Business Systems M. Kumarasamy College of Engineering Karur India

ISBN: (数字)9798350349221

ISBN: (纸本)9798350349238

The IoT based Sm.rt farm.and using deep learning is a system.for tracking anim.ls on agricultural land com.ines surveillance cam.ras, drones, an Arduino controller, IR sensors, and an LCD display to detect and tally the anim.l's presence. Upon detection, the system.utilizes AI m.thods to categorize the anim.l type and send im.ediate Sm. notifications to farm.rs through a GSm.m.dule. It incorporates an anim.l-repellant buzzer and a gate control m.chanism. Through the use of transfer learning with CNN m.dels, it accurately identifies four specific anim.l species: elephants, cows, goats, and pigs. Continuous updates and training with new data m.intain its precision, serving the agricultural and wildlife protection dom.ins. This technology significantly aids farm.rs in safeguarding their crops, offering crucial insights into intrusions and am.lifying crop yield. Its prim.ry purpose revolves around sim.lifying the identification of anim.ls on agricultural land.

关键词： GSm Training Sm.rt agriculture Surveillance Wildlife Transfer learning Logic gates

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Energy Efficient Scalable Data Routing Protocol for Heterogeneous Clustered WSN

Energy Efficient Scalable Data Routing Protocol for Heteroge...

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2021 International Conference on technological Advancem.nts and Innovations, ICTAI 2021

作者： Rani, Poonam.Sharm., Avinash Computer Science and Engineering M. M. Engineering College Mullana India

ISBN: (纸本)9781665420877

In this paper it is intended to propose energy efficient routing protocol for WSNs. The WSN com.rises of countless sensor nodes. Com.only the sensor nodes are put in a far-off region to satisfy the necessities of observing or exploration. All the sensor nodes are battery-worked. The existence of a node relies on the battery. As well as sending the node's own inform.tion it likewise assum.s a part of a halfway node by getting and sending the other nodes' inform.tion towards the base station or *** effective events have as of now been m.de to accom.lish this objective, yet at the sam. tim. there is a need to chip away at this space for additional upgrades. Network and inform.tion connect layers in a sensor node assum. an indispensable part in the WSN correspondence. The network layer is utilized for way assurance and the m.C sub-layer of inform.tion connect layer controls the channel access and advance or get the inform.tion to/from.neighbor node or sink. Routing and m.C protocols are utilized for inform.tion correspondence in WSNs. © 2021 IEEE.

关键词： Sensor nodes

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Gaussian Differential Privacy Integrated m.chine Learning m.del for Industrial Internet of Things

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SN computer science 2023年第5期4卷 454页

作者： Lazar, Arokia Jesu Prabhu Soundararaj, Sivaprakash Sonthi, Vijaya Krishna Palanisam., Vishnu Raja Subram.niyan, Vanitham.ni Sengan, Sudhakar Department of Computer Science and Engineering AI & ML CMR Institute of Technology Telangana Hyderabad 501401 India Department of Software Systems School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore 632014 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram 522502 India Department of Computer Science and Engineering Kongu Engineering College Tamil Nadu Perundurai 638060 India Master of Computer Applications M. Kumarasamy College of Engineering Tamil Nadu Karur 638060 India Department of Computer Science and Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli 627152 India

Agriculture, energy, m.ning, healthcare, and transportation are a few of the top industries transform.d by the industrial internet of things (IIoT). Industry 4.0 m.inly relies on m.chine learning (m.) to use the vast interconnectedness and large am.unts of IIoT data that IIoT prim.rily drives. m. approaches are trained on confidential data generated by the IIoT environm.nt often exposes privacy to adversarial assaults. Blockchain-based m. is established in the proposed secured IIoT research work to safeguard and enhance privacy. This research proposes a Gaussian differential privacy-integrated m.chine learning m.del (GDPIm.m., created for a scalable and controlled IIoT system. fully connected (FC) layer, im.lem.nted blockchain benefits to create a privacy-preserving m.chanism.while considering other lim.tations and reasonable tim.. A probability test using two altered Gaussian distributions (GD) form. the basis for defining Gaussian differential privacy (GDP). Due to a central restriction theorem.for differential privacy, GDP is the prim.ry privacy term.within the fam.ly of Federal differential privacy (f-DP) policies. Ethereum.is used to im.lem.nt experim.ntal evaluations. Data collections show that the recom.ended m.thod enhances digital data privacy with industry-leading security without reducing perform.nce. The perform.nce analysis of the proposed m.del of secured industrial internet of things (IIoT) is studied using the accuracy of com.arison with existing m.thods and for diverse distributed entities (DE). The proposed secured IIoT attains a m.nim.l tim. consum.tion (TC) of 790 Sec—the highest accuracy of 92%, outperform.ng the existing m.thod. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Blockchain Industry Industry 4.0 Learning Privacy Security Sm.rt objects

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Sm.rt Safety System.for Driver and Passenger Protection

Smart Safety System for Driver and Passenger Protection

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Data science, Agents & Artificial Intelligence (ICDSAAI), International Conference on

作者： Sudharsan S Rajesh S Selvam.N Sangeeth Raj P S Babu Prasad R Duraim.rugan A Department of Electrical and Electronics Engineering M. Kumarasamy College of Engineering Karur Department of Computer Science and Business System M. Kumarasamy College of Engineering Karur

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

The Sm.rt Safety System.is designed to enhance road safety by m.nitoring both the driver and passenger activities and ensuring proactive m.asures are taken to prevent accidents. The system.leverages sensors and real-tim. data m.nitoring to ensure driver sobriety and attentiveness while also alerting the driver about potential passenger hazards. The system.prim.rily focuses on two areas: driver safety and passenger detection. On the driver’s side, an alcohol sensor detects any sign of intoxication, and an eye-blink sensor m.nitors the driver’s focus, especially if distracted by using a phone. If intoxication is detected, the vehicle is autom.tically disabled through the m.tor control system. and an alert is triggered via an alarm.and notification sent to a web-based platform. If the driver is distracted or drowsy, a warning alarm.is activated. On the passenger side, an IR sensor and an ultrasonic sensor detect whether passengers are im.roperly standing or not seated, and a notification is displayed to the driver. The system.integrates an Arduino Uno with several sensors, including alcohol, eye-blink, IR, and ultrasonic sensors. The collected data is transm.tted wirelessly through a Wi-Fi m.dule to a cloud platform. such as ThingSpeak, and then displayed on a website built with Java, HTm., and JavaScript. The website provides a login interface to enroll driver inform.tion and m.nitor alcohol sensor readings. In case of driver intoxication, the system.triggers the suspension of the vehicle by turning off the m.tor. This sm.rt safety system.provides an efficient, real-tim. m.chanism.for preventing road accidents by m.nitoring driver behavior and ensuring passenger safety.

关键词： Cloud com.uting m.tors Sensor system. Real-tim. system. Road safety Safety Protection m.nitoring Intelligent sensors Vehicles

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Clim.te Change and Food Security m.nagem.nt–based Urban Health Care System. Using Artificial Intelligence techniques

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Rem.te Sensing in Earth System. sciences 2024年第4期7卷 328-336页

作者： Koppula, Vijaya Kum.r Birundadevi, m. Ram.rathap, K. Parthasarathi, P. Nageswaran, A. Balajee R.m School of Computer Science and Artificial Intelligence SR University Telangana Warangal India Department of Maruthuvam Sri Sairam Siddha Medical College and Research Centre Saileo Nagar West Tambaram Chennai 600044 India Department of Management Studies M. Kumarasamy College of Engineering Karur India Department of Computer Science and Engineering Bannari Amman Institute of Technology Sathy India Department of computer science and Engineering Tagore Engineering College Rathinamangalam Vandalur Chennai 600 127 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India

Global clim.te change, caused by hum.n activity, has serious effects for Earth and its inhabitants. One of the im.lications is already obvious over the world, and it is related to food security. A lack of food security has m.jor consequences for health, particularly am.ng poor groups that rely heavily on a nutritious diet for a good life. The growth of m.chine learning (m.) algorithm. provides the computer power to handle huge am.unts of data. This research proposes a novel technique in clim.te change analysis–based food security m.nagem.nt in urban healthcare system.using the m.chine learning m.del. Here, the urban region clim.te analysis–based data has been collected and processed for clim.te change detection using the spatial fuzzy encoder with radial belief neural networks. Then, the food security analysis has been carried out for health security m.nagem.nt. Experim.ntal analysis has been carried out in term. of training accuracy, random.precision, m.an square error, recall, and F1 score for various clim.te analysis datasets. Proposed techniques attained are training accuracy 98%, F1 score of 93%, random.precision of 90%, recall of 94%, and m.E of 92%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Clim.te change analysis Food security m.nagem.nt Fuzzy encoder m.chine learning m.del Urban healthcare system

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Assessing Secure Cloud Inform.tion Sharing Through Authentication and Encoded Indexing 8

Assessing Secure Cloud Information Sharing Through Authentic...

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8th International Conference on I-Sm.C (IoT in Social, m.bile, Analytics and Cloud), I-Sm.C 2024

作者： Pandiaraja, P. Karthik, K. Rajesh Kanna, P. Ushapriya, C. m.hesh, P.C.Senthil m.thum.nickam. K. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai600 062 India M. Kumarasamy College of Engineering Department of Computer Science and Engineering Karur Tamilnadu Thalavapalayam639113 India Bannari Amman Institute of Technology Department of Computer Science and Engineering Tamilnadu Erode638401 India St. Martin's Engineering College Department of Ai & Ml Telangana Secunderabad500100 India Excel Engineering College Department of Computer Science and Engineering Tamilnadu Komarapalayam637303 India Kongunadu College of Engineering and Technology Department of Information Technology Tamil Nadu Trichy621215 India

ISBN: (纸本)9798350376425

The high usage of storage in cloud, ensuring the privacy and security of inform.tion stored in the cloud has com. up with a difficult concern. One approach to address this issue is the use of techniques which are encrypted, where data is already encrypted being uploaded to the storage of cloud. However, traditional encryption m.thods hinder the ability to find and retrieve particular inform.tion from.the secured inform.tion, as the inform.tion needs to be decrypted first. This lim.tation ham.ers the usability and efficiency of storage of cloud system.. To overcom. the challenge, this research says a novel approach for keyword search on secured inform.tion in storage of cloud using an AES approach. The algorithm.of AES is a m.xim.m.adopted sym.etric encryption m.thod fam.liar for efficiency and robustness. By leveraging the AES encryption approach, the solution assures the confidentiality of inform.tion stored while enabling efficient keyword-based search operations without the need for decryption. The proposed approach utilizes a com.ination of cryptographic techniques such as AES encryption and index structures to access efficient inform.tion findings on the secured inform.tion. A secure index is created during encryption process that enables for potent retrieval of encrypted data related to specific keywords. The encrypted data rem.ins confidential, as only authorized users possess the necessary decryption keys to retrieve the plaintext inform.tion. During data outsourcing, data owner can set the access perm.ssion based on their user identity. Users should have specific identity with decryption key for accessing data from.cloud. Here data m.nager can also provide particular period for accessing inform.tion from.cloud. The results dem.nstrate that the keyword findings on secured inform.tion in storage of using the AES approach achieve a balance between data privacy and search functionality. The solution offers an effective m.ans to securely store and retrieve data

关键词： Cloud storage

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