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

作者： Kaur, Puneet Kaur, Kiranbir Verma, Deepak Kumar Singh, Kuldeep Kaushik, Keshav Singh, Vineeta Guru Nanak Dev University Department of Computer Engineering & Technology Punjab Amritsar India Department of Computer Science and Engineering Uttar Pradesh Kalyanpur India Guru Nanak Dev University Department of Electronics Technology Punjab Amritsar India Amity University Amity School of Engineering and Technology Punjab Mohali India

ISBN: (纸本)9798350350067

Wireless Sensor Networks (WSNs) have significantly transformed diverse domains such as industrial automation, healthcare, disaster management, and environmental monitoring. The complex interaction of routing protocols, essential for enabling smooth data transport despite the specific difficulties in WSN environments, is the core of their success. The objective of this study is to get a accurate understanding of routing algorithms specifically projected for wireless sensor networks. Expanding upon the essential features and significant disputes faced in WSN systems, admitting limited energy resources, bandwidth constraints, and node processing capabilities, the discussion accentuates the significance of effective routing protocols. Furthermore, it thoroughly analyzes many forms of routing protocols, including basic hierarchical and flat schemes, as well as advanced location-based and data-centric protocols. The protocol category is thoroughly examined, uncovering its unique benefits, limitations, and suitability for various WSN applications. Furthermore, the review reveals the latest developments and upcoming trends in WSN routing protocols, brooding areas such as energy efficiency, dependability, scalability, and adaptive resilience to changing network considerations. In conclusion, the evaluation furnishes a forward-looking view by outlining potential research areas and possible pathways for meliorating the designs of WSN routing protocols. The main goal is to heighten the efficacy and practicality of WSNs. In this work, we examined a number of routing algorithms according to important criteria including mobility, scalability, energy efficiency, and Quality of Service (QoS). We looked at how each method handles node mobility, performs as the network expands, guarantees dependable data transmission, and optimizes energy use. We also looked at ways for choosing the cluster head (CH), energy-saving data aggregation strategies, redundancy-reduction mechanisms, and the

关键词： Routing algorithms

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HydroPro: An IoT-Based Smart Water Bottle

HydroPro: An IoT-Based Smart Water Bottle

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2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Nirbhavane, Aadi Kushwaha, Riti Singal, Gaurav Tomar, Abhinav Pal, Vipin Gupta, Ankur Amity International School Delhi India School of Computer Science and Technology Bennett University Greater Noida India Netaji Subhas University of Technology Computer Science and Engineering Department Delhi India Rishihood University Newton School of Technology Department of Computer Science Sonipat India

ISBN: (纸本)9798350364866

Water is a necessity for the correct functioning of the human body. In the modern era, most people have hectic schedules, making it difficult for them to remember to drink enough water and track their water consumption. This problem of not being able to track the daily water intake becomes even more pronounced for people of older age groups. In addition, people on medications also require strict water intake to dilute the toxins that the medicines introduce in their body. We present our product - HydroPro, a smart water bottle aimed at encouraging our target audiences to better their hydration habits. Our product gives a more personalized water tracking facility to the user wherein we take the user's environment parameters into account (namely temperature and humidity) to notify the user whether they have consumed enough water. The objective is to enable effective management of daily water requirements and to ensure users drink good quality water. The result shows the working effectiveness of smart water bottle system which is also tested and validated on mobile application. © 2024 IEEE.

关键词： Bottles

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Deceptive Plastic: Unveiling the World of Financial Fraud

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Procedia computer science 2025年 259卷 416-423页

作者： Shikha Singh Bramah Hazela Pallavi Asthana Shagun Barnwal Garima Srivastava Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Uttar Pradesh Lucknow Campus INDIA Department of Electronic and Communication Engineering Amity School of Engineering and Technology Amity University Uttar Pradesh Lucknow Campus INDIA

As human society is developing, so is electronic commerce and with that the use of credit card are increasing. And along with this growth, as people prefer to shop using credit cards in both mode of payments, the possibility of fraud and fraud of credit card is also on rise. The criminals may steal the card physically, but more frequently, they use digital ways to obtain the credit card details along with the personal information linked to it in order to engage in illicit actions. There is a lot of overlap between credit card fraud and identity theft. Indeed, credit card theft is one of the most common forms of identity theft. In these cases, the personal information of victims is stolen to somehow get access to cards by registering a new account without the owner’s knowledge and certainly it is a form of cyberattack as well as data breach and is offensive crime. This behavior is both identity fraud and credit card fraud. In this study, we employ a CAT Boost, ADA Boost, LIGHT GRADIENT BOOSTING and CONVOLUTIONAL NEURAL NETWORK model to simulate the process of credit card transaction processing and display how it can be applied to the spot of such frauds. The dataset inspection method, factor determination, and techniques used for detection have a significant influence on the demonstration of fraud detection in credit card transactions. The accuracy for models can be determined by finding precision, recall, f1score, accuracy values but to compare the models, we will take ROC AUC Score into account. So, the ROC AUC Score of CAT BOOST, ADA BOOST, LIGHT GRADIENT BOOSTING and CONVOLUTIONAL NEURAL NETWORK model are 92.44, 79.74, 93.34, 95.25 respectively. And CONVOLUTIONAL NEURAL NETWORK is best among four with 95.25 ROC Score.

关键词： Machine learning ADA Boosting Light Gradient boosting CAT Boosting Convolutional neural network Undersampling oversampling SMOTE

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Trade-off analysis for different Sink locations in DEEC Protocol 2

Trade-off analysis for different Sink locations in DEEC Prot...

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2nd International Conference on computer science, engineering and Applications, ICCSEA 2022

作者： Agarwal, Aayush Nehra, Vibha Amity University Department of Computer Science and Engineering Amity School of Engineering and Technology UP Noida India

ISBN: (数字)9781665458344

ISBN: (纸本)9781665458344

Data collected from different sensors in a wireless sensor network is to be send to base station for storage and other utilities such as processing. The data is sent to the base station either as direct or multi-hop propagation based on distance of node to the base station. The location of base station may be inside or outside the sensor field based on the scenario at hand. This paper analyzes trade-off for different locations of base station for various levels of heterogeneity in DEEC protocol. The current work analyzes the standard network parameters such as field dimensions of 100x100 meters, 100 sensor nodes with similar compute ability but different amount of initial energies. On simulation of the network with respect to existing popular literature works, it is found that the placement of the base station at the center of the field lead to optimal utilization of network recourses. © 2022 IEEE.

关键词： Base stations

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Performance Evaluation Of Hsrp, Glbp And Vrrp With Interior Gateway Routing Protocol And Exterior Gateway Routing Protocol 12

Performance Evaluation Of Hsrp, Glbp And Vrrp With Interior ...

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12th International Conference on Cloud Computing, Data science and engineering, Confluence 2022

作者： Agarwal, Aayush Sharma, Shilpi Amity University Uttar Pradesh Amity School Of Engineering And Technology Department Of Computer Science And Engineering India

ISBN: (纸本)9781665437011

The year of 2019 and 2020, saw the world shifting from physical classes, meetings etc., to online mode due to the commence of worldwide pandemic called COVID-19. Due to this, new network infrastructures were required and among the networks, efficient protocols were required in order to ensure 100% uptime and availability. Among the network routing protocols used, it is prudent to find which routing protocol works best with which redundancy protocol, as they have different switching algorithms. Therefore, in this paper, interior gateway routing protocol (OSPF) and exterior gateway protocol (BGP) are being evaluated on their performance with a redundancy protocol (HSRP, GLBP and VRRP). The criterion of measuring the performance includes jitter, downtime, throughput and number of packets lost. The result will help to analyze which first hop redundancy protocol works best with which routing protocol. The result of this study indicates that OSPF has 4.52% better QoS values with HSRP and BGP has 5.12% better QoS values with GLBP. © 2022 IEEE.

关键词： Routing protocols

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People Counting in Public Spaces using Deep Learning-based Object Detection and Tracking Techniques

People Counting in Public Spaces using Deep Learning-based O...

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2023 International Conference on Computational Intelligence and Sustainable engineering Solution, CISES 2023

作者： Krishnachaithanya, N. Singh, Gurdit Sharma, Smita Dinesh, Rangisetti Sihag, Sumeet Ramsingh Solanki, Kamna Agarwal, Abhishek Rana, Mrinalini Makkar, Ujjwal School of Computer Science and Engineering Lovely Professional University Punjab Kapurthala India Amity School of Engineering and Technology Amity University Department of Computer Science and Engineering Uttar Pradesh Greater Noida India University Institute of Engineering and Technology Maharshi Dayanand University Rohtak Department of Computer Science and Engineering Haryana Rohtak India Lovely Professional University Department of Mechanical Engineering Punjab Kapurthala India

ISBN: (纸本)9798350323917

Recent advancements in deep learning and machine learning have enabled exact people counting in various applications including crowd management, security, and retail analytics. Deep learning algorithms have proven tremendous promise for accurate and efficient people counting in difficult contexts. This paper offers a technique for counting people that utilises deep learning with MobileNet SSD, centroid tracking, and trackable object script. Gathering and preparing a labelled dataset, training a MobileNet SSD model, implementing centroid tracking and the trackable object script, increasing system performance, testing it on real-world scenarios, and deploying it in a production environment are all part of the approach. The recommended approach provides a wide framework for creating and deploying a deep learning-based people-counting system that can be customized and tuned to match a number of applications and purposes. Additionally, we have added alerts on maximum capacity, timely scheduling and input feed from the internet. © 2023 IEEE.

关键词： Object detection

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A Concise Review of MRI Feature Extraction and Classification with Kernel Functions 3

A Concise Review of MRI Feature Extraction and Classificatio...

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3rd International Conference on Innovative Sustainable Computational Technologies, CISCT 2023

作者： Singh, Jagendra Arya, Chandrakala Yamsani, Nagendar Kumar, Mohit Singh, Prabhishek Bhagat, Vivek Kumar School of Computer Science Engineering & Technology Bennett University Greater Noida India School of Computing Graphic Era Hill University Dehradun India School of Computer Science and Artificial Intelligence SR University Warangal India Amity School of Engineering and Technology Amity University Noida India

ISBN: (纸本)9798350303360

Magnetic resonance imaging is a common medical imaging tool for the identification and monitoring of brain diseases. Accurate classification of MRI brain pictures is extremely beneficial for early diagnosis and therapy planning. In this study, a method for MRI classification and feature extraction using a Support Vector Machine (SVM) and hybrid RBF which is radial Basis function kernel is proposed. Some of the interconnected steps in the suggested methodology include pre-processing, hybrid RBF kernel creation, feature extraction, SVM classification, feature selection, model evaluation, and model optimization. The GLCM technique is utilized to derive texture characteristics from MRI images. A blend of multiple RBF kernels with different parameter settings yields a hybrid RBF kernel. Performance indicators are used to assess the SVM classifier after it has been trained on a training dataset. The hybrid RBF kernel and the SVM's parameters are altered using model optimization. The suggested methodology intends to classify MRI brain pictures appropriately for enhanced treatment planning and disease diagnosis. © 2023 IEEE.

关键词： Magnetic resonance imaging

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Cervical Cancer Classification using Multi-Scale, Multiple-Attention-based Deep Learning Approach

Cervical Cancer Classification using Multi-Scale, Multiple-A...

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2024 Asian Conference on Intelligent Technologies, ACOIT 2024

作者： Maurya, Ritesh Deshwal, Suvidha Rajput, Lucky Gopalakrishnan, T. Krishna, Raguru Jaya Amity Centre for Artificial Intelligence Amity University Noida India Amity School of Engineering & Technology Amity University Noida India Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India Department of Computer Science and Engineering Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India

ISBN: (纸本)9798350374933

Cervical cancer is a widely acknowledged health concern, especially in the areas lacking appropriate medical treatment. The early diagnosis and the explicit categorization of cervical lesions may bring about effective therapy and restrict the expansion of the disease. The novel approach proposed in this work employs a multi-scale, multi-attention based MobileNetV2 network for the categorisation of cervical cancer. The proposed model improves the efficiency of MobileNetV2, a lightweight convolutional neural network (CNN), by incorporating multi-scale and multi-attention techniques to improve feature extraction capabilities and categorisation accuracy. By incorporating multi-scale component, the suggested model can effectively detect features at different resolutions. Moreover, the integration of multi-attention mechanism allows the model to dynamically highlight salient features over multiple scales. The proposed method has been evaluated using single cell conventional Pap Smear images, exhibiting improved performance compared to existing approaches in terms of accuracy. The results suggest that the Multi-Scale, Multiple-Attention MobileNetV2-based network proves to be a useful tool for cervical cancer categorisation, offering potential interests for clinical diagnosis with an accuracy of 92.4. © 2024 IEEE.

关键词： cervical cancer categorisation deep learning MobileNetV2 multi-attention multi-scale transfer learning

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Navigating Web3 Evolution with Blockchain's Role in Shaping Next Generation Internet Semantics

Navigating Web3 Evolution with Blockchain's Role in Shaping ...

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2024 International Conference on Communication, computer sciences and engineering, IC3SE 2024

作者： Subhashini, P. Alekhya, J. Rana, Ajay Lakhanpal, Sorabh Veeresh, G. Al-Allak, Mustafa Abdulhussein Mlr Institute Of Technology Department Of Computer Science And Information Technology Telangana Hyderabad India Institute Of Aeronautical Engineering Department Of Computer Science And Engineering Telangana Hyderabad India Amity School Of Engineering And Technology Amity University Greater Noida India Lovely Professional University Phagwara India New Horizon College Of Engineering Bangalore India College Of Medical Technology The Islamic University Najaf Iraq

ISBN: (纸本)9798350366846

Web3 needs complex semantic frameworks to update, validate, and regulate data across decentralized networks as it grows. The whole semantic system of this study includes SV, SC, DOC, ISV, and SG. The Semantic Validation technique performs parametric validation, scoring, and threshold comparison to safeguard data integrity, whereas the Semantic Agreement algorithm combines meanings by adding agreement values. Decentralized ontologies are improved using Distributed Ontology Construction to accommodate new meaning linkages. connected Semantic Verification detects semantic meaning compatibility across linked networks. Lastly, meaning Governance enables individuals to decide on recommended meaning modifications without centralization. Comparative analysis examines the framework. Tables and illustrations indicate its dominance over key aspects. The recommended strategy generally outperforms Web3 evolution methods in security, scale, interoperability, user privacy, and government effectiveness. Visualizing the process with pie charts, layered analysis, and temporal trends shows its efficacy. This semantic framework's consistency, correctness, and flexibility are key responses to Web3's changes. The framework's continual refinement methods can shape Web3 Internet semantics as open networks change. This semantic framework helps establish a decentralized and connected Internet as bitcoin and Web3 technologies progress. It also allows Web3-aligned semantic development. © 2024 IEEE.

关键词： Semantics

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Impact of Gamification on student Learning: An Empirical Evidence 5th

Impact of Gamification on Student Learning: An Empirical Evi...

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5th International Conference on Entrepreneurship, Innovation, and Leadership, ICEIL 2023

作者： Garg, Anchal Madhulika Centre for Applied Computer Science School of Creative Technologies University of Bolton BoltonBL3 5AB United Kingdom Department of Computer Science and Engineering Amity School of Engineering and Technology Uttar Pradesh Noida India

ISBN: (纸本)9789819716814

Learner diversity is a matter for universities enrolling international students. Hence, learner engagement then becomes a major concern for instructors. This study uses gamification techniques to determine its impact on engagement and learning when it comes to diverse cohort of learners. A survey questionnaire method was used to identify the effect of gamification on engagement, motivation, performance, and learning. This empirical study revealed that quizzes supported by gamification enhanced engagement, performance, and learning but did not motivate learners to study outside the lecture theatre. This paper also summarizes the issues while using gamified quizzes in the classroom settings and provides potential solutions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： students

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