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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Raj, P. Michael Preetam Vittapu, Sravan K. Chinnasamy, P. Gupta, Manu Samatha, K. Sasivijaya, K. Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad India Nalla Narasimha Reddy Education Society's Group of Institutions Department of Electronics and Communication Engineering Hyderabad India Kalasalingam Academy of Research and Education Dept. of Computer Science and Engineering Tamil Nadu India Sreenidhi Institute of Science and Technology Department of Electronics and Computer Engineering Hyderabad India

ISBN: (纸本)9798331518592

In earlier developments, CMOS technology played a great role in realizing majority identifiers. There are huge drawbacks that affect the circuit's performance. To overcome the drawbacks of CMOS-based majority Identifiers, novel memristor-based majority and minority Identifiers have been proposed in this work. The features offered by memristor have motivated us to use the component and achieve greatly improved results compared to CMOS-based majority identifier circuits. After observing the behavior of the basic memristor-based majority identifier circuit, we have decided to design and implement a memristor-based majority and minority identifier circuit which can be used in many automation systems to increase quality and productivity. © 2024 IEEE.

关键词： CMOS integrated circuits

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Smart Home Automation Using AI and IoT with High Security 2

Smart Home Automation Using AI and IoT with High Security

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Rani, K. Pushpa Sreedevi, Pogula Veeranjaneyulu, P. Kanth, M. Ravi Allam, Sangeetha Mohanty, Jnyana Ranjan Mlr Institute of Technology Department of Computer Science Engineering Hyderabad500043 India G.Pulla Reddy Engineering College Department of Computer Science and Engineering Kurnool518007 India and Ai&ds Hyderabad India Vnr Vignana Jyothi Institute of Engineering and Technology Department of Cse Hyderabad India Mlr Institute of Technology Department of Computer Science & Engineering Hyderabad India Kalinga Institute of Industrial Technology University India

ISBN: (纸本)9798350370188

A well-known and widely utilized technology is smart home automation. The project's primary goal is to create an android-based, Wi-Fi enabled home automation which makes our daily life simpler and easier. in every automation technology which uses internet of things which is a developing network of common items that can share information and carry out tasks while you are occupied with other activities, from industrial machinery to consumer goods. A system known as a Wireless Home Automation System (WHAS) integrating AI & IOT allows users to remotely control common home features and operations using PCs or mobile devices. Both human and electric energy are to be conserved. Because it permits, there is a difference between other systems and home automation systems. © 2024 IEEE.

关键词： Automation

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GITA: Graph to Visual and Textual Integration for Vision-Language Graph Reasoning 38

GITA: Graph to Visual and Textual Integration for Vision-Lan...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Wei, Yanbin Fu, Shuai Jiang, Weisen Zhang, Zejian Zeng, Zhixiong Wu, Qi Kwok, James T. Zhang, Yu Department of Computer Science and Engineering Southern University of Science and Technology China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Australia Institute for Machine Learning University of Adelaide Australia Tencent China

Large Language Models (LLMs) are increasingly used for various tasks with graph structures. Though LLMs can process graph information in the textual format, they overlook the rich vision modality, which is an intuitive way for humans to comprehend structural information and conduct general graph reasoning. The potential benefits and capabilities of representing graph structures as visual images (i.e., visual graph) are still unexplored. To fill the gap, we innovatively propose an end-to-end framework, called Graph to vIsual and Textual IntegrAtion (GITA), which incorporates visual graphs into general graph reasoning. Besides, we construct the Graph-based Vision-Language Question Answering (GVLQA) dataset from existing graph data, which is the first vision-language dataset for general graph reasoning. Extensive experiments on the GVLQA dataset and five real-world datasets show that GITA outperforms mainstream LLMs on general graph reasoning. Moreover, experimental results demonstrate the effectiveness of the layout augmentation on visual graphs and pretraining on the GVLQA dataset. © 2024 Neural information processing systems foundation. All rights reserved.

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Alfred: Open-Source Autonomous Mobile Robot Platform with Augmented Physical Testbed 8

Alfred: Open-Source Autonomous Mobile Robot Platform with Au...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Naresh, Vishwesh Vhavle Kumar Sharma, Jatin Indraprastha Institute of Information Technology Delhi Department of Computer Science Engineering New Delhi India

ISBN: (纸本)9798350376425

This research study introduces Alfred, a novel open-source Autonomous Mobile Robot (AMR) platform and a physical testbed that enables the integration of virtual scenarios. This system allows for the development and evaluation of algorithms for localization, perception, and path planning in a safe and efficient manner. By combining virtual and physical elements, our camera-based localization testbed facilitates comprehensive testing of AMRs, ensuring their readiness for real-world deployment. The modular design of Alfred, with parts sourced within the Indian subcontinent, makes it a cost-effective and adaptable solution for robotics research and development. We demonstrate the effectiveness of our platform through experiments in localization, mapping, and navigation, showcasing its potential for advancing AMR technology. © 2024 IEEE.

关键词： Machine design

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Leukemia Cancer Detection in Microscopic Blood Samples using Optimized Convolutional Neural Network 3

Leukemia Cancer Detection in Microscopic Blood Samples using...

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3rd IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Himaja, Gadi Rao, Gadu Srinivasa More, Vinoothna Amedapu, Nitheesh Reddy Hamitha, Viyyapu Vinay Vuppuluri, Vishnuvardhan Doppalapudi, Dheeraj Chowdary Labhala, Harshita Ajay, Karri Gandhi Institute of Technology and Management Department of Computer Science and Engineering Rushikonda Visakhapatnam530045 India

ISBN: (纸本)9798350361186

Leukaemia causes blood cell abnormalities quickly. Leukocytes injure bone marrow or blood and are followed by an increase in growing lymphocytes. Gelatinous tissue produces most of the body's blood. Thus, early and accurate cancer detection is essential for effective treatment that improves survival. Manually studying blood samples from microscopic pictures to identify this illness is slow, inaccurate, and timeconsuming. This sickness is currently diagnosed manually by studying blood samples from microscopic images, which is arduous, slow, and imprecise. Furthermore, leukemic cells appear and act similarly to normal cells under a microscope, making identification more challenging. Though DL has developed advanced algorithms for detecting difficulties in recent decades, there is always room for improvement in performance, learning process, and efficacy. A hybrid approach using parallel swarm optimisation is more successful for identifying WBC leukaemia. To obtain high accuracy in picture classification, convolutional network hyperparameter tweaking is critical, but it involves significant computing effort. An automated leukaemia monitoring system for small blood samples was created utilising metaheuristics and parallel cat swarm optimisation (PCSO) to determine optimum convolutional neural network settings. Two public leukaemia blood sample databases, ALL IDB1 and ALL IDB2, are utilised. The method's resilience and effectiveness are shown by experimental findings and comparison with other cutting-edge algorithms under similar conditions. © 2024 IEEE.

关键词： Convolutional neural networks

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A Comprehensive Survey and Implementation of Health Kiosk Innovations: AI Integration, IoT Applications, and Predictive Healthcare Solutions 3

A Comprehensive Survey and Implementation of Health Kiosk In...

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3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Amrutesh, Aniverthy Bharadwaj, Shreelakshmi Darshan Kumar, T. Asha Rani, K.P. Gowrishankar, S. Dr. Ambedkar Institute of Technology Department of Computer Science and Engineering Karnataka Bengaluru560056 India

ISBN: (纸本)9798331515911

Kiosks, initially designed for administrative purposes, have rapidly evolved into vital tools in healthcare, offering a range of services such as diagnostics, telemedicine, and health data management. This paper presents a comprehensive survey of health kiosks, emphasizing their application in healthcare environments, particularly with the integration of AI, IoT, and predictive analytics. Key technologies, including advanced biometric sensors and AI-driven health insights, have significantly enhanced their functionality. The economic impact of deploying health kiosks, their integration with existing healthcare systems, and the importance of adhering to international medical standards are thoroughly examined. A review of academic research, patents, and industry innovations sheds light on the latest advancements, while case studies of real-world implementations demonstrate their growing adoption across different sectors. The paper also provides a comparative analysis of kiosk models globally, addressing challenges in deployment. Future trends such as AI and wearable technology integration, blockchain for secure health data management, and personalized healthcare services are explored, highlighting the potential for health kiosks to further revolutionize healthcare delivery. Considering the Literature available a practically feasible Health Kiosk is implemented with a custom ML model deployed with an accuracy of 95.3% is achieved. © 2025 IEEE.

关键词： Electronic health record

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Vehicle Target Detection with an Integrated Attention Mechanism 3

Vehicle Target Detection with an Integrated Attention Mechan...

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3rd International Conference on Cloud Computing, Big Data Application and Software engineering, CBASE 2024

作者： Wang, Yuzhuo Wang, Haihui Hu, Po Hu, Yuanzhong School of Computer Science and Engineering School of Artificial Intelligence Wuhan Institute of Technology Wuhan China

ISBN: (纸本)9798331506582

To address the problems of traditional vehicle detection models regarding equipment requirements, detection accuracy, and overlapping target leakage rate, this study proposes an improved vehicle target detection algorithm for YOLOv8. Firstly, we introduce EMA, an attention mechanism for cross-space learning, to improve the attention to feature information. Secondly, it combines EMA with the C2f module in the Neck network to fuse more important feature information, obtaining more accurate vehicle feature information. Finally, it uses the MPDloU loss function to speed up the model's convergence and improve detection accuracy. Experiments conducted on Pascal VOC and MS COCO datasets show that the performance of the improved algorithm proposed in this paper exceeds that of the original model. The enhanced model's mAP reaches 85.71%, 3.27% higher than the original model, improving vehicle target detection accuracy and being highly practical. © 2024 IEEE.

关键词： attention mechanism MPDIoU vehicle detection YOLOv8

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Identification of Bird via Acoustics for Bird Species Population Monitoring and Conservation

Identification of Bird via Acoustics for Bird Species Popula...

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2024 International Conference on Big Data Analytics in Bioinformatics, DABCon 2024

作者： Adhikari, Nilanjana Bhattacharya, Suman Sultana, Mahamuda Maiti, Ananjan Sengupta, Diganta Guru Nanak Institute of Technology Jis Computer Science and Engineering West Bengal Kolkata India

ISBN: (纸本)9798350378047

Nowadays, bird conservation has become a crucial part of the study. The paramount peril confronting avian species in jeopardy pertains to the degradation of their habitats. The chirping sound of birds can be heard with lots of noise and environmental sounds. So, monitoring and identification of bird sounds are more challenging. This study proposes meticulous monitoring and identifying bird sounds to ensure bird species' conservation and automate the remote monitoring of bird populations. Firstly, the data frame was generated from the acquired recorded dataset. Then, the data frames were segmented into slices of 0.5-second intervals so that the silent zones of the recorded dataset could be removed. Following this, unwanted noise was removed using the filter. Then, the Mel Frequency Cepstral Coefficients (MFCCs) spectrogram was generated using feature extraction methodology. From this spectrogram, a sound vector is generated. Monitoring and tuning different hyperparameter constraints using Principal Component Analysis (PCA), the model was subsequently trained using Dense Neural Network. The test demonstrates exceptional precision and reliability with a nominal margin of error. © 2024 IEEE.

关键词： Background noise

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Load balancing for software-defined network: a review

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International Journal of computers and Applications 2022年第8期44卷 746-759页

作者： Srivastava, Vivek Pandey, Ravi Shankar Department of Computer Science Engineering Birla Institute of Technology Mesra Ranchi India

Software Defined Networks (SDN) concept reduces the complexity of the traditional network. The decentralization of controlling issues of the traditional networks in SDN increases the popularity of this concept, but the difficulty in balancing the load persists in the SDN. If the sharing of the load is not uniform;the performance of the network is affected. Several research issues arise in managing the request of the forwarding devices and providing the correct solutions, these research issues are like traffic monitoring, security, quality of service, and load balancing. Earlier, many load balancing strategies have been proposed for the improvement of the performance of Software Defined Networks. This paper summarizes the research trends and their methodologies for the load balancing in the area of model-based, estimation-based, and nature-inspired algorithms. We have also compared the methodologies used for load balancing. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Quality of service

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Securing IoT Systems with AI-Infused Software and Virtual Replica Models 2

Securing IoT Systems with AI-Infused Software and Virtual Re...

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2nd IEEE International Conference on Integrated Intelligence and Communication Systems, ICIICS 2024

作者： Supriya, K. Sangeetha Jeno Lovesum, S.P. Arora, Renuka Bhatia, Rishu Yadwad, Sunita Natrayan, L. Department of Computer Science & Engineering Christ University Bengaluru India Department of Computer Science & Engineering Jagannath University NCR Bahadurgarh India Department of Electronics and Communication Engineering Ganga Institute of Technology and Management Jhajjar India Department of Computer Science and Engineering Faculty of Engineering and Technology Parul institute of Engineering and Technology Parul University Vadodara India Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai India

ISBN: (纸本)9798331504960

The proliferation of Internet of Things (IoT) devices has introduced significant security challenges due to the increased attack surface and the inherent vulnerabilities of interconnected systems. This paper proposes a novel security framework that integrates Artificial Intelligence (AI)-infused software and Virtual Replica Models, or Digital Twins, to enhance the robustness of IoT systems. The framework leverages AI-driven anomaly detection and predictive analysis to identify potential threats in real-time, while Digital Twins provide a virtual replica of the IoT ecosystem for continuous monitoring and simulation-based threat assessment. By fusing these technologies, the proposed solution enables proactive security measures, ensuring rapid response to cyberattacks and continuous system optimization. Extensive simulations and experimental results demonstrate the system’s ability to reduce attack detection times by 30%, while improving overall system resilience and minimizing false positive rates. This approach provides a scalable and adaptable solution for securing IoT infrastructures in various industries. © 2024 IEEE.

关键词： Risk assessment

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