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2023 Workshop on Advances in Computational Intelligence, ACI 2023

作者： Bhattacharya, Pronaya Chatterjee, Sudip Singh, Anupam Department of Computer Science and Engineering Amity School of Engineering and Technology Research and Innovation Cell Amity University Kolkata700135 India Department of Computer Science and Engineering Graphic Era Hill University Uttarakhand Dehradun India Department of Computer Science and Engineering Graphic Era Deemed to be University Uttarakhand Dehradun India

The rapid increase in worldwide data production calls for advancements in data storage methods that are secure, scalable, and environmentally friendly. This paper introduces a cutting-edge DNA-based data storage framework. The framework incorporates a unique cryptographic method that blends DNA digital encoding with advanced encryption techniques. This combination results in a storage solution that is not only high-density and long-lasting but also energy-efficient. Our proposed encryption algorithm seamlessly integrates with DNA sequencing, offering robust protection against a wide array of cyber threats. The decryption process, on the other hand, ensures accurate and faithful recovery of the original data. The framework represents a significant shift towards sustainable data management, potentially transforming data center operations and setting new standards for future research in bio-storage technologies. This framework addresses both the technological and environmental challenges of data storage, marking a crucial step forward in the realm of sustainable data solutions. © 2024 Copyright for this paper by its authors.

关键词： DNA

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Recognition of American sign language using modified deep residual CNN with modified canny edge segmentation

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Multimedia Tools and Applications 2025年 1-28页

作者： Hariharan, U. Devarajan, Devikanniga Kumar, P. Santhosh Rajkumar, K. Meena, M. Akilan, T. Department of Computer Science and Engineering Apex Institute of Technology Chandigarh University Punjab Mohali140413 India Department of Computer Science and Engineering GITAM University Karnataka Bengaluru561203 India Department of Information Technology Faculty of Engineering and technology SRM Institute of Science and Technology Ramapuram Tamil Nadu Chennai600089 India Department of Data Science and Business Systems School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamil Nadu Chennai603203 India Department of Computer Science and Engineering Sri Sairam Engineering College Tamil Nadu Tambaram602109 India Research Coordinator Dept. of IQAC Amity University Kolkata West Bengal 700135 India

American Sign Language (ASL) recognition aims to recognize hand gestures, and it is a crucial solution to communicating between the deaf community and hearing people. However, existing sign language recognition algorithms still have some drawbacks, such as difficulty recognizing hand movements and low recognition accuracy for most sign language recognition. A Modified Convolutional Neural Network (MCNN) deep residual 101 classifier-based American Sign Language identification system has been developed to address this problem. There are three main parts presents in the method. The first part is pre-processing the images to remove the noise, enhance the contrast of the picture, adjust the contrast level and smoothen the picture using various filters. The second part is the segmentation, and it’s used to partition the image using a modified canny edge detection method by removing all weak edges present in the image. Finally, classification will be done using the Modified CNN deep residual 101 classifiers. By classifying the image, the American Sign Language is accurately identified. This process is conducted through images. The outcome shows that the suggested approach has a 0.97% accuracy and a 0.05% False Positive Rate. Other CNN architectures such as resNet 50 and resNet 18 reached 0.90% and 0.80% accuracy, respectively, which is lower than our proposed method. In addition, the resNet 101 classifier effectively recognizes the difficult hand gestures through the image data. It obtains high recognition accuracy for 36 signs is 0 to 9 numbers and a to z alphabets from American Sign Language. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

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Diabetes Estimation Through Data Mining Using Optimization, Clustering, and Secure Cloud Storage Strategies

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SN computer science 2024年第6期5卷 781页

作者： Gupta, Shyam S. Pandey, Tushar Kumar Raju, Vadali Pitchi Shrivastava, Rajeev Pandey, Rajeev Nigam, Ankita Roy, Vandana Department of Computer Science and Engineering Amity School of Engineering and Technology (ASET) Amity University College of Community Science Central Agricultural University Indur Institute of Engineering & amp Technology Princeton Institute of Engineering & amp Technology for Women Hyderabad DoCSE UIT-RGPV Department of CSE Princeton Institute of Engineering and Technology for Women Hyderabad Department of EC Gyan Ganga Institute of Technology and Sciences

Asian Indians face a unique risk for type 2 diabetes, with earlier onset and diagnosis at lower BMIs than other populations. Their susceptibility to diabetes-related health risks is higher compared to white populations. India struggles with low public awareness, a shortage of healthcare professionals, and limited treatment accessibility. Innovative strategies using available technological resources could significantly improve diabetes management in India. These challenges, common in developing countries, suggest that insights from India’s experience could benefit global diabetes management. This study aims to develop a hybrid model for predicting type 2 diabetes mellitus (T2-DM) to enhance awareness and preventive strategies. Using the Pima Indian Diabetes Dataset, the model’s effectiveness is validated through various performance metrics. The Fuzzy C-Means (FCM) clustering method is introduced, outperforming traditional models by creating more cohesive clusters with fewer variables. To enhance FCM's effectiveness, the Particle Swarm Optimization (PSO) technique is integrated, preserving FCM's strengths while improving efficiency. The hybrid model's sensitivity is 5.85% higher than K-Means + C4.5, and specificity is 2.79% higher. The proposed model achieves greater accuracy (96.58%) than previous methods. This approach aims to improve diabetes care in India and offers a model adaptable worldwide, addressing a critical global health challenge. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： BMI Data mining Diabetic retinopathy FCM PSO T1-DM T2DM

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A Permissioned Blockchain Approach for Real-Time Embedded Control Systems 9th

A Permissioned Blockchain Approach for Real-Time Embedded C...

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9th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2023

作者： Bhattacharya, Pronaya Chatterjee, Sudip Datt, Rajan Verma, Ashwin Dutta, Pushan Kumar Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Kolkata West Bengal Kolkata700135 India Department of Computer Science and Engineering Institute of Technology Nirma University Gujarat Ahmedabad382481 India Department of Electronics and Communication Engineering Amity School of Engineering and Technology Amity University Kolkata West Bengal Kolkata700135 India

ISBN: (纸本)9783031440830

In real-time embedded control (RTEC) systems, sensors collect data which is processed and sent to different control nodes. RTEC deployments have numerous applications in diverse verticals like industrial control, healthcare, and vehicular networks. In such cases, a trusted and verifiable control is required, particularly when the data is kept in a distributed manner, and is exchanged over open wireless channels. Thus, blockchain (BC) is a viable option to store the sensor data between RTEC systems, which maintains a trusted ledger of associated operations. Existing works have not focused on the integration of BC in RTEC systems. Motivated by the gap, the paper presents a systematic approach to integrating BC in RTEC ecosystems. We present a reference architecture and discuss the device registration, the hyperledger fabric set up, and the task offloading strategy between edge gateways and cloud nodes, and present the performance analysis of the architecture. The discussion of open issues and challenges also highlights the practical implications of the approach, emphasizing its importance for future deployments of real-time embedded control systems. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Blockchain

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Implementing Newly Proposed Dynamic Tree Structure: Development, Integration, and Optimization

Implementing Newly Proposed Dynamic Tree Structure: Developm...

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2024 IEEE International Conference on Signal Processing and Advance Research in Computing, SPARC 2024

作者： Banerjee, Pallab Kumari, Sweety Kumar, Biresh Thakur, Kanika Gaurav, Kumar Kumar, Purushottam Amity University Jharkhand Dept. of Computer Science Engineering Jharkhand Ranchi India Galgotia University Dept. of Computer Science Engineering Greater Noida campus India Amity University Jharkhand Amity School of Information Technology Jharkhand Ranchi India

ISBN: (纸本)9798350385199

An innovative data structure called a 'dynamic tree' has important uses in algorithmic time complexity optimization. It creates well-organized trees by modifying the properties of several single-node trees, therefore preserving the forest structure. This structure is essential to improving the effectiveness of many algorithms. In this work, I particularly address the 'Maximum Flow method,' a crucial subtopic in the larger field of dynamic trees. One basic method for solving network flow issues is the Maximum Flow Algorithm, but it frequently runs into issues with time complexity. My research attempts to overcome these obstacles by using dynamic trees to enhance the efficiency of the algorithm. This work reduces the time complexity of network flow problems, leading to more effective solutions. The findings have potential implications in a variety of computing and real-world scenarios. © 2024 IEEE.

关键词： Ancestor Cut Evert Find Key Link Root Top tree

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AutoBots: A Botnet Intrusion Detection Scheme Using Deep Autoencoders 4th

AutoBots: A Botnet Intrusion Detection Scheme Using Deep Aut...

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4th International Conference on Computing, Communications, and Cyber-Security, IC4S 2022

作者： Verma, Ashwin Bhattacharya, Pronaya Prasad, Vivek Kumar Datt, Rajan Tanwar, Sudeep Department of Computer Science and Engineering Institute of Technology Nirma University Gujarat Ahmedabad382481 India Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University West Bengal Kolkata700135 India

ISBN: (纸本)9789819914784

Recently, with the massive exchange of data over Internet of Things (IoT) ecosystems, attacks surfaces have also intensified. In IoT, connected devices share data over open channels and thus are highly vulnerable to security and privacy attacks. Botnet-based attacks have been found to have a significant effect on the network-based system. Thus, in this paper, we present a scheme AutoBots, which differentiates the normal and anomaly behaviour of IoT devices among the connected network. To exploit this, we consider diverse parameters like network behaviour profiles and apply autoencoders to classify and detect anomalous traffic from normal traffic. We used the BASHLITE and MIRAI IoT botnet setup and trained our network with the N-BaIoT dataset that has both benign and malicious network traffic. We compared our scheme for metrics like attack detection time, attack detection with respect to hourly traffic, deep residual accuracy, and residual loss. The presented results signify the efficacy of the proposed scheme against conventional bot-detection schemes. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Intrusion detection

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Untangling Explainable AI in Applicative Domains: Taxonomy, Tools, and Open Challenges 4th

Untangling Explainable AI in Applicative Domains: Taxonomy, ...

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4th International Conference on Computing, Communications, and Cyber-Security, IC4S 2022

作者： Chaudhary, Sachi Joshi, Pooja Bhattacharya, Pronaya Prasad, Vivek Kumar Shah, Rushabh Tanwar, Sudeep Department of Computer Science and Engineering Institute of Technology Nirma University Gujarat Ahmedabad382481 India Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University West Bengal Kolkata700135 India

ISBN: (纸本)9789819914784

Recently, a paradigm shift is observed toward Industry 5.0, where tasks (processes) are automated at massive scales. This shift has initiated modern developments in artificial intelligence (AI) to support a plethora of applications like manufacturing, health care, vehicular net- works, and others. However, owing to the black-box nature of AI models, the research has shifted toward the proposal of novel techniques that aim toward the explainability and validity of these AI models. Thus, explainable AI (XAI) has become a norm in modern applicative domains, and the study of its frameworks and tools has become the buzzword among researchers. Thus, the paper intends to present the key concepts of XAI and aims at improving the model transparency. The survey systematically untangles the key concepts of XAI and presents a solution taxonomy in different applications. Modern XAI techniques are classified as self-explanatory, visual-based-model-agnostic, global surrogate, and local surrogate-model-agnostic. We also cover the tools and frameworks of XAI and discuss the open issues and challenges in practical realization. Thus, the survey intends to arm AI practitioners to design optimal solutions to realize XAI in practical use-case setups. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Machine learning

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Exploring the Impact of Carbon Emissions on Supply Chains of Imperfect Quality Items: A Game Theory Perspective 2nd

Exploring the Impact of Carbon Emissions on Supply Chains of...

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2nd Biennial International Symposium on Fluids and Thermal engineering, FLUTE 2023

作者： Mittal, Mandeep Dhanda, Anil Raghav, Tisha Phanden, Rakesh Kumar Department of Mathematics School of Computer Science Engineering and Technology Bennett University Greater Noida India Department of Mathematics Amity Institute of Applied Sciences Amity University Uttar Pradesh Noida India Amity School of Engineering and Technology Amity University Uttar Pradesh Noida India

ISBN: (纸本)9789819731725

This research study proposes a cooperative and non-cooperative game theory strategy. The study’s objectives are to examine how carbon emissions impact the supply chain, especially in means of quality control and cost restriction, and to evaluate the effectiveness of game theory in addressing the issue. To gather and evaluate both quantitative and qualitative data for the study, a mixed-methods technique is used. The importance of reducing carbon emissions in supply chains is emphasized in the study, as are the benefits of using cooperative and non-cooperative game theory strategies to achieve this goal. The paper improves knowledge on supply chain management by offering an approach for simulating carbon emissions in a network of supply chains. The results of this study benefit supply chain management and assist academics, policymakers, and sustainability practitioners. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Game theory

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Merging the Strengths of GPT-4 and DeepLab for Semantic Text Understanding in Digital Textbooks

Merging the Strengths of GPT-4 and DeepLab for Semantic Text...

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

作者： Anusha, B. Borah, Asha Rani Mishra, Gaurav Thethi, H Pal Al-Allak, Mustafa Abdulhussein Vidhya, B. Veda Institute Of Aeronautical Engineering Department Of Computer Science And Engineering Telangana Hyderabad India New Horizon College Of Engineering Department Of Computer Science Engineering Bangalore India Amity School Of Engineering And Technology Amity University Greater Noida India Lovely Professional University Phagwara India College Of Medical Technology The Islamic University Najaf Iraq Mlr Institute Of Technology Department Of Computer Science And Engineering Telangana Hyderabad India

ISBN: (纸本)9798350366846

Gathering all the necessary data is the major objective of this study so that a comprehensive picture can be painted of how new technologies might improve students' understanding of semantic content in digital textbooks. The recommendations for this approach make use of TIFA, CEG, and ACA, or the Adaptive Complexity Adjustment. This approach combines the best features of various algorithms. TIFA makes these learning aids easy to completely comprehend by combining written and visual material. Answering students' queries and providing answers that make sense in the context is CEG's responsibility. To make learning more tailored to everyone, ACA changes the difficulty of the content depending on performance metrics. Conversely, when students ask CEG questions, it finds answers. We compare the proposed method, Semantix Blend, to two more popular approaches, Textbook Classic and Trad Edu. Interpreting text, evaluating visual information, ensuring consistency in context, enabling customisation, making content more accessible, enhancing learning results, and many more advantages are all possible with Semantix Blend. The study's findings will contribute to the improvement of digital textbooks, leading to improved instruction for students in the long term. © 2024 IEEE.

关键词： Semantics

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Smart Healthcare in Improving the Quality of Life: Revolutionizing with Application of IoT and Block Chain technology

Smart Healthcare in Improving the Quality of Life: Revolutio...

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

作者： Das, Lipsa Singh, Divya Vats, Satvik Taliyan, Khushi Bhargava, Deepshikha Bhatnagar, Devang Amity School Of Engineering & Technology Amity University UP Greater Noida India Graphic Era Hill University Graphic Era Deemed To Be University Computer Science And Engineering Dehradun India

ISBN: (纸本)9798350366846

One of the many essential elements of life is one's health. Our healthcare systems has to possess to stay as secure as well as successful as it can be hoping for a healthier society. The establishment of sophisticated medical facilities which improve tracking of patients evaluation, and customized therapy has been brought feasible by the Internet Of Things(IoT), which is having an enormous impact upon the healthcare sector. In addition, healthcare facilities, pharmaceutical companies, diagnostic centres, and doctors might freely trade and maintain information and data about patients effectively with the use of blockchain-based technology. Blockchain-based tools are adequate to build confidence and recognized and access incorrect information provided by doctors. Blockchain innovations may therefor help with the privacy, efficiency, safety, and visibility of health related information trade in the medical sector. Through the help of such technology, hospitals can get precise as superior knowledge that will improve client analysis of data and help with the efficient handling of illness. Substantial studies and evaluations has been done to look into every potential as the use of blockchain technology possess to improve the current situation of the healthcare in general. The study seeks to provide an overview of the current state and advancement in the industries which promotes IoT- based healthcare systems. As a result, the study additionally explores into the possibilities of merging healthcare sensors, wearable gadgets, and various other modern medical tools that enable immediate time gathering of information. The article additionally dicusses the dangers and weakness that exist in that plag in IoT-based healthcare systems as well as its features, and also in addition to the results and remedies which currently exist to fix such issues and problems while safeguarding private information and data about patients. Lastly, this presents as well as examines and array for a

关键词： Diagnosis

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