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

作者： Sadhukhan, Ankan Samanta, Sreejani Pasari, Abhijit Samui, Sayantika Mandal, Dipayan Ghosh, Sandipta Guria, Mrinmoy Pal, Debrupa Computer Science and Engineering Narula Institute of Technology Kolkata India Computer Application Narula Institute of Technology Kolkata India

ISBN: (纸本)9798350378047

The pervasive presence of social media platforms has turned them into reservoirs of human emotions, providing a distinctive perspective into the intricate tapestry of digital sentiments. This research delves into the realm of emotional upheaval prevalent in online spaces, aiming to uncover signs of distress through the utilization of machine learning algorithms. By scrutinizing extensive volumes of social media data, this survey seeks to establish a pioneering framework for predicting the identification of individuals undergoing emotional distress. Many papers are published on machine learning approaches over the past few decades. In this paper, we provide a comprehensive survey of all best machine learning approaches in the current year to study or identify distress calls on social video through sentiment and media analysis. Furthermore, the challenges and benefits of using Machine Learning, along with its shortcomings, are summarized. Finally, open issues and their consequences for further research in the field of identifying individuals who are mentally depressed on social media are presented. © 2024 IEEE.

关键词： Adversarial machine learning

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Framework for classifying gait disorders and fall prevention

Framework for classifying gait disorders and fall prevention

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2025 International Conference on computer, Electrical and Communication Engineering, ICCECE 2025

作者： Saha, Rupa Karmakar, Koushik Biswas, Suparna Narula Institute of Technology Department of Computer Application India Narula Institute of Technology Department of Computer Science and Technology India Department of Computer Science & Engineering Makaut W B India

ISBN: (纸本)9798331513894

One of the crucial approaches that use tracking and analyzing human movement for the identification of functional disorders and illnesses of the human body is known as the gait analysis method. This method helps diagnose neurological and musculoskeletal conditions. It also tracks the effectiveness of rehabilitation. However, conventional techniques for analyzing gait frequently depend on costly items and methods like fixed lab apparatus, force plates, and motion capture devices. But new developments in wearable sensor technology and machine learning provide new methods that are cheaper, more affordable, portable, and easily accessible. It continuously tracks gait in real-world settings. In this work, the use of wearable sensors for gait analysis, which includes devices like magnetometers, gyroscopes, and accelerometers, is examined. They are integrated into gadgets like smartphones, insoles, and smartwatches and offer real-time kinematic data that machine learning algorithms can analyze. Some of the important gait parameters 1that are extracted from sensor data are stride length, cadence, and gait symmetry. Machine learning is used to process this data and use it for categorization and gait analysis. The suggested method improves patient monitoring outside of clinical settings. It supports individualized rehabilitation plans and also identifies early indicators of gait abnormalities. The use of the wearable sensor-based gait analysis may emerge as a game-changing medical tool. It offers constant, discrete monitoring and prompts intervention in gait-related disorders. This works explains it thoroughly. This report offers insights for upcoming researchers in the field by surveying the state of the art in wearable sensor-based gait analysis. © 2025 IEEE.

关键词： Wearable sensors

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Utilization of Two Cross Two Switch for Bitonic Sorting Circuit

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Micro and Nanosystems 2025年第1期17卷 45-57页

作者： Bhattacharjee, Subhasree Sarkar, Soumyadip Das, Kunal Sadhu, Arindam Sarkar, Bikramjit Department of Computer Application Narula Institute of Technology Kolkata India Department of Computer Science Acharya Prafulla Chandra College Kolkata India Department of Electronics & Communication Engineering Greater Kolkata College of Engineering and Management West Bengal India Department of Computer Science & Engineering JIS College of Engineering West Bengal India

Background: The synthesis of reversible logic has gained prominence as a crucial research area, particularly in the context of post-CMOS computing devices, notably quantum computing. Objective: To implement the bitonic sorting circuit, 2x2 switch, is used. The overarching objective of implementing a reversible sorting circuit is to mitigate power consumption while promising secure communication. The successful implementation of the bitonic sorting circuit utilizing the proposed 2x2 switch is validated through simulations conducted in IBM Qiskit. Methods: This study begins by employing the control swap gate to implement a 2x2 switch, aimed at enabling concurrent computing operations within multiprocessor systems to enhance throughput. Subsequently, following the successful implementation of the 2x2 switch, the study proceeds to design a bitonic sorting circuit. Results: Bitonic sort using a 2x2 switch on the IBM Quantum Experience (IBMQ) platform via the QISKit SDK in Python 3.6. Specifically, Qiskit v0.29.0 is utilized, with OpenQASM. OpenQASM serves as the quantum assembly and instruction language. Conclusion: This work presents a methodology for constructing a 2x2 switch, utilizing a reversible control swap gate as its core component. Additionally, it demonstrates the intricate development and implementation of a bitonic sorting circuit, capitalizing on this innovative switch architecture. © 2025 Bentham Science Publishers.

关键词： Quantum computers

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Machine Learning Techniques for Identifying Distressed Individuals on Social Media - A Survey

Machine Learning Techniques for Identifying Distressed Indiv...

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Big Data Analytics in Bioinformatics (DABCon), International Conference on

作者： Ankan Sadhukhan Sreejani Samanta Abhijit Pasari Sayantika Samui Dipayan Mandal Sandipta Ghosh Mrinmoy Guria Debrupa Pal Computer Science and Engineering Narula Institute of Technology Kolkata India Computer Application Narula Institute of Technology Kolkata India

ISBN: (数字)9798350378047

ISBN: (纸本)9798350378054

关键词： Surveys Ethics Machine learning algorithms Social networking (online) Surge protection Machine learning Mental health Predictive models Real-time systems Surges

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Quantum Transfer Learning for MNIST Classification Using a Hybrid Quantum-Classical Approach

arXiv

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arXiv 2024年

作者： Sarkar, Soumyadip Department of Computer Application Narula Institute of Technology Kolkata India

In this research, we explore the integration of quantum computing with classical machine learning for image classification tasks, specifically focusing on the MNIST dataset. We propose a hybrid quantum-classical approach that leverages the strengths of both paradigms. The process begins with preprocessing the MNIST dataset, normalizing the pixel values, and reshaping the images into vectors. An autoencoder compresses these 784-dimensional vectors into a 64-dimensional latent space, effectively reducing the data's dimensionality while preserving essential features. These compressed features are then processed using a quantum circuit implemented on a 5-qubit system. The quantum circuit applies rotation gates based on the feature values, followed by Hadamard and CNOT gates to entangle the qubits, and measurements are taken to generate quantum outcomes. These outcomes serve as input for a classical neural network designed to classify the MNIST digits. The classical neural network comprises multiple dense layers with batch normalization and dropout to enhance generalization and performance. We evaluate the performance of this hybrid model and compare it with a purely classical approach. The experimental results indicate that while the hybrid model demonstrates the feasibility of integrating quantum computing with classical techniques, the accuracy of the final model, trained on quantum outcomes, is currently lower than the classical model trained on compressed features. This research highlights the potential of quantum computing in machine learning, though further optimization and advanced quantum algorithms are necessary to achieve superior performance. © 2024, CC BY.

关键词： Qubits

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Framework for classifying gait disorders and fall prevention

Framework for classifying gait disorders and fall prevention

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International Conference on computer, Electrical & Communication Engineering (ICCECE)

作者： Rupa Saha Koushik Karmakar Suparna Biswas Department of Computer Application Narula Institute of Technology Department of Computer Science and Technology Narula Institute of Technology Department of Computer Science & Engineering MAKAUT W B

ISBN: (数字)9798331513894

ISBN: (纸本)9798331513900

关键词： Legged locomotion Machine learning algorithms Accuracy Tracking Reviews Real-time systems Biomedical monitoring Gait recognition Wearable sensors Smart phones

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Brain computer Interface: A Review 3rd

Brain Computer Interface: A Review

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3rd International Conference on Computational Advancement in Communication Circuits and Systems, ICCACCS 2020

作者： Pal, Debrupa Palit, Sujoy Dey, Anilesh Department of Computer Application Narula Institute of Technology Kolkata India Ericsson India Global Services Private Limited Kolkata India Department of Electronics and Communication Engineering Narula Institute of Technology Kolkata India

ISBN: (纸本)9789811640346

Brain-computer interface (BCI) enables their users to use brain signals instead of the brain’s normal peripheral nerve and muscle output paths to communicate or control external devices. Several methods can be used to obtain data from the brain sensors that basically monitor physical processes Brain computer interface technology is an emerging area of research with several applications in medical fields. In this review, we discuss the current status and future prospects of BCI technology and its applications in several fields. We will define BCI, examine BCI-related signals from the human brain, and describe the functional components of BCI. We will also review the different applications of BCI technologies in the field of medicine, in entertainment and games, safety and security and in biomedical. Finally, we will discuss the current restrictions of BCI technology, obstacles to its widespread clinical application, and expectations for the future. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Brain computer interface

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Blockchain-Enabled Secure and Fair Online Lottery Systems Using Smart Contracts

Blockchain-Enabled Secure and Fair Online Lottery Systems Us...

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2024 IEEE Silchar Subsection Annual Conference, SILCON 2024

作者： Datta, Suseta Mondal, Rituparna Roy, Rajdeep Banerjee, Sourav Biswas, Utpal Narula Institute of Technology Department of Computer Application West Bengal Kolkata India Techno India University Department of Computer Applications West Bengal Kolkata India University of Kalyani Department of Computer Science and Engineering West Bengal Kalyani India Kalyani Government Engineering College Department of Computer Science and Engineering West Bengal Kalyani India

ISBN: (纸本)9798331540821

In the capricious digital dominion, conventional online lottery systems come across consequential impediment regarding transparency, fairness, and security. This paper presents an inventive solution by merging Blockchain technology and smart contracts into online lotteries to take forward these challenges. The preferred disperse implementation capitalizes on Blockchain's decentralized category to covenant the translucency and immutability of lottery transactions, thereby undoing the requisite for trusted interceders. Smart contracts are immersed to automate the entire lottery process-from ticket provisioning to winner selection and payout-certifying agreement to preconceived rules and reinforcing contender trust. Through meticulous perusal and enactment, illustration of how Blockchain technology can transform online lottery systems, providing users with a secure, transparent, and fair platform have been performed. Furthermore, the suggested system's resistance to recurrent deceit and its prospective impression on the online gambling industry are talked about, foregrounding the welfares of a Blockchain-drove technique to online lotteries. © 2024 IEEE.

关键词： Smart contract

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Exploit Reversible Gates to Implement Fast Quantum Sorting Algorithm 1

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5th International Conference on computer and Communication Technologies, IC3T 2023

作者： Bhattacharjee, Subhasree Das, Kunal Sadhu, Arindam Sarkar, Soumyadip Sarkar, Bikramjit Department of Computer Application Narula Institute of Technology West Bengal Kolkata India Department of Computer Science Acharya Prafulla Chandra College West Bengal Kolkata India Department of Electronics and Communication Engineering Greater Kolkata College of Engineering and Management West Bengal Kolkata India Department of Computer Science and Engineering JIS College of Engineering West Bengal Kalyani India

ISBN: (数字)9789819997046

ISBN: (纸本)9789819997039

This paper proposes an algorithm of divide-compare-swap-based (DCS) sorting that reduces time complexity by utilizing quantum parallelism. A new cost optimized comparator circuit has been designed and simulated using qiskit for comparing two quantum numbers. The sorting process consists of divide, compare-swap and merge. The set of n quantum numbers are divided equally into two sub arrays followed by comparing-swapping of two middle elements. This process continues in two sub arrays till array with single element is found. The sorting circuit performs well in qiskit with time complexity n, which has a significant improvement over existing quantum sorting technique. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： computer circuits

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Enhancing Quantum Variational Algorithms with Zero Noise Extrapolation via Neural Networks

arXiv

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arXiv 2024年

作者： Bhattacharjee, Subhasree Sarkar, Soumyadip Das, Kunal Sarkar, Bikramjit Department of Computer Application Narula Institute of Technology Kolkata India Department of Computer Science Acharya Prafulla Chandra College West Bengal India Department of Computer Science and Engineering JIS College of Engineering West Bengal India

In the emergent realm of quantum computing, the Variational Quantum Eigensolver (VQE) stands out as a promising algorithm for solving complex quantum problems, especially in the noisy intermediate-scale quantum (NISQ) era. However, the ubiquitous presence of noise in quantum devices often limits the accuracy and reliability of VQE outcomes. This research introduces a novel approach to ameliorate this challenge by utilizing neural networks for zero noise extrapolation (ZNE) in VQE computations. By employing the Qiskit framework, we crafted parameterized quantum circuits using the RY-RZ ansatz and examined their behavior under varying levels of depolarizing noise. Our investigations spanned from determining the expectation values of a Hamiltonian, defined as a tensor product of Z operators, under different noise intensities to extracting the ground state energy. To bridge the observed outcomes under noise with the ideal noise-free scenario, we trained a Feed Forward Neural Network on the error probabilities and their associated expectation values. Remarkably, our model proficiently predicted the VQE outcome under hypothetical noise-free conditions. By juxtaposing the simulation results with real quantum device executions, we unveiled the discrepancies induced by noise and showcased the efficacy of our neural network-based ZNE technique in rectifying them. This integrative approach not only paves the way for enhanced accuracy in VQE computations on NISQ devices but also underlines the immense potential of hybrid quantum-classical paradigms in circumventing the challenges posed by quantum noise. Through this research, we envision a future where quantum algorithms can be reliably executed on noisy devices, bringing us one step closer to realizing the full potential of quantum computing. © 2024, CC BY.

关键词： Extrapolation

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