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Disruptive Technologies (ICDT), International Conference on

作者： Ritambhara Shailendra Narayan Singh Computer Science & Engineering Amity University Noida Utter Pradesh India Department of Computer Science & Engineering Amity School of Engineering and Technology Amity University Noida Utter Pradesh India

Innovation i.e., the process of new ideas that are useful or effective in different types of domains. Innovation should be taught in schools, homes, and other extra places. Innovative will be increased or improved with the help of Education Data Mining (EDM), which will improve the quality of Information. By employing BERT- type, objectives are to train representation from sequence process data, then fine-tunes these representations on subsequent prediction tasks, by WEKA and machine learning algorithms. In addition, we investigated students’ performance in exams using machine learning and symmetry-based learning algorithms. This article highly predicts female students pass more than boys students.

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Comprehensive Examination of Machine Learning Methods for Predicting Software Errors

Comprehensive Examination of Machine Learning Methods for Pr...

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2024 International Conference on Intelligent and Innovative Practices in engineering and Management, IIPEM 2024

作者： Kittusamy, Lingarasu Diwan, Tarun Dhar Madan, Parul Khatkale, Pravin B Vishnoi, Ankit Kaushik, Keshav Compunnel Inc 103 Morgan Ln #102 Plainsboro TownshipNJ08536 United States Atal Bihari Vajpayee University Bilaspur India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttarakhand Dehradun India Sanjivani University Maharashtra Kopargaon India Amity University Amity School of Engineering and Technology Punjab Mohali India

ISBN: (纸本)9798350390049

This paper presents a comprehensive examination of machine learning methods for predicting software errors, emphasizing the importance of algorithm selection, data quality, and class imbalance in the development process. The study analyzes various machine learning classifiers - including Support Vector Machine (SVM), C4.5, Logistic Regression (LR), Ripper, Instance-Based learner (IBk), Random Forest (RF), and Naive Bayes (NB) - and evaluates their performance under varying conditions of data imbalance, measured by the Matthews Correlation Coefficient (MCC). The findings reveal significant variability in classifier performance, highlighting the challenges associated with predictive modeling in imbalanced datasets. The research contributes to the field of software engineering by proposing a framework for integrating machine learning into software development workflows, aiming to enhance software reliability and mitigate the impact of errors in production environments. © 2024 IEEE.

关键词： Adversarial machine learning

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Design and Implementation of Array Multiplier using Compressor for Low Power

Design and Implementation of Array Multiplier using Compress...

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2022 International Conference for Advancement in technology, ICONAT 2022

作者： Kumar, Prashant Rai, Lalit Gupta, Neeraj Gupta, Rashmi J. C. Bose University of Science Technology YMCA Faridabad Dept. of Electronics Communication Engineering Faridabad121006 India Amity School of Engineering Technology Amity University Haryana Dept. of Computer Science Engineering Gurugram122413 India

ISBN: (纸本)9781665425773

Multiplication is an imperative part of Image Processing, and Digital Signal Processing (DSP) applications. The high speed is required in processing that is achieved by using Parallel Array Multiplier. In this paper, a conventional Array Multiplier is compared with conventional m:2 and m:3 compressor. The comparison of device utilization summary, memory used, delay and power for conventional array multiplier and compressor design is also presented in the paper. A new hybrid 16x16 bits multiplier that use both compressor module m:2 and m:3 has been proposed to achieve the benefits of both. The synthesizable structural VERILOG code is used to simulate and implement different architectures of multiplier. © 2022 IEEE.

关键词： Adders

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Development of Cloud based Smart Voice Assistant using Amazon Web Services

Development of Cloud based Smart Voice Assistant using Amazo...

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Applied Artificial Intelligence and Computing (ICAAIC), International Conference on

作者： Shambhavi Chauhan Deepak Arora Department of Computer Science and Engineering Amity School of Engineering and Technology Lucknow Amity University Uttar Pradesh India

Voice assistants can interpret what the user is most likely to want by deciphering questions that have been framed in a variety of different ways. Natural language interfaces are the predominant emphasis of voice assistants using AWS. The product category has come to be defined by the personal assistants that can communicate in own language and on a human level. The distribution of assistants to various computer devices has been affected by this emphasis on natural language interface. Finally, there are countless opportunities to enhance the Software. The proposed work conducted thorough a review of recent literature for this paper. This study looked at a number of articles from the past three years that discuss the use of voice assistants in the healthcare industry. Finally, the paper presented a web application called “Medico” which is a smart voice assistant with its applications in the medical sciences. It is an application created with Neo4j and AWS services connected. The primary motivation for creating this application was to use a smart voice assistant to help patients with their questions. While doctors can inquire about patients' medical history, including past ICU visits, diagnoses, and treatments received, individuals can only access their own medical information and not those of others. In addition, using the Neo4j Graph Data science Library, “Medico” may make basic treatment recommendations for specific patients.

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Design and Implementation of Real Time Image Retrieval System for De-Noising Space Images in Chandrayaan 3 Lunar Mission Using Autoencoders

Design and Implementation of Real Time Image Retrieval Syste...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Prince Shubham Pallab Banerjee Kanika Thakur Biresh Kumar Dipta Mitra Kumar Gaurav Department of Computer Science Engineering Amity University Ranchi Jharkhand India Amity School of Information Technology Amity University Ranchi Jharkhand India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

In the context of the Chandrayaan 3 Lunar Mission, this research paper introduces a real-time image retrieval and denoising system powered by autoencoders, designed to tackle the challenge of noisy space imagery. Leveraging advanced deep learning techniques, our system employs autoencoders to extract essential features from the noisy lunar images and subsequently retrieves and integrates similar, noise-free reference images from a comprehensive database. By doing so, it achieves real-time denoising, ensuring that the mission’s acquired lunar images are of high quality, thus facilitating more accurate scientific analysis. The paper details the architecture of the autoencoder-based denoising system, its training process using a meticulously curated lunar image dataset, and its seamless integration into the mission’s image processing pipeline. Experimental results underscore the system’s remarkable noise reduction capabilities, thereby playing a pivotal role in enhancing the Chandrayaan 3 mission’s scientific contributions, ultimately advancing our understanding of the lunar environment and bolstering the success of lunar exploration endeavours.

关键词： Deep learning Training Space missions Moon Noise reduction Autoencoders Image retrieval Feature extraction Real-time systems Noise measurement

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Smooth Imaging System Using Learning Generative Adversarial Network 5th

Smooth Imaging System Using Learning Generative Adversarial ...

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5th International Conference on Recent Developments in Control, Automation and Power engineering, RDCAPE 2023

作者： Saraswat, Shipra Rani, Kajal Kanotra, Ishita Singh, Aditya Kumar Amity School of Engineering and Technology Amity University Noida Noida India Department of Computer Science and Engineering ABES Institute of Technology Affiliated to AKTU Uttar Pradesh Lucknow Ghaziabad India

ISBN: (纸本)9789819600465

A method for smoothing the blur images by deblurring them using GAN is discussed in the paper. The method includes learning techniques to detect the type of filters applied to the image, all possible edges present in the image and counting all those details into account. This method makes assumptions about the filters on the image and uses techniques to de-filter all the affected pixels. This method can also handle the unconstrained blurs caused due to overexposure, underexposure, shaking of the camera lens, zooming of pixels and optical noise. Due to these unconstrained measures of the photograph, the image becomes blurred or semi-blur. The proposed method also focuses on constrains of prior information about blurring filters and parametric definitions of filters used. This method detects all possible blurred edges in its own way using the contrast of all blurry areas. The colour contrasts of blurred images are different from that of deblurred images. Also, it can work on both single-frame and multi-frame scenarios. The constrained parameters of the blurry areas in multi-frames are used in achieving improved quality images. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Discriminators

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Role of Predictive Data Analytics to Assess Long Term Impacts of Disaster 5

Role of Predictive Data Analytics to Assess Long Term Impact...

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5th International Conference on Information Systems and computer Networks, ISCON 2021

作者： Mishra, Shailendra Kumar Rahamatkar, Surendra Amity School of Engineering and Technology Amity University Raipur Department of Computer Science and Engineering Chhattisgarh India

ISBN: (纸本)9781665403412

Disaster management is one of the promising fields in research where future predictions and their effects are suggested based on the processing and analysis of historical data sets. Analyze and detect the long-term effects of a disaster is a very crucial and challenging task. At present, the governments, as well as private agencies, are facing a lot of difficulties while analyzing the disaster data. Because of that assessment of long-term effects for various parameters affecting education, job, employability, agriculture, social, etc., and also the impact on peoples living in those areas are difficult to analyze. This paper uncovers the framework to assess the long-term effects of disaster using trending Machine Learning algorithms i.e., XG Boost algorithms, Modified Random Forest, Modified SVM. The proposed framework analyzes the historical disaster data sets, its effects and predicts the impacts on various factors in case of occurrence of a similar disaster in the present scenario. This framework will also recommend the tentative safety measures and future impacts to the concerned authorities in case of a plausible disaster. At last, outcomes of the proposed framework will provide long-term impact analysis and recommendations through comparative analysis with different parameters which are derived from historical data sets. © 2021 IEEE.

关键词： Disasters

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Enhancing Driver Safety with Transfer Learning based Deep Learning Models for Drowsiness Detection

Enhancing Driver Safety with Transfer Learning based Deep Le...

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Electrical Electronics and Computing Technologies (ICEECT), International Conference on

作者： Stuti Dutta Deepak Arora Shivam Tiwari Amity School of Engineering and Technology Amity University Lucknow Uttar Pradesh India Department of Computer Science & Engineering Sharda University Greater Noida India

ISBN: (数字)9798350378092

ISBN: (纸本)9798350378108

In response to the escalating concern over road accidents due to driver drowsiness, this research delves into enhancing drowsiness detection systems using advanced deep learning techniques and transfer learning. Prior investigations have explored conventional methods, yet they often lack the precision demanded by real-world scenarios. Leveraging convolutional neural networks (CNNs) alongside model fine-tuning and transfer learning, our methodology aims to optimize drowsiness detection accuracy. Through rigorous experimentation, we achieved compelling results, showcasing significant enhancements in accuracy across various CNN architectures. For instance, with Max Pooling and 2 Dense layers, one of our CNN models achieved an accuracy score of 1 at epoch 2, with a remarkably low loss of 6.622934e-12, all while taking only 2.6648 seconds for training. These outcomes underscore its potential to revolutionize driver safety systems, offering promising avenues for future research and implementation in real-world contexts.

关键词： Deep learning Training Electric potential Accuracy Road accidents Transfer learning Neural networks Safety Convolutional neural networks Vehicles

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IoT in Health Care: Architectural Explorations, Pandemic Perspectives, and Future Horizon 5th

IoT in Health Care: Architectural Explorations, Pandemic Per...

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5th International Conference on Computing, Communications, and Cyber Security, IC4S 2023

作者： Arshi, Oroos Chaudhary, Aryan Chhabra, Gunjan Kaushik, Keshav Singh, Rashmi Bhardwaj, Neha School of Computer Science University of Petroleum and Energy Studies Uttarakhand Dehradun India BioTech Sphere Research Kolkata India Department of CSE Graphic Era Hill University Dehradun Dehradun India Graphic Era Deemed to Be University Uttarakhand Dehradun India Amity School of Engineering and Technology Amity University Punjab India Amity Institute of Applied Sciences Amity University Uttar Pradesh Noida India Sharda School of Basic Sciences and Research Sharda University Greater Noida India

ISBN: (纸本)9789819773701

The integration of IoT in health care is a game changer, transforming patient care, clinical workflows, and health management. Its significance stems from the ability to monitor patient vitals in real time, share data seamlessly, and make informed decisions. This work is an attempt to investigate the integration of Internet of Things (IoT) technologies within healthcare systems. It offers insights into its architectural underpinnings, pandemic applications, and future horizons. It explores the essential elements and system architectures specific to healthcare IoT, followed by an examination of current applications and their significance amidst the COVID-19 pandemic. Through a comprehensive review, this paper analyzes the technological landscape of IoT in health care during the pandemic, highlighting key innovations and their implications for patient care. It also provides a case study, including Philips Healthcare’s Care Coordinator, to provide practical insights into IoT-enabled healthcare solutions and their effectiveness. However, the paper also highlights challenges such as privacy concerns and interoperability issues that hinder the widespread adoption of IoT in health care. By providing a multidimensional perspective, this paper contributes to a deeper understanding of IoT’s role in reshaping healthcare delivery, emphasizing its potential to address critical challenges and shape the future of healthcare systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： COVID-19

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Critical management in India: special reference to Jharkhand

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DECISION 2025年 1-8页

作者： Bharadwaj, Preeti Aagneya Alias Avani Chakravarty, Soumitro Prasad, Umesh Amity School of Business Amity University Jharkhand Ranchi India Department of Management Birla Institute of Technology Mesra Ranchi India Department of Computer Science and Engineering Birla Institute of Technology Mesra Ranchi India

This paper aims at comprehending the critical management accounts in a unique but one of the poorest states of India: Jharkhand; since all of the hegemonic critical management education derives from the Western business school curriculum. The paper is conceptual in nature, is based on secondary sources, and utilizes a historical approach and the authors’ regional familiarity. The authors, on the basis of the secondary examination of available information, propose that, utilizing the extant theories of critical management for bringing Jharkhand at an appropriately even level of self-sustainability and holistic development is questionable. Therefore, the need of the hour is to reduce the influence of the Western theories of management on the current business school curriculum in Jharkhand; and gradually, incorporate local knowledge in the same. The paper looks at the importance of decolonizing and indigenizing education from the point of view of a poverty-stricken region, and also, how this brings out the related difference in the definition of ‘critical’ for a region.

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