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Dynamic Price Management System in a Distributed Cloud Environment 6

Dynamic Price Management System in a Distributed Cloud Envir...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Anand, Gurjapna Vashisht, Priyanka Singh, Simar Preet Amity University Department of Computer Science and Engineering Haryana India School of Computer Science and Technology Bennett University Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350304480

With the increase in the number of e-commerce applications on the internet, the demand and supply of commodities have increased. Though a static pricing system can be used in today's evolving market, prices of a commodity ought to be dynamically updated to improve revenues. The main challenge is to design a system dealing with real-time price updating based on the analysis of the available and complex data. The fundamental challenge is to design a dynamic price management system that meets the demand of customers and the availability of a commodity to maximize revenues with minimum cost and time involvement. In this paper, a Dynamic price management system (DPMS) for a flexible and connected smart nation has been designed to control and monitor the pricing of a commodity from selling platforms like retail, wholesale, the company's website, and e-commerce. Enormous pricing management system models have been researched, but in this paper, our objective is to provide a flexible, versatile, and intellectual pricing management system that handles the pricing of a commodity through a single interface for all the selling platforms. Smart pricing is the dynamic adjustment of prices or repricing of a commodity based on the market demand for a product. This model simplifies the vendors'problem of controlling a homogenous commodity's price component on different selling platforms like retail, wholesale, and e-commerce for a fully connected smart nation. © 2023 IEEE.

关键词： catalogue management cloud-based dynamic price model distributed cloud e-commerce pricing management smart nation

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Human Pose Estimation using Deep Learning Techniques 4

Human Pose Estimation using Deep Learning Techniques

引用

4th International Conference on Information Management and Machine Intelligence, ICIMMI 2022

作者： Grover, Anant Arora, Deepak Grover, Anuj Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Uttar Pradesh Lucknow Campus India

ISBN: (纸本)9781450399937

Human Pose Estimation is a method of detecting and classifying all the key human body joints. A 2D Human Pose Estimation method predicts the two-dimensional coordinates from an input image. Classical methods used deformable parts models for detecting body joints. This paper discusses the state-of-the-art Deep Learning based approaches for estimating human poses. It can be implemented by either using the top-down or bottom-up technique for pose estimation. Here, the authors have studied the Convolutional Pose Machines, Hourglass Network and MoveNet architectures for Pose Estimation. These architectures are compared against each other in terms of their efficiency by measuring the time taken by each of them and their accuracy by evaluating them using the Percentage of Detected Joints metric on the MPII dataset. The architectures were implemented by using TensorFlow and Open-Source libraries built using PyTorch. The inference results for each joint were compared individually for all the body joints. The Hourglass Network showed the best accuracy but is really slow. The MoveNet architecture is the second best according to accuracy but is very fast and can be used in real-time systems. © 2022 ACM.

关键词： Real time systems

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Evaluating the Ecological Footprint: Analyzing the Environmental Impact of Battery Energy Storage Systems within Electric Grids 7

Evaluating the Ecological Footprint: Analyzing the Environme...

引用

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

作者： Singh, S. Vikram Hussain, Shaik Saddam Singla, Atul Balaram, A. Bargavi, Y. Krishna Gowtham Raj, R. Amity University Amity School of Engineering & Technology Greater Noida India Vnr Vignana Jyothi Institute of Engineering and Technology Department of Computer Science & Engg Telangana Hyderabad India Lovely Professional University Phagwara India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Griet Department of Cse Bachupally Telangana Hyderabad India New Horizon College of Engineering Department of Mechanical Engineering Bengaluru India

ISBN: (纸本)9798350350067

This research paper shall cover a detailed assessment of the overall ecological impact of BESS within electric grids, which becomes a critical component if grid reliability is to be improved, renewable energy integration advanced, and the pledging of attainment of sustainable energy served. In this interdisciplinary study, life cycle analysis and environmental impact assessment in regard to conventional energy storage solutions will be integrated with comparative methods. The BESS focus is on quantifying emissions, resource depletion, and ecological disturbance, respectively, at various stages of manufacturing, operation, and end-of-life. Further, design mitigation strategies for reducing negative environmental impacts through the discussion on the role of recycling and second-life uses for used batteries. Results show that while BESS offers huge benefits in mitigating GHG by allowing greater integration of renewable energy sources, they have associated environmental-related problems with resource extraction and end-of-life wastes. Broad environmental legislation in new technologies is called for to be put in place for the improvement of the sustainability profile of BESS. The present work looks, with a balanced view, at the environmental benefits and global sustainability challenges connected with the deployment of BESS in electric grids. © 2024 IEEE.

关键词： Life cycle assessment

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Data-Driven Healthcare Management, Analysis, and Future Trends

Data-Driven Healthcare Management, Analysis, and Future Tren...

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

作者： Das, Lipsa Kumar, Ankesh Sharma, Vikrant Bhatnagar, Devang Singh, Sumit Tripathi, Nandita Amity School Of Engineering & Technology Amity University UP Greater Noida India Amity University UP Greater Noida India Computer Science And Engineering Graphic Era Hill University Graphic Era Deemed To Be University Dehradun India Amity Institute Of Information Technology Amity University UP Greater Noida India Allied Sciences Amity University UP Greater Noida India

ISBN: (纸本)9798350366846

Data-driven approaches are revolutionizing healthcare management and analysis, offering insights into patient care, operational efficiency, and future trends. The sum of information Big data' is, can do miracles. In the last 20 years, it has become a topic of interest because the potential lies within is enormous. Big Data is produced, stored and examined by several industries of public and private domain with the main aim to enhance their services. Big Data comes from variety of resources in medical industry such as medical patient records, test reports, and IOT medical devices. The large amount of data is generated by medical research which is vital to public healthcare. The data must be appropriately organised and analysed to obtain useful information. Else, finding solution through big data analysis will be like looking for needle in haystack. Set of difficulties frequently occur at every phase of managing Big Data which can only be overcome by installing advanced computer systems for its analysis. This paper examines the relationship between data science and healthcare with an intent to use complex metrics to make intelligent and accurate decisions. Important areas are data-driven approaches for enhancing medical administration, recognizing new developments influencing healthcare evolution, and the methods for evaluating large sets of medical data. By incorporating the data-driven techniques, the medical industry might able to improve the patient health, optimize operations and adjust to current as well as to continuously evolving situations. © 2024 IEEE.

关键词： Big data

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Energy Harvesting from Railway Tracks: Technologies and Applications 2

Energy Harvesting from Railway Tracks: Technologies and Appl...

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2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Saxena, Abhishek Reddy, Y Manohar Yadav, Suman Avdhesh Rajalakshmi, B. Gupta, Manish Jabbar, Kadim A. Abes Engineering College Department of Mechanical Engineering UP Ghaziabad201009 India Institute of Aeronautical Engineering Dundigal Hyderabad India Amity University Amity School of Engineering and Technology Uttar Pradesh Greater Noida India New Horizon College of Engineering Department of Computer Science Bangalore India Lovely Professional University Phagwara India National University of Science and Technology College of Engineering Technology Dhi Qar Iraq

ISBN: (纸本)9798350384277

Research on the creative use of kinetic energy in transport infrastructures has been directed by the constant search for sustainable energy solutions. Of them, railway tracks provide a particularly attractive pathway for energy collecting because of their vast network and the significant stresses applied during train movements. The latest technologies created for energy harvesting from railway tracks are explained in this article along with the workings, concepts, and efficiency of the different systems. The ability to transform mechanical stress and vibrations into electrical energy is closely examined in hybrid systems, electromagnetic devices, and piezoelectric transducers. A thorough analysis of the literature highlights both the technical developments and the difficulties, including those related to energy storage, affordability, and durability. In addition, this research investigates the uses of captured energy, which may improve the sustainability of railway systems by powering trackside sensors or adding to the grid. The appropriateness and efficacy of various harvesting systems under various operating circumstances may be inferred from a comparative study of their performance indicators. In order to fully use this renewable energy source, the report concludes by outlining future research areas and highlighting the integration of energy collecting technology with smart railway infrastructure. © 2024 IEEE.

关键词： Railroads

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A Role of Wearable Health technology in Smart Cities 3rd

A Role of Wearable Health Technology in Smart Cities

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3rd International Conference on Computational Electronics for Wireless Communications, ICCWC 2023

作者： Chauhan, Ritu Kaur, Harleen Mehta, Khushi Alankar, Bhavya Artificial Intelligence and IoT Lab Center for Computational Biology and Bioinformatics Amity University Uttar Pradesh Noida India Department of Computer Science and Engineering School of Engineering Sciences and Technology Jamia Hamdard New Delhi India Amity Institute of Biotechnology Amity University Uttar Pradesh Noida India

ISBN: (纸本)9789819719426

In this rapidly changing era of the world, healthcare devices are revolutionizing, which enables the continuous measurement of crucial biological markers for diagnostic purposes, physiological health monitoring, and evaluation. Hence, wearable devices have transformed into accessories, embedded clothing, body adaptors, and body implants. Additionally, the emergence of wearable healthcare devices that facilitates the diagnosis and prognosis by using tiny sensing devices and biomedical devices has greatly enhanced the efficiency as well as the quality of medical care facilities results in the tremendous advancements in semiconductor technology, biomedical technologies, and nano-sized materials over the past few decades. Meanwhile, the devices could provide real-time feedback, allowing users to analyze their health and monitor in a specific period that has been assigned to the smart wearable devices, even though the industries and manufacturers are intensely interested in interpreting the factors that influence the adoption of new smart technologies, which helps to improve the performance and viability of wearable devices to fascinate consumers. Hence, the advancements in technology are regarded as trustworthy equipment for everlasting monitoring of health that are frequently used to monitor and control a diverse of health tracking predictors in the surroundings, including monitoring health and wellness of the body. In recent years, it has been focused on the study of a wide range of parameters closer to advancements in smart technology. As a result, these smart devices are now utilized in a variety of healthcare monitoring applications, one of the most crucial aspects of data collection is the various factors based on bodily activities. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electronic health record

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Artificial Intelligence as Automated technology for Prediction of Breast Cancer 3rd

Artificial Intelligence as Automated Technology for Predicti...

引用

3rd International Conference on Computational Electronics for Wireless Communications, ICCWC 2023

作者： Chauhan, Ritu Kaur, Harleen Choudhary, Tisya Alankar, Bhavya Artificial Intelligence and IoT Lab Center for Computational Biology and Bioinformatics Amity University Uttar Pradesh Noida India Department of Computer Science and Engineering School of Engineering Sciences and Technology Jamia Hamdard New Delhi India Amity Institute of Biotechnology Amity University Uttar Pradesh Noida India

ISBN: (纸本)9789819719426

Artificial intelligence techniques are utilized in cancer research and oncology which involves medical data in the detection of cancer, subtype classification, and optimization of cancer treatment. This paper discusses artificial intelligence techniques, such as K-means cluster analysis and its data interpretation based on breast cancer diagnostic dataset. This study focuses on the database of digital images of fine needle aspirate (FNA) of breast mass which shows abnormal lump, and a clustering technique was applied on this dataset. This study represents various descriptive statistics techniques of the breast cancer diagnostic dataset. Furthermore, we have also tried to show a variety of techniques of descriptive statistics like KMO and Bartlett’s test, total variance representing initial eigenvalues and extraction sum of squared loadings, scree plots, and clustering techniques like ANOVA table, initial and final cluster centers, and the distance between initial and final cluster centers of K-means cluster analysis. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Lung cancer

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Advanced Strategies for Mitigating Anomalies in Vehicular Ad-Hoc Networks (VANETs)

Advanced Strategies for Mitigating Anomalies in Vehicular Ad...

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International Conference on Signal Processing and Communication (ICSC)

作者： Thuvva Anjali Rajeev Goyal Balaji G. N Computer Science and Engineering Amity School of Engineering and Technology Amity University Gwalior India Computer Science and Engineering School of CSE Vellore Institute of Technology Vellore India

ISBN: (数字)9798331511890

ISBN: (纸本)9798331511906

Vehicular Ad-Hoc Networks are emerging as critical infrastructure components in intelligent transportation systems, enabling seamless communication between vehicles and roadside units. These vulnerabilities can compromise the safety, reliability, and efficiency of the entire network, necessitating advanced strategies for anomaly detection and mitigation. Vehicular Ad Hoc Networks have evolved as an important component of intelligent transportation systems, improving traffic safety and efficiency. However, because to their dynamic and open nature, Vehicular Ad Hoc Networks are vulnerable to a variety of security vulnerabilities, including anomalies that can interrupt normal network operations. This work focuses on a complete analysis and assessment of several anomaly detection techniques in the context of Vehicular Ad Hoc Networks. Vehicular ad hoc networks allow wireless communication between automobiles and vehicle-to-infrastructure systems. The fundamental purpose of Vehicular Ad Hoc Networks is to improve roadway safety, comfort, and convenience. Vehicular Ad Hoc Networks differ from ad hoc networks in several ways. However, the lack of infrastructure and centralized administration renders them vulnerable to misbehavior, posing a severe danger to many elements of Vehicular Ad Hoc Networks. Given its importance, this important network requires strong security measures to maintain secure communication. The suggested technique for detecting anomalies and malicious nodes in Vehicular Ad Hoc Networks improves the technique by successfully selecting verifiers to detect malicious nodes, resulting in improved network performance.

关键词： Wireless communication Vehicle-to-infrastructure Vehicular ad hoc networks Safety Smart transportation Security Reliability Vehicle dynamics Intelligent transportation systems Anomaly detection

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Artificial intelligence in healthcare: medical named entity recognition based audio prescription generator 23

Artificial intelligence in healthcare: medical named entity ...

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Proceedings of the 5th International Conference on Information Management & Machine Intelligence

作者： Shweta Sinha Tushar Agarwal Pratiyush Pandey Computer Science and Engineering Amity university India Amity school of engineering and technology Amity university India Amity School of Engineering and Technology Amity University India

ISBN: (纸本)9798400709418

Artificial Intelligence has made significant contributions in various aspects and domains of human life, permeating fields such as Education, Healthcare, Economy, Socialization, Security, Agriculture, and Privacy. This research specifically delves into the promising possibilities and applications of AI in healthcare and medical domains, focusing on developing a Medical Named Entity Recognition (NER) model. The proposed approach involves using different pre-trained NER models and an in-house-generated corpora to train a personalized Spacy model. The research then conducts a thorough comparison of these models to understand their strengths and shortcomings. Widening the scope of the proposed research, we introduce an inventive mechanism to extract medical information from doctors' audio in real-time saved on buffer memory, deleted after use, which is then used to create patient medical prescriptions. The potential benefits of this mechanism are vast, expanding beyond reducing patient wait times, enhancing the clarity of prescriptions, maintains comprehensive patient histories, and finally introducing automation into the prescription drug ordering chain. Additionally, the proposed model eases the scheduling and management of medical tests and procedures based on doctor and patient availability. In jist, the proposed paper aims to present an innovative human-centric approach to automating interactions between patients and doctors and optimizing the delivery of healthcare services. Through the integration of modern-day AI services, The proposed mechanism has the potential to bring about a potential change in medical practices, providing a more efficient and effective breakthrough to patient care.

关键词： AI in Healthcare Artificial Intelligence Named Entity Recognition Natural Language Processing

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Keypoint Detection for Identifying Body Joints using TensorFlow 4

Keypoint Detection for Identifying Body Joints using TensorF...

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4th International Conference on Information Management and Machine Intelligence, ICIMMI 2022

作者： Grover, Anuj Arora, Deepak Grover, Anant Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Uttar Pradesh Lucknow Campus India

ISBN: (纸本)9781450399937

Keypoint Detection for the Body Joints is a process of finding and detecting all the important body joints of a human being. It takes an RGB image as input gives a list of keypoints as output. It can be applied for single-person body joints detection or multi-person body joints detection. The various architectures for detecting the human body joints can be compared using the Percentage of Detected Joints (PDJ), Object Keypoint Similarity (OKS) and mean Average Precision(mAP) evaluation metrics. The state-of-the-art body joint detection architectures like DeepPose, Higher Resolution Network and OpenPose architectures were studied and compared against each other. These architectures were evaluated on the COCO dataset for the 17 key body joints using the OKS and mAP evaluation metrics. The evaluation results on all the body joints were compared to each other for each architecture. The architectures were implemented using opensource implementations of the PyTorch and TensorFlow libraries. The HRNet architecture was the fastest and most accurate of all the architectures. © 2022 ACM.

关键词： Network architecture

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