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检索条件"任意字段=4th International Conference on Computational Methods in Science and Technology, ICCMST 2024"

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Big data analytics in healthcare: Applications, examples and challenges 4th

Big data analytics in healthcare: Applications, examples and...

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4th international conference on computational methods in science and technology, iccmst 2024

作者： Kaur, A. Goyal, S. Batra, N. Gupta, N. Ambala Haryana Mullana India Computer Science and Engineering Department CGC-College of Engineering Landran Mohali India

ISBN: (纸本)9781032911571

the healthcare sector is evolving at an exponential rate due to the speed of technological disruption and digital innovation. the size of healthcare data is increasing exponentially, making it more challenging to locate any kind of relevant information. Big data is currently changing how data is delivered traditionally by employing big data analytics techniques to produce insightful knowledge. In the healthcare sector, big data analytics offers numerous advantages, including the ability to identify serious illnesses early on and provide more effective care to the appropriate patient at the appropriate moment, thereby enhancing the standard of care. the quick analysis and integration of massive amounts of different types of data generated by various clinical settings, hospitals, other social media platforms, and medical data lakes is made possible by big data analytics tools. Many challenges must be addressed by the current health data analytics systems, which offer technical means for gathering, combining, processing, analysing, visualising, and interpreting data. this article delves into the intriguing topic of healthcare big data analytics. Due to a dearth of comprehensive study, this topic has not gotten enough attention in the past. this article covers the unique characteristics of big data, big data analysis tools, and the steps the healthcare business takes from data collection to data distribution. © 2025 the Author(s).

关键词： Electronic health record

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A comprehensive review of recent advances and challenges in artificial intelligence and machine learning 4th

A comprehensive review of recent advances and challenges in ...

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4th international conference on computational methods in science and technology, iccmst 2024

作者： Singla, Ishdeep Hans, Aarti Smiksha Diya Swami, Harsh Kumar Ranjan, Rahul Computer Science and Engineering Chandigarh University Mohali Gharuan India

ISBN: (纸本)9781032911571

Modern advances in Artificial Intelligence (AI) and Machine Learning (ML) have transformed many businesses and elements of everyday life. Machine learning and deep learning support disease diagnosis, drug development, and patient risk assessment. this study examines how healthcare organizations evaluate enormous data sets using machine learning. this paper examines pros and downsides of current methods and research obstacles. Our goal is to educate healthcare professionals and government organizations on machine learning-based big data analytics in intelligent healthcare. AIML-powered chatbots enable governments educate and serve residents. they assist people get permits, answer questions, and use government services. Assistants help students make appointments, answer inquiries, and offer course material. Lead generation, product recommendations, and marketing efforts using AIML chatbots may boost revenue. AIML helps companies make data-driven decisions, find patterns, and recognize trends using data analysis and predictive analytics. Machine Learning studies how computers learn and improve without programming. Machine learning (ML) is a very captivating technology that has garnered significant interest over the course of technological advancements. As indicated by its nomenclature, this attribute endows the computer with a capacity that enhances its resemblance to human behaviour: the ability to acquire knowledge. © 2025 the Author(s).

关键词： Adversarial machine learning

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Smart city using blockchain with artificial intelligence 4th

Smart city using blockchain with artificial intelligence

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4th international conference on computational methods in science and technology, iccmst 2024

作者： Gupta, Ayush Gupta, Ritikesh Shukla, Dhirendra Kumar Dagur, Arvind Department of Computer Science Engineering Galgotias University Uttar Pradesh Greater Noida India

ISBN: (纸本)9781032911571

Modern cities all over the world are undergoing significant transformations in order to install stunning architecture, offer smart services to citizens, create a safe, sustainable, and clean environment, and prepare areas for vulnerable populations. the primary driver behind many corporations’ forays into the realms of community development, health, water extraction, sanitation, products and consumption, preserving dynamism, housing, screening, and accessibility is the introduction of new technology. We are investigating these consequences in light of vision and information technology advancements over the years. To resurrect these sectors and build a new, safe, and sustainable megacity, new technology and skills must be made available. this combination offers a thorough comprehension of the societal issues that big cities face. It focuses on two recent technological investigates the potential of blockchain technology and artificial intelligence (AI) to better society. It also looks at the various applications of blockchain and edge AI. We examine the value of walking sweats in the domains of smart mobility and smart dynamism rather than relying solely on an ultra-modern smart megacity. In order to circumvent the law for commercial traffic, it outlines a clever algorithm that uses detection, counting, and speed recognition. It also discusses the usage of blockchain in secure, private information transport and exchange between buses and cars. business knowledge. this study should be read in conjunction with other artificial intelligence research papers that investigate the applications of edge AI and blockchain. © 2025 the Author(s).

关键词： Sustainable city

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Optimizing resource allocation in big data environments through a minimum-cost policy 4th

Optimizing resource allocation in big data environments thro...

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4th international conference on computational methods in science and technology, iccmst 2024

作者： Verma, Rohit Kumar Singh, Sukhvir Department of Computer Science Himachal Pradesh University Shimla India

ISBN: (纸本)9781032911571

When it comes to big data, the smartest thing is often allocating resources through cheapest channel. the latter involves assessing the costs and selecting the cheapest alternatives so as to make informed resource allocation decisions regarding, among others, processing capa bility, storage and network bandwidth. this way businesses can employ Big Data analytics using efficient algorithms for optimum use of resources. To solve the problem of achieving higher ac curacy in cloud computing environmentsfor information management system in terms of resource allocation, authors develop a minimum cost policy approach. It uses big data association mining techniques to come up with an allocation algorithm of resources for an information management system. In this Information Management System, Resource Distribution Data is pooled and re structured based on Keywords and Semantic Connection Features. In the subsequent context of cloud computing, the association rule features are extracted from information management system resources. For example, these derived association rules enable the internal resource allocation of the information management systems by creating a big data training set. the allocation process is enhanced even further with adaptive scheduling and big data association mining, enabling dy namic resource allocation control and optimization. the simulation results confirm the effective ness of this approach in terms of improved information management and resource utilization ef ficiency, which leads to interference mitigation and accurate resource allocation. © 2025 the Author(s).

关键词： Big Data Minimum Cost Resource Allocation Trust Management

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Detection of brain tumor from MRI images using EfficientNet: A deep learning approach 4th

Detection of brain tumor from MRI images using EfficientNet:...

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4th international conference on computational methods in science and technology, iccmst 2024

作者： Sharma, Geetika Sarda, Moksh Malik, Nikhil Singh, Harnoor Mishra, Rahul Grover, Somil Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India

ISBN: (纸本)9781032911571

Brain tumors are either cancerous or noncancerous masses of abnormal brain cells. Meningioma tumor, glioma tumor, and pituitary tumor are the three forms of brain cancers that are examined in this research. One essential diagnostic technique for the identification and diagnosis of brain tumors is brain tumor segmentation. Although manual brain tumor segmentation using MRI is possible, the accuracy and identification are not very good. the classification of abnormalities is a time-consuming task for physicians because it is not predictable and straightforward. However, tumor detection is difficult because tumors have complex appearances and boundary characteristics. In this work, we report on an automated method for detecting and diagnosing brain tumors from MRI images using EfficientNet. Specifically, we developed a preliminary report generation system that automatically provides the type of tumor, its corresponding ICD code, the tumor’s diameter and area, and the original input image with the tumor highlighted for visualization. this will be accomplished through the classification and segmentation of MRI images, with classification using Dense EfficinetNet to identify the tumor type and ICD code and segmentation using EfficientNet UNet to visualize the tumor and determine its diameter and area. A preliminary report for our paper is being created, which will use one MRI image of a brain tumor to diagnose tumor diameter and tumor area. © 2025 the Author(s).

关键词： Magnetic resonance imaging

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Features enhancement of micro-service based cab booking system using block-chain 4th

Features enhancement of micro-service based cab booking syst...

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4th international conference on computational methods in science and technology, iccmst 2024

作者： Rohit Singh, Neelaksh Shukla, Riya Singh, Ashutosh Kumar Department of Computer Science and Engineering Institute of Engineering and Rural Technology Prayagraj India Department of Computer Science and Engineering United College of Engineering and Research Prayagraj India

ISBN: (纸本)9781032911571

Cab booking services help people order taxis. Existing cab booking services use client server-based architecture. the paper gives a study of the architecture and workings of the Uber cab booking website (Dissanayake, March 18, 2021). It has a micro-service based architecture (Li et al. 2021). Load balancing (Al-Jaroodi et al. 2012) and stream processing (Besnard et al. 2013) are used to handle a large number of requests. the workload is divided among servers using Dispatch Optimization (Abid et al. 2022). It ensures fast responses, easy connection minimal downtime, and efficient use of resources. However, the use of servers increases the cost of service. Rider and driver depend on the server to connect. they don’t know if the system is charging them fairly. It reduces transparency and trust. the paper proposes a blockchain-based cab booking application to solve some of the problems. Trust, transparency, and decentralization can be ensured using blockchain. Transparent and immutable ledgers of blockchain ensure trust and reduce reliance on intermediaries. Smart contracts govern ride management, optimizing efficiency. Blockchain capabilities are used to ensure fair rides, direct interaction of passengers with drivers, and automated payments. the proposed system aims at combining existing technology with blockchain solution to ensure security and transparency along with scalability and quick response time. © 2025 the Author(s).

关键词： Reservation systems

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Mustard and wheat mildew disease classification using deep learning 4th

Mustard and wheat mildew disease classification using deep l...

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4th international conference on computational methods in science and technology, iccmst 2024

作者： Mishra, Prashant Kumar Singh, Jagrati Gautam, Prateek Raj Centre for Advanced Studies AKTU Lucknow India Indira Gandhi Delhi Technical University for Women Delhi India School of Computer Science UPES Dehradun India

ISBN: (纸本)9781032911571

this research presents a new tactic for the categorization of mustard and wheat mildew diseases through the appliance of sophisticated deep learning techniques. the proposed method employ complicated convolutional neural network (CNN) to examine and classify images illustrating plant leaves afflict by mildew diseases. Focusing on reasonably considerable crops like mustard and wheat, the research aims to present a consistent and proficient solution for the early classification and control of mildew outbreaks in farming environments. the introduction of our project involves congregation a complete dataset that includes images of both healthy and mildew-affected wheat and mustard leaves. To make sure a reliable input for the deep learning network, the dataset undergoes thorough preprocessing, including scaling, normalization, and expansion. the outcome of the experiment highlights the efficiency of the planned deep learning approach, achieving a noteworthy classification correctness of 98.76%. this remarkable correctness underscores the model’s robustness in distinguishing among healthy and mildew infected plant leaves, underscore its prospective as an important tool for early disease revealing and incorporation into precision cultivation practices. through an evaluation with modern models within the applicable body of research, our method established superior accuracy in its appraisal when evaluated. Our study contributes to the development of systems devoted to precise and programmed analysis of plant diseases. Such systems can improve agricultural efficiency and guarantee food security. © 2025 the Author(s).

关键词： Convolutional neural networks

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Emotion detection: Facial emotion detection using ML 4th

Emotion detection: Facial emotion detection using ML

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4th international conference on computational methods in science and technology, iccmst 2024

作者： Sharma, Sharad Chauhan, Ritik Vajpayee, Pooja School of Computing Science and Engineering Galgotias University Greater Noida India

ISBN: (纸本)9781032911571

Cognitive perception of images is an intense task, like guessing the truth of a thought or a mystery. In this process, we use different methods to solve the need to know the job. In recent years, emotional intelligence has received widespread attention due to its important role in improving human-computer interaction and emotional analysis. Because of its processes for extracting visual features, deep neural networks-particularly convolutional neural network (CNN)-are frequently employed in FER. A lot of research has been done on CNN, but only a few areas have solved the facial recognition (FER) problem. After many reports and studies, the shortcoming of most existing models is that they often consider the front profile and ignore the side profile of the current image, although different angular views are also important for the perspective model. this helps you make informed decisions about personal needs, providing support, or security threats. However, this proved to be too complex for computers, and feature extraction needed a wide range of image processing methods. Numerous machine learning techniques are appropriate for this particular purpose. To use machine learning for any kind of detection, an algorithm must first be trained and then tested on relevant data. this article examines some machine learning algorithms and strategies for extraction that aid in the analysis of human emotion. this review contains a comprehensive review of a variety of materials, methods, and measures commonly used in psychology research. It also highlights the challenges and limitations of current models, including dealing with uncertainties and cultural differences. Face recognition in large datasets poses additional challenges due to the diversity of images as well as the differences between side and front views. © 2025 the Author(s).

关键词： Convolutional neural networks

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ResNet-50: A breakthrough in plant disease detection accuracy for agricultural empowerment 4th

ResNet-50: A breakthrough in plant disease detection accurac...

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4th international conference on computational methods in science and technology, iccmst 2024

作者： Khan, Shadab Yadav, Anil Kumar Shukla, Shiv Shankar Prasad Shende, Vikas School of Computing Science and Engineering VIT Bhopal University Bhopal-Indore Highway Kothrikalan Madhya Pradesh Sehore India Madhya Pradesh Council of Science & Technology MPCST Madhya Pradesh Bhopal India

ISBN: (纸本)9781032911571

Agriculture is integral to the economy of every nation, providing essential crops for consumption. Identifying plant diseases is imperative for sustaining agricultural growth. Early detection of these diseases is vital to ensure a thriving and productive agricultural sector, preventing both financial losses and resource depletion. Crop farmers experience significant setbacks annually due to the impact of various diseases on their plants. Deep learning technology presents a promising solution to mitigate crop failure by enabling timely detection of diseases in plant leaves. In this research, the performance of Convolution Neural Network (CNN), Visual Geometry Group (VGG-16), DenseNet-121, and Residual Network (ResNet-50) models is evaluated using a new plant disease dataset containing 87,000 RGB images to identify crop infections. the accuracy rates obtained were 94.60% for CNN, 92.49% for VGG-16, 95.73% for DenseNet, and 98.67% for ResNet-50, demonstrating ResNet-50 superior performance. this application aims to aid farmers in diagnosing plant diseases simply looking at images of plant leave. Leveraging the ResNet-50 transfer learning model, the application distinguishes between both diseased and healthy leaves, accurately identifying the specific disease present. the objective is to empower farmers to conserve resources and minimize economic losses through early disease detection and the implementation of appropriate treatment measures. © 2025 the Author(s).

关键词： Plant diseases

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Enhancing data security through an integrated approach of multiple key cryptography and steganography in the wavelet domain 4th

Enhancing data security through an integrated approach of mu...

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4th international conference on computational methods in science and technology, iccmst 2024

作者： Hashem, Al-Fariji Ahmed Hussein Medvedeva, Marina A. Agbozo, Ebenezer Department of Big Data Analytics and Methods of Video Analysis Ural Federal University Ekaterinburg Russia

ISBN: (纸本)9781032911571

the quantity of data that may be incorporated and the picture quality must be compromised in order to embed data within an image. As a direct result of this increased distortion, the quality of the stego picture that is generated when more data is hidden within a carrier image will decrease. One thing may be taken into consideration is the difficulty of optimizing the process of embedding a substantial amount of data into an image. this article aims to provide an overview of the many methods of picture steganography and to present the several attempts that have been made to achieve image steganography via the use of deep learning and machine learning techniques. this work concluded with several potential directions for future photo steganographic-based deep learning research, and it indicated that these new directions may be investigated soon. the suggested approach ensures that even comparable letters are encrypted differently by encrypting data using a series of pseudorandom keys created from a single 16-bit seed. By using this strategy, the communication is not only more hidden but also safer against attempts at unauthorized decryption. After encryption, matrix encoding, which is made feasible by discrete wavelet transformation, embeds the encrypted data into the high-frequency sub-band of a cover image. the robust Peak Signal-to-Noise Ratio (PSNR) readings, which often exceed the 40 dB threshold, attest to the cover picture’s preservation as a result of this steganographic technique. these PSNR values, which exhibit relatively minimal optical distortion, will make the stego-image unnoticeable. In tests of performance, the proposed method demonstrated excellent imper-ceptibility, with PSNR values continuously over 46 dB and a low Bit Error Rate (BER) of around 3%, indicating a high degree of fidelity in the recovered data. © 2025 the Author(s).

关键词： Discrete wavelet transforms

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