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A Method for Predicting Cardiovascular Disorder using Machine Learning Techniques

A Method for Predicting Cardiovascular Disorder using Machin...

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2024 IEEE International Conference on Recent Advances in science and engineering technology, ICRASET 2024

作者： Hegde, Ramakrishna Pavithra, D.R. Shivashankara, S. Prasanna Kumar, G. Soumyasri, S.M. Nagashree, S. Vidyavardaka College of Engineering Affiliated to Visvesvaraya Technological University Belagavi India Jss Science and Technology University Sri Jayachamarajendra College of Engineering Mysuru India Kr Pete Krishna Government Engineering College Krishnarajapet India The National Institute of Engineering Mysore India Dept. of Computer Applications Vidya Vikas Inst. of Engg. and Tech. Affiliated to Visvesvaraya Technological University Belagavi India Vidya Vikas Institute of Engineering and Technology Mysuru India

ISBN: (纸本)9798350388602

Drastic increase of cardiovascular disease has led to a lot of adult's death. As per 'News 18' very year, 12 million young people in India die from heart disease. In most of these cases people experience cardiac arrest, some of which are normal. First, families of patients are vulnerable because it takes only a few minutes for a person to die of a heart attack, and it is difficult to get medical help in time. Second, most victims are under the age of 45. According to Dr. Maninder Sandhu, cardiologist and cardiologist at Artemis Hospital Gurgaon, 30 percent of people who suffer from heart disease are under the age of 45. This paper proposes a method that maybe used by laboratory technicians, doctors and users to understand whether there are any chances of having cardiovascular disease or not. The proposed system takes live data of patients and their lifestyle attributes these data are processed by the trained model to produce the output. In this model we haveused random forest classifier, linear regression, k-neighbors classifier & x gradient boost classifier. This model has attained maximum accuracy and least type one error in 'X- Gradient Boost'. We have concentrated more on type one error. The developed system shows whether the patient has any chances of cardiovascular disease or not. © 2024 IEEE.

关键词： Random forests

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IoT Enabled Water Flow Management and Monitoring System for Hydroelectric Power Generation

IoT Enabled Water Flow Management and Monitoring System for ...

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Decision Aid sciences and Application (DASA), International Conference on

作者： Abu Salman Shaikat Rumana Tasnim Jahid Hasan Md Zonayed Molla Rashied Hussein Shaekh Mohammad Shithil Abdullah Al Amin Dept. of Bharti School of Engineering and Computer Science Laurentian University of Sudbury Ontario Canada Dept. of Mechatronics Engineering World University of Bangladesh Dhaka Bangladesh Dept. of Mechanical Engineering Dhaka University of Engineering & Technology Dhaka Bangladesh Dept. of Computer Science & Engineering University of Asia Pacific Dhaka Bangladesh Dept. of Mechanical Engineering University Technology Malaysia Kuala Lumpur Malaysia

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

Water energy sources play a crucial role, particularly in providing electrical energy through hydroelectric power. Both the water flow rate and the water head determine the potential energy available from water. The hydroelectric system's energy generation directly depends on the water flow rate. A lower flow rate means less water is available to generate energy, even if the head is high. It is essential to increase the potential of the water flow so that it can generate enough electricity. Traditionally, the flow rate is restricted due to the limited capacity of single penstock. This work addresses this issue by introducing multiple penstock-based water flow management systems. Also, conventional water flow monitoring systems often face limitations, like relying on manual measurement, as it only provides periodic data, making it difficult to respond quickly to changes in flow conditions. IoT-based flow sensors leverage IoT technology to monitor water flow and transmit flow data in real-time, enabling operators to detect fluctuating flow conditions and implement timely adjustments to processes, therefore enhancing the overall efficiency. This work aims to design and develop an IoT-enabled prototype hydroelectric power generation system using multiple water flows for enhancing power generation efficiency. The prototype indicates the use of multiple pipes as penstocks in a dam. Additionally, if generating a significant amount of electricity is not required, the water flow can be discontinued, thereby automatically closing each pipeline. This work uses flow sensors, Kitsware software, Arduino IoT Cloud, and an LCD display to generate flow measurement data every ten seconds from multiple pipelines. Moreover, the system automatically generates Excel data and graphically represents multiple water flows, enabling the user to compare the water flow data. The completed work resulted in a hydropower system demonstrating enhanced output and effective compatibility with IoT for

关键词： Machine learning algorithms Pipelines Hydroelectric power generation Prototypes Production Real-time systems Software Sensors Software measurement Monitoring

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Unlocking the Mysteries of Speech: A Hybrid RNN-CNN Model for Vocal Language Identification

Unlocking the Mysteries of Speech: A Hybrid RNN-CNN Model fo...

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IEEE Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)

作者： Ganeshayya Shidaganti Pathanjali Harebailu Kishore Kumar K Mohammad Akmal Nagesh D Dept. of Computer Science and Engineering M.S. Ramaiah Institute of Technology Bangalore Karnataka India

Speech is the primary form of communication, and being able to identify the language used in an audio sample is crucial in numerous fields. Language identification serves a purpose in speech recognition, language translation, voice assistants, and many other domains. Traditional language identification systems rely on statistical or acoustic models, which frequently require extensive domain-specific knowledge and have limitations in accuracy and resilience. By employing a hybrid Recurrent neural network and Convolutional Neural Network, this paper aims to develop a novel method of language identification. The suggested approach entails spectrogram preprocessing of audio samples, Mel-Frequency cepstrum coefficient extraction, and Convolutional Neural Network and Recurrent neural network architecture model training on a sizable dataset. Recurrent neural networks are good at capturing temporal dependencies in data, while Convolutional Neural Networks are better at capturing spatial patterns. This methodology successfully identifies the languages with an overall accuracy of 93%, proving the efficacy of the proposed model.

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Evolutionary Intelligence: A Hybrid Neural Framework for Dynamic System Innovation 3

Evolutionary Intelligence: A Hybrid Neural Framework for Dyn...

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3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Sharma, Puneet Khan, J. Sulthan Ali Radhika, K. Thatipudi, Jayendra Gopal Sridevi, K. Upadhyay, Shrikant School of Cs & Ai Sr University Telangana Warangal India VelTech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of It India Department of Mca Angallu Andhrapradesh Madanapalle517325 India University of North Texas Dept. of Computer Science United States S.R.K.R Engineering College Department of It Chinamiram Andhra Pradesh Bhimavaram India Mlr Institute of Technology Department of Electronics and Communication Engineering Hyderabad India

ISBN: (纸本)9798331509675

The Adaptive Neural Evolutionary Framework for Building Dynamic Systems with Hybrid Intelligent Architectures is designed to address challenges in real-time adaptability, optimization, and performance of complex systems. This framework integrates Neural Networks (NNs), such as Long Short-Term Memory (LSTM) and Residual Networks (ResNet), with Evolutionary Algorithms (EAs), including Genetic Algorithms, to dynamically optimize hyperparameters and structural configurations. Preprocessing techniques like Wavelet Transform and Adaptive Contrast Enhancement (ACE) enhance data clarity and signal quality, significantly improving system input. The proposed hybrid framework achieves superior accuracy compared to traditional models, with a training accuracy of 96.8%, validation accuracy of 95.5%, and a testing accuracy of 96.9%. Experimental results demonstrate that the system performs exceptionally well under dynamic scenarios such as sudden input shifts, unseen data distributions, and resource constraints. Furthermore, the integration of adaptive feedback loops and neural plasticity ensures continual learning and model evolution in real-time. The framework's robustness and adaptability make it suitable for applications in predictive modeling, decision-making systems, and dynamic environments. © 2025 IEEE.

关键词： Wavelet transforms

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Classification and Evaluation Framework of Automated testing tools for agile software: Technical Review

Classification and Evaluation Framework of Automated testing...

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Mogeeb A.A. Moseh Nashwan Ameen Al-Khulaidi Abdu H. Gumaei Ayman Alsabry Ali A. A. Musleh Software Engineering Dept Faculty of Engineering & Information Technology Taiz University Taiz Yemen Industrial Dept. Engineering Dep Faculty of Engineering & Information Technology Taiz Univerity Taiz Yemen Computer Science Dept. College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University Al-Kharj Saudi Arabia Department of Computer Science International University of Technology Twintech Sana’a Yemen Faculty of Computer Science & Information Technology International University of Technology Twintech Sana’a Yemen

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

Test automation is crucial for agile software projects to enable frequent delivery of working software with cost and time and minimal bugs. However, selecting the right automated testing tool is considered challenging due to the wide range of such existing tools. Additionally, the challenges occur clearly due to several issues such as the programming code language, the categorization of the developed system, and the tester’s knowledge and skills. This paper aims to address this gap by proposing an evaluation framework for comparing and classifying the existing automated testing tools used in agile projects. The framework is developed based on an extensive literature review of existing agile testing methodologies and common commercial automation testing techniques. The key criteria for tool evaluation are identified to cover the main testing objective aspects such as test design support, testing interfaces, reporting capabilities, etc. These criteria are considered the core methodology for this study used to analyze and compare the popular open-source and commercial tools. The proposed evaluation framework provides agile practitioners with guidelines to assist in selecting the appropriate tools based on their specific project needs such as budget, timelines, and technical expertise. This study is considered a comparative evaluation of existing agile testing tools to highlight their key strengths and limitations. The findings of this study categorized the testing tools based on the interface, code, design, and report features. This research contributes to assisting the project developer and tester in selecting suitable tools for the adoption of automated testing tools in their agile software projects. It also identifies the direction for future work, such as integrations with modern development methodologies and technologies.

关键词： Codes Automation Reviews Agile software development Programming Software Software measurement

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Sinhala Sign Language Learning System for Hearing Impaired Community

Sinhala Sign Language Learning System for Hearing Impaired C...

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2023 4th International Informatics and Software engineering Conference (IISEC)

作者： Idushan K. A. S Dilshan P. G. T Jayasundera P. S Madhushan K. L. B Jenny Krishara Dinuka Wijendra Dept. of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

This research aims to develop a comprehensive system for Sinhala Sign Language (SSL) that includes a learning system, dynamic sign detection, audio/video to sign conversion, and vocal training. SSL plays a crucial role in facilitating communication for individuals who are deaf or hard of hearing in Sri Lanka. The learning system provides a platform for learning SSL and includes a text-to-sign language interpreter. The dynamic sign detection system uses computer vision techniques to identify and interpret dynamic signs accurately. The audio/video to sign conversion system bridges the gap between spoken language and SSL by converting auditory information into visual representations. The vocal training system focuses on enhancing the vocal skills of cochlear implanted children. This research contributes to the development of effective communication and language skills for SSL users.

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Demosaicing of Multispectral Imaging Camera data using Neural Networks

Demosaicing of Multispectral Imaging Camera data using Neura...

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BIT Conference (BITCON), International

作者： Sumita Gupta Sapna Gambhir Saru Dhir Simran Sapui Rana Majumdar Deepsikha Naskar Department of Computer Science & Engineering Amity School of Engineering & Technology Amity University UP Department of Computer Science College of Engineering and Computing George Mason University USA Dept. of Information Technology Amity School of Engineering & Technology Amity University UP India Department of Computer Science Sister Nivedita University

ISBN: (数字)9798331518394

ISBN: (纸本)9798331518400

In most digital cameras, the sensor uses a Bayer filter array to capture the image. This array records only one colour, either blue or green or red for every image pixel, resulting in a mosaic image. To retrieve the missing colour information in the captured image making use of cross-channel interpolation is referred to as demosaicing. Demosaicing, especially in the context of colour demosaicing (CDM), plays a vital role as the first step in obtaining high-quality colour images with single-chip cameras. Traditional demosaicing methods, used to reconstruct colour images from raw sensor data in digital cameras, have several drawbacks. They often result in a loss of spatial resolution, introduce artifacts, lack robustness in challenging conditions, and may require manual tuning for optimal performance. In contrast, neural networks offer advantages like end-to-end learning, improved image quality, robustness, flexibility, and state-of-the-art performance. They learn complex mappings directly from raw data, adapt to various conditions, and produce visually pleasing, high-resolution images. However, they require substantial training data and computational resources, making them less suitable for resource-constrained applications. In this paper, conventional interpolation methods are compared to deep-learning based approaches for image demosaicing. To validate the approach to image demosaicing, aerial images captured from the Mars Colour Camera have been used.

关键词： Image quality Interpolation Visualization Image color analysis Neural networks Training data Robustness Digital cameras Spatial resolution Tuning

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Women’s Rights in India

Women’s Rights in India

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Advanced Computing Technologies and Applications (ICACTA), International Conference on

作者： Andrea Alvares Leona Varghese Tiffany Jesus Sana Shaikh Dept. Of Computer Engineering Don Bosco Institute Of Technology Mumbai India

Violence against women and discrimination based on gender are still major problems in the world. It is critical to have access to legal resources in order to address these issues. This requirement is met by the Women’s Rights Portal, a web-based portal that offers a thorough database of laws and prior rulings concerning women’s rights. The platform also has a built-in chatbot system that makes use of natural language processing to offer users who need information or legal advice individualised support. The portal also employs machine learning algorithms to provide pertinent case searches in response to user inquiries. By giving women the legal knowledge and assistance needed to claim their rights and fight gender-based discrimination, the Women’s Rights Portal is a special and cutting-edge instrument that empowers women. Through this portal, women can access information about their rights and the legal resources available to them, empowering them to make informed decisions about their lives. The Portal is not only a valuable resource for women, but also for legal professionals, activists, and policymakers who seek to address gender-based discrimination.

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A Low-Cost Brine Level Measurement System for Farmers Through NB-IoT technology

A Low-Cost Brine Level Measurement System for Farmers Throug...

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2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Wang, Dao-Jiun Fanjiang, Yong-Yi Hung, Chi-Huang Hsiao, Yao-Yun Graduate Institute of Applied Science and Engineering Fu Jen Catholic University New Taipei City Taiwan Graduate Institute of Applied Science and Engineering Fu Jen Catholic University Dept. of Computer Science and Information Engineering New Taipei City Taiwan Graduate Institute of Applied Science and Engineering Fu Jen Catholic University Lee-Ming Institute of Technology Dept. of Information Technology New Taipei City Taiwan Lee-Ming Institute of Technology Dept. of Digital Multimedia New Taipei City Taiwan

ISBN: (纸本)9781665441544

Because of the usual changes in weather. In the past, farmers had to constantly check whether their crops were kept in a good growing environment. This research uses the Internet of Things technology to measure the water level of the pickled cabbage barrel using an ultrasonic module, lens and microcontroller (MCU). In addition to using a non-contact ultrasonic module, a lens is also used to capture the image of the pickled cabbage barrel, so that farmers can understand the situation remotely without leaving home. If the brine level is abnormal, farmers can be notified via instant messaging software. © 2022 IEEE.

关键词： Internet of things

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Identification of Paradigms of Heliacal Luminosity Through Onotological Mechanism and 5G Networks 4

Identification of Paradigms of Heliacal Luminosity Through O...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Santhakumar, D. Kumar, Neelam Sanjeev Arunprasath, R. Sekhar, G.G.Raja Jalal, Sarah Salah Al-Taee, Fay Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Chennai India Srm Institute of Science & Technology Department of Computer Science & Engineering Chennai Vadapalani26 India Sri Krishna College of ENGG. Eee DEPT. Tamilnadu Arakkonam India Koneru Lakshmaiah Education Foundation Department of Electrical & Electronics Engineering Guntur Andhra Pradesh Vaddeswaram India National University of Science and Technology Collage of Nursing Dhi Qar64001 Iraq Al-Farahidi University Baghdad Iraq

ISBN: (纸本)9798350360165

This paper develops a new ontological-based approach to network slicing in 5G backhaul networks, targeting low- or ultra-low-latency services. Our approach supports a modified A∗ approach with management of congestion to be more efficient than Dijkstra's approach in real time with the help of a precomputed heuristic function. It embeds the network quality-of-service factors in a combined measure. The proposed approach is embedded in a slice module, which is, in turn, encapsulated by a route computation element that is a slice module used to compute the optimal paths of network slices. According to experiment results, our approach showed an increase in the order of magnitude of processing time reduction in comparison with the Dijkstra algorithm. Especially in the case of complex network topologies, the system dynamically changes the path to ensure the packet delay is smaller than the specified level, to satisfy the low-latency requirements. These measurements from the performed end-to-end tests for the Speed test client, which allows URLLC in 5G backhaul networks, give the system the capability to differentiate between no- and low-latency-bound traffic. © 2024 IEEE.

关键词： 5G mobile communication systems

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