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检索条件"机构=School of Engineering and Technology Mechaical Engineering"

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Benchmarking Different Types of Interpolation Methods for Image Super-Resolution

Benchmarking Different Types of Interpolation Methods for Im...

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International Conference on Computing and Networking technology (ICCNT)

作者： Shivangi Gupta V Sandeep P.R. Rege V.J. Vijayalakshmi Komal Parashar T Vijayaraj Quantum University Research Center Quantum University School of Engineering and Technology Mechaical Engineering JAIN (Deemed to be University) Bangalore Karnataka Computer Vishwakarma Institute of Information Technology Pune Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Mechanical Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Photo exceptional resolution (SR) is a crucial project for many photograph-related programs with the goal of producing a better decision image from lower-resolution imagery. Distinct interpolation strategies are available to reconstruct excessive-resolution pics from decrease-resolution snapshots. The maximum broadly used interpolation algorithms are bilinear, cubic, and Lanczos interpolations. Benchmarking is performed. In benchmarking, metrics consisting of top signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and implied squared errors (MSE) are used to compare the overall performance of the different interpolation algorithms. In trendy, the Lanczos interpolation plays higher than bilinear and cubic interpolations in terms of reconstruction high-quality for picture SR. but, Lanczos interpolation is extra computationally pricey than the other strategies, which can limit its wide usage in SR programs. Benchmarking distinctive varieties of interpolation methods for picture SR can assist in deciding the maximum suitable interpolation set of rules for specific kinds of SR programs.

关键词： Measurement Interpolation Accuracy Superresolution Benchmark testing Indexes Image reconstruction Signal to noise ratio

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Unleashing the Potential of Battery Algorithms for Optimal Performance in Electric Vehicles

Unleashing the Potential of Battery Algorithms for Optimal P...

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Automation and Computation (AUTOCOM), International Conference on

作者： Ashwini B Gaurav Shukla Jaskirat Singh Suman Sau Prateek Aggarwal Ashutosh Pattanaik Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre for Interdisciplinary Research for Business and Technology Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Information Technology Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Engineering and Technology Mechaical Engineering JAIN (Deemed to be University) Bangalore Karnataka

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

The increasing demand for electric-powered vehicles (EVs) has brought about a growing desire for battery algorithms that can optimize battery performance. Those algorithms can substantially affect the range, charging time, and usual efficiency of EVs, making them an essential factor in the transition to a greener transportation system. However, there is nevertheless tons of potential to be unlocked in battery algorithms to enhance EV overall performance. Contemporary battery algorithms depend upon traditional management techniques, which may be restricted in their capability to adapt to changing situations and may need to utilize the skills of modern-day battery technologies fully. To absolutely unleash the capacity of battery algorithms, new procedures such as gadget mastering and artificial intelligence may be implemented. These superior strategies can examine and adapt to actual-time facts from the battery and its environment, taking into account extra correct and green control. Moreover, integrating data from diverse sensors and communiqué technology can provide an extra comprehensive understanding of the battery device, leading to higher performance and longer battery existence. It additionally allows predictive preservation, assisting in saving you from capacity disasters and amplifying the lifespan of batteries. With the aid of constantly optimizing battery algorithms, the range, charging time and typical overall performance of EVs may be drastically stepped forward, making them a possible alternative for consumers. It will, in the long run, accelerate the transition towards a sustainable and greener transportation system.

关键词： Temperature sensors Performance evaluation Electric potential Green products Transportation Prediction algorithms Real-time systems Batteries Temperature control State of charge

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Real-Time Reconstruction of 3D Space using Holographic Video

Real-Time Reconstruction of 3D Space using Holographic Video

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International Conference on Computing and Networking technology (ICCNT)

作者： Vivek Deshpande D. Anandha Silambarasan Hitesh Kalra R Reena Shivangi Gupta C Manjunath Department of Computer Engineering Vishwakarma Institute of Technology Pune Maharashtra India Department of Computer Science Engineering Karpagam Academy of Higher Education Coimbatore India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Information Technology Prince Shri Venkateshwara Padmavathy Engineering College Chennai Quantum University Research Center Quantum University School of Engineering and Technology Mechaical Engineering JAIN (Deemed to be University) Bangalore Karnataka India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The real-time Reconstruction of 3-D space and the usage of holographic video entail the capture and processing of films that have a three-dimensional shape in them. The manner of capturing the 3-dimensional shape includes: using a camera with the functionality to seize and technique the holographic photograph in a composite format, taking multiple photos, merging them into one hologram. Then, the photographs are processed in real-time with the usage of laptop imaginative and prescient algorithms for function extraction, segmentation, and 3-D object popularity. This application of the laptop, imaginative and prescient, allows the person to navigate and engage with the three-D illustration that is reconstructed in actual time. The reconstructed 3D scene is then rendered in the shape of an interactive 360-degree holographic video. This technology can provide a couple of applications in augmented and virtual reality gaming and immersive 3-D visualization of the captured environment.

关键词： Visualization Video games Three-dimensional displays Portable computers Shape Navigation Merging Streaming media Real-time systems Image reconstruction

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Next Generation Energy Storage Solutions for the Automotive Industry

Next Generation Energy Storage Solutions for the Automotive ...

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Automation and Computation (AUTOCOM), International Conference on

作者： Pavan Chaudhary Himanshu Makhija Ajit Kumar Nayak Romil Jain Sandeep V Samreen Fiza Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre for Interdisciplinary Research for Business and Technology Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Information Technology Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Engineering and Technology Mechaical Engineering JAIN (Deemed to be University) Bangalore Karnataka Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

The automobile industry is shifting closer to electrification; the need for dependable and efficient answers to electricity garages has become increasingly important. The present-day era of batteries, specifically lithium-ion, is attaining its limitations in terms of overall performance, price, and protection. Consequently, the development of next-era power storage answers is crucial to fulfill the growing demands of the enterprise. Subsequent-technology energy garage answers aim to enhance the constraints of present-day batteries by making use of new materials, designs, and technologies. It includes stable-state batteries, which use strong electrolytes as opposed to liquid ones, presenting better electricity density and improved protection. Other solutions include metallic-air batteries that use air as the cathode, promising extensively higher power densities. There are also traits in power garage devices that use ultra-capacitors, promising faster-charging instances and longer lifetimes. Those improvements are only some of the most effective advantages for the automobile enterprise, but they also have potential for packages in other regions, including renewable power storage. However, there are nevertheless challenges to conquer, including improving production procedures to reduce charges and increasing the durability and reliability of these next-technology solutions.

关键词： Lithium-ion batteries Industries Renewable energy sources Liquids Electricity Production Electrolytes Solid state batteries Automobiles Protection

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Real-Time Environmental Monitoring and Control Using Cyber-Physical Systems: A Case Study in Agriculture

Real-Time Environmental Monitoring and Control Using Cyber-P...

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Automation and Computation (AUTOCOM), International Conference on

作者： Dhananjay Kumar Yadav Amit Kumar Suprava Devi Abhinav Mishra Venkadeshwaran K V. Venkata Ramesh Reddy Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Engineering and Technology Mechaical Engineering JAIN (Deemed to be University) Bangalore Karnataka India Sponsored Research Presidency University Bangalore Karnataka India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Due to its nature, real-time environmental monitoring and control is an indispensable part of modern agriculture. At its core, it is the ongoing collection, analysis, and application of ecological data to improve crop yields while conserving resources and minimizing expenditures. This article proposes that cyber-physical systems are an effective organization that provides a building structure where real-time monitoring and control can be provided across different processes within agriculture. Here, we report on a detailed case study of the application of CPS as discussed for environmental monitoring and control in agriculture. This paper reviews the dominant components of CPS sensors, actuators, and communication systems and data analytics. Together, these elements help us to gather real-time data on critical environmental variables like temperature, humidity, soil moisture and nutrient levels. The algorithm analyzes the data and provides farmers with insights. With the help of CPS, farmers can automate and remotely monitor essential processes like watering, fertilization, pest control, etc., increasing efficiency while decreasing labor costs. Another benefit of CPS is that it makes accurate decisions in a timely manner using real-time data, which can yield better crops and be more effective in resource utilization.

关键词： Temperature sensors Actuators Accuracy Process control Cyber-physical systems Agriculture Real-time systems Sensor systems Sensors Environmental monitoring

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Integrating Real-Time Automation and Big Data Analytics in the Oil and Gas Industry

Integrating Real-Time Automation and Big Data Analytics in t...

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International Conference on Computing and Networking technology (ICCNT)

作者： Ashvin B Amale I K Kantharaj Bhandari Mahesh Ashok A. Amudha Lakshay Bareja Priya M Raut Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Nagpur Maharashtra India School of Engineering and Technology Mechaical Engineering JAIN (Deemed to be University) Bangalore Karnataka India Department of IT Vishwakarma Institute of Technology Pune India Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Agadtantra evam vidhi vaidyak Datta meghe ayurvedic medical college hospital and research centre wanadongri Nagpur India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The oil and gas industry is arguably one of the most important industries in this modern world because some say it supports civilization as we know it. With the changing dynamics and increased competition, this sector is growing in demand for convenient solutions to improve operations with higher profits. Implementing real-time automation and big data analytics has become vital for the oil and gas industry. Real-time automation refers to using a control system, sensors, and an IT solution to monitor or control operations in real-time. It leads to faster decision-making and efficiency in drilling, production, and distribution processes. At the same time, big data analytics is about storing and analyzing massive amounts of data from different sources—these are sensor data production processes for the oil and gas industry market trends. Big data analytics can intelligently detect patterns & trends with the help of sophisticated algorithms along with machine learning, based on which necessary insights are drawn that lead to better operations and decision-making. Why these technologies will transform the oil and gas sector: Individually, both powerful new technologies provide many benefits, but integrated, they can potentially change the game in this industry. When combined with real-time automation (robots and material handling equipment), it can lead to actionable insights as things are happening, helping the business get control of its operations and reduce cost, ultimately leading to increased profitability.

关键词： Automation Costs Oils Decision making Production Big Data Gas industry Real-time systems Sensor systems Petroleum industry

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Advanced Cryptographic and Clustering Techniques for Privacy and Anomaly Detection in Heterogeneous Cloud Environments

Advanced Cryptographic and Clustering Techniques for Privacy...

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International Conference on ICT in Business Industry & Government (ICTBIG)

作者： S. Kannimuthu Madhur Grover G. Sathi Pradeep Marwaha Kantharaj I K Monali Ravindra Borade Department of Information Technology Karpagam College of Engineering Coimbatore India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Mech Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India School of Engineering and Technology Mechaical Engineering JAIN Deemed to be University Karnataka India AI & Ds Vishwakarma Institute of Technology Pune India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518998

The study delves at machine learning methods that can spot out-of-the-ordinary occurrences in real life. The development of a secure anomaly detection system that enhances deployment-ready classification accuracy and execution speed is one goal of this endeavor. According to studies, data privacy and classification accuracy may both be enhanced with the right cryptography approach. Two components of privacy protection in commercial cloud systems are processing of information security and integrity. While processing, data processing security safeguards user data, and data integrity guarantees that data syntax and semantics remain unaffected while being sent. Hackers may take use of user data by breaking into key pairs using existing cryptography methods. There is a lack of consideration for noisy data in current anomaly detection systems. In response to the difficulties encountered in scientific research, we presented a low-computing-cost method for protecting user privacy while simultaneously detecting anomalies in cloud data. An efficient privacy-protecting cloud-based anomaly detection approach is introduced. For data collected by sensors on a massive scale, the method enhances cryptographic techniques. Data encryption is performed in the cloud on both individual and group servers. A more secure and private encryption method called RSA based on LPGWO (Local Pollination Grey Wolf Optimizer) is used for the encryption. To efficiently classify large datasets, the proposed method partitions them. Collaborative public servers detect anomalies using the NCM (Neutrosophic C-Means) method.

关键词： Cloud computing Data privacy Accuracy Machine learning algorithms Machine learning Encryption Sensors Cryptography Servers Anomaly detection

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Deep Learning For Improved Diabetes Detection: Integrating Lstm, Convolutional Neural Networks And Svm

Deep Learning For Improved Diabetes Detection: Integrating L...

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International Conference on ICT in Business Industry & Government (ICTBIG)

作者： Rajiv Gandhi N Ashmeet Kaur Ashutosh Pattanaik Shilpa M. Katikar S. Kannimuthu Bhavuk Samrat Department of Civil Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India School of Engineering and Technology Mechaical Engineering Jain (Deemed to be University) Bangalore Karnataka India Computer Vishwakarma Institute of Technology Pune India Department of Information Technology Karpagam College of Engineering Coimbatore India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518998

Diabetes is one among the eminent anomalies which can be identified using ECG derived signal. This implies that if diabetes is not adequately managed with medications /insulin support it is likely to escalate into severe complicated diseases such as stroke, kidney failure, and heart attack. Early diagnosis of diabetes is also important in the management of the condition. The overall purpose of this thesis is to discover approaches to identify diabetes employing heart rate variability (HRV) signals as measured by deep learning such that to achieve very high level of correctness in the detection process. From the comparison of accuracies, CNN 1 - SVM begins at 68. 4%, while CNN 2 - SVM improves to 75. CNN 3 – SVM cast further has the highest accuracy of 93 percent. On the other hand, when we incorporate LSTM with SVM, the network configuration of CNN 1- LSTM - SVM results in an accuracy of 74. 2%, which is slightly higher than the CNN 1 –SVM. CNN 2 - LSTM - SVM further improves the accuracy to 76. 4% while and the highest accuracy is observed with CNN 3 - LSTM - SVM at 95.7%. In most cases, a combination of Long Short-Term Memory (LSTM) with Convolutional Neural Networks (CNN) and support vector machine (SVM) provides a better accuracy over the various models.

关键词： Support vector machines Deep learning Accuracy Electrocardiography Stroke (medical condition) Diabetes Convolutional neural networks Heart rate variability Long short term memory Diseases

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The Impact of Ultra-Wideband Sensors in Industrial Automation and Robotics Applications

The Impact of Ultra-Wideband Sensors in Industrial Automatio...

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Automation and Computation (AUTOCOM), International Conference on

作者： Pavan Chaudhary Amritpal Sidhu Chinmayee Nayak Sidhant Das Kantharaj I K K.Naresh Kumar Thapa Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Centre for Artificial Intelligence and Machine Learning Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Engineering and Technology Mechaical Engineering JAIN (Deemed to be University) Bangalore Karnataka Department of Electrical and Electronics Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Ultra-Wideband technology has garnered a reputation as an enabler of advancing industrial automation and robotics applications. UWB sensors emit short pulses of electromagnetic radiation to measure and can deliver highly accurate and real-time data over long distances. Compared to other sensing technologies, UWB sensors have a remarkably broad frequency spectrum and provide high data rates at low power. There are several advantages of UWB sensors implemented in industrial automation and robotics. These are done in a lab with some reference; you can take the data offline. UWB sensors can complement and be used in integration with other technologies, such as lidar or vision systems, to achieve higher performance results for a complete perception of the environment. This allows better and more efficient decision-making for autonomous systems. UWB sensors deliver highly accurate and repeatable measurements for robotic movement monitoring and control. They are also used for asset monitoring and inventory control, which finally help logistics & SCM. UWB sensors also improve workplace safety by warning about potential collisions or other hazardous conditions.

关键词： Automation Accuracy Service robots Production Robot sensing systems Sensors Safety Collision avoidance Monitoring Ultra wideband technology

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An Analysis of Image-Based Segmentation Algorithms for Computer Vision Applications

An Analysis of Image-Based Segmentation Algorithms for Compu...

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International Conference on Computing and Networking technology (ICCNT)

作者： J Deepak Vishwesh Deshmukh D. Anandhasilambarasan Harsimrat Kandhari J. Jayashankari Shitij Goyal School of Engineering and Technology Mechaical Engineering JAIN (Deemed to be University) Bangalore Karnataka India Electrical Vishwakarma Institute of Technology Pune India Department of Computer Science Engineering Karpagam Academy of Higher Education Coimbatore india Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Information Technology Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Quantum University Research Center Quantum University

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Photo-based totally segmentation algorithms are an important place in trendy research in laptop vision for an extensive variety of trendy applications together with item popularity, facial recognition, and autonomous navigation. Such algorithms normally hire strategies that contain reading pix to understand edges, shapes, and different features in the surroundings. By means of making use of these techniques, scene objects may be diagnosed and segmented into distinct parts, making an allowance for further analysis and programs. This paper discusses the development and packages of brand new photograph-based segmentation algorithms, with an emphasis on algorithms based on pattern recognition and machine learning. Examples are supplied to illustrate the present-day country’s contemporary art and provide insights into the destiny development of those algorithms. This analysis helps to discover capacity areas for development and provides a top-level view state-of-the-art the overall performance of present-day current algorithms.

关键词： Image segmentation Computer vision Machine learning algorithms Portable computers Art Shape Face recognition Machine learning Autonomous robots

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