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International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Sivashankar. G Bhagyalakshmi Avinash Mohammad Shabbir Alam Manasi Vyankatesh Ghamande Keerat Kumar Gupta Ravi Rastogi Department of Computational Intelligence SRM Institute of Science and Technology Chennai Tamilnadu India Dept of Orthodontics & Dentofacial Orthopaedics JSS Dental College & Mysore Mysore Karnataka India Department of Computer Science College of CS &IT Jazan University Jizan Kingdom of Saudi Arabia Assistant Professor E and AS Vishwakarma Institute of Information Technology Pune India Department of Civil Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Scientist D Electronics Division NIELIT Gorakhpur Uttar Pradesh India

Unregulated glucose levels in the blood lead to the chronic disease diabetes. Diabetic foot ulcers (DFUs) and other devastating outcomes may be avoided with early detection. The lower limb of a diabetic patient may need to be amputated if they experience a DFU. DFU is difficult to diagnose and usually requires a number of expensive and time-consuming clinical investigations for the treating physician. Applying deep learning, machine learning, and computer vision techniques in today's age of data deluge has resulted in a number of solutions that can help doctors make more accurate diagnoses in less time. As a result, researchers have recently focused more on developing methods for automatically identifying DFU. Preprocessing, segmentation, feature extraction, and model training are all used in the suggested method. It does noise reduction and RGB to HSI color space conversion during preprocessing. OSTU thresholding segmentation is used for the separation. It uses histogram for feature extraction and Improved CNN-SVM for model training. The new method is compared to two common approaches, including CNN and CNN-SVM, and fares better than both.

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Evolution of electric vehicle and its future scope

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Materials Today: Proceedings 2020年 33卷 3930-3936页

作者： P.M. Sneha Angeline M. Newlin Rajkumar Research Scholar Department of Computer Science Engineering Anna University Regional Campus Coimbatore 641 046 India Assistant Professor Department of Computer Science Engineering Anna University Regional Campus Coimbatore 641 046 India

Electrification is one of the appropriate way to establish a clean and energy efficient transportation. The impact of electric vehicle on the environment is considered as a serious issue. The locomotive industry as well as power sector gets benefitted by the reliable technology provided by the electric vehicle. This green vehicle also helps in creating an alternative power source for household applications and provide ancillary services to the grid. It also helps in integrating the intermittent resources for vehicle charging. As this vehicle generates prominent feature of less maintenance and ease of charge at residential premises. The electric vehicle creates a significant role in power sector mainly in the application of smart grid and act as a smart vehicle through grid communication. The challenges imposed by the electric vehicle and its effects in the transportation and energy sector are elaborately addressed in this paper.

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A Survey on Video-based Evidence Analysis and Digital Forensic

A Survey on Video-based Evidence Analysis and Digital Forens...

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International Conference on Computing Methodologies and Communication (ICCMC)

作者： R. V. Mante Reshma Khan Assistant Professor Department of Computer Science & Engineering Government College of Engineering Amravati Maharashtra India M.Tech Scholar Department of Computer Science & Engineering Government College of Engineering Amravati Maharashtra India

ISBN: (数字)9781728148892

ISBN: (纸本)9781728148908

In the past couple of decades, the most emerging domain across the globe is Information Technology [IT]. It has made a significant contribution in cracking the criminal case and preparing the strong cases in the court of justice. IT technologies have become a vital tool for examination and gathering of the digital evidences. As crime rate is increasing day-by-day, in order to reduce the occurrence of crime and bring the culprit of the crime to justice, the computer forensics plays an indispensable role. With the recent technological developments, it has become more powerful and portable. Large amount of data has created stored and accessed everyday. Many technologically advanced devices are acting as repositories for the collected personal information. Such devices remain portable and accessible with a single click or even to the voice command. To have such large-scale information is important to get the conviction for the culprits but at the same time, investigating agencies has to maintain the privacy of the recovered data to make it admissible in the court. This gives rise to the security mechanism for such data. Collection, analysis, investigation and reporting of the digital data come under forensic science, which is a part of digital forensics domain. In this paper, we have presented a review on the existing researches available in the field of video forensic analysis.

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Advancing knowledge management in machine-to-machine communication - A comparative analysis of stacked ensembles for IoT device classification mechanisms

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AIP Conference Proceedings 2024年第1期3214卷

作者： Ganesh S. Pise Sachin D. Babar Parikshit N. Mahalle Smt. Kashibai Navale College of Engineering Pune Assistant Professor in Pune Institute of Computer Technology Pune India Department of Computer Engineering Sinhgad Institute of Technology Lonavala Research Guide Smt. Kashibai Navale College of Engineering Pune India Department of Artificial Intelligent and Data Science Vishwakarma Institute of Information Technology Pune India

The Machine-to-Machine (M2M) connection in the context of the Internet of Things (IoT), with the main goal of improving information management through advanced classification methods. As the number of IoT devices has grown, strong methods for efficiently classifying them are needed to make contact smooth and make the best use of resources. This study compares two cutting-edge machine learning techniques called Stacked Ensembles to see which one is better at making IoT device classification more accurate and reliable. The paper research looks at different classification models within Stacked Ensembles and compares how well they work to more standard methods. The study system has a large collection with a lot of different IoT devices and different communication methods and network situations. The paper focused is to find the best Stacked Ensemble setups for accurate and efficient device classification in M2M communication by carefully testing and evaluating them. The study adds to the fields of machine learning and the Internet of Things, but it also looks at information management in M2M networks, which is a very important topic. We expect that system effectiveness, resource usage, and general network performance will all get better by using advanced sorting methods. It is hoped that the study results will help people create and use strong knowledge management strategies. This will make the M2M communication setting smarter and more flexible as the IoT world changes.

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A review on statistical analysis for data science

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AIP Conference Proceedings 2023年第1期2916卷

作者： Venkat Kumar Perumalla Himanshu Gupta Department of Mathematics Chandigarh University Gharuan - 140413 Mohali Punjab India Assistant (professor) Department of Computer Science and Engineering Chandigarh University Gharuan - 140413 Mohali Punjab India

This study makes a speciality of a way to use the Statistical Analysis for Data science approach to a real-international commercial enterprise scenario. Through this paper, the prominence of the Statistical Learning is known. Statistical Learning helps us, locating out the answer for a statistical inferential trouble through which it is easy to discover a predictive characteristic primarily based on the information we have. Statistical learning performs a distinguished position in the various fields like computer Vision, Speech Recognition, Emotion and Gender identification of Data science.

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Detection and Classification of Breast Cancer Using improved Grey Wolf Algorithm

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IOP Conference Series: Materials science and engineering 2021年第1期1084卷

作者： T Senthil J Deepika R. Nithya Assistant Professor Deparment of Electronics and Communication Engineering EngineeringBannari Amman institute of TechnologySathyamangalam ErodeTamilnadu India Assistant professor.Department of Information Technology Engineering Bannari Amman institute of TechnologySathyamangalam ErodeTamilnadu India Assistant professor.Department of Computer Science Engineering Engineering Bannari Amman institute of TechnologySathyamangala ErodeTamilnadu India

Breast Cancer is the hazardous infection among young ladies and most significant reason for developing destruction rate. Physically anticipation of this affliction takes longer hours and structures are to be had in significantly less number, there's motivation to expand a mechanized forecast machine for early expectation and visualization of malignancy. The sort of considerate and threatening tumor are accomplished the use of type methodologies of device becoming acquainted with wherein the device is found from the past records and predicts the sorts of late sources of info. This paper is an overall report on the execution of models utilizing Logistic Regression, Support Vector Machine (SVM) and Gray wolf algorithm(GWO). The outcomes are assessed with the exactness, accuracy, affectability, explicitness and False Positive Rate boundaries for every calculation and are thought about. These procedures are coded in Java and executed in MATLAB, the Image handling Environment. Our investigations have demonstrated that Gray wolf is the best for prescient examination with an exactness of 92.7%.We surmise from our test results that SVM is the appropriate calculation for expectation and in general Gray wolf has performed well close to SVM.

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The Burn Grafting Image Reclamation Redefined with the Peak-Valley Approach

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Critical Reviews™ in Biomedical engineering 2025年第2期53卷 21-35页

作者： B. P. Pradeep Kumar E. Naresh (Corresponding author A. Ashwitha Kadiri Thirupal Reddy N. N. Srinidhi Department of Computer Science and Design Atria Institute of Technology Bangalore VTU Karnataka India Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India Assistant Professor Department of CSE Malla Reddy Engineering College for Women Hyderabad Telangana Department of Computer Science and Engineering Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India

Burn injuries constitute a significant public health challenge, often necessitating the expertise of medical professionals for diagnosis. However, in scenarios where specialized facilities are unavailable, the utility of automated burn assessment tools becomes evident. Factors such as burn area, depth, and location play a pivotal role in determining burn severity. In this study, we present a classification model for burn diagnosis, leveraging automated machine learning techniques. Our approach includes an image reclamation system that incorporates the peak and valley algorithm, ensuring the removal of noise while consistently delivering high-quality results. By using skewness and kurtosis, we demonstrate substantial improvements in diagnostic accuracy. Our proposed system sources key features from enhanced grafting samples using peak valley transformation, enabling the computation of BQs and a unique bin analysis to enhance image reclamation. Our experimental results highlight efficiency gains, notably growing the matching features of graft samples for 14 matching images. The intended work involves the creation of a burn classification reclamation model. The proposed approach utilizes a support vector machine (SVM). The evaluation of the model will be conducted using an untrained catalogue, with a specific focus on its effectiveness in reclaiming images that necessitate grafts and distinguishing them from those that do not. Our approach holds promise in grafting sample reclamation in emergency settings, thereby expediting more accurate diagnoses and treatments for acute burn injuries. This work has the latent to save lives and improve patient upshots in burn traumas.

关键词： burn grafting image reclamation peak-valley approach LUV color space support vector machine

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A Survey on Automatic Text Summarization Techniques

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Journal of Physics: Conference Series 2021年第1期2040卷

作者： S Hima Bindu Sri Sushma Rani Dutta Assistant Professor Department of Computer Science and Engineering Koneru Lakshmaih University Assistant Professor Department of Computer Science and Engineering Koneru Lakshmaih University.

In recent years, there is a tremendous explosion in the amount of text data on the internet and in the archives of news articles, scientific papers, legal documents and even in online product reviews. Text summarization is playing an important role in automatic content creation, minutes of meeting generation, helping disabled people and also for quick online document reading. To achieve these, several automation techniques have been proposed in various researches. In this regard, performing an exclusive survey on different methods, approaches of automatic text summarization which are published in different articles in most recent three years.

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Collision avoidance for a multi copter using ultrasonic sensor embedded with Arduino Uno

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AIP Conference Proceedings 2023年第1期2855卷

作者： N. C. Ajay Vishwath Ashish Prajapati Tanishka Mourya Lokesha Gangadharani Assistant Professor Department of Aeronautical Engineering Parul Institute of Engineering and Technology Parul University Vadodara India. UG Student Department of Aeronautical Engineering Parul Institute of Engineering and Technology Parul University Vadodara India. UG Student Department of Computer Science Engineering Parul Institute of Engineering and Technology Parul University Vadodara India.

This research work focuses on the Collision Avoidance for a Quadcopter or a Hexacopter using Ultrasonic sensor Embedded with Arduino Uno. The work starts from the definition of Quadcopter and Hexacopter flight controls proceeds to the flight control’s response while encountering an Obstacle. The work further carried to avoid the same. The research idea is about using the ultrasonic sensor being embedded with arduino board for any kind of obstacle detection. This research work has been carried out keeping in mind the principle that ultrasonic sensor sends and receive signal to measure distance. So the positioning of sensor explained in this paper adds a weight age to this research work. Sensors in Quadcopter are used to detect any obstacle during the flying mode to avoid collision.

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Effects of business intelligence tools on financial performance of it industry

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AIP Conference Proceedings 2024年第1期2971卷

作者： Yeluri S. D. S. Sri Vardhan U. M. Gopal Krishna I. Tejaswini K. Samuel Johnson Israel P. Prathyusha Assistant Professor Department of Computer Science and Engineering Sumathi Reddy Institute of Technology for women Ananthasagar Telangana VIT – AP School of Computer Science & Engineering VIT – AP University Andhra Pradesh India VIT – AP School of Business VIT – AP University Andhra Pradesh India Sumathi Reddy Institute of Technology for Women Warangal Telangana India

The goal of Business Intelligence is to look into, combine, and logically collect and analyse data from different customer information sources, the environment, competitors, and markets, etc., in order to judge how well businesses in the IT industry are doing. The goal of this study is to find out how Business Intelligence tools affect how well IT companies do financially. The method is a descriptive survey that can’t be used in real life. As part of the study, 420 IT experts from IT companies in Hyderabad were looked into as part of the statistical population. Also, confirmatory factor analysis was used to check the validity of the 25-item questionnaire, and validity analysis was used to gather data. The results showed that Business Intelligence had a big effect on the financial performance system of the organisation. Still, Business Intelligence made IT companies more innovative. Financial Forecasting and Financial Control System affect the financial performance system by 0.11 and 0.05 points, respectively. The Fund Management System affects the financial performance system by -0.07 points. The Financial Performance System is affected by the Internal Audit System by 0.05. The effects of Financial Forecasting, Financial Control System, and Internal Audit System on the organization’s financial performance system. Thus, it can be concluded that Structured Equation Modelling in IBM SPSS AMOS has been used to indirectly examine the impact of Business Intelligence tools on financial performance. Surprisingly, these three elements are required to improve financial performance.

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