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1st International Conference on Advances in Electrical and Computer Technologies, ICAECT 2019

作者： Jagdish, Mukta Jerritta, S. Department of Computer Science and Engineering Vels Institute of Science Technology & Advanced Studies VISTAS Chennai India Department of Electronics and Communication Engineering Vels Institute of Science Technology & Advanced Studies VISTAS Chennai India

ISBN: (纸本)9789811555572

Background: To identify and monitor the occurrence of oil spill in the ocean using image data obtained from different satellites. It is to characterize and identify type and other physical characteristics of oil using appropriate image processing techniques and to predict the physical characteristics of oil spill using machine learning methods. Methods: In this paper, forty sample images were used with wavelet transform analysis and machine learning techniques. For wavelet analysis (SYMLET family such as sym2, sym3, sym4, sym5, sym6, sym7, sym8 analysis) and machine learning, k-nearest neighbor algorithm is applied to optimize the oil spill feature sets. Features included RGB, spreading, complexity, standard deviation, entropy, ellipticity, intensity and correlation coefficient. This experiment was conducted on RADARSAT-2 SAR images. The features were classified using k-nearest neighbor algorithm. Seventy percent of features used for training and thirty percent for testing. Results: The results show that oil spill classification achieved by wavelet transforms and machine learning algorithms outperformed very well with similar parameter settings, especially with 70% training data and 30% testing data using confusion matrix. It also represents 92.6581% accuracy for crude oil using SYMLET 5 analysis which indicates better characterization of oil spills. Results denote oil spill detection using synthetic-aperture radar (SAR) remote sensing which provides an excellent tool in oil spill characterization;various features can be extracted from SAR data set. © Springer Nature Singapore Pte Ltd 2020.

关键词： Wavelet transforms

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Characterization of Microstructure and Mechanical Behaviour in Activated Tungsten Inert Gas Welded Dissimilar AA Joint of AA 5083 and AA 6061 Alloys

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Journal of The Institution of Engineers (India): Series D 2024年第3期105卷 1865-1873页

作者： VettumPerumal, Sundar Suyamburajan, VijayAnanth Chidambaranathan, Vettivel Singaravel Nelson, Leema Department of Mechanical Engineering VELS Institute of Science Technology and Advanced Studies Tamilnadu Chennai India Department of Mechanical Engineering Chandigarh College of Engineering and Technology Degree Wing Sector 26 Chandigarh160019 India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India

Aluminium alloys have a wide range of use in the manufacturing industries. Fusion welding procedures frequently use metal inert gas and tungsten inert gas (TIG) welding to combine aluminium alloys (AA).Overdue to AA's high expansion coefficient, high thermal conductivity and high electrical conductivity, it is more challenging to weld AA than steel. The capacity of TIG welding thick structures cannot be welded in one pass. Activated TIG (A-TIG), a novel development in TIG welding, has been created. With this technique, a single pass results in an ultra-deep penetration. The A-TIG welding procedure for combining AA 6061 and AA 5083 is described in this publication. The varied welding parameters' effects such as welding current, flux and filler rod for improving hardness have also been explored. Compared to conventional TIG welding, the TiO2 flux used in A-TIG welding enhanced the depth of penetration DOP and lowered the bead width. The TiO2 flux significantly improved weld hardness and reduced bead width. EDS and SEM analysis revealed changes in alloy composition and microstructure. This study successfully established dissimilar joints between AA 6061 and 5083 using A-TIG welding, with enhanced DOP and mechanical properties. The TiO2 flux played a vital role in altering surface tension and improving weld characteristics. The findings contribute to the understanding of A-TIG welding in dissimilar alloys, specifically AA 6061 and 5083. © The Institution of Engineers (India) 2023.

关键词： Microstructure

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Implementation of vacuum braking system in four wheeler

Implementation of vacuum braking system in four wheeler

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International Conference on Newer trends and Innovations in Mechanical engineering, ICONTIME 2020

作者： Shaisundaram, V.S. Karthick, S. Karikalan, L. Department of Automobile Engineering Vels Institute of Science Technology and Advanced Studies Chennai India

In railway locomotives, vacuum brakes is using as an alternative of air brake. The vacuum pump, brake pipe is using to make vacuum. The integral arrangement of brake cylinders uses the vacuum tank to applications of the brake. Currently a lot of light duty vehicle are built with the vacuum assist the hydraulic brake system. The vacuum brake system is used to analysis the functioning in both light and heavy vehicle. The vacuum was formed from the engine and use to building the application of the brake. The systems operation are alike an air brake system. In the vacuum brake systems, the vacuum was used before compressed air which used in the air braking system. The design and modified systems include vacuum braking system. © 2020 Elsevier Ltd. All rights reserved.

关键词： Engines

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Analysis of Gastric Signal After Consumption of the Pre-Processed Food by Using FFT Transform

Analysis of Gastric Signal After Consumption of the Pre-Proc...

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2023 International Conference on Sustainable Communication Networks and Application, ICSCNA 2023

作者： Gowtham, R. Chandrasekaran, R. Vels Institute of Science Technology & Advanced Studies Department of Biomedical Engineering Chennai India

ISBN: (纸本)9798350313987

In this study the effects of pre-processed food in the gastric cycle have been discussed in detail. In the modern days the consumption of the pre-processed food is increased tremendously among the young aged group people. Due to the high CHO concentration, meal volume, meal temperature, fat content and protein content in the pre-processed affects the gastric cycle per minute. The changes in the gastric cycle leads to irritable bowel syndrome, gastroesophageal reflux, tachy-gastria and brady-gastria. In this study the electro gastro graphic signal is acquired from the subject before and after consumption of the pre-processed food to evaluate the difference between the gastro graphic signal. The acquired signal is pre-processed using band pass IIR filters and the smoothening is done by using mean average method. The Fast fourier transform is applied to the pre-processed gastro graphic signal to check the different FFT range of the EGG to estimate the spectral range and the dominant frequencies. Based upon the gastric cycle per minute and the dominant frequency the pre processed foods are classified into healthy food or unhealthy food. © 2023 IEEE.

关键词： brady-gastria EGG signal IIR filter and FFT transform tachy-gastria

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Synthesis and testing of aluminium composite using industrial waste as reinforcement

Synthesis and testing of aluminium composite using industria...

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International Conference on Newer trends and Innovations in Mechanical engineering, ICONTIME 2020

作者： Akash, R. Muraliraja, R. Suthan, R. Shaisundaram, V.S. Department of Mechanical Engineering Panimalar Engineering College Chennai India Department of Mechanical Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Department of Automobile Engineering Vels Institute of Science Technology and Advanced Studies Chennai India

Composite is made of two or more elements with different physical or chemical properties are combined together to form a new material. The property of the produced material shows elevated properties when compared to individual elements. Composites has two major elements called matrixes and reinforcements. Aluminium matrix composites are commonly used in many industrial and automobile applications because of its availability, high strength to weight ratio, good wear and corrosion resistance. Reinforcement is added into the composite to improve the tribological and mechanical properties, also it reduces the cost of the composites. The Al2O3 and SiC are the favourable elements for aluminium to make to make internal bonding between the matrix and reinforcement. In this research work, the new material is formulated using powder metallurgy process, aluminium is selected as matrix material and waste Al2O3material from oil refinery industry is used as reinforcement material. The composition of new materials is 0%, 5% and 10% were added as reinforcement based on weight. The produced substrate is tested for mechanical properties such as hardness, compression. The tribological properties such as wear and friction were tested using pin on disc tribometer. The characterisation is done on the produced substrate using scanning electron microscope, energy dispersive X-Ray analysis and X-Ray diffraction. © 2020 Elsevier Ltd. All rights reserved.

关键词： Hardness

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Experimental investigations of mechanical behavior of friction stir welding on aluminium alloy 6063

Experimental investigations of mechanical behavior of fricti...

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International Conference on Newer trends and Innovations in Mechanical engineering, ICONTIME 2020

作者： Sivabalan, S. Sridhar, R. Parthiban, A. Sathiskumar, G. Department of Mechanical Engineering Vels Institute of Science Technology and Advanced Studies Chennai India

The conventional welding of Aluminum alloy 6063 faced many problems related porosity in the fusion zone and loss in Mechanical properties. To overcome these difficulties the Similar Aluminum alloy 6063 were welded by using friction stir welding process and the mechanical characteristics and microstructure were investigated by varying the Tool rotation speed, welding speed and axial force. Microstructure of different zones were analyzed and observed by electron optical microscope. The tensile properties and hardness is evaluated for AA6083 Welded joints. It is found that welding speed 72 mm/ min, Tool rotation speed 1000 rpm, axial force 14.5 KN Produces better tensile strength. Welded zones categorizes three different zones are interfacial zone, Nugget zone and parent metal were investigated. © 2020 Elsevier Ltd. All rights reserved.

关键词： Friction stir welding

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Analysis of Raw 3D Images of Stages of Alzheimer's Disease Using Deep Learning 9

Analysis of Raw 3D Images of Stages of Alzheimer's Disease U...

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9th International Conference on Biosignals, Images, and Instrumentation, ICBSII 2023

作者： Thamizhvani, Tr Hemalatha, Rj Rachel Cynthia, V. Swetha, S. Vels Institute of Science Technology and Advanced Studies Department of Biomedical Engineering Chennai India

ISBN: (纸本)9798350338171

Alzheimer's disease is defined as a brain ailment that progressively impairs thinking, cognitive skills, and the capacity to complete most basic tasks. Memory loss, cognitive changes, and other neuronal brain disorders are all symptoms of AD, a degenerative condition. Since risk awareness encourages patients to take preventative measures even before the onset of irreversible brain damage, an absolute diagnosis of Alzheimer's disease is vital. Total brain atrophy and hippocampal atrophy are considered to be the main diagnostic tests for the condition. For this condition, early identification is important, and automatic system design is required. Computer-assisted methods are implemented for the analysis of AD in several types of research and the outcomes are constrained due to the congenital findings. Early stages of AD can be diagnosed but not predicted because prediction is only useful before the disease manifests itself. Deep learning (DI) techniques are used to analyze the raw MRI 3D images to identify AD and its progressive stages. The efficiency of the deep learning networks is defined to be less, which is indefinite for diagnosing AD stages. Therefore, processing of the images is necessary for the detection and to predict the progression of AD. © 2023 IEEE.

关键词： Magnetic resonance imaging

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A Systematic Review on Detection of Gastric Cancer in Endoscopic Imaging System in Artificial Intelligence Applications 5th

A Systematic Review on Detection of Gastric Cancer in Endosc...

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5th International Conference on Data and Information Sciences, ICDIS 2023

作者： Pooja, K. Kishore Kanna, R. Department of Biomedical Engineering Vels Institute of Science Technology and Advanced Studies Chennai India

ISBN: (纸本)9789819969050

Artificial intelligence and disease detection go hand in hand. Convolutional neural networks, a significant area of artificial intelligence applications, are crucial in the detection of stomach cancer. AI’s significance in cancer research and clinical applications is becoming increasingly recognized. Cancers like stomach and gastric cancer are ideal test subjects to determine whether early efforts to apply AI to medicine can result in beneficial outcomes. Deep learning (DL) and machine learning (ML) are two examples of AI-derived concepts. The definition of ML refers to the capability of learning data features without explicit programming. It seeks to improve the efficacy by computing methods. ML-based predictive prognostic models are becoming more prevalent in cancer research. The objective of this review paper focused on the role in the artificial intelligence improvements in treatment, prognosis, and diagnosis gastric cancer. Artificial neural networks and convolutional neural network have gained a lot of attention for biomedical applications. The main goal of the ML subset known as DL is to challenge multilayer intelligence networks. When it comes to the clinical management of stomach cancer, there is a lot more to be discussed. Despite rising efforts, it is important to adapt machine learning and artificial intelligence to enhance stomach cancer diagnostics. It can be used to enhance visual modalities for treatment and diagnosis procedures, even though that it can be slow and difficult. It might eventually turn into a helpful tool for doctors. Moreover, artificial intelligence changes ideas about the future of medicine as well as the effectiveness of diagnostic and treatment procedures. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Convolutional neural networks

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Comparative analysis of thrust force, roughness and roundness error in drilling of aluminium composites using RSM, ANN and fuzzy logic

Comparative analysis of thrust force, roughness and roundnes...

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作者： Babu, S. Senthil Dhanasekaran, C. Department of Mechanical Engineering VELS Institute of Science Technology & Advanced Studies Chennai India

Making holes without any defect in a solid product made of hybrid Aluminium composite material, is a difficult job in assembly industries. Hybrid composite of Aluminium 7075 reinforced with ceramic materials like silicon carbide, boron carbide, graphite and mica are used in automobile and structural industries due to their excellent mechanical properties. Thrust force developed during drilling, Error in the circularity and poor surface finish of the drilled holes are some of the common problems faced in the drilling process. Hence, to optimise the quality of drilling, analysing these responses under various conditions of drilling by varying the drilling factor become essential. This study discusses the development of various models to predict the thrust force developed, roughness and circularity error in the holes drilled on a hybrid metal matrix composite. Testing of drilling is conducted in CNC vertical machining centre using Titanium aluminium nitride (TiAlN) coated carbide drill tool of 5 mm diameter. Various drilling factors considered in our study are point angle of the drill tool, drilling speed and feed rate. Multiple regression equations using RSM, Artificial neural network (ANN) and Fuzzy Logic algorithms are used to develop the prediction models. The predicted values of thrust force, surface roughness and circularity error from these models are found to be matching with the observed experimental values. © 2023

关键词： Hybrid composites

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A Prototype Design for the Detection of Skin Cancer Types Using Tensorflow 5

A Prototype Design for the Detection of Skin Cancer Types Us...

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5th IEEE International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2023

作者： Ajay, S. Leym Thamizhvani, T.R. Vels Institute of Science Technology and Advanced Studies Department of Biomedical Engineering Chennai India

ISBN: (纸本)9798350338287

Cancer cells that develop abnormally in the regions of the skin are called melanoma. Unusual changes in the skin might be a sign of various cancers because melanoma skin cells are not all identical and they do not usually create many symptoms. The precise and accurate identification of diseases has been a considerable difficulty, but recent developments in computer vision and deep learning have made it possible to meet the following standards. The Proposed methodology is an innovative solution that aids in developing a device prototype for the identification of skin cancer. Different modules of deep learning algorithms have shown tremendous success in classifying various skin cancer conditions. With the help of the deep learning algorithms, that have been trained on a set of skin cancer image datasets using different types of neuron-wise and layer-wise visualization techniques. The model is deployed using the Django web framework for the early identification of skin cancer. The layers in the deep learning network record the colors and textures of lesions specific to skin illnesses upon diagnosis, which simulates human decision-making. These deep learning layers are embedded in the device prototype for the identification of the different types of skin cancer. Thus, a prototype with deep learning systemic algorithms with 97% efficiency is designed for the identification of different skin cancer. © 2023 IEEE.

关键词： Learning algorithms

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