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

作者： Patil, Parth Inamdar, Vibhav Powar, Rohan Patil, Atharv Mulla, Amaan Jadhav, Ranjita D. Y. Patil College of Engineering & Technology Department of Computer Science and Engineering Kolhapur India

ISBN: (纸本)9798350360165

Pneumonia is an infection that leads to inflammation and fluid accumulation within the pulmonary system. Pneumonia can be caused by bacterial, fungal or viral infection. Pneumonia causes breathing difficulties as the air sacs in the lungs might be filled with fluid or pus. It can lead to fever and coughing, often accompanied by the production of yellow, green or even bloody mucus. Pneumonia is a major cause of death throughout the globe. Pneumonia diagnosis is done using an X-ray of the lungs. Pneumonia detection software can detect pneumonia in early stages which can lead to lower mortality rates. With advanced deep learning neural networks such as CNN, Xray images can be classified as pneumonic or non-pneumonic. This can be integrated into a software package that can work across different systems to help people detect pneumonia with just their lung X-rays. © 2024 IEEE.

关键词： Software packages

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detection of Vehicle lights and Classification of Its State 3

Detection of Vehicle Lights and Classification of Its State

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3rd International Conference on Advanced Computing Technologies and Applications, ICACTA 2023

作者： Kumar Jha, Raman D y Patil College of Engineering Department of Computer Engineering Pune India

ISBN: (纸本)9798350348347

The lights of a vehicle are an essential part of it. It not only helps to drive but also helps in controlling the vehicle. In this paper, a novel method is presented for the detection of vehicle headlights and taillights. This paper also classifies the state of the vehicle lights. Vehicles that are near to the camera are considered for the experiment and the size of the vehicle light had a significant impact on the detection accuracy. Indian driving dataset (Idd) was used for the training and testing of the model. Idd consists of the rural and urban roads of Hyderabad and Bengaluru City. It covers various light conditions like day and night and scenarios like a smaller number of vehicles and a greater number of vehicles for detection. Some data preprocessing was also performed before using the dataset for the experiment. The model first detects the vehicle light and then it also classifies the state of the vehicle light. For vehicle light detection, some of the widely used object detection models such as YOlO, Faster RCNN, and MobileNet are used. For the classification of the state of the vehicle light, a color thresholding approach was used to develop the system. The system achieved a mean average precision(mAP) of 91.1%. It classifies it as Headlight on, Taillight on, or light off. The model performance was also evaluated and tested on Idd videos and it was very promising. © 2023 IEEE.

关键词： Image segmentation

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Model Study of Reinforced Earth Wall Using dune Sand as a Backfill Material 9th

Model Study of Reinforced Earth Wall Using Dune Sand as a Ba...

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9th Indian Young Geotechnical Engineers conference, 9IYGEC 2023

作者： Shah, Manish V. Shah, Alpa J. Kalsariya, Vimal Shukal, Sparsh Department of Applied Mechanics L. D. College of Engineering Ahmedabad India

ISBN: (纸本)9789819766420

As reinforced earth walls are more durable and aesthetically better finished when compared to conventional retaining walls, the flexible nature of reinforced earth mass enables a reinforced earth wall to withstand large differential settlements without distress. Reinforced earth walls are consequently economical when the height of the structure is large or ground conditions are unfavorable and suitable backfill materials are locally available. The main objective of the research is to evaluate the feasibility of dune sand as a sustainable fill material for reinforced earth walls through the infusion of synthetic reinforcement at suitable positions. dune sand from Jaisalmer district, Rajasthan, is used as a backfill material for reinforced earth walls. For this purpose, load settlement and load–displacement tests were carried out on dune sand and River Sand, with a mix proportion of 1(dS):1(RS), 1.5(dS):1(RS), and 2(dS):1(RS) using a large-scale model test setup. To measure the displacement and settlement, dial gauges were set up in the RE wall model to measure the vertical settlement of the backfill material and the lateral displacement of the RE wall. The vertical pressure distribution at the base of the RE wall using three different methods: Uniform pressure distribution, Trapezoidal pressure distribution, and Meyerhof’s pressure distribution, Vertical stress distribution on horizontal and vertical planes, active earth pressure were calculated for the justification of the experimental results. The results depicted a mixture of 1(dune Sand):1(River Sand) to be satisfactory. With the increase in the percentage of dune sand in the backfill, the composition shows an increase in lateral displacement. The vertical settlement of 2(dune Sand):1(River Sand) is much less compared to other proportions. © The Author(s), under exclusive license to Springer Nature Singapore Pte ltd. 2025.

关键词： Sand

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Smart Stethoscope for Remote Healthcare Monitoring Using IoT: A Cost-Effective Solution 3

Smart Stethoscope for Remote Healthcare Monitoring Using IoT...

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3rd IEEE Asian Conference on Innovation in Technology, ASIANCON 2023

作者： Rao, Yeshoviraj Singh Mehta, Bhavin Kathiriya, Ami dharvia, Abhishek Pancholi, devansh Patel, Harshal L.D. College of Engineering Biomedical Engineering Department Ahmedabad India

ISBN: (纸本)9798350302288

Worldwide, the major cause of death is Cardiac dysfunction, which can be detected through heart sounds. Acoustic stethoscopes are one of the oldest methods of auscultation. An ordinary acoustics-based stethoscope is limited in providing high-quality sound in noisy environments. This paper addresses the problem of cost-effectively making a smart stethoscope using modern electronics and computing technologies for cardiac auscultation. Along with that, to have telemedicine involved with the utmost accuracy possible. A signal conditioning circuit is designed to process the auscultation signals measured by a condenser microphone using a Preamplifier, a High pass filter, a low Pass Filter, and an Op-Amp Subtractor. An ESP32 development board is used to convert the signal to digital format and transmit the signal through Bluetooth to an Android application to visualize signals. The smart stethoscope is designed to record and transmit real-time heart sounds to healthcare professionals while considering cost-effectiveness and portability. In the future, we can use the recorded signals to predict cardiac disorders using deep learning models. © 2023 IEEE.

关键词： Cost effectiveness

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location-Based Geographical-Spatial data Mining for detection and Visualization of Reported Problems using Image Processing Techniques 14

Location-Based Geographical-Spatial Data Mining for Detectio...

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14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Harsoor, Anita Soma, Bhavani P D A College of Engineering Department of Computer Science and Engineering Kalaburagi India

We face many possible problems/issues in our daily lives, such as potholes, garbage filling, uncomfortable parking, broken roads, etc. To report that kind of problem becomes a great hassle. To solve this problem we developed a Geographical-Spatial data Mining System (GdMS), an android mobile application named Civicawareness for retrieving and analyzing textual data with geographical locations and photos as proof. The model has four constituents: data collection, data pre-processing, data analysis, and data visualization. Here, we use the k-means algorithm for clustering and SVM for classification. This system will collect a large number of data that will be used by common people to post the problems they have found. © Grenze Scientific Society, 2023.

关键词： data mining

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Modified Mackenzie Equation and CVOA Algorithm Reduces delay in UASN

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computer Systems Science & engineering 2022年第5期41卷 829-847页

作者： R.Amirthavalli S.Thanga Ramya N.R.Shanker Department of Computer Science and Engineering Velammal Engineering CollegeChennai66India Department of Information Technology R.M.D Engineering CollegeTiruvallur1206India Department of Computer Science and Engineering Aalim Muhammed Salegh College of EngineeringChennai55India

In Underwater Acoustic Sensor Network(UASN),routing and propagation delay is affected in each node by various water column environmental factors such as temperature,salinity,depth,gases,divergent and rotational *** sound velocity increases the transmission rate of the packets and the high dissolved gases in the water increases the sound *** dissolved gases and sound velocity environment in the water column provides high transmission rates among UASN *** this paper,the Modified Mackenzie Sound equation calculates the sound velocity in each node for energy-efficient *** Ratio Optimization Method(GROM)and Gaussian Process Regression(GPR)predicts propagation delay of each node in UASN using temperature,salinity,depth,dissolved gases *** gases,rotational and divergent winds,and stress plays a major problem in UASN,which increases propagation delay and energy *** values from GPR and GROM leads to node selection and Corona Virus Optimization Algorithm(CVOA)routing is performed on the selected *** proposed GPR-CVOA and GROM-CVOA algorithm solves the problem of propagation delay and consumes less energy in nodes,based on appropriate tolerant delays in transmitting packets among nodes during high rotational and divergent *** simulation results,CVOA Algorithm performs better than traditional dF and lION algorithms.

关键词： Gaussian process regression(GPR) golden ratio optimization method(GROM) corona virus optimization algorithm(CVOA) water column variation dissolved gases acoustic speed divergent wind rotational wind

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Feasibility Study of Offshore Triceratops-Supported Floating Offshore Wind Turbine

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Journal of The Institution of Engineers (India): Series A 2024年第2期105卷 295-305页

作者： Srinivasan, Chandrasekaran Serino, Giorgio Chauhan, Yogesh J. Sanghvi, Chaitanya Gohil, Aishwary Deptartment of Ocean Engineering Indian Institute of Technology Madras Chennai India Deptartment of Structural Engineering University of Naples Federico II Naples Italy Deptartment of Applied Mechanics L. D. College of Engineering Ahmedabad India

Many countries have updated their renewable energy policies, in which considerable attention is drawn towards offshore wind energy. Offshore industry has witnessed many evolved structural platforms, whether they are fixed or floating. As far as the oil and gas industry is concerned, there are various floater schemes currently in practice, such as SPAR, Tension-leg Platform, and Semi-Submersible. Among these, Triceratops is a new concept which has many structural benefits over existing floating platforms. Several studies have reported their advantages and applications in oil and gas industry. The current study focuses on the feasibility of offshore Triceratops as an alternate floater scheme for Floating Offshore Wind Turbines (FOWTs) in deep waters. The coupled dynamic analysis due to wind-induced motion and hydrodynamics of the platform under waves are examined. Wind loads are modelled using OpenFAST, and the results are coupled in ANSYS Workbench to obtain hydrodynamic diffraction and motion responses. The responses for the two floater schemes, i.e. SPAR and Triceratops-supported FOWT, are compared, and the necessary conclusions are laid to provide insights into the feasibility of using the Offshore Triceratops for supporting FOWT. © The Institution of Engineers (India) 2024.

关键词： Tension-leg platforms

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An Efficient Technique for the Better Recognition of Oral Cancer using Support Vector Machine 7

An Efficient Technique for the Better Recognition of Oral Ca...

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7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Manikandan, J. devakadacham, Sterlin Rani Shanthalakshmi, M. Arockia Raj, Y. Vijay, K. Rajalakshmi Engineering College Thandalam Computer Science and Engineering Chennai India R. M. D. Engineering College Computer Science and Engineering Kavaraipettai India Sri Venkateswara College of Engineering Computer Science and Engineering Chennai India PSNA College of Engineering and Technology Computer Science and Engineering Dindugal India

ISBN: (纸本)9798350397253

Accuracy is among the most important factors in a disease diagnosis. It is essential to select the characteristics that you find most pertinent for the highest accuracy. This study aims to more accurately predict the presence of the primary stage of squamous cell carcinoma using fewer indicators. Stages of oral cancer were first demonstrated to be predicted by 25 features. The variety of features that are obtained from various patient records is indirectly decreased in this study through the combination of the unified medical system using hybrid features selection techniques to identify the characteristics that are most useful for the identification of oral cancer. Hybrid feature selection has been used to condense 25 qualities into 14 features. The diagnosis of patients with oral cancer is then predicted using four classifiers: Updatable Naive Bayes, Multilayer Perceptrons, K-Nearest Neighbor, and Support Vector Machines. Also, the data show that, after adding feature development decisions with SMOTE during the preprocessing phases, the support vector machine's performance surpasses other machine learning techniques. © 2023 IEEE.

关键词： Support vector machines

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Software-defined-Storage Performance Testing Using Mininet

Software-Defined-Storage Performance Testing Using Mininet

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2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems, ICITEICS 2024

作者： Naik, deepak Ranoji Ghonge, Vilas d. Thube, Smita Mangesh Khadke, Abhijit Mali, Yogesh Kisan Borate, Vishal Kisan G.H. Raisoni College of Engineering and Management Department of Computer Engineering Pune India Viit Department of Computer Engineering Pune India Nutan Maharashtra Institute of Engineering and Technology Department of Computer Engineering Pune India G H Raisoni College of Engineering & Management Department of Aiml Pune India Dr D y Patil College of Engineering & Innovation Department of Computer Engineering Pune India

ISBN: (纸本)9798350382693

Customary capacity the board methods are turning out to be less powerful for dealing with this huge volume of information because of the improvement of server farms and the unforeseen ascent away requirements. By eliminating the capacity control exercises out of the genuine information stockpiling media and placing them in the product layer of a concentrated regulator, Programming Characterized Stockpiling offers an answer for this issue. An insightful programming stack named 'programming characterized foundation' may deal with reasonable product equipment. A software engineer known as programming characterized capacity controls information capacity assets without the utilization of real equipment. Making the capacity engineering of a genuine Programming Characterized Stockpiling framework with no reenactment or imitating is an exorbitant and unsafe technique. Subsequently, the framework should be recreated prior to being utilized, in actuality. In this manner, virtualized proving grounds for such frameworks should be reenacted before genuine execution and sending. In this article, we evaluate software-defined storage engineering using the Programming described Association (PdA) test framework, Mini-net. This framework is designed, assembled, and ready to advance without revisiting the established assembly structure. The core components of Mini-net have been modified to address data distribution challenges in contemporary Sd storage and to scale storage capacity appropriately within this simulated environment. © 2024 IEEE.

关键词： Software testing

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Advancements in Early detection of lung Cancer using YOlOv7 5

Advancements in Early Detection of Lung Cancer using YOLOv7

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： More, Abhijeet Shinde, Snehal R. Patil, Pooja Mahesh Kane, dhanashri Siddhant Mali, Yogesh Kisan Borate, Vishal Kisan Pillai Hoc college of Engineering and Technology Departments of Computer Engineering Maharashtra Rasayani India Mgm College of Engineering Department of Computer engineering Navi Mumbai India G.H Raisoni College of Engineering and Management Pune Wagholi India Dr D Y Patil College of Engineering Innovation Pune Talegaon India

ISBN: (纸本)9798331504403

lung cancer, a leading cause of death worldwide, requires early detection for effective treatment. Traditional diagnostic methods often prove inadequate, highlighting the need for advanced techniques. This research explores the application of YOlOv7, a state-of-the-art object detection algorithm, for identifying malignant nodules in CT scans. By utilizing machine learning-based image processing and object detection, YOlOv7 demonstrates superior performance in accurately detecting even small lung nodules. Its efficiency and accuracy surpass previous methods, offering hope for early diagnosis and intervention. This research contributes to the advancement of lung cancer detection and highlights the potential of machine learning in revolutionizing medical imaging. By enabling earlier diagnosis, YOlOv7 can significantly improve patient outcomes and save lives. © 2024 IEEE.

关键词： lung cancer

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