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An Effective Deep Learning Approach for Kidney Stone Detection in CT Scan Images using Convolutional Neural Network

An Effective Deep Learning Approach for Kidney Stone Detecti...

引用

Computing, Applications and systems (COMPAS), IEEE international conference on

作者： Md. Nurul Islam Md. Fuad Hasan Khan Chowdhury Fariha Nusrat Dept. of Computer Science and Engineering University of Scholars Dhaka Bangladesh Dept. of Computer Science and Engineering United International University Dhaka Bangladesh Dept. of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh

ISBN: (数字)9798331529765

ISBN: (纸本)9798331529772

Kidney stones represent a significant global health concern, frequently causing individuals to seek immediate medical care due to intense pain. Radiological imaging modalities are one of the most common modes of diagnosis, but specialist interpretation is always important for accuracy. In this paper, we present computer vision in an automated kidney stone detection system that involves five stages: loading the dataset, preprocessing data, loading the InceptionV3 model, predicting, and evaluating performance. Various methods of preprocessing and data augmentation were utilized to make the model less biased and more robust. This study uses the InceptionV3 architecture to classify kidney stones in CT scan images of KUB (Kidney, Ureter, and Bladder). We utilize a total dataset of 433 participants, either diagnosed with kidney stones or in a normal state. 278 cases are diagnosed with kidney stones, and 165 are normal cases. The proposed approach achieved an impressive 98.55% accuracy across performance metrics when evaluated on an independent test dataset.

关键词： measurement Accuracy Computed tomography Computational modeling Loading computer architecture Predictive models Data models Reliability Load modeling

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Enhancing Academic Feedback systems with Deep Learning and Ensemble Methods

Enhancing Academic Feedback Systems with Deep Learning and E...

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Advances in computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), international conference on

作者： Hemant Sharma Hiren Joshi Dept. Computer Science Gujarat University Ahmedabad India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

This paper attempts to improve the academic feedback systems via complex deep learning and ensemble methods. Leveraging the NIRF Rankings 2022 dataset that provides radical performance metrics of Indian academic institutions, the project would attempt to develop trustworthy models to monitor and facilitate improvement in the academic feedback system. The techniques used in data preparation prevent missing values, outliers, and categorical data in using advanced machine learning models. In order to construct the model and capture fine-grained patterns linked to academic achievement, 1D Convolutional Neural Networks (CNNs) along with Multi-Layer Perceptrons (MLPs), both individually and in combination, are employed extrapolated from the National Institutional Ranking Framework to obtain data. Precision, accuracy, recall, along with the F1-score will be used to evaluate these models' performance. By the time these findings are finished, they should be able to provide practical advice on how to improve academic evaluations' effectiveness and advance educational institutions' more flexible feedback systems.

关键词： Deep learning measurement Accuracy Computational modeling Multilayer perceptrons Data models Ensemble learning Hybrid learning Convolutional neural networks Reliability

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Symbolic regression-based hybrid models for a manufacturing process

Symbolic regression-based hybrid models for a manufacturing ...

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international conference on Control, Decision and Information Technologies (CoDIT)

作者： Seulki Han Debasish Mishra Krishna R. Pattipati George M. Bollas Department of Chemical & Biomolecular Engineering University of Connecticut Storrs CT USA Data Science & Information Systems Krea University Sri City Andhra Pradesh India Department of Electrical & Computer Engineering University of Connecticut Storrs CT USA

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

Hybrid models are increasingly employed to simulate intricate physical processes by combining domain expertise embedded in physics-based models with process measurements-based data. The combination of domain knowledge and measurement data results in hybrid models that lead to high-accuracy decisions, extrapolation capabilities, and compliance with basic physical laws. Surrogate modeling, one aspect of hybrid modeling, involves a simplified model to capture the physics in a process, emphasizing an adaptable mathematical expression. This study applies hybrid modeling to address the intricate tool wear process in precision machining by developing a recursive model using symbolic regression.

关键词： Adaptation models Manufacturing processes Machining Predictive models Feature extraction Mathematical models Data models Time measurement Information technology Physics

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The Neutron Fluence Rate measurement and Control Simulation of Adaptive Algorithm Simulates the Algorithm in Nuclear Power Plant

The Neutron Fluence Rate Measurement and Control Simulation ...

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international conference on Information systems and computer Aided Education (ICISCAE)

作者： Gang Guan Mengfei Shi Guoqing Liu Tao Zhang Yu Wang Yangjiang Nuclear Power Co. Ltd. Yangjiang China CGN Digital Technology Co. Ltd. Beijing China

ISBN: (数字)9798350350760

ISBN: (纸本)9798350350777

This project intends to use the step reaction data of nuclear power generation unit to establish its adaptive parameter model. Then the predictive control algorithm based on energy density equivalence relation is studied. The neutron flow rate variation in the power range of nuclear instruments in nuclear power plants is a key protection parameter of nuclear power plants, and its reasonable correction can not only ensure that it can continue to play its role in the case of rebound, drop rod and other failures, but also prevent the shutdown caused by pressure dumping at the beginning and end of the life cycle, thereby reducing t he economy of nuclear power plants. In this paper, the correction factor of neutron energy rate is simulated by means of simulation and analysis. The algorithm does not need to strictly model the specific modeling mode of the system, and has low real-time performance, good tracking performance and robustness, and can effectively eliminate unmeasurable disturbance. The method is proved to be feasible by computer simulation.

关键词： Adaptation models Temperature Computational modeling Instruments Neutrons Software Robustness Real-time systems Transient analysis Power generation

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Design of a force sensing needle guide for an MRI-compatible robotic prostate biopsy system 9

Design of a force sensing needle guide for an MRI-compatible...

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9th IEEE RAS/EMBS international conference for Biomedical Robotics and Biomechatronics (BioRob)

作者： Liu, Rongrong Ko, Seong Young Chonnam Natl Univ Sch Mech Engn Gwangju 61186 South Korea Chonnam Natl Univ Grad Sch Mech Engn Gwangju 61186 South Korea

ISBN: (数字)9781665458498

ISBN: (纸本)9781665458498

Prostate biopsy is the gold standard for detecting prostate cancer. Magnetic Resonance Imaging (MRI), which provides higher spatial contrast and resolution than transrectal ultrasound (TRUS) or computer tomography (CT), is expected to improve the accuracy of prostate cancer diagnosis. On this account, a novel robotic prostate biopsy system guided by only MRI is under development. For its safe remote placement and insertion, the robotic system will include a 3-degree-of-freedom (DOF) force sensing needle guide using multiple fiber Bragg grating sensors. On the premise of protecting the human body from being accidentally injured by the movement of the robotic system, it helps to provide a faster and more accurate tissue sampling function. There are currently no studies on force sensing needle guides. For ease of manufacturing process and for increasing force sensitivity, a unique separable force-sensitive block is proposed to fix the sensors, and a total of 3 fibers with two FBGs each are used. Simulation modeling is used in the design and optimization of the unique force-sensitive block. The relationship between the various forces and the FBG strain values is studied. Through the simulation analysis results, it is expected that the proposed needle guide would measure the forces with high accuracy.

关键词： Temperature measurement Force measurement Sensitivity Magnetic resonance imaging Force Biopsy Robot sensing systems

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Comparative Study of Multilingual Intelligent Virtual Assistant

Comparative Study of Multilingual Intelligent Virtual Assist...

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Advancement in Computation & computer Technologies (InCACCT), international conference on

作者： Pallavi Yevale Nilesh Uke Department of Computer Engineering Vishwakarma Institute of Information Technology International Institute of Information Technology Pune India Department of Computer Engineering Indira College of Engineering and Management Pune India

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

Every conversational system or goal-oriented dialogue system must have spoken language understanding (SLU), which is a crucial element. To help the user achieve their desired goals, it is essential to comprehend the user's statement. The multilingual intelligent virtual assistant model based techniques for accurately reacting to the user without delay are taken into consideration by many studies in recent days, but very few review articles are available on multilingual virtual assistant. In this study, multilingual intelligent virtual assistant systems were examined. To enhance accuracy and F1 measure regarding the multilingual intelligent virtual assistant model, benefits and downsides of every strategy, challenges and potential areas for future research are observed. The challenges examined in the study such as over fitting issues, lack of datasets, failure in recognizing low resource images, and poor detection performance can be overcome by future researches.

关键词： Location awareness Accuracy Reviews Social networking (online) Virtual assistants Computational modeling Medical services Time measurement Multilingual Time factors

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A Finite Element Analysis Model for Internal Partial Discharges Under DC Voltage

A Finite Element Analysis Model for Internal Partial Dischar...

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2022 IEEE international Power Modulator and High Voltage conference, IPMHVC 2022

作者： Saghafi, Mohammadreza Ghassemi, Mona Lehr, Jane Borghei, Moein Kordi, Behzad Oliver, Derek Virginia Tech Department of Electrical and Computer Engineering BlacksburgVA United States University of New Mexico Department of Electrical and Computer Engineering UM Albuquerque United States Avalanche Energy Designs SeattleWA United States University of Manitoba Department of Electrical and Computer Engineering WinnipegMB Canada

ISBN: (纸本)9781665471657

While the topic of partial discharges (PD) has been well studied for ac systems, it is immature for de systems. Although much work has been done and significant progress has been made on PD measurement and detection techniques, this is not the case for PD modeling. To address these technical gaps, a finite element analysis (FEA) model for internal PD under dc is, for the first time, developed to help understand the mechanisms behind PD under dc voltages. The model is validated through experimental studies where testing samples, one with a void and another without any void, are built using 3D printing. The sample which has a void inside will cause internal PD. There is a good agreement between the measured and simulated magnitude of charges and the frequency of PD signals under de voltages. © 2022 IEEE.

关键词： Finite element method

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Analysis of Techniques for Cotton Crop Disease Detection & Monitoring

Analysis of Techniques for Cotton Crop Disease Detection & M...

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Intelligent systems and Advanced Applications (ICISAA), international conference on

作者： Prajakta S. Gupta A. V. Zade Computer Science & Engineering G. H. Raisoni University Amravati India

ISBN: (数字)9798331539948

ISBN: (纸本)9798331539955

Cotton is one of the most important crops in the world, playing an important role in the textile industry and contributing to the economy of many countries. However, cotton plants are susceptible to many diseases that reduce yield and quality. Early and accurate detection of these diseases is important for effective management and control, thus minimizing financial losses. Traditional diagnostic methods require expert judgment, are time-consuming and complex, and are generally impractical for large-scale applications. Therefore, there is interest in advances in machine learning and computer vision to develop automated systems for cotton disease prediction and detection. This project focuses on the development and evaluation of machine learning models for cotton leaf disease detection using Transfer Learning (TL) techniques and hybrid models. Cotton, being a vital crop, is susceptible to numerous diseases that can significantly affect yield and quality. Early detection and accurate classification of these diseases are crucial for timely intervention and minimizing economic losses. In this study, we applied several TL models, including VGG16 and VGG19, and assessed their performance using a comprehensive dataset of cotton leaf digital images.

关键词： Training measurement Accuracy Biological system modeling Computational modeling Transfer learning Crops Cotton Textile industry Diseases

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Estimation of rotation measurement error of objects using computer simulation

Estimation of rotation measurement error of objects using co...

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international Youth conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Ekaterina V. Shmatko Nikita Yu. Sivov Anton Yu. Poroykov Department of Physics Named After V.A. Fabrikant National Research University "MPEI" Moscow Russian Federation

In optical instrumentation, one of the tasks is to estimate the instrumental error of existing and developing measurement systems. There are two main approaches to solving this problem: theoretical estimation, physical and computer simulation. This paper presents an approach to computer simulation of an optical system for measuring the position of a freely rotating platform. The simulation was performed in the Unity3D environment. It consisted of generating synthetic images of a freely rotating platform at different positions with defined parameters. The measurement error was determined by comparing the positions measured on the synthesised images with the positions given in the simulation. The paper presents the dependence of the measurement error on the image processing parameters and on the position of the virtual camera relative to the rotating platform obtained in the simulation.

关键词： measurement errors Instruments Computational modeling computer simulation measurement uncertainty Optical variables measurement Position measurement

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NAND-measure: An Android App for Marker-based Spatial measurement 16

NAND-measure: An Android App for Marker-based Spatial Measur...

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16th international joint conference on computer Vision, Imaging and computer Graphics Theory and Applications (VISIGRAPP) / 16th international conference on computer Vision Theory and Applications (VISAPP)

作者： Benndorf, Maik Jugl, Maximilian Haenselmann, Thomas Gaedke, Martin Tech Univ Chemnitz Dept Comp Sci Chemnitz Germany Univ Appl Sci Mittweida Fac Appl Comp Sci & Biosci Mittweida Germany

ISBN: (纸本)9789897584886

In a disaster scenario, a quick decision must be made whether a bridge is stable enough to be used. The natural frequencies of a bridge can provide information about its condition. The actual frequencies (e.g. measured by the acceleration sensor built into a smartphone) must be compared with the desired frequencies. The desired frequencies can be approximated for example with the Finite Element Method (FEM).Among other parameters, the FEM requires the dimensions of the bridge. Numerous applications for spatial measurement for different purposes are offered in the mobile App-stores. However, most of these apps are limited to short distances of up to five meters and are not suitable for the aforementioned scenario. In this article, we present NAND-Measure - an application for spatial measurements for short distances (below one meter) up to distances of 50 meters. Two methods have been implemented - a stereoscopic approach with a single camera and an approach based on the pinhole camera model. Both methods were evaluated by taking sixty over different distances. Overall, the approach based on the pinhole camera model was more accurate and showed smaller deviations.

关键词： Spatial measurement Pinhole Camera Theory Stereoscopy Android

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