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Cloud-Infused AWS Services: Automobile Database Management System

Cloud-Infused AWS Services: Automobile Database Management S...

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International Conference on Networking, Embedded and Wireless Systems (ICNEWS)

作者： Uthej K Nagandla Krishna Sai Keerthan Nikhil Kumar Musunuru Beena B M Dept. of Computer Science and Engineering Amrita School of Computing Bengaluru India

ISBN: (数字)9798350367461

ISBN: (纸本)9798350367478

A Cloud-based Automobile Database Management System serves as a specialized software application dedicated to efficiently managing databases hosted on cloud infrastructure, encompassing both system hard drives and networked servers. Various types of DBMS are intricately designed to oversee and regulate databases tailored for specific purposes. In the context of organizing comprehensive information on automobiles, leveraging cloud technology is not merely beneficial but imperative. As part of our strategic initiative, we are implementing a cutting-edge approach that involves the utilization of diverse cloud services, including S3 (Simple Storage Service), EC2 (Elastic Compute Cloud), and IAM (Identity and Access Management), Cognito, Cloud Watch, Simple Notification System (SNS), AWS RDS (Relational Database Service). Our proactive strategy involves the development of an intuitive user interface hosted on the cloud. This interface empowers customers to seamlessly select and explore their preferred vehicles based on individual usage criteria. The innovative integration of cloud services, such as S3 for robust storage, EC2 for scalable computing power, and IAM for secure access control, ensures scalability, accessibility, and smooth functionality, RDS optimizes database management, SNS enables real-time communication, and CloudWatch ensures proactive monitoring. Cognito enhances user authentication and authorization. This comprehensive approach not only enhances the overall user experience but also simplifies the process of selecting a dream vehicle for our customers. A comparative analysis has been sustained for AWS Servies, MySQL of 38% more reliable in retrieval time with Google Cloud Platform (GCP), MySQL.

关键词： Scalability Relational databases User interfaces Aerodynamics Real-time systems Database systems Automobiles Reliability Vehicle dynamics Monitoring

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Cardiovascular Disease Prediction Utilizing Machine Learning and Feature Selection with Clonal Selection Algorithm

Cardiovascular Disease Prediction Utilizing Machine Learning...

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Sustainable Technologies for Industry 4.0 (STI), International Conference on

作者： Wahidur Rahman Riasaad Haque Aneek Md. Moinuddin Md. Shadman Sakib Md. Sadiq Iqbal Mohammad Motiur Rahman Dept. of Computer Science and Engineering Uttara University Uttara Dhaka Bangladesh Dept. of Computer Science and Engineering Z.H. Sikder University of Science and Technology Bhedarganj Shariatpur Dept. of Computer Science and Engineering University of Information Technology and Sciences Dhaka Bangladesh Dept. of Computer Science and Engineering Bangladesh University Adabor Bangladesh Dept. of Computer Science and Engineering Mawlana Bhashani Science and Technology University Tangail Bangladesh

A substantial and rising number of patients suffer from cardiovascular diseases, including heart attacks, heart failure, and other related illnesses. This case surge places increasing pressure on healthcare professionals and administrators while patients grapple with growing medical costs. To address these challenges, an automated system is necessary within the healthcare sector. In this paper, we present a cardiovascular health monitoring system that incorporates Machine Learning techniques. The study employed feature selection techniques on a secondary dataset. The study has used a nature-inspired technique, namely the Clonal Selection Algorithm (CSA) and Maximum Relevance Minimum Redundancy (mRMR) technique, to identify the most prominent feature in the detection of cardio-vascular illness. This approach was combined with a collection of Machine Learning classifiers. A group of experimental data has been listed to assess the suggested model's effectiveness. The research findings indicated a maximum accuracy rate of 100% when employing the proposed algorithms and orientations. The study also discusses the performance analysis for CSA and mRMR using a set of performance evaluation matrices. Based on the obtained results, it can be inferred that the suggested model will likely exhibit a high level of effectiveness in identifying cardiovascular diseases.

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An Improved Diagnostic Approach for Classifying Tomato Leaf Diseases using Ensemble Deep Learning based Technique

An Improved Diagnostic Approach for Classifying Tomato Leaf ...

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

作者： Salil Batra Gouri Shankar Chakraborty Joy Chakra Bortty Sourav Das Polok Tamjid Ahmed Tanvir Ahmed Taki Dept. of Computer Science and Engineering Lovely Professional University Phagwara Punjab India Department of Computer Science Westcliff University Irvine California USA

ISBN: (数字)9798350367904

ISBN: (纸本)9798350367911

Tomato is one of the most common vegetables that has high commercial importance for abundant production to meet the huge demand world-wide. There are several challenges that put impact on the mass production of tomato, and which are required to be resolved timely. One of the major challenges is tomato leaf diseases where different types of diseases are there which need to be identified correctly to protect the plants, otherwise it can cause severe harm to the plants which ultimately effects the production of tomato. To have a solution, several scientists and researchers have been working on this to classify diseases in a very initial stage. Diseases of the plants can be classified from leaf image, but it’s difficult to identify disease manually by observing through eyes. Deep learning techniques are being used to identify different types of disease using the leaf image. Several existing approaches have been discussed in this study where different detection processes have been proposed. But, in most of the cases, several limitations have been observed regarding the performance of those traditional frameworks. In this study, a novel disease detection approach has been proposed to detect multiple types of tomato leaf disease through analyzing the leaf images. Here, after combing the performances of four CNN models (MobileNetv2, ResNet50, VGG19, VGG16), an ensemble deep learning technique has been applied to identify different types of the tomato leaf disease as well as to classify the healthy and affected leaf. The performance achieved from the proposed ensemble framework ensures optimum accuracy of 96.7% with efficiency. A proper comparative analysis has been presented that supports the novelty and potentiality of the work.

关键词： Deep learning Mass production Image segmentation Accuracy Explainable AI Production Aerospace electronics Ensemble learning Diseases Residual neural networks

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Perceptual Crack Detection for Rendered 3D Textured Meshes

Perceptual Crack Detection for Rendered 3D Textured Meshes

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International Workshop on Quality of Multimedia Experience, QoMEx

作者： Armin Shafiee Sarvestani Wei Zhou Zhou Wang Dept. of Electrical & Computer Engineering University of Waterloo Canada School of Computer Science and Informatics Cardiff University United Kingdom

ISBN: (数字)9798350361582

ISBN: (纸本)9798350361599

Recent years have witnessed many advancements in the applications of 3D textured meshes. As the demand continues to rise, evaluating the perceptual quality of this new type of media content becomes crucial for quality assurance and optimization purposes. Different from traditional image quality assessment, crack is an annoying artifact specific to rendered 3D meshes that severely affects their perceptual quality. In this work, we make one of the first attempts to propose a novel Perceptual Crack Detection (PCD) method for detecting and localizing crack artifacts in rendered meshes. Specifically, motivated by the characteristics of the human visual system (HVS), we adopt contrast and Laplacian measurement modules to characterize crack artifacts and differentiate them from other undesired artifacts. Extensive experiments on large-scale public datasets of 3D textured meshes demonstrate effectiveness and efficiency of the proposed PCD method in correct localization and detection of crack artifacts. Moreover, to quantify the performance of the proposed detection method and validate its effectiveness, we propose a simple yet effective weighting mechanism to incorporate the resulting crack map into classical quality assessment (QA) models, which creates significant performance improvement in predicting the perceptual image quality when tested on public datasets of static 3D textured meshes. A software release of the proposed method is publicly available at: https://***/arshafiee/crack-detection-VVM

关键词： Image quality Solid modeling Visualization Three-dimensional displays Quality assurance Visual systems Predictive models

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Intelligent Car Parking System Using WSN 6

Intelligent Car Parking System Using WSN

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6th Global Conference on Wireless and Optical Technologies, GCWOT 2023

作者： Ratti, Steve Azarsh Pirzada, Nasrullah Shah, Syed Mohammad Ali Naveed, Anjum Mehran University of Engineering & Technology Jamshro Department of Telecommunication Engineering Hyderabad Pakistan Mehran University of Engineering & Technology Hyderabad Pakistan Hazara University Mansehra Dept. of Computer Science & Technology Mansehra Pakistan

ISBN: (纸本)9798350333718

Numerous technologies are constantly being created due to the rapid rise in the standardization and automation of operational and management systems. It simplifies procedures and allows microelectronics technology to advance more often. It was managed by an Android app and controlled by sensor networks and parking systems. The wireless sensor network manages parking spot management, parking lot reservations, vehicle navigation, and other complex circumstances. This study suggests a wireless sensor network-based and android app-based intelligent parking system. Sensors installed beneath enable the cutting-edge parking system to function. The research suggests an intelligent parking system that uses wireless sensor networks and IR, magnetic, and light sensors. The ground-level sensors used by the advanced parking system function. The base station receives the node/slot information, and the base station delivers data to FTP. At the user's request, FTP transmits details about nodes and spaces to mobile devices. The idea came from using an IoT application to control the automobile parking system, which is crucial to our daily lives. For this purpose, a mobile application for Android called Smart Parker was developed. It provides information about a parking lot, such as available or reserved spaces. Sensors at the base station will send information about parking spaces to the FTP server. The user of the innovative payment system is required to pay to park the car. Cash is first collected using cash counters, but maintaining them is challenging. Later, different methods are employed to collect the payment. The payment is made by an Automated Vehicle Identification (AVI) tag using RFID technologies. Smart, debit, and credit cards are contact methods, whereas RFID technology and mobile devices are contactless alternatives. The smart parking system on FPGA (Finite State Machine Modeling) works on two main modules, i.e., the identification module and slot checking module. The

关键词： Internet of things

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Hybrid Quantum Classical Machine Learning with Knowledge Distillation

Hybrid Quantum Classical Machine Learning with Knowledge Dis...

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IEEE International Conference on Communications (ICC)

作者： Mingze Li Lei Fan Aaron Cummings Xinyue Zhang Miao Pan Zhu Han Dept. of Electrical and Computer Engineering University of Houston TX USA Dept. of Electrical and Computer Engineering Engineering Technology University of Houston TX USA Department of Computer Science Kennesaw State University Marietta GA USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

The rapid advancement of machine learning (ML) and the growing need for computational power have led to the exploration of quantum computing, which offers significant potential for faster complex calculations. However, Quantum Machine Learning (QML) faces challenges due to the limited number of qubits and noise of quantum circuits, particularly with Noisy Intermediate-Scale Quantum (NISQ) devices. These challenges severely limit the current capacity to train accurate and stable Quantum Machine Learning Models. In this paper, we propose a novel framework for QML that employs the knowledge distillation method to harness the power of well-trained classical machine learning (CML) models and enhance the training performance of QML models. In this framework, we utilize the well-trained CML as a teacher model to assist the training of the student QML model using the knowledge distillation method. By distilling knowledge from the robust CML model, our framework can potentially address the problem of the barren plateau which hinders effective model training. Knowledge distillation is well suited for this framework through the transfer of knowledge without parameter sharing. Through empirical tests, our framework has demonstrated not only an increase in the accuracy of QML models but also a notable improvement in training stability.

关键词： Training Analytical models Accuracy Computational modeling Qubit Machine learning Stability analysis

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Analysis of the Influence of Students' Identity on Academic Performance

Analysis of the Influence of Students' Identity on Academic ...

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2022 IEEE International Multi-Conference on engineering, computer and Information sciences, SIBIRCON 2022

作者： Pustovalova, Natalya V. Avdeenko, Tatiana V. Novosibirsk State Techinal University Dept. Automation and Computer Engineering Novosibirsk Russia Novosibirsk State Techinal University Dept. Applied Mathematics and Computer Science Novosibirsk Russia

ISBN: (纸本)9781665464802

This paper presents the results of ongoing work. Today, personalization is one of the main trends in education. Universities collect and analyze data about the students' identity and their needs in order to develop specialized systems that support the personalization of the educational process. The purpose of the current work is to verify the applicability of the "Learner model"that was designed previously. This model is one of the main component of universities' intelligent learning system architecture. This model is based on the results of psychometric test. We increased the sample of students by including new observations and new predictors. Having performed preliminary data preparation, we obtained linear regression models. The results of psychometric tests were used as independent predictors (regressors). We tested students from the 2nd to 4th year of the Faculty of Applied Mathematics and Informatics. The dependent variable is the general ECTS score, as well as the average score for the groups of disciplines (mathematical, work-oriented, humanitarian). We compared the resulting models with those obtained using a smaller sample. In general, our conclusion was confirmed. © 2022 IEEE.

关键词： Students

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LexChain: A Blockchain-based Solution to Safeguard Electronic Evidence in Legal Systems

LexChain: A Blockchain-based Solution to Safeguard Electroni...

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International Symposium on Digital Forensic and Security (ISDFS)

作者： Neha Adhikari Manan Chhajed Divya Raichura Prasenjit Bhavathankar Dept. of Computer Science and Engineering(AIML) Sardar Patel Institute of Technology Mumbai India Dept. of Computer Engineering(AIML) Sardar Patel Institute of Technology Mumbai India

ISBN: (数字)9798331509934

ISBN: (纸本)9798331509941

The adoption of digitization has revolutionized data storage technology, resulting in improved accessibility, efficiency, collaboration, and reduced storage costs. A significant impact of this can be seen in legal systems such as case management tools and e-evidence in litigation. However, ensuring the integrity and authenticity of digital evidence poses major challenges. Forensic evidence is the most sensitive and tangible part of legal investigations and traditional methods for storing physical records and standard digital practices for document storage and forensic evidence preservation are at risk of manipulation and unauthorized access. Such issues raise concerns about the integrity of evidence in legal cases. Beyond the security concerns, manual processes such as storage, management and authentication of evidence are expensive and suffer from delays. The proposed system addresses these challenges using blockchain technology to build a robust system that securely stores all legal documents and forensic evidence. Utilizing a blockchain framework such as Ethereum can boost the security of the legal system while also automating the legal process and ensuring compliance with data privacy regulations through smart contracts, thus improving efficiency, reducing costs, and ensuring reliability and transparency.

关键词： Costs Digital forensics Storage management Smart contracts Memory Regulation Blockchains Safety Reliability Standards

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A Dual-Port, and Single-Element Planar Inverted-F Antenna for Current 4G/5G Portable Applications 21

A Dual-Port, and Single-Element Planar Inverted-F Antenna fo...

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21st International Multi-Conference on Systems, Signals and Devices, SSD 2024

作者： Alja'Afreh, Saqer S. Altakhaineh, Amjaad T. Al-Shamaileh, Mallak H. Matarneh, Aser M Daoud, Omar R. Al-Khawaldah I, Mohammad School of Engineering and Computing American International University Electrical and Computing Engineering Al-Jahra Kuwait Pioneers International Academy Data Science and Machine Learning Dept. Amman Jordan Al-Ahliyya Amman University Communications and Computer Engineering Amman Jordan

ISBN: (纸本)9798350374131

A first-hand, low-profile, two-port planar inverted-F antenna is proposed for current 4G/5G sub-3 GHz hand-portable multiple-input and multiple-output (MIMO) applications. The design features a profile of about 5 mm and dual-coplanar feeds, which are isolated using only a modified top plate, while the shared ground plane is not perturbed as in previous designs. An open-edge slot on the top of the PIFA provides a 3λ/4 current path. The proposed antenna covers approximately a 15% impedance bandwidth fraction in the range of 2.45-2.85 GHz. The simulated results, including scattering parameters, far-field radiation patterns, and the envelope correlation coefficient, all exhibit excellent features. © 2024 IEEE.

关键词： Antenna feeders

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Quality analysis of distributed max-plus algebra based morphological wavelet transform 2

Quality analysis of distributed max-plus algebra based morph...

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2nd International Conference on Artificial Intelligence, Computational Electronics and Communication System, AICECS 2023

作者： Shetty, Shravya S Ashwini, B. Venugopala, P.S. Kumaki, Takeshi Computer Science and Engineering NMAM Institute of Technology NITTE Deemed to Be University Udupi India Dept of Information Science and Engg NMAM Institute of Technology NITTE Deemed to Be University Udupi India Dept of Electronics and Computer Engg Ritsumeikan University 1-1-1 Noji-Higashi Kusatsu Shiga525-8577 Japan

This proposed technique employs a disseminated data embedding watermarking strategy that is based on a morphological wavelet transform and uses Max-plus algebra to achieve high image quality, big data capacity, and reasonable operational cost. Previously, we had to use a simple MMT watermarking methodology and estimated that using image quality parameters, primarily considering the diagonal component (HH). For embedding watermarks after the decomposition process carried through MMT, the presented distributed data embedding strategy, however, emphasises on middle frequency signal-groups. We have used hypothesized watermarking technique to process five benchmark images during the experiments to examine the scheme's capability. The PSNR and the SSIM values are elevated by the proposed approach. The combined (high and low) frequency's PSNR value is preferable towards the high frequency's. It is also remarked that the middle-frequency SSIM value is higher than the high-frequency value. © Published under licence by IOP Publishing Ltd.

关键词： Wavelet transforms

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