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检索条件"任意字段=2015 2nd International Conference on Engineering Technology and Application"

共 27583 条记录，以下是201-210 订阅

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Antenna for C Band applications using a Modified Sierpinski Carpet Fractal Patch 2

Antenna for C Band Applications using a Modified Sierpinski ...

引用

2nd international conference on Microwave, Antenna and Communication, MAC 2024

作者： Muthukumaravel, K. Santhanam, Suganthi Roever Engineering College Department of Eelctronics and Communciation Engineering Tamilnadu Perambalur India K.Ramakrishnan College of Technology Department of Eelctronics and Communciation Engineering Tamilnadu Tiruchirappalli India

ISBN: (数字)9798350350104

ISBN: (纸本)9798350350104

This research presents a modified shape of a gain-maximizing Sierpinski carpet fractal patch antenna. The Modified Sierpinski Carpet Fractal Patch Antenna (MSCFPA) is created in this work. It resonates at five frequencies: 1.77 and 7.2 GHz for the 0th iteration and GHz for the 1st iteration 2.4,3.3,4.9,7.3 and 8.2 GHz. Different performance factors are seen at all frequencies, such as voltage standing wave ratio, return losses, and radiation pattern. FR4 glass resin with the base has a height of 1.6 mm and a relative permittivity of 4.4 mm. A coaxial probe feed feeds the antenna, and It is simulated with the CST Microwave Studio 2021 application. The construction of the proposed antenna is simple. It is looked into between 1 and 10 GHz bands. The Fractal Patch Antenna that was made works well and Suitable for C band applications. © 2024 IEEE.

关键词： Microwave antennas

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Development of a Nail-based application for the Detection of Disease using Image Processing 2

Development of a Nail-based Application for the Detection of...

引用

2nd DMIHER international conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Gote, Pradnyawant M. Kumar, Praveen Dhale, Trishul Mishra, Gaurav Vedprakash Faculty of Engineering and Technology Department of Computer Science & Design Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Computer Science & Medical Engineering Maharashtra Wardha442001 India Jawaharlal Nehru Medical College Department of Radiodiagnosis Maharashtra Wardha442001 India

ISBN: (纸本)9798331528713

Disease diagnosis using non-invasive techniques is a key determinant in the improvement of outcomes in patients and the enhancement of precautionary health measures. The study focuses on the design and development of a nail-based detection application employing image processing techniques to detect diseases such as systemic disease, fungal disease, Leukonychia (White spots on nails) and Paronychia (Nail bed infection) through analysis of the patterns of the fingernails and other related symptoms. The developed system integrates several techniques, comprising a customized imaging application, a user-friendly interface, and software for real-time image processing and disease classification. A variety of algorithms proposed for image processing, such as Median filtering, Sobel Mask and HOG features, are designed to extract important features from nail images and then use machine learning models that match these features against a database of established markers of various diseases. Comprehensive testing utilizing an annotated dataset of nail images demonstrated the system's accuracy in classifying certain diseases, further showcasing its potential for possible usage as a proficient tool for early disease diagnosis. Thus, this application is easy to use, user-friendly interface, and provides advancements in diagnosing diseases both in clinical settings and in the comfort of one's home. The incorporation of this technology into routine clinical practice might facilitate the possibility of early diagnosis and early intervention, which could improve patient outcomes and reduce healthcare system burdens. © 2024 IEEE.

关键词： Median filters

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Automated Wearable Device to Detect Drowning Incidents in Water Bodies 2

Automated Wearable Device to Detect Drowning Incidents in Wa...

引用

2nd IEEE international conference on Advances in Information technology, ICAIT 2024

作者： Basthikodi, Mustafa Shetty, Shreya S. Yashmitha, B. Shetty, Shravya R. Prakruthi, P.D. Computer Science and Engineering Department Sahyadri College of Engineering and Management Mangalore India Information Science and Engineering Department Sahyadri College of Engineering and Management Mangalore India

ISBN: (纸本)9798350383867

Drowning is a leading cause of unintentional death worldwide, with a significant number of fatalities occurring in natural bodies of water, swimming pools, and other aquatic environments. Timely and accurate detection of drowning incidents is critical for preventing tragic outcomes. This provides an overview of challenges, methods, and technologies associated with drowning detection. In the proposed work, we have developed a wearable device supplemented by web application that aims to detect drowning incidents effectively. The system incorporates sensors designed to detect distress signals or abnormal movement patterns underwater, enhancing safety by promptly alerting nearby individuals or authorities to the situation. The sensors are utilized to monitor critical parameters such as SpO2, heartbeat, water presence, as well the temperature and humidity levels of the individual. Key components of this system include the ESP8266 NodeMCU and the Arduino Uno board R3, which provide wired connectivity and microcontroller capabilities, respectively. By continuously monitoring these vital signs and environmental factors, the system can accurately identify potential drowning incidents and trigger timely alerts. © 2024 IEEE.

关键词： Wearable sensors

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Landmark Scene Classification Using Vision Transformer 2

Landmark Scene Classification Using Vision Transformer

引用

2nd IEEE international conference on Data Science and Network Security, ICDSNS 2024

作者： Sangeetha, M. Sunil, G. Shnain, Ammar Hameed Shruthi, B.S. Ahamed, A.U. Shabeer V.S.B. Engineering College Department of Cse Karur India Sr University School of Computer Science & Artificial Intelligence Warangal India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq Nitte Meenakshi Institute of Technology Department of Civil Engineering Bengaluru India Jamal Mohamed College Affiliated to Bharathidasan University Department of Computer Science Tiruchirapalli India

ISBN: (纸本)9798350373110

In building the navigation software application, the Landmark plays an important factor in visual place recognition. There is major problem for performing the classification to visual recognition, due to change of environments like summer, winter, rainy season the place changes. To overcome the problem, the paper proposes a vision transformer as classification for place recognition. In vision transformer the first stage is considerations images are divided into various parts, then it converts into sequence embedding by moving it. To keep information at correct position, the embedding position is used in the parts and the sequence result is sent to various multihead attention layers for final result generation. For validating the proposal, we performed the vision transformer model on the two different datasets such as paris and oxford datasets. The result obtained by performing the vision transformer is demonstrated the other existing model in terms of accuracy in two datasets the given values are 90.63% and 87.30% respectively. © 2024 IEEE.

关键词： application programs

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A Review on Machine Learning Assisted Drying Behaviour Prediction of Agricultural Seeds and Fruits 2

A Review on Machine Learning Assisted Drying Behaviour Predi...

引用

2nd DMIHER international conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Jawre, Sandip Verma, Prateek Kothare, Chandrakant B. Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Artificial Intelligence and Data Science Maharashtra Wardha India Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Maharashtra Wardha India Shri Shankarprasad Agnihotri College of Engineering Department of Mechanical Engineering Maharashtra Wardha India

ISBN: (纸本)9798331528713

Machine learning approaches have been more popular in recent years across many scientific and engineering fields, with the potential to improve drying behavior and thermal property predictions in terms of accuracy and efficiency. Agricultural seeds and fruits must be handled carefully after harvest because drying has a considerable impact on their quality, shelf life, and overall worth. To optimize drying processes and guarantee product quality, drying kinetics and thermal characteristics must be accurately predicted. This review article outlines the basic principles of drying, emphasizes their significance in determining the ideal drying conditions, and provides a thorough overview of the application of machine learning methods for predicting the drying kinetics and thermal properties of agricultural seeds and fruits. Then, in the context of their applications to drying prediction, a summary of several machine learning approaches, including artificial neural networks, support vector machines, and decision trees have been discussed. © 2024 IEEE.

关键词： Fruits

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Optimizing Event Management application through Data Analytics Driver and Dynamic Exploration 2

Optimizing Event Management Application through Data Analyti...

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2nd IEEE international conference on Advances in Information technology, ICAIT 2024

作者： Saravana Gokul, G. Senthil Pandi, S. Deepak Kumar, K. Sheriff, Muqaddam Aaqli Krishnamurthy, R. Department of CSE Rajalakshmi Engineering College Chennai India Department of CSE REC Chennai India

ISBN: (纸本)9798350383867

Event management plays a pivotal role in various domains, ranging from corporate conferences to music festivals. The adoption of technology and event management applications has revolutionized the industry, streaming applications processes and enhancing user experiences. This literature review explores the existing literature on event management applications, highlighting their impact on event planning, execution, and overall success. The Event Publishing System (EPS) is a comprehensive software solution that simplifies event publishing, registration, ticketing, marketing, communication, analytics, and mobile accessibility, all while maintaining robust security and customization options. EPS streamlines the entire event management process, providing a user-friendly platform for organizers to efficiently plan and execute successful events, whether they are corporate conferences or social gatherings, while enhancing the attendee experience and optimizing resource allocation. © 2024 IEEE.

关键词： Resource allocation

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Purity Unveiled: The Power of Ensemble Bagging in Water Quality 2

Purity Unveiled: The Power of Ensemble Bagging in Water Qual...

引用

2nd international conference on Advances in Computation, Communication and Information technology, ICAICCIT 2024

作者： Singh, Bhanupartap Gill, Kanwarpartap Singh Kumar, Mukesh Rawat, Ruchira Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Uttarakhand Dehradun India Graphic Era Deemed to be University Uttarakhand Dehradun India

ISBN: (纸本)9798331541217

Ensuring access to clean water is crucial for maintaining public health. Effective management of water resources and the reduction of pollution rely heavily on accurate predictions of water quality. Water quality can be assessed through various indicators, such as pH levels, dissolved oxygen, water clarity, and nutrient concentrations, which vary across different locations. Bagging classifiers, a widely used machine learning technique, are employed to enhance the accuracy and stability of predictive models for water quality. With the application of bagging classifiers, an accuracy of approximately 76% is anticipated. This approach demonstrates the effectiveness of ensemble learning methods in improving water quality prediction models. The proposed methods aim to optimize the assessment process for water quality, contributing to better environmental management and ensuring the availability of clean water for all communities. © 2024 IEEE.

关键词： Adversarial machine learning

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Firewall technology Strategy Analysis and application Research 2

Firewall Technology Strategy Analysis and Application Resear...

引用

2nd IEEE international conference on Electrical engineering, Big Data and Algorithms, EEBDA 2023

作者： Liu, Renshan Hulunbeier University Inner Mongolia Hailar Hulunbuir China

ISBN: (纸本)9781665462532

This paper first analyzes the network security evaluation method PDDR model, and makes an in-depth study of the firewall technology in the PDDR model, compares the characteristics of different firewalls, takes the stateful firewall as an example to analyze its workflow and security characteristics, and focuses on the key applications of dualchannel protocol, security zone policy, VPN technology, NAT technology and so on. Finally, the ENSP simulator simulates the configuration process of the firewall in the secure network, studies the application scenarios of the firewall in the network security, and provides reliable security technology methods for the protection of network information. © 2023 IEEE.

关键词： Network security

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Employing a Deep Neural Network to Identify and Categorize Leaf Diseases in Tomato Plant in Their Early Stages 2

Employing a Deep Neural Network to Identify and Categorize L...

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2nd IEEE international conference on Advances in Information technology, ICAIT 2024

作者： Bhatt, Chandradeep Saini, Parveen Kumar Sawan, Vikash Sharma, Sanjay Singh, Teekam Taranath, N.L. Department of CSE Graphic Era Hill University Uttarakhand Dehradun India Department of CSE Chandigarh University Gharuan Punjab Mohali India Department of Computer Engineering & Applications GLA University Uttar Pradesh Mathura India Computer Application Department SGRR Univeristy Dehradun India Graphic Era Deemed to be University Dehradun India School of CSE Presidency University Rajanukunte Bengaluru India

ISBN: (纸本)9798350383867

Tomato production makes a good contribution to the world economy as an element of agriculture. Tomato plants are vulnerable to different types of diseases that might create a negative impact on the production of the Tomato yield. Identification of this type of vulnerable disease at its early stage is important. This research work proposed a 9-layer Deep Neural Network to identify the leaf disease in the tomato plant. Deep learning technology of neural network approach was used in this method to classify the different leaf diseases in the tomato plant. The performance accuracy was obtained at 97.32% through the proposed method. © 2024 IEEE.

关键词： Plant diseases

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Research on Fault Prediction System of Mechanical Automation System Based on Deep Learning 2

Research on Fault Prediction System of Mechanical Automation...

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2nd international conference on Mechatronics, IoT and Industrial Informatics, ICMIII 2024

作者： Wang, Zhaiyi Shandong Polytechnic College School of Energy and Materials Engineering Jining272067 China

ISBN: (纸本)9798350386639

In this paper, the equipment failure prediction model is established first. Secondly, the integration of SQL language and JAVA technology with cloud computing technology realizes the intelligent cloud management of equipment. Then the mathematical model and system are studied empirically. Using the predictive model to do preventive maintenance work can reduce the downtime caused by failures. The intelligent monitoring technology of the cloud is used to monitor the status of the device, so that the operator can receive the fault information correctly. In this project, random network (GERT) is used as network characterization, which can effectively deal with the problem of estimating the number of equipment failures. In this way, the accurate prediction of the number of equipment failures is achieved. This is of great significance to the scientific management of the equipment. The practical application proves that this method can solve the problem of equipment management well, and the failure rate of equipment is reduced by about 20%. This study provides a new way for predicting the equipment failure quantity. © 2024 IEEE.

关键词： Preventive maintenance

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