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检索条件"任意字段=8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023"

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Anomaly Detection for Vertical Plant Wall System using Novel Support Vector Machine in Comparison with Artificial Neural Network for improving accuracy 8

Anomaly Detection for Vertical Plant Wall System using Novel...

引用

8th ieee international conference on Science, Technology, engineering and Mathematics, ICONSTEM 2023

作者： Meghana, M. Radhika, S. Sheeja Kumari, V. Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamilnadu Chennai602105 India

ISBN: (纸本)9798350347791

Aim: New Support Vector Machine and Artificial Neural Network are used to construct a plant wall system for indoor climate management. Materials and Methods: To detect indoor climatic changes in vertical plant wall systems, a Machine Learning Method that compares Artificial Neural Network and Innovative Support Vector Machine was created. the G Power calculator yielded 534 samples. 1068 samples and 80% Pretest Power. Results: Innovative Support vector machine had the highest accuracy in indoor changes at 68.42% and the lowest mean error at 58.58%. Groups are statistically insignificant. Conclusion: New Support Vector Machine technique outperforms Artificial Neural Network in indoor control. © 2023 ieee.

关键词： Support vector machines

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AI Based Smart Cleaner with IOT Integration 8

AI Based Smart Cleaner with IOT Integration

引用

8th ieee international conference for Convergence in Technology, I2CT 2023

作者： Ambadkar, Prachi Kumbhare, Prashansa Bonde, Chaitanya Shukla, Harsh Vidhale, Kartik Dharkar Bhushan G H Raisoni College of Engineering Department of Electronics and Telecommunication Nagpur India

ISBN: (纸本)9798350334012

the usage of self-sufficient systems to complete pertinent and delicate projects is quickly growing. But it is impossible to overstate its importance in a number of industries. In this post, an automatic floor cleaner that uses an Arduino Nano and hand gestures from artificial intelligence is presented. three ultrasonic sensors, an Arduino microcontroller, two tools with DC motors, an RF 433 module, and an accelerometer make up the system. By communicating alerts to a microcontroller through an interface, ultrasonic sensors are used to identify impediments along the robotics route. the micro-controller directs the robotic to move in the other direction by turning on the motors in order to go around the recognized obstruction. Additionally, two DC vehicles for cleaning *** the use of sensors on an Arduino board, a VLSI test bench can be improved quickly, and hand gestures give a human control over the device. Rapid processing and an intuitive user interface are the main benefits. Recent years have seen a significant increase in the number of individuals using open source software and hardware, which has led to the emergence of a new generation by simplifying and enticing complex tasks. © 2023 ieee.

关键词： Microcontrollers

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Prediction of SDN Heterogeneous Network Traffic Based on Improved LSTM with Self-attention Mechanism 8

Prediction of SDN Heterogeneous Network Traffic Based on Imp...

引用

8th international conference on Power and Renewable Energy, ICPRE 2023

作者： Zhao, Xiangcai Du, Dajun Zhang, Yi Shanghai University Shanghai Key Laboratory of Power Station Automation Technology School of Mechanical Engineering and Automation 200072 China

ISBN: (纸本)9798350328813

As heterogeneous network system becomes more and more complex and diversified, it brings the non-stationary and high burst characteristics of network traffic data, leading to difficulties in scheduling network resources. To address this issue, a traffic prediction method for heterogeneous networks based on software-defined networking (SDN) is proposed. First, the SDN-based heterogeneous network measurement and control system (HN-MCS) is investigated, where a network traffic measurement scheme is designed and deployed to achieve real-time monitoring and acquisition of traffic data. Second, the traffic prediction model based on long short-term memory (LSTM) with self-attention mechanism is constructed to enhance the accuracy and reliability of the predicted traffic data. Finally, compared with the prediction models based on support vector regression (SVR), LSTM and bi-directional LSTM (Bi-LSTM), the experimental results confirm that the proposed model can more effectively predict the network traffic and have higher prediction accuracy. © 2023 ieee.

关键词： Heterogeneous network measurement and control systems (HN-MCS) long short-term memory(LSTM) neural network self-attention mechanism software-defined networking(SDN) traffic measurement

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Recognition of E-Commerce through Big Data Classification and Data Mining Techniques Involving Artificial Intelligence 8

Recognition of E-Commerce through Big Data Classification an...

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8th international conference on Communication and Electronics systems, ICCES 2023

作者： Mandala, Vishwanadham Rajavarman, R. Jamunadevi, C. Janani, R. Avudaiappan, T. Indiana University Bloomington United States K. Ramakrishnan College of Technology Department of Computer Science and Engineering Tamilnadu Trichy India Pg Kongu Engineering College Department of Computer Technology India Sri Krishna College of Engineering and Technology Coimbatore India

ISBN: (纸本)9798350396638

the e-commerce or electronic commerce is defined as the process of interchange the goods and services on online platform. this is a commercial exchange of goods based on internet. Several advantages of the online trade include time saving through quicker buying of products, enhances marketing and advertising in easier way and helps in the faster comparison of the price and product overall performance. this electronic commerce includes various data that are needed to be processed and stored to function properly over the internet. Hence this needs the big data and its classification. this helps to provide the data that are necessary in trading through online platform. this is done through the Big Data Analytics which helps to enhance the decision making process through analysing the data. To increase the number of customers and vendors in the online platform, the big data analytics in involved. Further this is enhanced and implemented through the data mining techniques and artificial intelligence. © 2023 ieee.

关键词： Big data

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A Comparison of Clustering vs YOLO for Drone Swarm Centroid Detection 8

A Comparison of Clustering vs YOLO for Drone Swarm Centroid ...

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8th international conference on Robotics and Automation engineering, ICRAE 2023

作者： Kumari, Nisha Lee, Kevin Ranaweera, Chathurika Barca, Jan Carlo School of Information Technology Deakin University Melbourne Australia

ISBN: (纸本)9798350327656

the rapid advancement of drones has led to the emergence of drone swarm applications in various domains, including surveillance, search and rescue, and package delivery. Efficient coordination and formation control of drone swarms is crucial for accomplishing complex tasks. the research presented in this paper proposes a novel approach for detecting individual drones in drone swarm formations through the utilisation of the K-means clustering algorithm. the algorithm assigns drones to the nearest centroids, creating cohesive subgroups and optimizing formation quality. To assess its efficacy, a comparative analysis is conducted between the K-means clustering algorithm and you only look once (YOLO) based computer vision detection algorithm. through extensive simulation experiments, it is found that the K-means clustering algorithm outperforms the YOLO-based detection algorithm in terms of formation quality and computational efficiency. It consistently achieves more accurate and stable swarm formations making it suitable for real-time swarm control applications. the results of this presented research open the way for the effective use of drone swarms in a wide range of real-world applications and contribute to the development of cutting-edge swarm control approaches. © 2023 ieee.

关键词： computer vision

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Effective Visualization Electrification System via PSCADA Event Log in Railway Industry

Effective Visualization Electrification System via PSCADA Ev...

引用

international conference on software engineering and computer systems (icsecs)

作者： Syamsul Azrin Bin Kamaruddin Hairulazwan Bin Hashim Elmy Johana Binti Mohamad Nazwa Hidayah Binti Mohamad Halim Bin Mamat Department of Mechanical Engineering Centre for Diploma Studies Universiti Tun Hussein Onn Malaysia Johor Malaysia Industry Centre of Excellence for Railway (ICoE-Rel) Faculty of Engineering Technology Universiti Tun Hussein Onn Malaysia Johor Malaysia Department of Electrical Engineering Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Johor Malaysia Department of Quality Health Safety Environment & System Assurance Pestech Technology Sdn. Bhd. Selangor Malaysia Department of Electrification Keretapi Tanah Melayu Berhad Kuala Lumpur Malaysia

Rail transport has been one of the main intercity passenger train operators in Malaysia. the Electrification Department is the most important department to make sure the trains have enough power to operate and is responsible for the maintenance of the power supply infrastructure and SCADA system to ensure the Electrification System is accurately monitored and controlled and assure the Reliability, Availability, Maintainability and Safety of the system. the key issue faced by this department is related to reporting on maintenance. the report was very time-consuming to prepare because it was on a paper-based method, and information was presented badly due to the lack of a visualization tool and being vulnerable to data quality problems. To address this issue, the current study aims to propose a tool that provides screening and detecting of device fault status using a dashboard developed using Microsoft Power BI by extracting the raw data log from the Power SCADA server. We demonstrate the process of adopting the cloud-based dashboard using Power BI at the strategic management level. the development of the dashboard system is adopted from the previous research framework, consisting of four main stages which are designing, data analyzing process, visualizing, and validating. One of the findings is that the data cleansing process is the most important stage to produce the right information. this interactive tool made instant visibility of device status and assisted the maintenance team to capture the status trends. the study benefits to the organization are to reduce 86% of the time and cost to prepare the maintenance reporting and planning.

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A Low-cost ESP32-driven Wireless Key Generation System Based on Response Mechanism 8

A Low-cost ESP32-driven Wireless Key Generation System Based...

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8th international conference on computer and Communication systems, ICCCS 2023

作者： Zhang, Huaicong Yu, Jiabao Chen, Xudong Tian, Ye Qi, Wangdong Hu, Aiqun School of Cyber Science and Engineering Southeast University Nanjing China School of Information Science and Engineering Southeast University Nanjing China Purple Mountain Laboratories Nanjing China Research Institute of China Mobile Communications Corporation Department of Security Technology Beijing China

ISBN: (纸本)9781665456128

In recent years, secret key generation method based on the physical layer of wireless channel has been widely studied. Since Channel State Information (CSI) is a fine-grained characterization of channel information, there are currently many studies using CSI for key generation. However, existing CSI extraction tools have the problem that the time interval between uplink and downlink interaction is uncertain, which may result in insufficient reciprocity of CSI. In this paper, we propose a channel measurement method based on the response mechanism of the ieee 802.11 protocol, and develop a low-cost and universal CSI extraction tool using ESP32. We further design and implement a wireless key generation system based on the tool. To evaluate the performance of the proposed method, we have conducted extensive experiments in an indoor environment. Results show that our method can obtain highly reciprocal CSI in both static and mobile scenarios and can achieve a high key generation rate at around 1788.23 bits/s. © 2023 ieee.

关键词： ieee Standards

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A Comprehensive Review on Precision Agriculture and Machine Learning Approach in Bangladesh 8

A Comprehensive Review on Precision Agriculture and Machine ...

引用

8th ieee international conference for Convergence in Technology, I2CT 2023

作者： Rahman, Syed Ishtiak Chowdhury Iwase, Shifa Abian, Arefin Ittesafun Ghosh, Tapotosh Farid, Dewan Md. Department of Computer Science & Engineering United International University United City Madani Avenue Badda Dhaka1212 Bangladesh

ISBN: (纸本)9798350334012

Agriculture is seen as a key pillar of the economy of Bangladesh. the country produces an enormous variety of crops. To ensure stability by preventing losses and maintaining supply and market demand, the integration of advanced technology like Machine Learning (ML) in agriculture is beneficial. With the growth of Big Data techniques and powerful computers, ML has opened up new possibilities for data-intensive research in a variety of disciplines of crop cultivation. Since crops are one of the main components of agriculture, our main concerns are issues relating to crops such as disease detection, crop price and yield prediction. Disease infected crops cause significant loss. Producers need to have the right information on which crops should be harvested where and when. Again, ensuring fair price of crops is mandatory for economical balance and stability. this paper provides an in-depth review of the research on ML applications in agricultural systems. A combination of ML and agriculture can provide great suggestions and in-depth insights for farmers in decision support and action. © 2023 ieee.

关键词： Crops

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An Intelligent Method for Credit Card Fraud Detection using Improved CNN and Extreme Learning Machine 8

An Intelligent Method for Credit Card Fraud Detection using ...

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8th international conference on Communication and Electronics systems, ICCES 2023

作者： Yamini, Kalva Anitha, V. Polepaka, Sanjeeva Chauhan, Rahul Varshney, Yukti Singh, Mukesh Sri Ramachandra Institute of Higher Education and Research Cyber Security in Cse Tamilnadu Chennai India Imayam College of Engineering Department of Computer Science and Engineering Tamilnadu Trichy India Griet Department of Aimle Telangana Hyderabad India Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Moradabad Institute of Technology Department of Computer Science & Engineering Uttar Pradesh Moradabad India Graphic Era University Department of Computer Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350396638

Credit card fraud has been on the rise in recent years. Criminals are taking advantage of the public by pretending to be legitimate businesses or individuals in order to steal their money. So, it is essential to combat this type of fraud. this research study has developed a novel method for spotting suspicious credit card transactions. the proposed approach may provide most of the necessary information to spot illegal or fraudulent financial transactions. As technology advances at an unprecedented rate, it becomes more difficult to monitor the illegal transactions and money transfers. With the recent developments in machine learning, artificial intelligence, and other critical areas of IT, it is now possible to automate this process and save huge amounts of labor involve in recognizing credit card fraud. After receiving an input image, it is preprocessed and features are retrieved by using principal component analysis, and then the data is used for training the CNN-ELM model. the proposed method achieves a higher accuracy (about 98.7%) than other methods like CNN and ELM. © 2023 ieee.

关键词： Principal component analysis

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Online Complaint Management System using Image Recognition 8

Online Complaint Management System using Image Recognition

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8th international conference on Communication and Electronics systems, ICCES 2023

作者： Balakrishnan, S. Janet, J. Rohith, T. Sakthivel, R. Sanjaiy Kumar, T.N. Sri Krishna College of Engg. and Technology Dept. of Computer Science and Business Systems Tamilnadu Coimbatore India Sri Krishna College of Engg. and Technology Dept. of Computer Science and Engineering Tamilnadu Coimbatore India

ISBN: (纸本)9798350396638

Clean and safe environments are the responsibility of the government. Currently, people have to lodge their complaints with the Municipal Corporation, and then workers take time to respond to them. In this paper we have made a platform to overcome the communication gap between the user and the municipal corporation. this research study proposes an online complaint management system in a web application, where the citizen can lodge a complaint by taking a picture. After the picture being uploaded, image recognition is used to automatically detect the problem raised by the user and Google map API to detect the location automatically. As soon as the problem has been resolved, the municipal corporation must upload a completed status picture to verify that the work has been completed. the aim of this application is to overcome the communication gap between user and Municipal Corporation, to simplify the process of raising complaints and to maintain a clean and safe environment. © 2023 ieee.

关键词： Image recognition

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