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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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A Novel Single-Anchor-based Visible Light Positioning Approach 8

A Novel Single-Anchor-based Visible Light Positioning Approa...

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

作者： Zhou, Jiasheng Jiang, Jiale Zhao, Kai Zhuang, Yuan Mapping and Remote Sensing Wuhan University State Key Laboratory of Engineering in Surveying Wuhan China

ISBN: (纸本)9781665456128

With the growing demand for indoor positioning, various technologies are being explored, and visible light positioning (VLP) has become a popular choice due to its cost-effectiveness and efficient deployability. However, the current commonly used VLP methods are always based on the multi anchors, which means high wiring and controller costs. thus, a self-designed single anchor which integrated several Light Emitting Diodes (LEDs) is first proposed in this work. the highly integrated hardware requires less cost, and the smaller receiver means more applications can be adapted. Further, to reduce the workload of fingerprint information collection, the calibrated propagation model is used to generate new fingerprint information, which significantly increases the efficiency of the fingerprint database's construction and maximizes the use of stable visible light signals with little interference. the feasibility of the proposed hardware and methods is evaluated through a room-scale implementation, which shows that localization accuracy improves by 75.56% and 55.27% when using densified fingerprint points. Additionally, the study carefully evaluates the performance of different neighbor points' quantities and different kinds of distances, and Weighted K-Nearest Neighbor is tested, which yields superior results compared to the commonly used K-Nearest Neighbor. © 2023 ieee.

关键词： Cost effectiveness

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Wireless Sensor Network-based Intrusion Detection Technique using Deep Learning Approach of CNN-GRU 8

Wireless Sensor Network-based Intrusion Detection Technique ...

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

作者： Sagar, Anita Anushkannan, N.K. Indumathi, G. Vasant Muralidhar, Nikale Dhamotharan, K.A. Malini, P. Patliputra -University College of Commerce Arts & Science Department of Physics Bihar Patna India Kathir College of Engineering Department of Ece Tamilnadu Coimbatore India Srm Institute of Science and Technology Cse Ramapuram Tamilnadu Chennai India Ayat Shikshan Sanstha's Dada Patil Mahavidyalaya Karjat Department of Physics Karjat Maharashtra Ahmednagar India Erode Sengunthar Engineering College- Autonomous Computer Science and Engineering Erode Tamilnadu Perundurai India K. Ramakrishnan College of Engineering Department of Electronics and Communication Engineering Trichy Tamil Nadu Samayapuram India

ISBN: (纸本)9798350396638

In a WSN, sensors are always collecting information and transmitting it to other nodes. their primary uses are in fields like defense, smart city development, and agricultural monitoring. the WSN needs to perform at a premium for these uses. Yet, there are many potential security concerns that could compromise a WSN's performance. Any interference with the WSN could severely degrade its functionality and lead to catastrophic failures. As a result, having the ability to quickly identify and stop intrusions is crucial. the goal of this proposed is to use a GRU-CNN model for quick detection and prevention of any intrusion. After receiving the input, the proposed method uses normalization and discretization for preprocessing the data, PSO (Particle Swarm Optimization) for feature extraction, CFS for feature selection and finally training the model by CNN-GRU. To better detect intrusions in wireless sensor networks, a GRU-CNN hybrid neural network model was presented;although the CNN module is responsible for extracting the feature vector from other high-dimensional data, the GRU module is responsible for from time sequence data to extract the feature vector. © 2023 ieee.

关键词： Wireless sensor networks

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Channel Robust RF Fingerprint Identification Method with Narrow Band Differential Constellation Trace Figure 8

Channel Robust RF Fingerprint Identification Method with Nar...

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8th international conference on Signal and Image Processing, ICSIP 2023

作者： Meng, Xiangqi Peng, Linning Song, Ruowei Fu, Hua Hu, Aiqun Southeast University School of Cyber Science and Engineering Nanjing China Purple Mountain Laboratories for Network and Communication Security Nanjing China Institute of Advanced Technology University of Science and Technology of China Hefei China Southeast University School of Information Science and Engineering Nanjing China

ISBN: (纸本)9798350397932

RF fingerprint (RFF) identification in wideband wireless communication systems is vulnerable to interference from wireless channel variations. this paper proposes a channel robust RFF identification method with narrow band differential constellation trace figure (NB-DCTF). A particular narrowband filter bank is designed to extract narrow-band RFF features from 802.11 preamble signal. the RFF features of 12 subcarriers in the short training symbol are respectively extracted and drawn into the NB-DCTF. A convolutional neural network (CNN) is then designed to identify different devices using NB-DCTF features. In the experiment, we construct a testbed including 11 mobile phones and one universal software radio peripheral (USRP) platform as the receiver. the classification accuracy in static state can reach 98.9%, and that in mobile state can reach 92.6%. © 2023 ieee.

关键词： software radio

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Study on Data Mining Technology for Online and Offline E-Commerce Users Based on Big Data 8

Study on Data Mining Technology for Online and Offline E-Com...

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

作者： Bu, Yantao Liu, Shanshan Computer and Information Engineering College Guizhou University of Commerce Guizhou Guiyang China Guizhou University of Commerce Department of Foreign Languages Guizhou Guiyang China

ISBN: (纸本)9781665456128

Data mining technology can comprehensively analyze the feedback of these products. At the same time, it can also limit the interpretation of time and other data, making the results of its data analysis more accurate and reliable. After analyzing user feedback, adjust the product to meet user needs and promote corporate profitability. this article synthesizes the online e-commerce management data level indicators of multiple enterprises. Statistical analysis and integration of user mining models are conducted through analysis of data mining and enterprise model data. Conduct statistics on the data results through surveys. the development results of group data were evaluated through simulation operations. this questionnaire is distributed online in the form of a questionnaire star, which can effectively avoid the limitations of the questionnaire. In the corresponding tests, a total of four sets of data from 2000 to 2015 were selected to test the response of the entire algorithm under different user connections. In traditional mode, the response time has increased from 60 seconds to 500 seconds. Based on this algorithm, the response time is greatly shortened. When the algorithm carries an extreme value, the response time is about 700s. the test results show that the statistical accuracy of the optimal management model is generally 95%. Above, the accuracy rate of traditional algorithms is generally below 80%. the management model in this article has the shortest calculation time, averaging only 10 seconds. the research results show that the user electronic management model proposed in the study has a good labeling level. It can help enterprises conduct more reasonable and meaningful management. © 2023 ieee.

关键词： Big data

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Research on the path of integrating the excellent traditional culture into the Ideological and political precision teaching in colleges and universities driven by artificial intelligence 8

Research on the path of integrating the excellent traditiona...

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8th international conference on Information systems engineering, ICISE 2023

作者： Ding, Hengyue Zhang, Bo WTU College of International Business and Economics Ideological and Political Science Department Wuhan430000 China Wuhan Donghu University School of Computer Science Wuhan430000 China

ISBN: (纸本)9798350307009

At present, the precision teaching supported by intelligent technology has some shortcomings in practice, such as single technology bias, lack of thinking of educational cognitive logic, and weakening of teachers' role status. One of the reasons lies in the lack of theoretical perspective on the academic logic of technology-enabled precision teaching. From the perspective of educational cognition, on the basis of clarifying the concept connotation of precision teaching, the research analyzes the existing practical difficulties in the process of its development, such as goal setting, diagnostic evaluation and activity development. Based on the function analysis of intelligent technology, the realization logic of intelligent technology-enabled precision teaching goal, evaluation and activity accurate development is discussed: With the help of group analysis, individual needs diagnosis, mapping relationship analysis to achieve accurate target setting;With the help of data acquisition, analysis mining and visualization technologies, the automatic implementation and intelligent analysis of evaluation are realized to facilitate the hierarchical and precise intervention of the application of evaluation results. With the help of resource recommendation and tool assistance, it can help the accurate design and practice of multiple learning activities, and provide support for the process intervention and real-time feedback of learning activities. © 2023 ieee.

关键词： Data visualization

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Investigative Study of Installed Solar Energy System at Islamic University of Gaza 8

Investigative Study of Installed Solar Energy System at Isla...

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8th international engineering conference on Renewable Energy and Sustainability, ieCRES 2023

作者： Elaydi, Hatem Zaqout, Hosam Rafeeq Ayesh, Mohammed Sameeh Salha, Ahmed Mahmoud Hammad, Omar Kayed Islamic University of Gaza Electrical & Smart Systems Engineering Department Gaza Palestine

ISBN: (纸本)9798350300758

the Islamic University of Gaza, IUG, relies on several sources of energy to meet its electricity demands. Since Gaza Strip suffers from a chronic blackout electricity problem where electricity is being cutoff from the main electrical distribution company for over 50% of the time, it uses several other options to compensate for those times. In the past, it mainly relied on diesel power generators;however, it recently started to relies more and more on its rooftops solar PV systems to meet its electricity demands. IUG solar PV systems works both on grid and off grid;however, in order to achieve the greatest benefit from the system, it is preferred to use on grid connection. this research focuses on investigating integrated analytical data of the solar system in terms of its production capabilities and efficiency. the study is based on the analysis of the solar system located on the southern side of IUG main campus. Based on the data collected from the electrical meters on the system and its statistical representation for the year 2021, the study provides suggestions to improve and to develop the system and to solve identified system's problems. the project relied on the methodology of monthly data collection of 2021 and its analysis by means of computer programs - Excel and Python. the results of the research present a detailed study of the solar system in the southern side of the Islamic University, detailed accurate numerical values for the amount of energy produced and consumed, financial return provided by the system, obstacles and recommendation to increase its efficiency. the study shows an annual reduction of the university electricity bill of about $70,000 that can be increased to $100,000 by following the recommendations. © 2023 ieee.

关键词： Solar energy

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Freshy Pal: A Proposal of an Interactive Web based Tool to Automatically Detect Microbial Growth on White Bread 8

Freshy Pal: A Proposal of an Interactive Web based Tool to A...

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

作者： Pitroda, Harshee Kolhe, Abhay NMIMS University Mukesh Patel School of Technology Management & Engineering Department of Computer Engineering Mumbai India

ISBN: (纸本)9798350334012

Bread has long been a staple food in kitchens across the country and is devoured by billions of people worldwide. Despite being so widely consumed, the bread usually only remains fresh for a short while. Bread can develop molds and microbial growth, making it unhealthy to ingest and potentially harmful to one's health. As a result, it is necessary to determine whether the bread is safe to consume. Hence, Freshy Pal, an interactive web-based application tool was created, that makes significant use of new technologies such as image processing, machine learning, and deep learning to identify bread spoilage given an image of the slice of bread. the primary goal of designing this application is to assist users in determining whether bread is safe to ingest because bread spoilage can cause allergic responses and respiratory difficulties, further removing the clearly spoilt portion of the bread and consuming the remainder is equally harmful. So, after Freshy Pal classifies bread as unsafe to consume, it instructs the users on how to properly dispose of and handle the moldy bread. Freshy Pal also educates its users on how to keep their bread safe from mold growth. Two different methodologies were used to develop the system. the first approach employed extensive Image Processing and Machine Learning methods. the following machine learning algorithms were used: Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, Naive Bayes, and Ada Boost. Random Forest and Ada boost achieved the greatest accuracy of 96.67%. the second approach employed Deep Learning-based Image Classification utilizing Convolutional Neural Networks, here an accuracy of 98% was achieved using the pre-trained model VGG16. the outcomes of both techniques are contrasted on a variety of grounds. the deep learning-based method achieved higher accuracy, but it required longer training time and larger data size. © 2023 ieee.

关键词： Learning systems

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One-Stage Object Detector Using Feature Fusion and Dual Attention 8

One-Stage Object Detector Using Feature Fusion and Dual Atte...

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8th ieee international conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Zhang, Di Zhang, Weimin Li, Fangxing Liang, Kaiwen Yang, Yuhang Zhong, Zhide School of Mechatronical Engineering Beijing Institute of Technology China Beijing Institute of Technology Ministry of Education Key Laboratory of Biomimetic Robots and Systems China Beijing Advanced Innovation Center for Intelligent Robots and Systems China

ISBN: (纸本)9798350300178

Multi-scale object detection and small object detection are important tasks in computer vision and robotics. Traditional one-stage object detection algorithms are fast, but cannot adapt to changes in object scale perfectly and have low accuracy for small object detection. In this paper, we proposed a one-stage object detector using feature fusion and attentional mechanisms. this detector has better adaptability and higher accuracy with marginal extra cost. Our algorithm is based on the CenterNet framework, with modifications and enhancements. First, we used a feature pyramid network with bidirectional cross-scale connections to enable the full integration of lower layers and topmost features, which improved the network's adaptability to scale changes. Second, we proposed a dual attention module that integrates spatial attention and channel attention and added it to every layer of the pyramid, so that the network can focus more on useful information, which enhances the network's capability to detect small objects. Using a lightweight backbone, our algorithm achieves 40.2 mAP on COCO at 33 fps on a Titan Xp GPU, up to 3 mAP compared to CenterNet with the same backbone. Besides, for the small targets in COCO, our algorithm achieves 20.63 mAP, Which is 30% higher than CenterNet. We also tested our algorithm on a body part detection dataset of Pascal, Voc,which further demonstrates the effectiveness of our algorithm in terms of application. © 2023 ieee.

关键词： Object detection

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Real-time Driver Drowsiness Detection and Assistance System using Machine Learning and IoT 8

Real-time Driver Drowsiness Detection and Assistance System ...

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

作者： Sudarshan, Pragathi Bhardwaj, Vivek Virender Lovely Professional University Computer Science and Engineering Punjab Phagwara India Manipal University Jaipur Department of Computer Science and Engineering Rajasthan Jaipur India Chandigarh University Punjab Mohali India

ISBN: (纸本)9798350396638

Road transport is often regarded as the most cost-convenient and preferred mode of transportation for both freight and passengers. Road transportation makes up about 87% of all passenger transport and 60% of all freight transportation in the nation. Some of the advantages of road transportation are its ease of accessibility, flexibility to individual demands, and cost savings. But all this comes with a cost. According to MoRth., the number of people killed in traffic accidents caused by driving vehicles has consistently risen every year. Particularly, there are more fatalities and serious injuries than minor ones, and the harm caused by major accidents is growing. Heavy cargo truck accidents and high-speed bus crashes while driving at night has particularly become major social issues. these misadventures are caused by driver fatigue, microsleep, and drowsiness. Out of these, driver fatigue contributes more to freight accidents. this paper aims to implement an intelligent processing system that drastically reduces road accidents. this research will develop a system capable of monitoring the driver in real-time and m, ensuring he is in his active state, letting him in real-time in case sleep or fatigue is detected. Existing drowsiness detection systems just have accuracy for detection but are not up to the mark when it comes to prevention. We will design a system to alert the driver physically. Here, this research will make use of a machine learning algorithm called the Haar cascades algorithm and the Internet of things for hardware setup. this technology will alert the driver if his or her eyes are maintained closed for an extended period by triggering an alarm and spraying water at a positioned spot to get back to his active state. Also, a cloud system will be involved to send an alert message to the concerned person to be aware of the driver's condition. © 2023 ieee.

关键词： Internet of things

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OSDaR23: Open Sensor Data for Rail 2023 8

OSDaR23: Open Sensor Data for Rail 2023

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

作者： Tagiew, Rustam Klasek, Pavel Tilly, Roman Koppel, Martin Denzler, Patrick Neumaier, Philipp Klockau, Tobias Boekhoff, Martin Schwalbe, Karsten German Centre for Rail Traffic Research Federal Railway Authority Dresden Germany Digitale Schiene Deutschland Db Netz Ag Berlin Germany FusionSystems GmbH Chemnitz Germany

ISBN: (纸本)9798350327656

To achieve a driverless train operation on mainline railways, actual and potential obstacles for the train's driveway must be detected automatically by appropriate sensor systems. Machine learning algorithms have proven to be powerful tools for this task during the last years. However, these algorithms require large amounts of high-quality annotated data containing railway-specific objects as training data. Unfortunately, all of the publicly available datasets that tackle this requirement are restricted in some way. therefore, this paper presents OSDaR23, a multi-sensor dataset of 45 subsequences acquired in Hamburg, Germany, in September 2021, that was created to foster driverless train operation on mainline railways. the sensor setup consists of multiple calibrated and synchronized infrared (IR) and visual (RGB) cameras, lidars, a radar, and position and acceleration sensors mounted on the front of a rail vehicle. In addition to the raw data, the dataset contains 204091 polyline, polygonal, rectangle, and cuboid annotations in total for 20 different object classes. It is the first publicly available multi-sensor dataset annotated with a variety of object classes that are relevant for the railway context. OSDaR23, available at ***/dataset/osdar23, can also be used for tasks beyond collision prediction, which are listed in this paper © 2023 ieee.

关键词： computer vision

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