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检索条件"任意字段=2023 3rd International Conference on Detection Technology and Intelligence System, DTIS 2023"

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Binary Function Similarity detection Based on Text Semantics 3

Binary Function Similarity Detection Based on Text Semantics

引用

3rd international conference on Artificial intelligence and Computer Engineering, ICAICE 2022

作者： Lu, Shuai Mu, Chao Zhang, Guannan Liu, Shanshan Zhao, Xuewei Qilu University of Technology Shandong Academy of Sciences Jinan250014 China Shandong Institute of Scientific and Technical Information Jinan250014 China

ISBN: (纸本)9781510663473

Binary code similarity is that different binary codes obtained from the same source code compiled by different compiler configurations are similar. Binary code similarity detection is often used to evaluate whether functions in two binary codes are similar. This technique has critical applications in intellectual property protection and IoT security, such as code plagiarism detection, malware detection, vulnerability detection, etc. In this paper, we propose a text semantics-based binary function similarity detection model SBFS, which firstly transforms binary functions into function texts by preprocessing assembly instructions;then learns function texts to obtain semantic embedding vectors using a natural language processing model;Finally, the similarity between two functions is measured by calculating the cosine distance between the embedding vectors of the two functions. Experimental results show that the SBFS model can achieve cross-architecture detection and higher accuracy with 98.2% in the binary function similarity detection task. © 2023 SPIE.

关键词： Semantics

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Control Method of Wire Repairing Robot Based on Semantic Segmentation and Current detection 3

Control Method of Wire Repairing Robot Based on Semantic Seg...

引用

2023 3rd international conference on Artificial intelligence and Industrial technology Applications, AIITA 2023

作者： Zhang, Lingrui Wang, Xuhong Fan, Shaosheng College of Electrical and Information Engineering Changsha University of Science & Technology China

The traditional repair of conductors in power systems, using manual work at height, carries a high level of risk. To ensure personnel safety and improve operational efficiency. Based on the development of a conductor repair robot using pre-stranded wires, the focus is on a semantic segmentation-based adaptive conductor arc sag control method, which enables the robot to adapt to conductors with different arc sags by segmentation identification of the conductor, offset calculation, and proportional-integral controller design to realize the robot hanging on the conductor. Subsequently, the winding gap is monitored according to the change of motor current, and a fuzzy controller is used to realize the robot winding operation. The robot prototype tests show that the robot is capable of adapting to the wire pitch and completing soft repair work. © Published under licence by IOP Publishing Ltd.

关键词： Robots

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A Fuzzy Logic-Based Intrusion detection system for WBAN Against Jamming Attacks 1

引用

3rd international conference on Electronic Engineering and Renewable Energy, ICEERE 2022

作者： Bengag, Asmae Bengag, Amina Moussaoui, Omar Mohamed, Blej MATSI Research Laboratory ESTO Mohammed First University Oujda Morocco

ISBN: (数字)9789811962233

ISBN: (纸本)9789811962226

Wireless Body Area Network (WBAN) is a set of special nodes called medical sensors. These sensors are very useful and helpful for making the user able to connect everywhere and every time. However, they suffer from many problems like the low computing capacity, energy and memory space. In terms of security, WBAN systems are threatened by various types of attacks due to the wireless communication. This technology must have a robust mechanism to detect attacks for making medical applications more reliable and safety. In our work, we have focused on identifying jamming attacks from WBAN using the fuzzy logic system (FLS) that is one of the powerful mechanisms of artificial intelligence (AI) to determine different network cases. The proposed system used one of the fuzzy inference methods named Mamdani model and based on three network parameters Packet delivery ratio (PDR), received strength signal indicator (RSSI) and energy consumption amount (ECA). Our intrusion detection system is simulated by using MATLAB 9.0 and Castalia for analyzing the output result as jamming detection index (JDI). © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Medical applications

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Rewarding Reviews with Tokens Using Smart Contracts 3

Rewarding Reviews with Tokens Using Smart Contracts

引用

3rd international conference on Innovative Practices in technology and Management, ICIPTM 2023

作者： Devendran, K. Rajasekar, Vani Sharma, Vandana Elngar, Ahmed A. Prasanna Kumar, K.R. Kongu Engineering College Department of Cse Erode India Amity University of Technology Amity University India Beni-Suef University Faculty of Computers and Artificial Intelligence Beni-Suef City Egypt Kongu Engineering College Department of It Erode India

ISBN: (纸本)9798350336238

Research shows that 68% of online purchases are influenced by the reviews of the products that are being sold. Online retailers know the importance of online reviews and how those reviews impact their business. Online review sites are widely used in the hotel sector and by online retailers. Because these evaluations account for such many sales, there is always the risk that they may be exploited or interfered with. The issue is that these systems are highly centralized, leaving them vulnerable to manipulation and control. In this paper, we discussed the possibility of a decentralized, unbiased review system and an abstract implementation of that system. This review system will be a collection of smart contracts which can be deployed on the Ethereum blockchain. The blockchain's decentralized characteristic might be used to establish an unbiased and fair review system that increases consumer connections and confidence. On Test Networks, we build and test smart contracts in this project. The architectural flow and system components are also provided. In conventional review systems, the user usually adds a new review, and this review is stored in a centralized database of the service provider. The service provider can edit the review, it can also be permanently deleted from the platform. Since reviews drive a major part of the sales, this control over the reviews system can affect users who might have found the deleted review to be useful. A blockchain is a continuously increasing collection of linked and encrypted documents known as blocks. When a blockchain is used, a digital item's ability to duplicate indefinitely is eliminated. Consumer review systems might benefit from blockchain's decentralized and tamper resistant features. © 2023 IEEE.

关键词： Smart contract

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Natural Language Processing to Improve Content Retrieval Performance 3

Natural Language Processing to Improve Content Retrieval Per...

引用

3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Jadhav, Varsha D. Doda, Devendra Kumar Swarup, Lakshya Kumar, Ritesh Pandian, Rajesh Rufina, Princy Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Vivekananda Global University Department of Electrical Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science Engineering Karnataka Bangalore India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India

ISBN: (纸本)9798350319125

Latest studies in herbal Language Processing (NLP) have targeted improving the accuracy of statistics retrieval through leveraging machines better to recognize the use and scope of human language. Employing NLP strategies makes it far more feasible to system massive units of files and better identify the applicable content in them. Content related to a user's query can then be taken care of and ranked based on the similarity of the language used in the file. NLP strategies permit a more accurate representation of content material and can help retrieve the maximum relevant statistics. Furthermore, NLP can be prolonged beyond traditional search engines like Google to research textual content-primarily based information, such as emails and social media posts, for areas that include sentiment analysis and customer support. This paper explores the capacity of NLP to enhance content material retrieval overall performance in more than a few situations. It additionally outlines valuable techniques for evaluating the effectiveness of such structures. Dialogue and conclusion refer to approaches by which the implementation of NLP can convey improved accuracy to content material retrieval. © 2023 IEEE.

关键词： Discussion effectiveness implementation representation similarity

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Empowering Early Diagnosis: Optimizers Revolutionizing Breast Cancer detection with DenseNet 3

Empowering Early Diagnosis: Optimizers Revolutionizing Breas...

引用

3rd international conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Pranati, V. Khatri, Narendra Sharma, Harish Shukla, Praveen Kumar Manipal Institute of Technology Manipal Academy of Higher Education Department of Biomedical Engineering Manipal576104 India Manipal Institute of Technology Manipal Academy of Higher Education Department of Mechatronics Manipal576104 India School of Computer Science and Engineering Manipal University Jaipur Department of Artificial Intelligence and Machine Learning Jaipur India School of Computer and Communication Engineering Manipal University Jaipur India

ISBN: (纸本)9798350342338

Breast cancer, a highly lethal disease with a significant global impact, requires early detection to reduce its mortality rate. The emergence of pre-trained Deep Learning (DL) algorithms, commonly utilized for object detection, image classification, and image segmentation, has advanced early breast cancer detection. Several researchers have explored early breast cancer detection using pre-trained DL algorithms in conjunction with classifiers or other existing methods. However, existing research lacks a thorough examination of optimizers and their potential influence on the behaviour of these pre-trained algorithms. This study aims to comprehensively investigate the behaviour of the pre-trained DenseNet201 model under various optimizer and learning rate configurations. The analysis reveals that the DenseNet model achieved superior performance (100% accuracy) with the SGD (Stochastic Gradient Descent), and RMSProp optimizers at a learning rate of 10-2 and 10-3, respectively. However, at a learning rate of 10-4, the Adam optimizer demonstrated the highest accuracy of 99%. © 2023 IEEE.

关键词： Breast Cancer detection DenseNet201 Learning Rates Optimizers Pre-trained DL algorithms

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A Novel Optimization Algorithm for Smart Video Surveillance system and Change Object detection 3rd

A Novel Optimization Algorithm for Smart Video Surveillance...

引用

3rd international conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2023

作者： Siddiqui, Fahad Siddiqi, Shafaq Sukkur IBA University Sukkur Pakistan Graz University of Technology Graz Austria

ISBN: (纸本)9783031488573

Security has been a significant concern in every aspect of life. Traditional surveillance systems require a huge amount of storage capacity to save recorded videos. Moreover, as these systems are not fully automated, object detection and change detection need a lot of computational power in real-time surveillance. Finding a specific event or object in the recorded videos becomes more tedious and time-consuming. Since the last decade, researchers and developers have been working on the optimization and improvement of surveillance systems. This paper mainly focuses on surveillance system optimization by presenting an algorithm that not only optimizes objects and change detection but also requires comparatively less time in searching for a particular object from the library of recorded videos. The paper also presents a software application that offers various unique features such as searching for a specific object and on-time notification on targeted object detection. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object detection

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Design of Electric Power monitoring and early warning system Based on Beidou 3

Design of Electric Power monitoring and early warning System...

引用

3rd international conference on Sensors and Information technology (ICSI)

作者： Liu, Xiaohong Guan, Weimin Li, Donghua Xun, Sichao Zhang, Guomin Xu, Feng Yancheng Power Supply Co State Grid Yancheng Jiangsu Peoples R China Nanjing Inst Technol Line Elect Power Coll Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781510666122;9781510666139

This paper is based on GIS technology, through access to multi-source meteorological data, meteorological information, geographic information, and power grid equipment combined with correlation analysis, thus designed the power grid meteorological disaster warning information release system, realize the state grid disaster warning, statistical analysis, model, archives, professional maintenance, industry maintenance part of six power grid disaster warning information monitoring. The system can display all kinds of power disaster data information graphically, and realize the forecast and early warning of power disasters. The field experiment effect shows that the power grid meteorological disaster warning information system can provide professional meteorological warning support for realizing the fine management of the power grid and improving the disaster prevention capacity of the power grid.

关键词： early warning risk detection line galloping platform control

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Fashionable Four Wheeler Parking to Reduce the Human Intervention and to Enhance the Flexibility in Parking system Using IoT 3

Fashionable Four Wheeler Parking to Reduce the Human Interve...

引用

3rd international conference on Innovative Practices in technology and Management, ICIPTM 2023

作者： Manoj, P. Varun, C.M. Keerthi Kumar, N. Padhye, Pradip Kumari, K. Aruna Das, Puja Sarkar, Swagata Vidyavardhaka College of Engineering Department of Civil Engineering Mysore India R.M.K. Engineering College Department of Computer Science and Business System Kavaraipettai India Bms Institute of Technology and Management Department of Mechanical Engineering Bengaluru India School of Management Dr. Vishwanath Karad Mit World Peace University Pune India Gitam University Department of Mathematics Visakhapatnam India Hiralal Mazumder Memorial College for Women Department of Computer Science Kolkata India Sri Sai Ram Engineering College Department of Artificial Intelligence and Data Science Chennai India

ISBN: (纸本)9798350336238

Due to the lack of a mechanism in place to check online for parking availability, it is now quite difficult to find a parking spot in congested regions. Imagine being able to access information about parking slot availability on your phone and not having to move around to do so. The cutting-edge parking system powered by IoT can overcome this issue. The IoT-based parking system makes it simple to check the availability of parking spaces online. With the aid of this device, the parking system might be fully automated. You might have automatic admission, payment, and exit processes. A NodeMCU-based IOT-based car parking system is being created using five IR sensors, two servo motors, and NodeMCU. Three IR sensors are utilised to determine whether parking spaces are available, and two IR sensors are used at the entry and exit gates to identify vehicles. Based on the sensor value, servo motors control the gates' opening and closing. In this part, we'll show you how to upload data to the cloud that is reachable from anywhere using the Adafruit IO platform. © 2023 IEEE.

关键词： Infrared detectors

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End to End Scalable Image Coding for Machines 3

End to End Scalable Image Coding for Machines

引用

3rd international conference on Intelligent Communications and Computing, ICC 2023

作者： Wu, Zijun Wang, Hanming Wang, Huifen Zhang, Yuan China Telecom Big Data and Artificial Intelligence Shanghai China

ISBN: (纸本)9798350308327

With the rapid advancements in image data acquisition technology, there has been a significant improvement in the resolution of captured images. This progress enables clear display of intricate details. However, to support downstream tasks such as object detection and semantic segmentation, image encoding in machine vision requires compression and transmission of source images for machine analysis. Additionally, it involves allocating transmitted bitstreams to different task networks and controlling bit rates. In this article, we propose a deep progressive image codec framework specifically designed for machine vision tasks. Our approach consists of several key steps. Firstly, we convert the image into a potential tensor representation. Then, utilizing a depth-constrained image encoder, we encode each element of the tensor into a marching plane. Subsequently, we decode the marching planes into images of varying quality based on the decoding points' priority. To enhance the framework's suitability for machine vision tasks, we perform joint training with downstream task networks. This collaborative training ensures that the codec aligns effectively with the requirements of these tasks. By integrating the feedback from the downstream networks, we optimize the codec's performance in relation to machine vision objectives. Experimental results demonstrate that the proposed framework not only effectively guarantees the accuracy of downstream tasks but also enables substantial savings in transmission bit rates. Additionally, the framework meets the demands of reconstructing images of varying quality without requiring further training. © 2023 IEEE.

关键词： Deep neural networks

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