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A hybrid wrapper technique enabled Network Intrusion Detection System for Software defined networking based IoT networks 3

A hybrid wrapper technique enabled Network Intrusion Detecti...

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3rd international conference on Artificial intelligence For Internet of Things, AIIoT 2024

作者： Ramaiah, Mangayarkarasi Padma, Adla Vishnukumar, Ravula Rahamathulla, Mohemmed Yousuf Chithanuru, Vasavi Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India

ISBN: (纸本)9798350372120

In the age of smart era, usage of IoT devices is inevitable. As the number of IoT devices increases, the amount of data they generate also increases, which in turn leads to security breaches. Continuous monitoring through SDN is the appropriate solution to mitigate security breaches. SDN introduces a new architecture where the control plane operates independently of the data plane. While this design allows applications in the base plane to interact with network components via the controller, it also creates security concerns. An attacker could exploit vulnerabilities in the control plane, potentially leading to significant data breaches. Amid a lot of research in various venues to address the security aspects of SDN, a simple and robust Intrusion detection system is necessary for the current context. Hence, a hybrid-wrapped enabled feature selection RF-RFE has been included in determining the highly influential features upon the derived features and a fine-tuned machine learning-based model to detect the anomalies at the earliest possible in the context of SDN has been trained and tested on SDN-IoT dataset. The tested results reveal that RF-based RF-RFE-SDNIoT-NIDS obtained 99% of its binary and multi-classification accuracy using minimal features compared to other machine learning models. © 2024 IEEE.

关键词： Intrusion detection

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Movement Pattern Recognition in Boxing Using Raw Inertial Measurements 3rd

Movement Pattern Recognition in Boxing Using Raw Inertial Me...

引用

3rd international conference on Optimization, Learning Algorithms and applications (OL2A)

作者： Puchalski, Radoslaw Giernacki, Wojciech Poznan Univ Tech Poznan Poland

ISBN: (纸本)9783031530357;9783031530364

In the paper, a new machine-learning technique is proposed to recognize movement patterns. The efficient system designed for this purpose uses an artificial neural network (ANN) model implemented on a microcontroller to classify boxing punches. Artificial intelligence (AI) enables the processing of sophisticated and complex patterns, and the X-CUBE-AI package allows the use of these possibilities in portable microprocessor systems. The input data to the network are linear accelerations and angular velocities read from the sensor mounted on the boxer's wrist. By using simple time-domain measurements without extracting signal features, the classification is performed in real-time. An extensive experiment was carried out for two groups with different levels of boxing skills. The developed model demonstrated high efficiency in the identification of individual types of blows.

关键词： activity recognition artificial intelligence artificial neural networks edge computing microcontrollers

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The Classification of Software Requirements using Large Language Models: Emerging Results and Future Directions 3

The Classification of Software Requirements using Large Lang...

引用

3rd international conference on Cloud Computing, Big Data Application and Software Engineering, CBASE 2024

作者： Zhang, Yizhuo Li, Yanhui School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China School of Computer Wuhan Qingchuan University Wuhan China

ISBN: (纸本)9798331506582

In recent years, large language models (LLMs) have demonstrated exceptional capabilities across various tasks. However, the effectiveness of LLMs in software requirement classification has yet to be thoroughly explored. This paper aims to bridge this gap by evaluating the performance of multiple LLMs (including GPT-3.5, GPT-4, GPT-4o, HuggingChat, Gemini, and DeepSeek) under different task prompts, focusing specifically on the binary classification of functional requirements (FR) versus non-functional requirements (NFR), as well as the multi-class classification of non-functional requirements. Experimental results show that HuggingChat achieved the highest accuracy and F1 score in the binary classification task, outperforming other models;meanwhile, GPT-4 performed relatively well in the multi-class classification task. Through the analysis of these results, this paper provides important references for future research and applications in software requirement classification and explores potential directions for LLM-based software requirement classification. © 2024 IEEE.

关键词： Application programs

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Enhancing Drug Repositioning Through Collaborative Metric Learning: A Novel Approach 3

Enhancing Drug Repositioning Through Collaborative Metric Le...

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3rd international conference on Artificial intelligence For Internet of Things, AIIoT 2024

作者： Gajendran, Sudhakaran Logeswari, G. Balasubramanian, Kaavin Om Kumar, C.U. Thangaramya, K. Vellore Institute of Technology School of Electronics Engineering Chennai Campus India Vellore Institute of Technology School of Computer Science and Engineering Chennai Campus India Vellore Institute of Technology School of Computer Science and Engineering Vellore India

ISBN: (纸本)9798350372120

Inthe era of big data, leveraging computational approaches for drug repurposing emerges as a promising and efficient method to uncover novel applications for existing medications. This methodology bears significant potential for advancing precision medicine. Deviating from traditional drug development methods, drug repositioning emerges as a costeffective and low-risk strategy. Framed as a top-K recommendation task, the drug repositioning challenge involves aligning medications with the most probable diseases using data related to drugs and diseases. In this work, collaborative metric learning is applied to predict the top diseases that can be recommended to drugs. Firstly, pre-processing of the drugdisease association dataset obtained from CTD database is done, in addition to obtaining drug related data from the same. Secondly, sampling of the dataset is done using SMOTE technique to address the imbalance issue caused due to far lesser number of drug-disease pairs with known associations than the pairs with no known associations in the dataset. Finally, using collaborative metric learning in conjunction with the balanced drug and disease related data, novel drug-disease interaction (DDI) associations are predicted. Latent vectors of drugs and diseases are obtained precisely, and the association probability of drug-disease pairs is then determined using them. According to the experimental analysis, the method works better than the most advanced medication repositioning strategies. © 2024 IEEE.

关键词： Drug interactions

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Semantic Relationship Model of Chinese international Core Vocabulary in Artificial intelligence Scenarios 3

Semantic Relationship Model of Chinese International Core Vo...

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3rd IEEE international conference on Social Sciences and intelligence Management, SSIM 2023

作者： Zhu, Ying Shandong Institute of Commerce and Technology Jinan China

ISBN: (纸本)9798350327786

The rapid progress of Artificial intelligence (AI) has gained widespread attention worldwide, and its applications in industries have inspired a strong interest in the semantic relationship. As one of the hotspots of AI research, Chinese international core words have been valued and favored by scholars. An in-depth exploration was conducted in this study for the semantic connections of Chinese international core words in AI with a literature review. There were disagreements on the definition of word concepts in AI, which directly affects theoretical innovation and application. With the continuous development of science and technology, numerous vocabularies are added, and their meanings are constantly changing. At present, the academic community still lacks an in-depth understanding of the relationship between the Chinese international Core Vocabulary and AI so it is necessary to research it. Combining the historical evolution of terms, the semantic meanings at different times and contexts were investigated to provide a basis for further study. Existing studies were limited at the lexical level and lacked in-depth exploration from the syntactic perspective, thus failing to demonstrate the complex semantic relationships among Chinese international core vocabulary. In this study, the Semantic Relational Model of international Chinese Core Vocabulary in AI Scenarios (SRMCCV) was developed based on linguistic theory and computer processing technology. Statistical analysis methods such as word frequency statistics were used to explore the semantic logic of frequently used words and analyze relevant literature and new corpus. The model revealed the potential connections between words and semantic interactions in AI. The results can be used to improve the quality of international Chinese language teaching. © 2023 IEEE.

关键词： Semantics

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Hand-eye calibration of line structured-light sensor based on double-sphere constraints 3

Hand-eye calibration of line structured-light sensor based o...

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2023 3rd international conference on Detection technology and intelligence System, DTIS 2023

作者： Ruan, Yisheng Deng, Zhengping Hao, Fei Chen, Ruwen School of Mechanical Engineering Nanjing Institute of Technology Nanjing211167 China

Aiming at the complex problem of solving the positional relationship between the line laser sensor at the end of the robot wrist and the coordinate system of the end flange, a line laser hand-eye calibration method based on a double ball fixed target is proposed. Firstly, a double standard ball with known radius and center distance is used as a reference tool, and the point cloud data of a single contour line is collected several times, and the coordinates of the two ball centers under the camera coordinate system can be obtained according to the center coordinates of the circle obtained from the fitted circle combined with the Pythagoras theorem. Then, according to the principle that the two spherical centers are fixed under the robot base coordinate system, the rigid transformation matrix between the line laser sensor and the robot is successively solved. When solving the rotation matrix, the constraint of the distance between the spherical centers of the two balls is introduced to obtain a solution with better accuracy. Experimental results show that the method has better overall performance compared with the traditional single-ball hand-eye calibration method. © Published under licence by IOP Publishing Ltd.

关键词： robots

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Based-on Computer Vision applications for Bus Stop Passenger Detection System 3

Based-on Computer Vision Applications for Bus Stop Passenger...

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3rd IEEE international conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2023

作者： Chang, Yu-Cheng Tsai, Hua-Wen Huang, Chao-Yi Wu, Zong-Rong Department of Computer Information and Network Engineer Lunghwa University of Science and Technology Taiwan Department of Bachelor's Program in Intelligent Robot National Yunlin University of Science and Technology Taiwan

ISBN: (纸本)9798350333862

Passenger transport is one of the most common ways of commuting in Taiwan. It plays an important role in the transportation system due to its large number of stations, dense frequency, and cheap transportation. Due to the unfriendly transportation environment and a large number of passengers, a blind spot of passenger transportation exists, which leads to traffic accidents at the station. We research to make the Bus Stop Passenger Detection System. Taking the object detection of Wheelchairs into consideration, it is more convenient to assist the disabled to find the passenger transportation system, which makes Taiwan's transportation system more convenient. © 2023 IEEE.

关键词： Object detection

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Analysis and Detection of Orange Images Based on Improved Faster R-CNN Algorithm and Feature Data Analysis 3

Analysis and Detection of Orange Images Based on Improved Fa...

引用

3rd IEEE international conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2023

作者： Wang, Shigang Liao, Xianghua Ma, Kai School of Automation Guangxi University of Science and Technology Liuzhou China

ISBN: (纸本)9798350333862

Orange is one of the fruits with the largest planting area in China, and the harvesting work is huge in the harvest season. Therefore, the orange picking robot is often used to replace workers for picking work. In order to enable the picking robot to better detect orange fruits in the natural environment, we established an improved faster R-CNN detection model based on the growth characteristics of oranges. First, to reduce the orange detection model, VGG16 was replaced by MobileNetv2 as the feature extraction network of this algorithm. Secondly, to make the model fit better, the size of the anchor frame was fine-tuned. Finally, aiming at the problem that trees of orange are easy to overlap and block each other, a double-NMS algorithm was designed to replace NMS and remove redundant rectangular frames. The experimental results show that the improved algorithm has higher detection accuracy and lower missed detection rate, which provides a new method for improving the intelligence of the picking robot. © 2023 IEEE.

关键词： Image enhancement

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Analysis on the Application of Artificial intelligence technology in College Teaching 3rd

Analysis on the Application of Artificial Intelligence Techn...

引用

3rd EAI international conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2023

作者： Ren, Yuankun Wenxin, Jiang Lu, Hailan Liaoning Shenyang110036 China Nanning University Guangxi Nanning530200 China

ISBN: (纸本)9783031631351

The application of artificial intelligence technology in university teaching presents broad potential and prospects. Through personalized teaching, artificial intelligence can provide customized teaching materials and guidance based on students’ learning styles and levels;Through big data analysis, artificial intelligence provides teachers with detailed information on students’ learning situations, which helps to better guide and coach students;At the same time, artificial intelligence can also utilize virtual laboratories and simulated environments to develop safer and more practical learning experiences. In addition, artificial intelligence technology can also provide automated evaluation and feedback, reducing the workload of teachers. In summary, the application of artificial intelligence technology in university teaching can improve students’ learning outcomes and teachers’ teaching quality, bringing new opportunities for innovation and progress in the field of education. With the further development of technology and the continuous promotion of applications, artificial intelligence will continue to play a more important role, laying a solid foundation for cultivating more outstanding talents in higher education. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Artificial intelligence

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Topical Issues of the Use of Artificial intelligence Technologies in Education and Law 3

Topical Issues of the Use of Artificial Intelligence Technol...

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3rd international conference on technology Enhanced Learning in Higher Education, TELE 2023

作者： Gridchina, Nelli Savvina, Natalia Zavyalov, Sergey Russian Academy of Advocacy and Notaries Moscow Russia Lipetsk State Technical University Department of Physical Culture Russia Russian State Academy of Intellectual Property Moscow Russia

ISBN: (纸本)9798350326567

According to the Constitution, the right of every person to education is guaranteed in the Russian Federation. The relevance of research. The authors of the article note that modern education in Russia and internationally is undergoing significant changes due to the active introduction of artificial intelligence into human life. Artificial intelligence (AI) is a way to make a computer - controlled robot or program capable of thinking as intelligently as a person. The basis for the creation of artificial intelligence are the following sciences and technologies: computer science, biology, psychology, linguistics.. The novelty of the research lies in determining the main directions of transformation of the educational process at the university in the conditions of cybersocialization of society. The purpose of the study is to identify the possibilities and problems of using artificial intelligence in the educational process and jurisprudence. The main tasks that need to be solved in this work: 1. To understand the reasons for the creation of artificial intelligence and the possibilities of its application in education and law at the present stage of development of society;2. To explore possible areas of application of artificial intelligence technologies in the educational process;3. To reveal the prospects of using artificial intelligence in teaching students and schoolchildren;4. Evaluate the pros and cons of using artificial intelligence in education and law. The object of research in this article is artificial intelligence technologies. The subject of the research is the ways of improving and developing artificial intelligence in its application in education and law. The degree of scientific development of the topic of the publication. In the studies of A. A. Verbitsky, N. S. Ilyushenko, N. B. Strekalova, N. S. Kramarenko, A. Yu. Kvashina, S. D. Karakozova, A. *** and A. ***, on which this article is based, talk about the properties of digital education

关键词： Informatization

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