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An Intrusion detection Framework with Optimized Feature Selection and Classification Combination Using Support Vector Machine 3

An Intrusion Detection Framework with Optimized Feature Sele...

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3rd IEEE international conference on Electronic technology, Communication and Information, ICETCI 2023

作者： Tianyao, Luo Huadong, Huang Run, Li Guangxi International Business Vocational College Nanning530007 China

ISBN: (纸本)9798350398410

As intelligent devices and related technologies continue to develop, abnormal traffic detection has become a major issue in the field of internet security. Malicious attacks can have a negative impact on systems and cause a decline in computational performance. One of the technologies used to identify intruder activity and assess system security by sending out notifications is intrusion detection systems. In this endeavor, we employ the diversified NSL-KDD dataset for intrusion detection to introduce a novel feature selection and classification merging technique using support vector machines (SVM). The goal of this technique is to increase the capability of intrusion classification by considerably reducing the input feature set from the training data. The process of choosing significant input training features and discarding unimportant ones in supervised learning results in a feature subset that can produce greater classification accuracy. In our tests, we used the KDDTest+ and KDDTest-21 data sets' various input feature subsets as input features for the SVM classifier. According to the experimental findings, the suggested technique obtains classification accuracy of 88.25% when using only KDDTest+ and 72.42% when using KDDTest-21. © 2023 IEEE.

关键词： Support vector machines

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Research on CBRN Practical Assessment technology Based on Artificial intelligence technology 3rd

Research on CBRN Practical Assessment Technology Based on Ar...

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3rd international conference on Advanced Intelligent Technologies, ICAIT 2022

作者： Wang, Junhua Yang, Hongyu Dong, Wenbin Zhang, Minghu Zhang, He Jing, Yunke Zhao, Xin Dalian Naval Academy Dlian116018 China

ISBN: (纸本)9789819952021

Combined with the common practical assessment problems in the field of CBRN, which have the problems of high subjective factors and inconsistent assessment standards, this paper proposes the feasibility design scheme of the assessment system based on intelligent identification technology, and analyzes the key technologies such as target recognition technology and expert system involved in the system. While verifying the feasibility of the assessment system design scheme based on intelligent identification technology, it provides ideas for the construction of the assessment system based on intelligent identification technology. It also provides a good solution to improve the quality of assessment. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Expert systems

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Integration of Internet of Things, Data Sets, and Cloud computing towards Space-Science 5.0 3

Integration of Internet of Things, Data Sets, and Cloud comp...

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3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Deshpande, Rashmi Sameer Pandey, Ashutosh Buddhi, Dharam Chandhar, Kothakonda Muni Raju, Adusupalle Patidar, Vijay Dr D y Patil Institute of Engineering Management and Research Akurdi Pune India Srmscet Bareilly Department of Basic Science Uttar Pradesh Bareilly India Uttaranchal Institute of Technology Uttaranchal University India Sr University School of Computer Science and Artificial Intelligence Telangana Warangal India Department of Marketing India Parul University Department of Aero India

ISBN: (纸本)9798350399264

technology has been influenced by the Internet of Things technology (IoT) in many different ways. It started as a network of interconnected devices communicating over the Internet has become tremendously complex system as network nodes were added and particular IoT domains were formed. There are numerous sub domains for IoT. IoT has yet to be implemented in a number of fields, including healthcare, robotics, and other related ones. one of the space research technologies that is advancing quickly. Over the past few decades, space research has grown significantly, with studies covering exo-planet discovery, colonization, space communication, and the potential for life on distant planets. In this study, we propose an unique Internet of Space Things (IoST) infrastructure that is cloud-compatible for the rapidly expanding and far-reaching field of space technology. The essay offers a thorough logical and physical architecture that takes into account ground stations, interstellar communication, public networks, cloud providers, enterprise networks, and cloud networks. The study will be helpful towards scientists and researchers working on IoT, emerging technologies, migration, robot assisted surgeries, space farming, etc. © 2023 IEEE.

关键词： Space research

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Artificial intelligence Integrated Biomedical Implants system Developments in Healthcare 3

Artificial Intelligence Integrated Biomedical Implants Syste...

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3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Mohamed, Nachaat Singh Solanki, Madhav Praveena, Hirald Dwaraka Princy, Anni Das, Saptorshi Verma, Devvret Uae Homeland Security Universiti Sains Malaysia Rabdan Academy Abu Dhabi United Arab Emirates Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India Mohan Babu University ECE School of Engineering Tirupati India Panimalar Engineering College Computer and Communication Engineering India Kiit Deemed to Be University Kiit School of Management India Graphic Era Deemed to Be University Department of Biotechnology Uttarakhand Dehradun India

ISBN: (纸本)9798350399264

AI technology (AI) has become more and more common recently, with numerous applications in many areas of industries. Since composite is a biologically, natural bone component that will be used to create a powerful but stable blood relationship with the nearby articular cartilage, electrically deposited coats made of crystals are also beneficial in a host of clinical situations. With HVSFS, Ips, and Ethics and moral, bio corrosion inhibitors made of Hap granules were heated sprayed onto Ti plates. Calcium phosphate has gained a lot of attention recently in the fields of corrosion inhibitors and nanomaterials (HA). Devices sprayed with HA have high mechanical properties and cytocompatibility due to the porous covering. Thermal anatase covering has exceptional interfacial adhesion. © 2023 IEEE.

关键词： Titanium dioxide

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Multilevel Face Mask detection system using Ensemble based Convolution Neural Network 3

Multilevel Face Mask Detection System using Ensemble based C...

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3rd international conference on Secure Cyber Computing and Communications, ICSCCC 2023

作者： Gupta, Vishan Kumar Gupta, Avdhesh Tyagi, Vikas Pandey, Priyank Gupta, Richa Kumar, Dinesh Sir Padampat Singhania University Department of Cse Rajasthan Udaipur India Ajay Kumar Garg Engineering College Department of Information Technology UP Ghaziabad India National Institute of Technology Department of Cse Punjab Jalandhar India Graphic Era Deemed to Be University Department of Cse UK Dehradun India Graphic Era Hill University Department of Cse UK Dehradun India Krishna Institute of Engineering & Technology Department of Cse UP Ghaziabad India

ISBN: (纸本)9798350300710

Due to COVID outbreak face mask detection in the industry as well as in any gathering playing an important role. Either person worn facemask or not worn. In this CORONA situation, Use of a face mask is one such preventative that is crucial. Facial recognition technologies are now used by many businesses and organizations for their own general purposes. We are all aware of how important it has become to always wear a mask when we travel. However, as we all know, it is impossible to monitor who is wearing a mask and who is not. If some person who worn the mask, then it is not confirmed whether he/she worn it correctly or not. We make the use of AI in our daily life. We achieve this with the help of a deep learning, where we train the model using various convolution neural network approaches and created a hybrid model using bagging-based ensemble learning. Here, detection is performed based on voting-based classification so that we can enhance the accuracy of our model. We have found dataset from MAFA and Kaggle. The hybrid approach of C2N model achieved exceptional accuracy with the use of a dataset of face mask detection that contains both with and without face mask photographs. In our multilevel facemask detection system at the first level our model will predict whether the person worn facemask or not and at its second level it will predict the correctness of facemask, whether it is worn correct or not. © 2023 IEEE.

关键词： Convolution

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Applications of Machine Learning in Modern Power systems: A Comprehensive Review 3

Applications of Machine Learning in Modern Power Systems: A ...

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3rd international conference on New Energy and Power Engineering, ICNEPE 2023

作者： Mirsaeidi, Sohrab Mendoza, Alejandro Zavaleta Ghaffari, Kimia Yousaf, Muhammad Zain Muttaqi, Kashem M. He, Jinghan Beijing Jiaotong University School of Electrical Engineering Beijing China Beijing Jiaotong University School of Economics and Management Beijing China Hubei University of Automotive Technology School of Electrical and Information Engineering Shiyan China University of Wollongong School of Electrical Comp. and Telecom. Engineering Wollongong Australia

ISBN: (纸本)9798350393224

The demand for electrical power has increased due to population growth, electronic technology advancements, and environmental concerns. This has led to a significant modernization of the power system that incorporates renewable energy sources and electronic components for measurement, communication, and control. However, these changes have added new challenges to the management and control of modern power systems that cannot be overcome using traditional analytical methods. Artificial intelligence (AI), specifically Machine Learning (ML) techniques, have recently been deployed by a wide number of researchers from different fields thanks to their adaptability and learning ability at a higher speed. These techniques are adequate for large, non-linear, and multi-variable problems such as modern power systems. Therefore, this paper aims to provide an extensive review of recent ML techniques as well as their usage in modern power systems in terms of power quality, power stability, energy and load forecasting, protection and fault diagnosis, and cybersecurity. Finally, the main challenges associated with the implementation of ML techniques for future modern power systems are pointed out. © 2023 IEEE.

关键词： artificial intelligence machine learning Modern power systems

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Ship Ranging Based on Monocular Imaging and Applications 3

Ship Ranging Based on Monocular Imaging and Applications

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3rd international conference on Electronic Information Engineering and Computer Communication, EIECC 2023

作者： Li, Boshi Chen, Xianqiao Xie, Kai Chen, Jianfeng School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China

ISBN: (纸本)9798350359961

Environmental perception, including object recognition and distance estimation, is a crucial aspect in the field of computer vision. Although distance estimation has received relatively less attention compared to object recognition, its accuracy becomes particularly crucial in specific scenarios, such as when ships are entering ports or gates. In such situations, precise distance control is essential, as errors could lead to the risk of collisions between the ship and the dock. Due to significant variations in the sizes of ships, traditional distance estimation methods often exhibit substantial errors. To mitigate these inaccuracies, this paper proposes a self-Adaptive ship size estimation approach. In addition to introducing an adaptive model, we further design a distance estimation model incorporating tilt information to enhance the accuracy of distance estimation, especially for objects closer to the camera. Experimental results demonstrate the effectiveness of this approach in improving the accuracy of distance measurements, particularly in overhead perspectives. © 2023 IEEE.

关键词： component Distance estimation, monocular vision

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A Fuzzy Logic-Based Framework for Accurate detection of Infectious Diseases 3rd

A Fuzzy Logic-Based Framework for Accurate Detection of Infe...

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3rd international conference on Applied intelligence and Informatics (AII)

作者： Anitha, S. Balachandar, K. Arun Sudha, S. Sri Shakthi Inst Engn & Technol Coimbatore Tamil Nadu India Srinivas Univ Mangalore Karnataka India Wipro Technol Bangalore Karnataka India

ISBN: (纸本)9783031686382;9783031686399

The proposed framework is designed to enhance the early detection and diagnosis of diseases, aiming to improve treatment efficiency and boost recovery rates. It operates by processing data collected from wearable devices through a fuzzy inference system (FIS) consisting of key components: fuzzifier, Knowledge Discovery in Databases (KDD), a predictor, and defuzzifier. Fuzzifier renovates raw input data from wearable devices into fuzzy values suitable for use within the fuzzy inference system. KDD analyzes the fuzzified data to uncover important patterns and insights necessary for training the prediction model. The Predictor utilizes both the fuzzified data and insights from KDD to train a model capable of detecting diseases based on the processed data. Defuzzifier then translates the fuzzy output from the prediction model into clear, actionable values. The research employs the Weka tool to analyze a dataset related to monkeypox. Using the J48 algorithm, a fuzzy decision tree is constructed, and eight fuzzy rules are established based on the C4.5 algorithm. With approximately 25,600 instances in the dataset, 16,682 are correctly classified (66.728%), while 8,318 are incorrectly classified. This fuzzy logic-based approach aims to expedite disease detection processes, thereby reducing the need for hospitalization. Furthermore, it seeks to enhance the interaction between healthcare providers and patients, ultimately improving overall healthcare delivery.

关键词： Fuzzy-Logic assisted Framework Fuzzy Inference Engine Disease Diagnose

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A Critical Analysis of Applying Computer Vision In Building an Intelligent system 3

A Critical Analysis of Applying Computer Vision In Building ...

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3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Ballari, Syed Omar Srinivas, Angalkuditi Gupta, Manish Dhobal, Kiran Akabarkhan, Pathan Shahnavajkhan Reddy, Dasari Veera Guru Nanak Institutions Technical Campus Department of Civil Engineering Telangana Ibrahimpatnam501506 India Koneru Lakshmaiah Education Foundation Department of CSE India Lovely Professional University Phagwara India Uttaranchal University Uttaranchal Institute of Technology India Sankalchand Patel University Shri C.J. Patel College of Computer Studies Faculty of Computer Science India SR University School of Computer Science and Artificial Intelligence Telangana Warangal India

ISBN: (纸本)9798350399264

The terminology "computer vision"refers to the method that leverages technologies of intelligent systems such as artificial intelligence (AI) to enable computers to gather useful information from visual sources. The automated activities are demonstrated previously using computer vision understanding. The definition, examples, as well as uses of computer vision, are covered in this article. For computer vision to be totally successful there must be a huge collection. When they lack the knowledge required to execute the task at hand, these systems periodically discover trends, which cause this to occur. Hence, the research has evaluated the notion of computer vision in diverse fields of operations through the literature review as well as in the analysis and discussion portion of the study. Since the literature review and data analysis of the research is done through secondary sources, an imperative notion of review has been gathered and presented. Therefore, the significance of computer vision in assembling intelligent systems like AI and other new technologies has given discussed in the research. © 2023 IEEE.

关键词： Intelligent systems

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Feature Matching Based Conveyor Belt Anomaly detection 3

Feature Matching Based Conveyor Belt Anomaly Detection

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3rd Guangdong-Hong Kong-Macao Greater Bay Area Artificial intelligence and Big Data Forum, AIBDF 2023

作者： Yin, Chenglong Zhang, Fei Hao, Bin Pang, Xiaoyu Fu, Zijian Inner Mongolia University of Science and Technology School of Information Engineering Inner Mongolia Baotou014017 China

ISBN: (纸本)9798400716362

In the field of industrial automation, computer vision is becoming more and more popular. At present, the traditional conveyor belt anomaly detection will consume a huge amount of manpower and material resources, this paper proposes a way that can effectively reduce manpower and improve the correct rate. The algorithm first adopts multiple cameras, which are used as the acquisition medium for feature extraction, and the collected images on the conveyor belt, image processing and feature extraction techniques to find the unique features on the conveyor belt for preservation, and through these unique features on the conveyor belt, carry out the subsequent feature comparison, and if the subsequent detection of the existence of images with similar features, the algorithm will carry out the comparison, and if it exceeds the threshold, it will carry out the abnormality alarm. Experiments have proved that the algorithm has good performance in conveyor belt anomaly detection. © 2023 Copyright held by the owner/author(s).

关键词： Anomaly detection

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