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Enhancing Hyperspectral Image Compression Through Stacked Autoencoder Approach 6

Enhancing Hyperspectral Image Compression Through Stacked Au...

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6th International Conference on Electrical engineering and Information and communication Technology, ICEEICT 2024

作者： Afrin, Afsana Haque, Md. Rakibul Mamun, Md. Al Inst. of Information and Communication Technology Rajshahi University of Engineering Technology Rajshahi6204 Bangladesh Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798350385779

Hyperspectral Image (HSI) consisting of numerous high-resolution spectral bands creates challenges of the high dimensionality problem in HSI classification which hinder real-life applications despite their abundance of information. We present a lossy compression approach using stacked autoencoders to reduce high dimensionality problem in this paper. The pro-posed method utilizes stacked autoencoders to extract features from HSIs, allowing compression and subsequent reconstruction. The study demonstrates improved Peak Signal-to-Noise Ratio (PSNR) of 70.43, 60.87 and 61.36 on three distinct HSI datasets-Salinas, Botswana, and KSC respectively compared to previous autoencoder-based compression method. Additionally, the impact of compression on classification accuracy is assessed using a 3D-2D CNN model, achieving an average accuracy of 99 % across the datasets. Improved compression along with high classification accuracy shows our proposed method's usefulness. © 2024 IEEE.

关键词： Image enhancement

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Performance Analysis of the 2D-Unitary ESPRIT Algorithm for 5G mmWave networks

Performance Analysis of the 2D-Unitary ESPRIT Algorithm for ...

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2024 Wave Electronics and its Application in Information and Telecommunication Systems, WECONF 2024

作者： Fokin, Grigoriy Grishin, Ilya Sinilnikov, Alexander Sevidov, Vladimir The Bonch-Bruevich Saint Petersburg State University Of Telecommunications Software Defined Radio Laboratory Saint Petersburg Russia The Bonch-Bruevich Saint Petersburg State University Of Telecommunications Department Of Communication Networks Saint Petersburg Russia Fed. State Budgetary Inst. Order Of The Red Banner Of Labor Radio R. and D. Inst. Named After M.I. Krivosheev Center For Satellite Communication Saint Petersburg Russia S.M. Budyonny Vas Department Of Radio Engineering Saint Petersburg Russia

ISBN: (纸本)9798350364989

This paper analyzes the 2d-unitary ESPRIT algorithm and investigates its feasibility in 5G networks. The content of this paper can be divided into three parts. In the first two parts of the paper, the mathematical model of the direction of arrival (DoA) algorithm is given. The third part of the paper describes the simulation results of beamforming scenarios considering DoA location in 5G mmWave ultra-dense networks (UDNs). The contribution of this study is the investigation of the dependence of the resolution threshold and accuracy of the 2d unitary ESPRIT algorithm on the number of elements in the antenna array and the value of SINR. © 2024 IEEE.

关键词： 5G mobile communication systems

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LIVES: XAI-based Secure UAV communication Framework for Essential Items Delivery

LIVES: XAI-based Secure UAV Communication Framework for Esse...

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Artificial Intelligence and Data engineering (AIDE), International Conference on

作者： Vidhi Ruparelia Sneh Shah Lakshin Pathak Rajesh Gupta Sudeep Tanwar Sahil Sawhney Ankur Gupta Department of Electronics and Communication Engineering Inst. of Technology Nirma University Ahmedabad India Department of Computer Science and Engineering Institute of Technology Nirma University Ahmedabad India Department of Computer Science & Engineering Model Institute of Engineering & Technology Jammu & Kashmir India

ISBN: (数字)9798331527518

ISBN: (纸本)9798331527525

The application of Unmanned Aerial Vehicles (UAVs) for securely delivering essential items during extreme conditions includes numerous challenges, particularly in ensuring identification of potential threats. To solve this challenge, we propose a strong framework that makes use of Boosting algorithms, with a particular focus on XGBoost to enhance attack classification in UAV-based delivery systems. The XGBoost model achieved an accuracy of 93%, a precision of 0.9312, a recall of 0.9311, and an F1 score of 0.9283 , which makes it a highly suitable model for security of UAVs. Explainable AI (XAI) is used to further enhance classification including SHAP and LIME to identify the most influential features, such as the barometer and battery levels. Our framework provides a comprehensive solution for secure UAV-based deliveries. The experimental results proves the effectiveness of the proposed model which shows its potential for real-life applications.

关键词： Accuracy Explainable AI Autonomous aerial vehicles Boosting Data engineering Barometers Classification algorithms Batteries Security

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A Non-normal Warning System for Dam Operation Using Machine Learning 24

A Non-normal Warning System for Dam Operation Using Machine ...

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24th IEEE/ACIS International Winter Conference on Software engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2022

作者： Chang, Meng-Wei Liu, I-Hsien Liu, Chuan-Kang Lin, Wei-Min Su, Zhi-Yuan Li, Jung-Shian Inst. Computer and Communication Engineering National Cheng Kung University Dept. of Electrical Engineering Tainan Taiwan National Chin-Yi University of Technology Dept. of Artificial Intelligence and Computer Engineering Taichung Taiwan Chia Nan University of Pharmacy and Science Dept. of Multimedia and Game Development Tainan71710 Taiwan

ISBN: (纸本)9798350310412

A country's critical infrastructures are heavily related to the quality of life and safety of the people. As a result, the security protection aspect of critical infrastructure has gained more and more attention nowadays, especially the security of its industrial control system (ICS). To avoid the abnormal condition happening in the critical infrastructure which could put people in great danger, a system that is capable of detecting any abnormal state of the ICS promptly is needed. Fortunately, due to the dramatic growth of the applications of machine learning in recent years, some researchers have already proposed anomaly detection methods with machine learning to provide inst.nt warning and protection for ICS. However, most of the existing anomaly detection research tends to only target one cause that harms the system, such as attacks on the network or physical equipment failures. The ICS will be more comprehensively secured if the anomaly detection system can cover multiple aspects of the ICS. Therefore, we have established a non-normal warning system with the Generative Adversarial Network (GAN) for dam operations in this study, which can detect various types of non-normal operations and notify relevant personnel right away. Note that we use real historical data to make predictions and verify our warning system, and we improve it even more by implementing the visual analysis method, which makes up the indecipherable results often found in unsupervised learning. © 2022 IEEE.

关键词： Critical infrastructures

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Threat Analysis of Cyber Security Exercise for Reservoir Testbed Based on Attack Tree

Threat Analysis of Cyber Security Exercise for Reservoir Tes...

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International Symposium on Computing and Networking Workshops (CANDARW)

作者： Sú-Goân Tân I-Hsien Liu Jung-Shian Li Dept. of Electrical Engineering Inst. of Computer and Communication Engineering National Cheng Kung University Tainan Taiwan

As operational technology (OT) and information technology (IT) are getting closer in industrial control systems (ICS) nowadays, the security of critical infrastructure (CI) has become an important issue, which may have a great influence on people's livelihood, economy, and even safety. Therefore, governments around the world have conducted a series of cyber security exercises, which is one of the most effective ways to maintain and optimize the security, so as to cultivate the information security capabilities of government agencies and enterprises in the face of cyber attacks. In this paper, we present the framework and situations of the cyber security exercise with two scenarios on our reservoir testbed, and then analyze the threats based on the attack tree model and give the security recommendations to protect the critical infrastructure according to the results of the practical exercise and analysis.

关键词： Integrated circuits Measurement Analytical models Industrial control Knowledge based systems Government Reservoirs

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Experimental verification of NP-complete problems via linear optics 13

Experimental verification of NP-complete problems via linear...

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13th International Conference on Wireless communications and Signal Processing, WCSP 2021

作者： Li, Jian Liu, Tongjun Hou, Tianlei Wang, Xiaorun Liu, Chenxi Dai, Pan Wang, Qin Nanjing University of Posts and Telecommunications Inst. of Quant. Info. and Technology Broadband Wireless Communication and Sensor Network Technology National Engineering Research Center Key Lab of Ministry of Education Telecommunication and Networks Nanjing China

ISBN: (纸本)9781665407854

Non-deterministic polynomial (NP)-complete problems are collections of intractable problems for classical computers, but they may be easier to solve for quantum computers. Considering that practical quantum computers and networks are still under development, it is necessary to find alternatives to solve these problems. Simulations with linear optics offer a good choice since much of the research on quantum information is executed with this approach. In this work, based on Aaronson's protocol (Theory Comput, 5, 1, 2009) ad Arrazola et. al.'s linear optics scheme (npj Quantum Inf, 78, 022310, 2018), we present a demonstration of the NP-complete 2-out-of-4 SAT problem for 4 variables. The experimental results show that NP-complete problems can be well simulated through linear optical systems. © 2021 IEEE.

关键词： Quantum optics

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A Method for Predicting Cardiovascular Disorder using Machine Learning Techniques

A Method for Predicting Cardiovascular Disorder using Machin...

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Recent Advances in Science and engineering Technology (ICRASET), International Conference on

作者： Ramakrishna Hegde D R Pavithra S Shivashankara G Prasanna Kumar S M Soumyasri S Nagashree Computer Science and Engg. Vidyavardaka College of Engineering Affiliated to Visvesvaraya Technological University Belagavi India Electronics & Communication Engg. Sri Jayachamarajendra College of Engineering JSS Science and Technology University Mysuru India Computer Science and Engg. KR Pete Krishna Government Engineering College Krishnarajapet India Information Science & Engg. The National Institute of Engineering Mysore India Dept. of Computer Applications Vidya Vikas Inst. of Engg. and Tech Affiliated to Visvesvaraya Technological University Belagavi India Electronics and communication Engg Vidya Vikas Institute of Engineering and Technology Mysuru India

ISBN: (数字)9798350388602

ISBN: (纸本)9798350388619

Drastic increase of cardiovascular disease has led to a lot of adult’s death. As per “News 18” very year, 12 million young people in India die from heart disease. In most of these cases people experience cardiac arrest, some of which are normal. First, families of patients are vulnerable because it takes only a few minutes for a person to die of a heart attack, and it is difficult to get medical help in time. Second, most victims are under the age of 45. According to Dr. Maninder Sandhu, cardiologist and cardiologist at Artemis Hospital Gurgaon, 30 percent of people who suffer from heart disease are under the age of 45. This paper proposes a method that maybe used by laboratory technicians, doctors and users to understand whether there are any chances of having cardiovascular disease or not. The proposed system takes live data of patients and their lifestyle attributes these data are processed by the trained model to produce the output. In this model we haveused random forest classifier, linear regression, $\mathbf{k}$-neighbors classifier & x gradient boost classifier. This model has attained maximum accuracy and least type one error in “X- Gradient Boost”. We have concentrated more on type one error. The developed system shows whether the patient has any chances of cardiovascular disease or not.

关键词： Heart Accuracy Linear regression Cardiac arrest Predictive models Nearest neighbor methods Feature extraction Prediction algorithms Classification algorithms Random forests

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Size-Reduced Patch Antenna Loaded with a Metamaterial Substrate Made of Periodic Metal Strips Operating at 900MHz 13

Size-Reduced Patch Antenna Loaded with a Metamaterial Substr...

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13th International Conference on Microwave and Millimeter Wave Technology, ICMMT 2021

作者： Lu, Hao Xu, Xiaofei Shanghai University School Of Communication And Engineering Shanghai200444 China Key Lab. Of Specialty Fiber Opt. And Optical Access Networks And Shanghai Inst. For Adv. Commun. And Data Sci. Shanghai University Shanghai200444 China

ISBN: (纸本)9781665434379

A microwave patch antenna is studied with reduced patch size operating at 900MHz. The new antenna is featured with a metamaterial substrate that is made from periodic metal strips. One antenna is numerically demonstrated with a patch size of 54mm×60mm. It resonates at 898MHz with a relative bandwidth of 3.8%. The electrical patch size is only 0.16×0.18, much beyond the 0.5 limitation for a conventional patch antenna. The metamaterial antenna is shown with a very high efficiency 95.8%, even for such a small prototype. © 2021 IEEE.

关键词： Microstrip antennas

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Data Transfer Methods and Algorithms in Wireless Sensor networks for IoT-based Remote Monitoring System of Hybrid Energy Supply Sources

Data Transfer Methods and Algorithms in Wireless Sensor Netw...

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2022 International Conference on Information Science and communications Technologies, ICISCT 2022

作者： Siddikov, Ilkhomjon Khujamatov, Halimjon Khasanov, Doston Reypnazarov, Ernazar Iminov, Abdurasul Tashkent Inst. of Irrigation and Agricultural Mechanization Engineers National Research University Department of 'Use of Electrical Technologies and Electrical Equipment' Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Faculty of 'Komputer Engineering' Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of 'Data Communication Networks and Systems' Tashkent Uzbekistan Academy of the Ministry of Internal Affairs of the Republic of Uzbekistan Department of 'Information Technologies' Tashkent Uzbekistan

ISBN: (纸本)9781665472296

The most important requirement in the provision of telecommunication services is its continuous provision. Continuity of services depends mainly on the uninterrupted power supply of telecommunications equipment. for this reason, today, scientists are conducting research on continuous monitoring of energy supply sources, prediction and early detection of possible failures and outages. In particular, wireless sensor networks are widely used in real-time monitoring of energy supply sources and have become the center of interest. In this article, the data transmission processes and transmission problems of wireless sensor networks used in monitoring systems are studied. Also, several algorithms aimed at improving the effectiveness of wireless sensor networks and improving the efficiency of data transmission are proposed in the article. © 2022 IEEE.

关键词： Wireless sensor networks

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A Non-normal Warning System for Dam Operation Using Machine Learning

A Non-normal Warning System for Dam Operation Using Machine ...

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ACIS International Conference on Software engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD)

作者： Meng-Wei Chang I-Hsien Liu Chuan-Kang Liu Wei-Min Lin Zhi-Yuan Su Jung-Shian Li Dept. of Electrical Engineering Inst. Computer and Communication Engineering National Cheng Kung University Tainan Taiwan dept. of Artificial Intelligence and Computer Engineering National Chin-Yi University of Technology Taichung Taiwan dept. of multimedia and Game Development Chia Nan University of Pharmacy and Science Tainan Taiwan

关键词： Integrated circuits Training Visualization Dams Machine learning Alarm systems Generative adversarial networks

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