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International Journal of Interactive Mobile Technologies 2022年第9期16卷 164-174页

作者： Al-Rami, Bandar Alheeti, Khattab M. Ali Aldosari, Waleed M. Alshahrani, Saeed Matar Al-Abrez, Shahad Mahdi Dean of Faculty of Computer Studies Arab open University Riyadh Saudi Arabia College of Computer Sciences and Information Technology Computer Networking Systems Department University of Anbar Ramadi Iraq Department of Computer Engineering Prince Sattam Bin Abdulaziz University Al Kharj Saudi Arabia Faculty of Computer Science and Information Technology Saudi Electronic University Riyadh Saudi Arabia

During the past decades, smart farming became one of the most important revolutions in the agriculture industry. Smart farming makes use of different communication technologies and modern information sciences for in-creasing the quality and quantity of the product. On the other hand, drones showed a major potential for enhancing imagery systems and re-mote sensing usage for many different applications such as crop classification, crop health monitoring and weed management. In this paper, an intelligent method for classifying crops is proposed to use a transfer learning approach based on a number of drone images. Moreover, the Convolution-al Neural Network (CNN) method is used as a classifier to improve efficiency for obtaining more accurate results in the training and testing phases. Various metrics are measured to evaluate the efficiency of the proposed model such as accuracy rate of detection, error rate and confusing matrix. It is found to be proven from the experimental results that the proposed method presents more efficient results with an accuracy detection rate of 92.93% © 2022. International Journal of Interactive Mobile *** Rights Reserved.

关键词： Drones

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An Agent Based Travel Assistant for the Dutch Railway Network 37

An Agent Based Travel Assistant for the Dutch Railway Networ...

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37th International Conference on Information Technologies, InfoTech 2023

作者： Rothkrantz, Leon Beelen, Martijn Delft University of Technology Faculty of Electronic Engineering Mathematics and Computer Science Mekelweg 4 CD Delft2628 Netherlands Czech Technical University in Prague Faculty of Transportation Sciences Czech Republic

ISBN: (纸本)9798350338058

For many years the Dutch NS Railway Company runs all trains in the Netherlands. It can be expected that next year different transport companies will exploit the Dutch railway network. Possible that they will use different systems to design timetables, generate travel plans and to handle delays. In this paper we research the coordination between different systems. A prototype of distributed systems in different areas has been developed using agent technology. The system has been tested in simulation studies. © 2023 IEEE.

关键词： Intelligent agents

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Enhanced Coyote Optimization with Deep Learning Based Cloud-Intrusion Detection System

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computers, Materials & Continua 2023年第2期74卷 4319-4336页

作者： Abdullah M.Basahel Mohammad Yamin Sulafah M.Basahel E.Laxmi Lydia Faculty of Economics and Administration King Abdulaziz UniversityJeddahSaudi Arabia E-commerce Department College of Administrative and Financial SciencesSaudi Electronic UniversityJeddahSaudi Arabia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India

Cloud Computing(CC)is the preference of all information technology(IT)organizations as it offers pay-per-use based and flexible services to its *** the privacy and security become the main hindrances in its achievement due to distributed and open architecture that is prone to *** Detection System(IDS)refers to one of the commonly utilized system for detecting attacks on *** proves to be an effective and promising technique,that identifies malicious activities and known threats by observing traffic data in computers,and warnings are given when such threatswere *** current mainstream IDS are assisted with machine learning(ML)but have issues of low detection rates and demanded wide feature *** article devises an Enhanced Coyote Optimization with Deep Learning based Intrusion Detection System for Cloud Security(ECODL-IDSCS)*** ECODL-IDSCS model initially addresses the class imbalance data problem by the use of Adaptive Synthetic(ADASYN)*** detecting and classification of intrusions,long short term memory(LSTM)model is *** addition,ECO algorithm is derived to optimally fine tune the hyperparameters related to the LSTM model to enhance its detection efficiency in the cloud *** the presented ECODL-IDSCS model is tested on benchmark dataset,the experimental results show the promising performance of the ECODL-IDSCS model over the existing IDS models.

关键词： Intrusion detection system cloud security coyote optimization algorithm class imbalance data deep learning

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Design of a Hexad-Polarization Antenna With High Isolation and Switchable Feed Network 12

Design of a Hexad-Polarization Antenna With High Isolation a...

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12th International Conference on Electrical and computer engineering, ICECE 2022

作者： Rahman, Muhammad Asad Rahman, Md. Naimur Hossain, Md. Azad Hasan, Maodudul Nishiyama, Eisuke Toyoda, Ichihiko Chittagong University of Engineering and Technology Faculty of Electrical and Computer Engineering Bangladesh Saga University Department of Electrical and Electronic Engineering Saga Japan

ISBN: (纸本)9798350398793

This article presents a multi-layer hexad-polarization compatible reconfigurable square shaped patch antenna. With an intent to use in the sub-6 GHz spectrum, the proposed antenna's polarization can be switched among horizontal linear polarization (LP), vertical LP, slant ±45° LP, right-hand circular polarization (RHCP), and left-hand CP (LHCP) by controlling PIN diodes in switchable feed network. By incorporating two orthogonal aperture-coupled switchable feed networks and a 180° phase shifter, the proposed antenna can operate at single or dual feeding mode. The horizontal and vertical LP can be attained by exciting single port. On the other hand, slant +45° LP,-45° LP, RHCP, and LHCP can be achieved by switchable dual port excitation. Low cross-polarization and high isolation in each mode make the proposed antenna more attractive for wireless applications. The proposed antenna has 10-dB impedance bandwidth of 1.19% for LP, 0.89% for LHCP, and 1.19% for RHCP. Moreover, 3-dB axial ratio (AR) bandwidth of 5.97% for RHCP and 7.19% for LHCP are attained. Better isolation characteristic ( © 2022 IEEE.

关键词： Polarization

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A comprehensive survey on 6G-security: physical connection and service layers

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Discover Internet of Things 2025年第1期5卷 1-30页

作者： Saeed, Mamoon M. Saeed, Rashid A. Hasan, Mohammad Kamrul Ali, Elmustafa Sayed Mazha, Tehseen Shahzad, Tariq Khan, Sunawar Hamam, Habib Sana00967 Yemen Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia Department of Electronics Engineering College of Electronics Engineering Sudan University of Science and Technology Omdurman Sudan Bangi43600 Malaysia Department of Electrical and Electronic Engineering Faculty of Engineering Red Sea University Port Sudan33312 Sudan School of Computer Science National College of Business Administration and Economics Lahore54000 Pakistan Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Computer Engineering COMSATS University Islamabad Sahiwal Campus Sahiwal57000 Pakistan Department of Computer Science and Software Engineering International Islamic University Islamabad44000 Pakistan School of Electrical Engineering University of Johannesburg Johannesburg2006 South Africa BP 1989 Av. Grandes Ecoles Libreville Gabon Bridges for Academic Excellence-Spectrum Tunis Tunisia Department of Computer Science School Education Department Government of Punjab Layyah31200 Pakistan Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India

After adopting 5G technology, businesses and academia have started working on sixth-generation wireless networking (6G) technologies. Mobile communications options are expected to expand in areas where previous generations could not do so. 6G networks are anticipated to be constructed using various diverse technologies. These encompass diverse cutting-edge advancements, such as distributed ledger systems like blockchain, visible light communications (VLC), post-quantum cryptography, edge computing, molecular communication, THz, and other advances. These advances necessitate a reassessment of previous security strategies from a security perspective. In the future, networks must adhere to stricter criteria for authentication, encryption, access control, connectivity, and detection of harmful activities. Ensuring privacy and dependability necessitates the implementation of supplementary security protocols. The essay explores the primary concerns and challenges related to the security of the 6G network. This paper describes the improvements in security in communications from 1G through 6G. This paper divides security in the sixth generation into three layers: physical, connection, and service. Each layer-by-layer discusses the standard technologies and security issues for each technology proposed in each sixth-generation security layer. All proposed solutions for each of the three layers are discussed in Sixth Generation Security. It also reviews all proposed solutions for each layer, indicating the proposed solution and its limitations. © The Author(s) 2025.

关键词： 5G mobile communication systems

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Road Traffic Signs Recognition in Automatic Driving under Extreme Environments 2

Road Traffic Signs Recognition in Automatic Driving under Ex...

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2022 2nd International Conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2022

作者： Chi, Juntian Feng, Zhuangzhou Zhang, Weipeng Faculty of Electronic Information Engineering South-Central Minzu University Wuhan China Faculty of Computer and Information Engineering Huali College Guangdong University of Technology Guangzhou China Faculty of Computer Science and Technology Shaanxi University of Science and Technology Xi'an China

ISBN: (纸本)9783800760268

Traffic sign recognition (TSR) in automotive driving ensures smooth driving and prevents accidents by collecting and recognizing the road traffic sign information, giving instructions or warnings, and making operations more manageable and safer. Most current traffic recognition methods are based on machine learning methods and perform well. However, Road traffic sign recognition in Automatic extreme environments needs to be further emphasized. In this paper, CNN is used to recognize road traffic signs under extreme weather conditions to help drivers deal with barriers in foggy or highlight situations. This technique provides an efficient way for drivers to identify the traffic signs in the foggy or highlight conditions, decreasing the frequency of traffic wrecks. Firstly, we adopt the methods to blur the picture, and then the processed image is used for training. A multi-layer convolution neural network learning algorithm is proposed. The results of the tests show that the average recognition rate of the algorithm for traffic signs in the natural environment is 97.1%, and the false recognition rate is less than 1%. The results of the experiments suggest that the algorithm we employed in our research works has an accurate recognition degree and can improve the recognition speed of the existing algorithms. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Traffic signs

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Remarks on Gibbs Permutation Matrices for Ternary Bent Functions 53

Remarks on Gibbs Permutation Matrices for Ternary Bent Funct...

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53rd IEEE International Symposium on Multiple-Valued Logic, ISMVL 2023

作者： Stanković, Radomir S. Stanković, Milena Moraga, Claudio Astola, Jaakko T. Mathematical Institute of Sasa Belgrade Serbia Faculty of Electronic Engineering Department of Computer Science Niš Serbia Technical University of Dortmund Faculty of Computer Science Dortmund Germany Tampere University of Technology Department of Signal Processing Tampere Finland

ISBN: (纸本)9781665464161

As in the binary case, ternary bent functions are a very small portion of the set of all ternary functions for a given number of variables. For example, for n = 2, there are 486 ternary bent functions out of 19683 ternary functions, which is 2, 47%, and this number reduces exponentially with the increase of n. However, finding, or alternatively, constructing them is a challenging task. A possible approach is based upon the manipulation of known ternary bent functions to construct other ternary bent functions. In this paper, we define Gibbs permutation matrices derived from the Gibbs derivative with respect to the Vilenkin-Chrestenson transform and propose their usage in constructing bent functions. The method can be extended to p-valued bent functions, where p is a prime larger than 3. © 2023 IEEE.

关键词： Matrix algebra

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Autonomous Pharmaceutical Care with Large Language Models

Autonomous Pharmaceutical Care with Large Language Models

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Dou, Yutao Deng, Zike Xing, Tao Xiao, Jian Peng, Shaoliang Hunan University College of Computer Science and Electronic Engineering Changsha410082 China University of Hong Kong Faculty of Engineering Department of Computer Science Hong Kong999077 Hong Kong Guilin University of Technology College of Computer Science and Engineering Guilin541006 China Central South University Xiangya Hospital Department of Pharmacy Changsha410008 China

ISBN: (纸本)9798350386226

In modern healthcare systems, physicians often diagnose and prescribe within their specific fields of expertise. However, this compartmentalized approach may not fully assess the overall health condition of patients, leading to potential risks associated with polypharmacy, such as drug-drug interactions. Consequently, pharmaceutical care becomes a critical systemic task, typically managed by clinical pharmacists. Despite their crucial role, clinical pharmacists face challenges in providing personalized medication guidance due to the vast and rapidly evolving body of medical knowledge. With the advancement of artificial intelligence and large language models (LLMs), these technologies have demonstrated significant potential in pharmaceutical care by effectively reducing medication errors and adverse drug events, and alleviating the workload of healthcare professionals. However, existing LLMs still struggle with the accurate interpretation and automated execution of tasks in complex clinical scenarios like pharmaceutical care. To address these challenges, we developed the Shennong-Agent system, a multi-agent framework for LLMs with integrated multimodal inputs. Shennong-Agent is enabled to analyze and segment tasks using chained reasoning and autonomously perform complex pharmacy care tasks using tools such as knowledge retrieval and web search. Rigorously evaluated by medical experts, this system not only surpasses existing LLMs in performance but also enhances its capabilities through reinforcement learning with human feedback. © 2024 IEEE.

关键词： Multi agent systems

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A Review on Heart Diseases Prediction Using Artificial Intelligence 1st

A Review on Heart Diseases Prediction Using Artificial Intel...

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1st International Conference on Machine Intelligence and Emerging Technologies, MIET 2022

作者： Hasnat, Rehnuma Al Mamun, Abdullah Musha, Ahmmad Tahabilder, Anik Department of Electrical and Electronic Engineering Pabna University of Science and Technology Pabna Bangladesh Faculty of Engineering and Technology Multimedia University Melaka Malaysia Department of Computer Science Wayne State University DetroitMI United States

ISBN: (纸本)9783031346217

Heart disease is one of the major concerns of this modern world. The insufficiency of the experts has made this issue a bigger concern. Diagnosing heart diseases at an early stage is possible with Artificial Intelligence (AI) techniques, which will lessen the needed number of experts. This paper has initially discussed different kinds of heart diseases and the importance of detecting them early. Two popular diagnosis systems for collecting data and their working function are then highlighted. Different types of Model architectures in the corresponding field are described. Firstly, the Support Vector Machine (SVM) machine learning algorithm is described, and secondly, popular deep learning model architecture such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), etc. are highlighted to detect heart disease. Finally, discussion, comparison, and future work are described. This article aims to clarify AI’s present and future state in medical technology to predict heart diseases. © 2023, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Diseases

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Spiral Fractal Compression in Transform Domains for Underwater Communication

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Annals of Data Science 2024年第3期11卷 1003-1030页

作者： Selim, A. Taha, Taha E. El-Fishawy, Adel S. Zahran, O. Hadhoud, M.M. Dessouky, M.I. El-Samie, Fathi E. Abd El-Hag, Noha ERTU Cairo Egypt Department of Information Technology Faculty of Computers and Information Menoufia University Shebeen El-Kom32511 Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Al mahalla Al kubra Algarbia31951 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh11671 Saudi Arabia

This paper presents a simplified fractal image compression algorithm, which is implemented on a block-by-block basis. This algorithm achieves a Compression Ratio (CR) of up to 10 with a Peak Signal-to-Noise Ratio (PSNR) as high as 35 dB. Hence, it is very appropriate for the new applications of underwater communication. The idea of the proposed algorithm is based on the segmentation of the image, first, into blocks to setup reference blocks. The image is then decomposed again into block ranges, and a search process is carried out to find the reference blocks with the best match. The transmitted or stored values, after compression, are the reference block values and the indices of the reference block that achieves the best match. If there is no match, the average value of the block range is transmitted or stored instead. The effect of the spiral architecture instead of square block decomposition is studied. A comparison between different algorithms, including the conventional square search, the proposed simplified fractal compression algorithm and the standard JPEG compression algorithm, is introduced. We applied the types of fractal compression on a video sequence. In addition, the effect of using the fractal image compression algorithms in transform domain is investigated. The image is transferred firstly to a transform domain. The Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are used. After transformation takes place, the fractal algorithm is applied. A comparison between three fractal algorithms, namely conventional square, spiral, and simplified fractal compression, is presented. The comparison is repeated in the two cases of transformation. The DWT is used also in this paper to increase the CR of the block domain pool. We decompose the block domain by wavelet decomposition to two levels. This process gives a CR for block domain transmission as high as 16. The advantage of the proposed implementation is the simplicity of computation. We f

关键词： Discrete wavelet transforms

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