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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Wu, Ruixuan Shi, Yuliang Yuan, Haitao Bi, Jing Zhang, Jia Beijing University of Technology Faculty of Information Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Lyle School of Engineering Southern Methodist University Dept. of Computer Science DallasTX United States

ISBN: (纸本)9798350337020

Mobile devices (MDs) cannot fully run all computation/delay-sensitive tasks due to their limited computing resources. Mobile edge computing (MEC) meets the demand by providing massive resources for MDs and offloading task partitions to MEC servers. However, task offloading also brings communication delay and energy consumption. Therefore, it is challenging to associate resource-constrained MDs with appropriate MEC servers to minimize power consumption. To address this problem, a constrained mixed integer nonlinear program is formulated to optimize the total energy consumption of the system including MDs and MEC servers. To solve this problem, this work designs an improved meta-heuristic optimization algorithm called Self-adaptive and Multi-population Differential Annealed Optimization (SMDAO). Experimental results demonstrate that compared with its two state-of-the-art peers, the proposed SMDAO yields the best solution with the smallest total energy consumption in the least time. © 2023 IEEE.

关键词： computation offloading energy optimization Mobile edge computing multi-population optimization simulated annealing

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Network Anomaly Detection with Stacked Sparse Shrink Autoencoders and Improved XGBoost

Network Anomaly Detection with Stacked Sparse Shrink Autoenc...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Bi, Jing Guan, Ziyue Yuan, Haitao Zhang, Jia Beijing University of Technology Faculty of Information Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Southern Methodist University Dept. of Computer Science Lyle School of Engineering DallasTX United States

ISBN: (纸本)9798350337020

Efficient and accurate identification of network anomalies is of great significance to the construction of network security systems in the information age. It is highly challenging to accurately detect abnormal behaviors in the increasing network data. Currently, classification methods based on feature extraction of autoencoders have been proven to be suitable for network anomaly detection. However, traditional detection models with autoencoders have poor detection accuracy in the face of massive network features. In addition, the hyperparameter optimization of their models cannot be effectively solved. For network anomaly detection, this work proposes a new network anomaly detection method named SAXP, which integrates Stacked sparse shrink Autoencoders and a XGBoost model based on genetic simulated annealing Particle swarm optimization (GSPSO). Specifically, features extracted by stacked sparse shrink autoencoders are introduced into the XG Boost model for classification, and GSPSO is used to optimize the hyperparameters of XGBoost. Experimental results based on two real-life data sets demonstrate that the proposed SAXP achieves higher recognition accuracy than several state-of-the-art algorithms. © 2023 IEEE.

关键词： autoencoders feature extraction Network anomaly detection particle swarm optimization XGBoost

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Web Traffic Anomaly Detection Using a Hybrid Spatio-temporal Neural Network

Web Traffic Anomaly Detection Using a Hybrid Spatio-temporal...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Bi, Jing Xu, Lifeng Yuan, Haitao Zhang, Jia Beijing University of Technology Faculty of Information Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China School of Engineering Dept. of Computer Science in Lyle Southern Methodist University DallasTX United States

ISBN: (纸本)9798350337020

Nowadays, rapid development of Internet has brought a sharp increase in traffic data. Abnormal traffic haS serious impact on network security. Traffic anomaly detection can be achieved by extracting characteristics of network traffic to detect anomalous intrusions, and therefore, anomaly detection algorithms are of great significance to maintenance of network security. This work proposes a hybrid spatio-temporal neural network with attention named CTGA to effectively identify anomalous traffic. CTGA combines a Convolutional neural network (CNN), a Temporal convolutional network (TCN), a bidirectional Gated recurrent unit network (BiGRU), and a self-Attention mechanism. It automatically extracts temporal and spatial features of sequences from raw data by sliding window preprocessing followed by CNN, TCN, BiGRU, and the self-attention mechanism to detect anomalous data. CNN is used to extract spatial features of time sequences and reduce the loss of spatial information. In the sequence, TCN obtains short-term features. Long-term dependencies in the data are captured by BiGRU, and the self-attention mechanism obtains important information in the sequence. Finally, experiments with the real-life Yahoo S5 dataset prove that CTGA outperforms other approaches substantially. © 2023 IEEE.

关键词： Anomaly detection bidirectional gated recurrent unit convolutional neural network self-attention temporal convolutional network

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Accurate Prediction of Workloads and Resources with Multi-Head Attention and Hybrid LSTM for Cloud Data Centers

Accurate Prediction of Workloads and Resources with Multi-He...

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作者： Bi, Jing Ma, Haisen Yuan, Haitao Zhang, Jia Beijing University of Technology School of Software Engineering Faculty of Information Technology Beijing100124 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Southern Methodist University Department of Computer Science Lyle School of Engineering DallasTX75205 United States

Currently, cloud computing service providers face big challenges in predicting large-scale workload and resource usage time series. Due to the difficulty in capturing nonlinear features, traditional forecasting methods usually fail to achieve high prediction performance for resource usage and workload sequences. Besides, there is much noise in original time series of resources and workloads. If these time series are not de-noised by smoothing algorithms, the prediction results can fail to meet the providers' requirements. To do so, this work proposes a hybrid prediction model named VAMBiG that integrates Variational mode decomposition, an Adaptive Savitzky-Golay (SG) filter, a Multi-head attention mechanism, Bidirectional and Grid versions of Long and Short Term Memory (LSTM) networks. VAMBiG adopts a signal decomposition method named variational mode decomposition to decompose complex and non-linear original time series into low-frequency intrinsic mode functions. Then, it adopts an adaptive SG filter as a data pre-processing tool to eliminate noise and extreme points in such functions. Afterwards, it adopts bidirectional and grid LSTM networks to capture bidirectional features and dimension ones, respectively. Finally, it adopts a multi-head attention mechanism to explore importance of different data dimensions. VAMBiG aims to predict resource usage and workloads in highly variable traces in clouds. Extensive experimental results demonstrate that it achieves higher-Accuracy prediction than several advanced prediction approaches with datasets from Google and Alibaba cluster traces. © 2016 IEEE.

关键词： Time series analysis

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Energy efficient indoor localisation for narrowband internet of things

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1150-1163页

作者： Ismail Keshta Mukesh Soni Mohammed Wasim Bhatt Azeem Irshad Ali Rizwan Shakir Khan Renato RMaaliw III Arsalan Muhammad Soomar Mohammad Shabaz Computer Science and Information Systems Department College of Applied SciencesAlMaarefa UniversityRiyadhSaudi Arabia Department of CSE University Centre for Research and Development Chandigarh UniversityMohaliPunjabIndia Department of Computer Science and Engineering National Institute of TechnologySrinagarIndia Asghar Mall College Rawalpindi Higher Education Department(HED)Govt.of the PunjabRawalpindiPakistan Department of Industrial Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddahSaudi Arabia College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)RiyadhSaudi Arabia College of Engineering Southern Luzon State UniversityLucbanQuezonPhilippines Department of Automation Electronics and Electrical EngineeringGdansk University of TechnologyGdańskPoland Arba Minch University Arba MinchEthiopia

There are an increasing number of Narrow Band IoT devices being manufactured as the technology behind them develops *** high co‐channel interference and signal attenuation seen in edge Narrow Band IoT devices make it challenging to guarantee the service quality of these *** maximise the data rate fairness of Narrow Band IoT devices,a multi‐dimensional indoor localisation model is devised,consisting of transmission power,data scheduling,and time slot scheduling,based on a network model that employs non‐orthogonal multiple access via a *** on this network model,the optimisation goal of Narrow Band IoT device data rate ratio fairness is first established by the authors,while taking into account the Narrow Band IoT network:The multidimensional indoor localisation optimisation model of equipment tends to minimize data rate,energy constraints and EH relay energy and data buffer constraints,data scheduling and time slot *** a result,each Narrow Band IoT device's data rate needs are met while the network's overall performance is *** investigate the model's potential for convex optimisation and offer an algorithm for optimising the distribution of multiple resources using the KKT *** current work primarily considers the NOMA Narrow Band IoT network under a single EH ***,the growth of Narrow Band IoT devices also leads to a rise in co‐channel interference,which impacts NOMA's performance *** simulation,the proposed approach is successfully *** improvements have boosted the network's energy efficiency by 44.1%,data rate proportional fairness by 11.9%,and spectrum efficiency by 55.4%.

关键词： artificial inteligence detection of moving objects internet of things

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Next-generation pediatric care:nanotechnology-based and AI-driven solutions for cardiovascular,respiratory,and gastrointestinal disorders

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World Journal of Pediatrics 2025年第1期21卷 8-28页

作者： Waldenice de Alencar Morais Lima Jackson G.de Souza Fátima García-Villén Julia Lira Loureiro Fernanda Nervo Raffin Marcelo A.C.Fernandes Eliana B.Souto Patricia Severino Raquel de M.Barbosa Laboratory of Galenic Pharmacy Department of PharmacyFederal University of Rio Grande Do NorteNatal 59012-570Brazil InovAI Lab nPITI/IMDFederal University of Rio Grande Do NorteNatalRN 59078-970Brazil Department of Pharmacy and Pharmaceutical Technology School of PharmacyUniversity of GranadaCampus of Cartuja18071 GranadaSpain Department of Computer Engineering and Automation Federal University of Rio Grande Do NorteNatalRN 59078-970Brazil Laboratory of Pharmaceutical Technology Faculty of PharmacyUniversity of PortoRua Jorge de Viterbo Ferreira2284050-313 PortoPortugal Industrial Biotechnology Program University of Tiradentes(UNIT)AracajuSergipe 49032-490Brazil Department of Pharmacy and Pharmaceutical Technology School of PharmacyUniversity of SevilleC/Professor García González241012 SevilleSpain

Background Global pediatric healthcare reveals significant morbidity and mortality rates linked to respiratory,cardiac,and gastrointestinal disorders in children and newborns,mostly due to the complexity of therapeutic management in pediatrics and neonatology,owing to the lack of suitable dosage forms for these patients,often rendering them“therapeutic orphans”.The development and application of pediatric drug formulations encounter numerous challenges,including physiological heterogeneity within age groups,limited profitability for the pharmaceutical industry,and ethical and clinical *** drugs are used unlicensed or off-label,posing a high risk of toxicity and reduced *** these circumstances,some regulatory changes are being performed,thus thrusting research innovation in this *** sources Up-to-date peer-reviewed journal articles,books,government and institutional reports,data repositories and databases were used as main data *** Among the main strategies proposed to address the current pediatric care situation,nanotechnology is specially promising for pediatric respiratory diseases since they offer a non-invasive,versatile,tunable,site-specific drug *** engineering is in the spotlight as strategy to address pediatric cardiac diseases,together with theragnostic *** integration of nanotechnology and theragnostic stands poised to refine and propel nanomedicine approaches,ushering in an era of innovative and personalized drug delivery for pediatric ***,the intersection of drug repurposing and artificial intelligence tools in pediatric healthcare holds great *** promises not only to enhance efficiency in drug development in general,but also in the pediatric field,hopefully boosting clinical trials for this *** Despite the long road ahead,the deepening of nanotechnology,the evolution of tissue engineering,and the combination of traditional techniques with artificia

关键词： Artificial intelligence Conventional therapy Nanotechnology Pediatrics Theragnostics

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Internet of Things Protocols (IoTp) Literature Review 7

Internet of Things Protocols (IoTp) Literature Review

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7th International Conference on Future Networks and Distributed Systems, ICFNDS 2023

作者： Alamery, Ali Shehab, Mohanad Abd Mahmood, Omar Abdulkareem Hammadi, Yousif I Aziz, Ahmed Muthanna, Mohammed Saleh Ali Balad Al-hadeth Group Company Baghdad Iraq Department Of Medical Instruments Engineering Techniques Bilad Alrafidain University College Diyala Iraq Electrical Engineering Department College Of Engineering Mustansiriyah University Baghdad Iraq Department Of Computer Science Faculty Of Computer And Artificial Intelligence Benha University Egypt Department Of International Business Management Tashkent State University Of Economics Tashkent Uzbekistan Department Of Communications Engineering College Of Engineering University Of Diyala Diyala Iraq Institute Of Computer Technologies And Information Security Southern Federal University Taganrog347922 Russia

ISBN: (纸本)9798400709036

Considering today's variety of technologies and devices connected to the network, a huge number of manufacturers, there are many problems of their interaction and the need to create and adopt specialized communication standards and protocols. This article is devoted to the description of various protocols proposed by the IEEE, IETF and ITU for use in the framework of the concept of the Internet of Things. The article includes a description of the protocols of the application, transport, network and data link layers of the TCP / IP model. It also discusses protocols designed specifically to meet IoT requirements. A brief description of the protocols and the principle of operation of each of them are given. This review article contributes to a more correct choice of protocols when building a network, detecting and managing devices, and establishing interaction between objects of the Internet of Things. © 2023 ACM.

关键词： Internet of things

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Virtual Laboratory Work for Studying the Spectrum of Radio Signals

Virtual Laboratory Work for Studying the Spectrum of Radio S...

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2022 International Conference on Actual Problems of Electron Devices engineering, APEDE 2022

作者： Gubsky, Dmitry S. Daineko, Yevgeniya A. Kleschenkov, Anatoly B. Ipalakova, Madina T. Aitmagambetov, Altai Z. Southern Federal University Computer Modeling and Applied Electrodynamics Department Rostov-on-Don Russia International It University International and Scientific Affairs Dept. Almaty Kazakhstan Southern Federal University Faculty of Physics Rostov-on-Don Russia International It University Computer Engineering and Information Security Dept. Almaty Kazakhstan International It University Electronics and Telecommunications Department Almaty Kazakhstan

computer models of spectrum analyzer and signal modulators have been created.. These models are included in the virtual laboratory. A laboratory work has been created to study the spectrum of modulated radio signals. ... 详细信息

ISBN: (数字)9781665406130

ISBN: (纸本)9781665406123

关键词： Spectrum analyzers

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automation 5.0: The Key to Systems Intelligence and Industry 5.0

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

automation has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： automation machinery intelligence

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Finite element investigation of disk transducers from porous piezoceramics of complex structure with cymbal end-caps in external medium

Finite element investigation of disk transducers from porous...

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International Seminar Day on Diffraction

作者： Andrey V. Nasedkin Anna A. Nasedkina Mohamed E. Nassar Institute of Mathematics Mechanics and Computer Science Southern Federal University Russia Faculty of Electronic Engineering Menoufia University Menouf Egypt

The paper considers two main applications of the transducers in the form of a piezoelectric disk with two metal plate end-caps, which are usually called cymbal transducers. The first variant of the cymbal transducer is an energy harvesting device. Here, the cymbal transducer is located inside the asphalt pavement and generates electric fields under low-frequency oscillatory mechanical action on the pavement. The second version of the transducer is located in a liquid medium and, under the electrical influence oscillating at the first resonant frequency, generates acoustic waves. For both cases, we investigate the efficiency of transducers for four types of piezoceramic materials: solid piezoceramics, conventional porous piezoceramics, and porous piezoceramics with thin and thick layers of metallization of the pore surfaces. The studies were carried out numerically using the finite element method in the ANSYS package. The calculation results showed that the use of porous piezoceramics or porous piezoceramics without or with metallized pore surfaces can increase the efficiency of electromechanical transformations compared to dense ones. Moreover, the fact whether the transducer is excited by the electric potential difference or by the electric current plays a significant role for actuator applications.

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