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computers, Materials & Continua 2023年第3期74卷 6119-6143页

作者： Chen Wei-wei He Wei Zhu Hai-long Zhou Guo-hui Mu Quan-qi Han Peng College of computer science and information Engineering Harbin Normal UniversityHarbin150500China Rocket Force University of Engineering Xi’an710025China

The prediction of processor performance has important referencesignificance for future processors. Both the accuracy and rationality of theprediction results are required. The hierarchical belief rule base (HBRB)can initially provide a solution to low prediction accuracy. However, theinterpretability of the model and the traceability of the results still warrantfurther investigation. Therefore, a processor performance prediction methodbased on interpretable hierarchical belief rule base (HBRB-I) and globalsensitivity analysis (GSA) is proposed. The method can yield more reliableprediction results. Evidence reasoning (ER) is firstly used to evaluate thehistorical data of the processor, followed by a performance prediction modelwith interpretability constraints that is constructed based on HBRB-I. Then,the whale optimization algorithm (WOA) is used to optimize the ***, to test the interpretability of the performance predictionprocess, GSA is used to analyze the relationship between the input and thepredicted output indicators. Finally, based on the UCI database processordataset, the effectiveness and superiority of the method are verified. Accordingto our experiments, our prediction method generates more reliable andaccurate estimations than traditional models.

关键词： Hierarchical belief rule base(HBRB) evidence reasoning(ER) interpretability global sensitivity analysis(GSA) whale optimization algorithm(WOA)

FINE:Future Internet iNnovation Environment

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China Communications 2015年第1期12卷 146-147页

作者： BI Jun Institute for Network sciences and Cyberspace Tsinghua University Department of computer science Tsinghua University Tsinghua National Laboratory for information science and Technology(TNList)

This article introduces FINE(Future Internet iNnovation Environment) project,which is supported by National High-tech R&D Program( "863" Program) of China.

关键词：互联网环境创新

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Interpolation-tuned salient region detection

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science China(information sciences) 2014年第1期57卷 51-59页

作者： LIU Yang LI XueQing WANG Lei NIU YuZhen School of computer science and Technology Shandong University Department of computer science and Technology Weifang College

Image salient region detection is very useful in many multimedia applications,such as image retrieval,adaptive content delivery,and adaptive *** existing methods are based on centersurround diferences,usually detecting the diferences around region boundaries,so these methods emphasize the high-contrast edges instead of detecting the *** from traditional methods,our method smoothly propagates salient region information to the whole image by performing color interpolation and produces such saliency maps that uniformly highlight the whole salient regions and have high contrast between salient regions and *** compare our method with five state-of-the-art salient region detection methods on a large public data *** proposed method not only generates visually reasonable results but also achieves higher precision and better recall rates.

关键词： salient region detection color interpolation high contrast uniformly highlight

Scale-free brain ensemble modulated by phase synchronization

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Journal of Zhejiang University-science C(computers and Electronics) 2014年第10期15卷 821-831页

作者： Dan WU Chao-yi LI Jie LIU Jing LU De-zhong YAO Department of Biomedical Engineering School of Computer and Information TechnologyBeijing Jiaotong University Neuroinformation of Ministry of Education University of Electronic Science and Technology of China

To listen to brain activity as a piece of music, we proposed the scale-free brainwave music(SFBM) technology, which could translate the scalp electroencephalogram(EEG) into music notes according to the power law of both EEG and music. In the current study, this methodology was further extended to a musical ensemble of two channels. First, EEG data from two selected channels are translated into musical instrument digital interface(MIDI) sequences, where the EEG parameters modulate the pitch, duration, and volume of each musical note. The phase synchronization index of the two channels is computed by a Hilbert transform. Then the two MIDI sequences are integrated into a chorus according to the phase synchronization index. The EEG with a high synchronization index is represented by more consonant musical intervals, while the low index is expressed by inconsonant musical intervals. The brain ensemble derived from real EEG segments illustrates differences in harmony and pitch distribution during the eyes-closed and eyes-open states. Furthermore, the scale-free phenomena exist in the brainwave ensemble. Therefore, the scale-free brain ensemble modulated by phase synchronization is a new attempt to express the EEG through an auditory and musical way, and it can be used for EEG monitoring and bio-feedback.

关键词： Brainwave Ensemble Music Scale-free Synchronization

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Interference Mitigation in D2D Communication Underlying Cellular Networks:Towards Green Energy

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computers, Materials & Continua 2021年第7期68卷 45-58页

作者： Rana Zeeshan Ahamad Abdul Rehman Javed Shakir Mehmood Mohammad Zubair Khan Abdulfattah Noorwali Muhammad Rizwan Department of computer science Xian Jiaotong UniversityXi’anChina Department of Cyber Security Air UniversityIslamabadPakistan Department of information and Technology Northwest UniversityXianChina Department of computer science College of Computer Science and EngineeringTaibah UniversityMadinahSaudi Arabia Department of Electrical Engineering Umm Al-Qura UniversityMakkahSaudi Arabia Department of computer science Kinnaird College for WomenLahore54000Pakistan

Device to Device(D2D)communication is emerging as a new participant promising technology in 5G cellular networks to promote green energy networks.D2D communication can improve communication delays,spectral efficiency,system capacity,data off-loading,and many other fruitful scenarios where D2D can be ***,induction of D2D communication in reuse mode with the conventional cellular network can cause severe interference issues,which can significantly degrade network *** reap all the benefits of induction of D2D communication with conventional cellular communication,it is imperative to minimize interference’s detrimental *** power control can minimize the negative effects of interference and get benefits promised by D2D *** this work,we propose two power control schemes,Power Control Scheme 1(PCS 1)and Power Control Scheme 2(PCS 2),to minimize the interference and provide performance *** results observe improvements with PCS 1 and PCS 2 as compared to without using any power control scheme in terms of data rate in both uplink and downlink communication modes of Cellular User Equipment(CUE).

关键词： Interference mitigation green IoT green networks D2D power control spectral efficiency reuse mode

Automatic Heart Disease Detection by Classification of Ventricular Arrhythmias on ECG Using Machine Learning

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computers, Materials & Continua 2022年第4期71卷 17-33页

作者： Khalid Mahmood Aamir Muhammad Ramzan Saima Skinadar Hikmat Ullah Khan Usman Tariq Hyunsoo Lee Yunyoung Nam Muhammad Attique Khan Department of computer science and information Technology University of SargodhaSargodha40100Pakistan School of systems and Technology University of Management and TechnologyLahore54782Pakistan COMSAT University Islamabad Wah CampusWah CanttPakistan College of computer Engineering and sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea Department of computer science HITEC University TaxilaPakistan

This paper focuses on detecting diseased signals and arrhythmias classification into two classes:ventricular tachycardia and premature ventricular *** sole purpose of the signal detection is used to determine if a signal has been collected from a healthy or sick *** proposed research approach presents a mathematical model for the signal detector based on calculating the instantaneous frequency(IF).Once a signal taken from a patient is detected,then the classifier takes that signal as input and classifies the target disease by predicting the class *** applying the classifier,templates are designed separately for ventricular tachycardia and premature ventricular *** of a given signal with both the templates are computed in the spectral *** empirical analysis reveals precisions for the detector and the applied classifier are 100%and 77.27%,***,instantaneous frequency analysis provides a benchmark that IF of a normal signal ranges from 0.8 to 1.1 Hz whereas IF range for ventricular tachycardia and premature ventricular contraction is 0.08–0.6 *** indicates a serious loss of high-frequency contents in the spectrum,implying that the heart’s overall activity is slowed *** study may help medical practitioners in detecting the heart disease type based on signal analysis.

关键词： Heart disease signals preprocessing detection machine learning

A Fused Machine Learning Approach for Intrusion Detection System

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computers, Materials & Continua 2023年第2期74卷 2607-2623页

作者： Muhammad Sajid Farooq Sagheer Abbas Atta-ur-Rahman Kiran Sultan Muhammad Adnan Khan Amir Mosavi School of computer science National College of Business Administration and EconomicsLahore54000Pakistan Department of computer science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam 31441Saudi Arabia Department of CIT The Applied CollegeKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Software Gachon UniversitySeongnam13120Korea John von Neumann faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia faculty of Civil Engineering TU-DresdenDresden01062Germany

The rapid growth in data generation and increased use of computer network devices has amplified the infrastructures of *** interconnectivity of networks has brought various complexities in maintaining network availability,consistency,and *** learning based intrusion detection systems have become essential to monitor network traffic for malicious and illicit *** intrusion detection system controls the flow of network traffic with the help of computer *** deep learning algorithms in intrusion detection systems have played a prominent role in identifying and analyzing intrusions in network *** this purpose,when the network traffic encounters known or unknown intrusions in the network,a machine-learning framework is needed to identify and/or verify network *** Intrusion detection scheme empowered with a fused machine learning technique(IDS-FMLT)is proposed to detect intrusion in a heterogeneous network that consists of different source networks and to protect the network from malicious *** proposed IDS-FMLT system model obtained 95.18%validation accuracy and a 4.82%miss rate in intrusion detection.

关键词： Fused machine learning heterogeneous network intrusion detection

Indoor Electromagnetic Radiation Intensity Relationship to Total Energy of Household Appliances

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computers, Materials & Continua 2022年第3期70卷 5421-5435页

作者： Murad A.A.Almekhlafi Lamia Osman Widaa Fahd N.Al-Wesabi Mohammad Alamgeer Anwer Mustafa Hilal Manar Ahmed Hamza Abu Sarwar Zamani Mohammed Rizwanullah Department of Electrical Engineering–Communication Engineering Sana’a UniversityYemen Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of computer science King Khalid UniversityMuhayel AseerSaudi Arabia&Faculty of Computer and ITSana’a UniversitySana’aYemen Department of information systems King Khalid UniversityMayahel AseerKSA Department of computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The rapid technological developments in the modern era have led to increased electrical equipment in our daily lives,work,and *** this standpoint,the main objective of this study is to evaluate the potential relationship between the intensity of electromagnetic radiation and the total energy of household appliances in the living environment within the building by measuring and analyzing the strength of the electric field and the entire electromagnetic radiation flux density of electrical devices operating at frequencies(5 Hz to 1 kHz).The living room was chosen as a center for measurement at 15 homes in three different environmental regions(urban,suburbs,and open areas).The three measurement methods are(Mode 1:people in a sitting position with electrical appliances *** 2:People in a standing position with electrical appliances *** 3:People are in the upright positionwhile turning off the electrical devices)in the living *** measurement methods and their results reinforce the importance of this *** results showed that the average electric field strengthmeasured inMode 2 ismuch greater than the two methods,and we also found less electromagnetic radiation in Mode 3 than in the two *** results remain within the recommended overall exposure developed by the International Committee for the Prevention of Non-Ionizing Radiation and the International Electrotechnical Commission.

关键词： Exposure assessment electromagnetic field household appliances indoor various environments epidemiology

Motion Enhanced Model Based on High-Level Spatial Features

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computers, Materials & Continua 2022年第12期73卷 5911-5924页

作者： Yang Wu Lei Guo Xiaodong Dai Bin Zhang Dong-Won Park Ming Ma College of computer science and Engineering Inner Mongolia UniversityHohhot010021China Department of information and Communications PaiChai UniversityDaejeon35345Korea

Action recognition has become a current research hotspot in computer *** to other deep learning methods,Two-stream convolutional network structure achieves better performance in action recognition,which divides the network into spatial and temporal streams,using video frame images as well as dense optical streams in the network,respectively,to obtain the category ***,the two-stream network has some drawbacks,i.e.,using dense optical flow as the input of the temporal stream,which is computationally expensive and extremely time-consuming for the current extraction algorithm and cannot meet the requirements of real-time *** this paper,instead of the dense optical flow,the Motion Vectors(MVs)are used and extracted from the compressed domain as temporal features,which greatly reduces the extraction ***,the motion pattern that MVs contain is coarser,which leads to low *** this paper,we propose two strategies to improve the accuracy:firstly,an accumulated strategy is used to enhance the motion information and continuity of MVs;secondly,knowledge distillation is used to fuse the spatial information into the temporal stream so that more information(e.g.,motion details,colors,etc.)is *** results show that the accuracy of MV can be greatly improved by the strategies proposed in this paper and the final recognition for human actions accuracy is guaranteed without using optical flow.

关键词： Action recognition motion vectors two-stream knowledge distillation accumulate strategy

Application of Moore-Penrose Inverse in Deciding the Minimal Martingale Measure

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Acta Mathematicae Applicatae Sinica 2010年第4期26卷 653-660页

作者： Luo-gen Yao Gang Yang Xiang-qun Yang information Department of Hunan Business College Changsha 410205China College of Mathematics and computer science Hunan Normal UniversityChangsha 410081China

The Moore-Penrose inverse is an important tool in *** paper shows that the MoorePenrose inverse is also an effcient technique in determining the minimal martingale measure if a security price follows a semi-martingale which satisfies some structure *** extend a result of Dzhaparidze and Spreij concerning the Moore-Penrose inverse to the case that the Moore-Penrose inverse of any matrix-valued predictable process is still ***,we obtain an explicit formula of the minimal martingale measure by employing the Moore-Penrose ***,the minimal martingale measure in a generalized Black-Scholes model is found.

关键词： Moore-Penrose inverse minimal martingale measure semi-martingales structure condition

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