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Proceedings of the fourth ACM international conference on Web search and data mining

作者： Wong, Tak-Lam Bing, Lidong Lam, Wai Department of Computer Science and Engineering Chinese University of Hong Kong Shatin Hong Kong Department of Systems Engineering and Engineering Management Chinese University of Hong Kong Shatin Hong Kong

ISBN: (纸本)9781450304931

We have developed a framework aiming at normalizing product attributes from Web pages collected from different Web sites without the need of labeled training examples. It can deal with pages composed of different layout format and content in an unsupervised manner. As a result, it can handle a variety of different domains with minimal effort. Our model is based on a generative probabilistic graphical model incorporated with Hidden Markov Models (HMM) considering both attribute names and attribute values to extract and normalize text fragments from Web pages in a unified manner. Dirichlet Process is employed to handle the unlimited number of attributes in a domain. An unsupervised inference method is proposed to predict the unobservable variables. We have also developed a method to automatically construct a domain ontology using the normalized product attributes which are the output of the inference on the graphical model. We have conducted extensive experiments and compared with existing works using product Web pages collected from real-world Web sites in three different domains to demonstrate the effectiveness of our framework. Copyright 2011 ACM.

关键词： Websites

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Advance Artificial Intelligence Technique for Designing Double T-Shaped Monopole Antenna

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computers, Materials & Continua 2021年第12期69卷 2983-2995页

作者： El-Sayed M.El-kenawy Hattan F.Abutarboush Ali Wagdy Mohamed Abdelhameed Ibrahim Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Electrical Engineering Department College of EngineeringTaibah UniversityMedina 42353Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza 12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Machine learning(ML)has taken the world by a tornado with its prevalent applications in automating ordinary tasks and using turbulent insights throughout scientific research and design *** is a massive area within artificial intelligence(AI)that focuses on obtaining valuable information out of data,explaining why ML has often been related to stats and data *** advanced meta-heuristic optimization algorithm is proposed in this work for the optimization problem of antenna architecture *** algorithm is designed,depending on the hybrid between the Sine Cosine Algorithm(SCA)and the Grey Wolf Optimizer(GWO),to train neural networkbased Multilayer Perceptron(MLP).The proposed optimization algorithm is a practical,versatile,and trustworthy platform to recognize the design parameters in an optimal way for an endorsement double T-shaped monopole *** proposed algorithm likewise shows a comparative and statistical analysis by different curves in addition to the ANOVA and *** offers the superiority and validation stability evaluation of the predicted results to verify the procedures’accuracy.

关键词： Antenna optimization machine learning artificial intelligence multilayer perceptron sine cosine algorithm grey wolf optimizer

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Radiation detection based heterogeneous Wireless Sensor Network

Radiation detection based heterogeneous Wireless Sensor Netw...

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1st International Conference on engineering and Technology, ICET 2012

作者： Elmagid, Amira A. A. El-Ghanam, S.M. Kamh, S.A. Ramadan, Rabie A. Al-Tabbakh, Shahinaz M. Marie, Mahmoud Physics Department Girls Collage for Art Science and Education-Ain Shams University Cairo Egypt Computer Engineering Department Faculty of Engineering Cairo University Cairo Egypt Systems and Computer Engineering Department Faculty of Engineering El-Azhar University Cairo Egypt

ISBN: (纸本)9781467348089

Sensor deployment is one of the important problems in Wireless Sensor Network (WSN). Deployment affects the coverage of the network especially in critical applications such as in radiation detection. The contributions of this paper are 1) formulating the radiation detection deployment problem in a mathematical form where optimal solutions could be obtained, 2) utilizing one of the famous heuristic algorithms such as Genetic Algorithms (GA) for large scale deployment problems, 3) due to the importance of radiation detection, the paper focus on some of the characteristics of radiation detection problem including the subareas importance and the some of the sensors characteristics such as sensors' sensing and communication, etc. and 3) introducing a GA and Fuzzy logic as a hybrid solution to the problem in order to control the GA crossover and mutation percentages. Although, the concept of the hybrid algorithm is introduced in this paper for sensor deployment, it could be used to solve many other optimization problems. Through a large set of experiments with different problem settings, the efficiency of the proposed algorithms is verified. © 2012 IEEE.

关键词： Fuzzy logic

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Stabilization With Prescribed Instant for High-Order Integrator systems

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IEEE Transactions on Cybernetics 2023年第11期53卷 7275-7284页

作者： Kuang, Jiyuan Gao, Yabin Chen, Chih-Chiang Zhang, Xiaoju Sun, Yizhuo Liu, Jianxing Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China National Cheng Kung University Department of Systems and Naval Mechatronic Engineering Tainan70101 Taiwan Harbin Institute of Technology School of Mathematics Harbin150001 China

This article develops a new controller design approach to stabilize system states onto the equilibrium at an arbitrarily selected time instant irrespective of the initial system states and parameters. By the stabilization approach, the actual convergence time (not the bound of actual convergence time) is independent of the initial value of system states. This feature differentiates our proposed prescribed-instant stability from conventional fixed, predefined, and prescribed time stability. In this work, we propose the controller design method for the prescribed-instant stability of n-order integrator systems. The proposed control is bounded and can gradually go to zero at an arbitrarily selected time instant, at which the system states reach zero simultaneously. This special stability of the controlled system is analyzed by reduction to absurdity. In simulations, an example of comparison with frequently used prescribed-time control is presented to show the difference. Moreover, the proposed stabilization method is validated by a magnetic suspension system with matched disturbances. © 2013 IEEE.

关键词： Stability criteria

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A Statistical Model for Topically Segmented Documents

A Statistical Model for Topically Segmented Documents

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14th International Conference on Discovery science

作者： Ponti, Giovanni Tagarelli, Andrea Karypis, George ENEA - Portici Research Center Italy Department of Electronics Computer and Systems Sciences University of Calabria Italy Department of Computer Science and Engineering Digital Technology Center University of Minnesota Minneapolis MN United States

ISBN: (纸本)9783642244766

Generative models for text data are based on the idea that a document can be modeled as a mixture of topics, each of which is represented as a probability distribution over the terms. Such models have traditionally assumed that a document is an indivisible unit for the generative process, which may not be appropriate to handle documents with an explicit multi-topic structure. This paper presents a generative model that exploits a given decomposition of documents in smaller text blocks which are topically cohesive (segments). A new variable is introduced to model the within-document segments: using this variable at document-level, word generation is related not only to the topics but also to the segments, while the topic latent variable is directly associated to the segments, rather than to the document as a whole. Experimental results have shown that, compared to existing generative models, our proposed model provides better perplexity of language modeling and better support for effective clustering of documents.

关键词： Probability distributions

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Analysis for jump phenomena in random response of a Duffing oscillator using continuous wavelet transform (2nd report, analysis by complex wavelet transform)

Analysis for jump phenomena in random response of a Duffing ...

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作者： Tamura, Shinji Funakoshi, Yoshifumi Kato, Yuto Department of Electronic and Control Systems Engineering Interdisciplinary Faculty of Science and Engineering Shimane University 1060 Nishikawatsu-cho Matsue-shi Shimane 690-8504 Japan

Stochastic jump phenomena in the random responses of a Duffing oscillator subjected to narrow band excitation are investigated. The stochastic jump phenomena correspond to the existence of multiple stationary responses, which differ in phase to the excitation. In our previous paper, the product of each real wavelet of response and excitation is proposed as the phase of each frequency component. But taking the moving average of the product over one period is necessary because of pulsation. In this paper, the product of the complex wavelet transform of the response and the complex conjugate of that of the excitation is used to evaluate phase of each frequency component. The central value of unstable region of the phase in the frequency response function is used as the center of the range of the principal value of the complex argument, and the value and bounds of unstable region are taken as the threshold for phase obtained from the wavelet transforms. Using this range of principal value of complex argument and thresholds, two states of the response are successfully identified, as well as the previously proposed criterion using real wavelet transform. © 2011 The Japan Society of Mechanical Engineers.

关键词： Wavelet transforms

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Pattern recognition of EEG signals during right and left motor imagery ∼ the detection of the misrecognition

Pattern recognition of EEG signals during right and left mot...

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SICE Annual Conference 2005

作者： Mori, Daiki Inoue, Katsuhiro Kumamaru, Kousuke Pfurtscheller, Gert Department of Systems Innovation and Informatics Factory of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Fukuoka Japan Department of Medical Informatics Institute of Biomedical Engineering Graz University of Technology Graz Austria

Electroencephalograph (EEG) recordings during right and left motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based bra in-computer interface (BCI) can provide a new communication channel to replace an impaired motor function. It can be used by e.g., handicap users with amyotrophic lateral sclerosis (ALS). In this study, statistical pattern recognition method based on AR model was introduced to discriminate the EEG signals recorded during right and left motor imagery. And the detection of the misrecognition was tried. Finally, the possibility of the detection of the misrecognition was confirmed. © 2005 SICE.

关键词： Electroencephalography

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The Impact of the Digital Transformation of Education on Literacy 7

The Impact of the Digital Transformation of Education on Lit...

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7th IEEE International Conference and Workshop Obuda on Electrical and Power engineering, CANDO-EPE 2024

作者： Farkas, Imre Kovari, Attila Rajcsanyi-Molnar, Monika Institute of Computer Engineering University of Dunaujvaros Department of Computer Systems and Control Technology Dunaujvaros Hungary Eszterházy Károly Catholic University Institute of Digital Technology Faculty of Computer Science Eger Hungary Obuda University Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Budapest Hungary John Von Neumann University GAMF Faculty of Engineering and Computer Science Kecskemét Hungary Institute of Social Sciences University of Dunaujvaros Department of Economics and Management Dunaujvaros Hungary

ISBN: (纸本)9798331531119

During the COVID19 epidemic, people of all ages from all walks of life around the world have become inevitably familiar with and almost dependent on the digital tools of the age and the opportunities they offer. A change had to take place very quickly that was unprecedented. This process has also affected education. During the time of the reading lock-in, there was a proliferation of digital curricular content. The second time around, online education came to the fore, thanks to less or well-functioning online platforms, and has since become part of everyday teaching. What is the effectiveness and usefulness of sharing knowledge in this way? Is literacy still needed at all? Can online and hybrid (a controlled mix of face-to-face and online) education replace the well-established contact and face-to-face education? The study show that the respondents believe that online education has had an impact on literacy and that it is perceived to have a positive impact. The results indicate that online education has a positive impact on the literacy levels of students, as it facilitates knowledge acquisition and enhances digital literacy skills. © 2024 IEEE.

关键词： digital education digital literacy digital-informatics literacy

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Learning-Based Artificial Algae Algorithm with Optimal Machine Learning Enabled Malware Detection

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computer systems science & engineering 2023年第9期46卷 3103-3119页

作者： Khaled M.Alalayah Fatma S.Alrayes Mohamed K.Nour Khadija M.Alaidarous Ibrahim M.Alwayle Heba Mohsen Ibrahim Abdulrab Ahmed Mesfer Al Duhayyim Department of Computer Science College of Science and ArtsNajran UniversitySharurahSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Computer Department Applied CollegeNajran UniversityNajran66462Saudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Malware is a‘malicious software program that performs multiple cyberattacks on the Internet,involving fraud,scams,nation-state cyberwar,and *** malicious software programs come under different classifications,namely Trojans,viruses,spyware,worms,ransomware,Rootkit,botnet malware,*** is a kind of malware that holds the victim’s data hostage by encrypting the information on the user’s computer to make it inaccessible to users and only decrypting it;then,the user pays a ransom procedure of a sum of *** prevent detection,various forms of ransomware utilize more than one mechanism in their attack flow in conjunction with Machine Learning(ML)*** study focuses on designing a Learning-Based Artificial Algae Algorithm with Optimal Machine Learning Enabled Malware Detection(LBAAA-OMLMD)approach in computer *** presented LBAAA-OMLMDmodelmainly aims to detect and classify the existence of ransomware and goodware in the *** accomplish this,the LBAAA-OMLMD model initially derives a Learning-Based Artificial Algae Algorithm based Feature Selection(LBAAA-FS)model to reduce the curse of dimensionality ***,the Flower Pollination Algorithm(FPA)with Echo State Network(ESN)Classification model is *** FPA model helps to appropriately adjust the parameters related to the ESN model to accomplish enhanced classifier *** experimental validation of the LBAAA-OMLMD model is tested using a benchmark dataset,and the outcomes are inspected in distinct *** comprehensive comparative examination demonstrated the betterment of the LBAAAOMLMD model over recent algorithms.

关键词： computer networks machine learning security malware detection feature selection ransomware

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Temperature estimation of cooking vessel content via EKF and Sliding Mode Observers in induction cooking systems

Temperature estimation of cooking vessel content via EKF and...

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作者： Boccuni, Antonio Capisani, Luca M. Del Bello, Francesco De Vito, Daniele Ferrara, Antonella Paderno, Jurij Department of Electrical Engineering University of Pavia Pavia Italy Department of Computer Engineering and Systems Science University of Pavia Pavia Italy Altran Italia Roma Italy Italy

ISBN: (纸本)9783902661937

The problem of estimating the thermal state of an induction cooking system is analyzed. The first step is to model the thermal system composed by the cooktop, the pot, and the pot content. Then, by relying on the formulated model, the aim is to design a suitable state observer, so that an estimation of the temperature of the cooking vessel content can be made online. Two kinds of observers are proposed. An Extended Kalman Filter (EKF) and a Sliding Mode Observer (SMO). A comparison of the performances which can be obtained with these two solutions is then made by relying on experimental results obtained on a real induction cooktop heating a pot containing a certain quantity of water. © 2011 IFAC.

关键词： Extended Kalman filters

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