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Survivability Modeling and Analysis of Mobile Ad Hoc Network with Correlated Node Behavior

Procedia Engineering 2013年 53卷 435-440页

作者： A.H. Azni Rabiah Ahmad ZulAzriMohamad Noh Center for Advanced Computing Technology (C-ACT) Faculty of Information Technology and Communication University Technical Malaysia Melaka

This paper present a new survivability model based on correlated node behavior to study the global survivability of mobile ad hoc networks. The model uses k-correlated survivability model for correlated node behavior of mobile ad hoc networks which is an extended version of k-connectivity of individual node model. The k-correlated survivability model takes correlated degree to measure node correlation as a new function of survivability. The study evaluates the impact of correlated node behavior particularly selfish, malicious and fails nodes toward network resilience and survivability. The results show that correlated node behaviors have more adverse effects on the survivability.

关键词： Survivability Correlated node behavior Mobile ad hoc network

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Opinion Mining of Movie Review using Hybrid Method of Support Vector Machine and Particle Swarm Optimization

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Procedia Engineering 2013年 53卷 453-462页

作者： Abd. Samad Hasan Basari Burairah Hussin I. Gede Pramudya Ananta Junta Zeniarja Centre for Advanced Computing Technology (C-ACT) Faculty of Information and Communication Technology Universiti Teknikal Malaysia Melaka (UTeM) Hang TuahJaya 76100 Durian Tunggal Malacca Malaysia Faculty of Information and Communication Technology University ofDian Nuswantoro Semarang Indonesia

Nowadays, online social media is online discourse where people contribute to create content, share it, bookmark it, and network at an impressive rate. The faster message and ease of use in social media today is Twitter. The messages on Twitter include reviews and opinions on certain topics such as movie, book, product, politic, and so on. Based on this condition, this research attempts to use the messages of twitter to review a movie by using opinion mining or sentiment analysis. Opinion mining refers to the application of natural language processing, computational linguistics, and text mining to identify or classify whether the movie is good or not based on message opinion. Support Vector Machine (SVM) is supervised learning methods that analyze data and recognize the patterns that are used for classification. This research concerns on binary classification which is classified into two classes. Those classes are positive and negative. The positive class shows good message opinion; otherwise the negative class shows the bad message opinion of certain movies. This justification is based on the accuracy level of SVM with the validation process uses 10-Fold cross validation and confusion matrix. The hybrid Partical Swarm Optimization (PSO) is used to improve the election of best parameter in order to solve the dual optimization problem. The result shows the improvement of accuracy level from 71.87% to 77%.

关键词： Opinion Opinion mining Sentiment Sentiment analysis SVM SVM-PSO

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SOCIFS feature selection framework for handwritten authorship

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International Journal of Hybrid Intelligent Systems 2013年第2期10卷 83-91页

作者： Pratama, Satrya Fajri Muda, Azah Kamilah Choo, Yun-Huoy Muda, Noor Azilah Center of Advanced Computing and Technologies Faculty of Information and Communication Technology University Teknikal Malaysia Melaka Durian Tunggal Melaka Malaysia

The uniqueness of shape and style of handwriting can be used to identify the significant features in confirming the author of writing. This paper is meant to propose a novel feature selection framework for Swarm Optimized and Computationally Inexpensive Floating Selection (SOCIFS), by exploring existing feature selection frameworks, and compare the performance of proposed feature selection framework against various feature selection methods in Writer Identification in order to find the most significant features. The promising applicability of the proposed framework has been demonstrated in the result and worth to receive further exploration in identifying the handwritten authorship.

关键词： Computationally inexpensive feature selection framework particle swarm optimization significant features writer identification

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Classification Simulation of RazakSAT Satellite

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Procedia Engineering 2013年 53卷 472-482页

作者： Asmala Ahmad Center of Advanced Computing Technologies (C-ACT) Faculty of Information and Communication Technology Universiti Teknikal Malaysia Melaka (UTeM) Hang Tuah Jaya Melaka Malaysia

This study presents simulation of land cover classification for RazakSAT satellite. The simulation makes use of the spectral capability of Landsat 5 TM satellite that has overlapping bands with RazakSAT. The classification is performed using Maximum Likelihood (ML), a supervised classification method that is based on the Bayes theorem. ML makes use of a discriminant function to assign pixel to the class with the highest likelihood. Class mean vector and covariance matrix are the key inputs to the function and are estimated from the training pixels of a particular class. The accuracy of the classification for the simulated RazakSAT data is accessed by means of a confusion matrix. The results show that RazakSAT tends to have lower overall and individual class accuracies than Landsat mainly due to the unavailability of mid-infrared bands that hinders separation between different plant types.

关键词： RazakSAT Maximum Likelihood Accuracy

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Immune ant swarm optimization for optimum rough reducts generation

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International Journal of Hybrid Intelligent Systems 2013年第3期10卷 93-105页

作者： Pratiwi, Lustiana Choo, Yun-Huoy Muda, Azah Kamilah Muda, Noor Azilah Computational Intelligence and Technologies Research Group Center of Advanced Computing and Technologies Faculty of Information and Communication Technology Universiti Teknikal Malaysia Melaka Durian Tunggal Melaka Malaysia

Ant Swarm Optimization refers to the hybridization of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms to enhance optimization performance. It is used in rough reducts calculation for identifying optimally significant attributes set. This paper proposes a hybrid ant swarm optimization algorithm by using immunity to discover better fitness value in optimizing rough reducts set. By integrating PSO with ACO, it will enhance the ability of PSO when updating its local search upon quality solution as the number of generations is increased. Unlike the conventional PSO/ACO algorithm, proposed Immune ant swarm algorithm aims to preserve global search convergence of PSO when reaching the optimum especially under the high dimension situation of optimization with small population size. By combining PSO with ACO algorithms and embedding immune approach, the approach is expected to be able to generate better optimal rough reducts, where PSO algorithm performs the global exploration which can effectively reach the optimal or near optimal solution to increase fitness value as compared to the past research in optimization of attribute reduction. This research is also to enhance the optimization ability by defining a suitable fitness function with immunity process to increase the competency in attribute reduction and has shown improvement of the classification accuracy with its generated reducts in solving NP-Hard problem. The proposed algorithm has shown promising experimental results in obtaining optimal reducts when tested on 12 common benchmark datasets. Result for rough reducts and fitness value performance has been discussed and briefly explored in order to identify the best solution. The experimental analysis on the initial results of IASORR has been proven to offer a better quality algorithm and to maintain PSO's performance, which are also encouraging in t-test analysis, for most of the tested datasets.

关键词： Rough reducts particle swarm optimization ant colony optimization immunity ant swarm optimization

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10 GHz Microstrip Spanar Antennas: An Experimental Analysis

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Journal of Physics: Conference Series 2014年第1期495卷

作者： Mohd Azlishah Othman Hazwani Azman Mohd Nor Husain Mohamad Zoinol Abidin Abd Aziz Yahaya Abd Rahim Ahmad Nairn Che Pee Mohamad Radzi Motsidi Mohd Fairuz Iskandar Othman Mohd Azlishah bin Othman Microwave Research Group Centre for Telecommunication Research and Innovation (CeTRI) Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia Communication Multimedia Network and Systems Reseach Group Centre of Advanced Computing Technology Faculty of Information Technology and Multimedia Communication Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia

This paper presents Spanar Antenna designed using CST Microwave Studio Simulation 2011. The proposed antenna was designed to operate at 10 GHz, which suggested return loss, S11 must be less than -10 dB and voltage standing wave ratio (VSWR) must be less than 2. The best performance of simulation of Spanar Antenna was obtained at a small size of 24.8 mm × 8.0 mm with dimension board of FR4 substrate 31.7 mm × 18.5 mm. The thickness (h) and dielectric constant (εr) of substrate were 1.6 mm and 4.7. An analysis between simulation result and measurement result has been compared in order to see the antenna performance.

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An Alternative to SOCIFS Writer Identification Framework for Handwritten Authorship

An Alternative to SOCIFS Writer Identification Framework for...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Satrya Fajri Pratama Azah Kamilah Muda Ajith Abraham Noor Azilah Muda Computational Intelligence and Technologies (CIT) Research Group Center of Advanced Computing and Technologies Faculty of Information and Communication Technology Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysi

ISBN: (纸本)9781479906505

The uniqueness of shape and style of handwriting can be used to identify the significant features in confirming the author of writing. Acquiring these significant features leads to an important research in Writer Identification (WI) domain. This paper is meant to explore the usage of improved discretization method and explore an alternative to Cheap Computational Cost Class-Specific Swarm Sequential Selection (C4S4) WI framework for Swarm Optimized and Computationally Inexpensive Floating Selection (SOCIFS) feature selection technique in order to find the unique significant features. This paper proposes a novel feature selection framework for handwritten authorship. The promising applicability of the proposed framework has been demonstrated and worth to receive further exploration in identifying the handwritten authorship.

关键词： computationally inexpensive feature selection significant features writer identification handwritten authorship Feature extraction Authorship Writers Frameworks Alarm devices Handwriting dike swarms

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Study of [Formula: see text] and [Formula: see text] production in [Formula: see text] collisions at [Formula: see text] and search for anomalous quartic gauge couplings with the ATLAS experiment

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The European physical journal. C, Particles and fields 2017年第9期77卷 646页

作者： M Aaboud G Aad B Abbott O Abdinov B Abeloos S H Abidi O S AbouZeid N L Abraham H Abramowicz H Abreu R Abreu Y Abulaiti B S Acharya S Adachi L Adamczyk J Adelman M Adersberger T Adye A A Affolder T Agatonovic-Jovin C Agheorghiesei J A Aguilar-Saavedra S P Ahlen F Ahmadov G Aielli S Akatsuka H Akerstedt T P A Åkesson E Akilli A V Akimov G L Alberghi J Albert P Albicocco M J Alconada Verzini S C Alderweireldt M Aleksa I N Aleksandrov C Alexa G Alexander T Alexopoulos M Alhroob B Ali M Aliev G Alimonti J Alison S P Alkire B M M Allbrooke B W Allen P P Allport A Aloisio A Alonso F Alonso C Alpigiani A A Alshehri M I Alstaty B Alvarez Gonzalez D Álvarez Piqueras M G Alviggi B T Amadio Y Amaral Coutinho C Amelung D Amidei S P Amor Dos Santos S Amoroso G Amundsen C Anastopoulos L S Ancu N Andari T Andeen C F Anders J K Anders K J Anderson A Andreazza V Andrei S Angelidakis I Angelozzi A Angerami A V Anisenkov N Anjos A Annovi C Antel M Antonelli A Antonov D J Antrim F Anulli M Aoki L Aperio Bella G Arabidze Y Arai J P Araque V Araujo Ferraz A T H Arce R E Ardell F A Arduh J-F Arguin S Argyropoulos M Arik A J Armbruster L J Armitage O Arnaez H Arnold M Arratia O Arslan A Artamonov G Artoni S Artz S Asai N Asbah A Ashkenazi L Asquith K Assamagan R Astalos M Atkinson N B Atlay K Augsten G Avolio B Axen M K Ayoub G Azuelos A E Baas M J Baca H Bachacou K Bachas M Backes M Backhaus P Bagnaia M Bahmani H Bahrasemani J T Baines M Bajic O K Baker E M Baldin P Balek F Balli W K Balunas E Banas A Bandyopadhyay Sw Banerjee A A E Bannoura L Barak E L Barberio D Barberis M Barbero T Barillari M-S Barisits J T Barkeloo T Barklow N Barlow S L Barnes B M Barnett R M Barnett Z Barnovska-Blenessy A Baroncelli G Barone A J Barr L Barranco Navarro F Barreiro J Barreiro Guimarães da Costa R Bartoldus A E Barton P Bartos A Basalaev A Bassalat R L Bates S J Batista J R Batley M Battaglia M Bauce F Bauer H S Bawa J B Beacham M D Beattie T Beau P H Beauchemin P Bechtle H P Beck H C Beck K Becker M Becker M Beckingham C Becot A J Beddall A Beddall Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco. CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France. Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK USA. Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan. LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France. Department of Physics University of Toronto Toronto ON Canada. Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz CA USA. Department of Physics and Astronomy University of Sussex Brighton UK. Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel. Department of Physics Technion: Israel Institute of Technology Haifa Israel. Center for High Energy Physics University of Oregon Eugene OR USA. Department of Physics Stockholm University Stockholm Sweden. The Oskar Klein Centre Stockholm Sweden. INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy. ICTP Trieste Italy. International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan. Faculty of Physics and Applied Computer Science AGH University of Science and Technology Kraków Poland. Department of Physics Northern Illinois University DeKalb IL USA. Fakultät für Physik Ludwig-Maximilians-Universität München Munich Germany. Particle Physics Department Rutherford Appleton Laboratory Didcot UK. Institute of Physics University of Belgrade Belgrade Serbia. Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania. Laboratório de Instrumentação e Física Experimental de Partículas-LIP Lisbon Portugal. Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada Spain. Department of Physics Boston University Boston MA USA. Joint Institute for Nuclear Research JINR Dubna Dubna Russia. INFN Sezione di Roma Tor Vergata Rome Italy. Dipartimento di Fisica Università di Roma

This paper presents a study of and triboson production using events from proton-proton collisions at a centre-of-mass energy of recorded with the ATLAS detector at the LHC and corresponding to an integrated luminosity of 20.2 fb . The production cross-section is determined using a final state containing an electron, a muon, a photon, and neutrinos ( ). Upper limits on the production cross-section of the final state and the and final states containing an electron or a muon, two jets, a photon, and a neutrino ( or ) are also derived. The results are compared to the cross-sections predicted by the Standard Model at next-to-leading order in the strong-coupling constant. In addition, upper limits on the production cross-sections are derived in a fiducial region optimised for a search for new physics beyond the Standard Model. The results are interpreted in the context of anomalous quartic gauge couplings using an effective field theory. Confidence intervals at 95% confidence level are derived for the 14 coupling coefficients to which and production are sensitive.

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Using game engine for 3D terrain visualisation of GIS data: A review

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IOP Conference Series: Earth and Environmental Science 2014年第1期20卷

作者： Ruzinoor Che Mat Abdul Rashid Mohammed Shariff Abdul Nasir Zulkifli Mohd Shafry Mohd Rahim Mohd Hafiz Mahayudin School of Multimedia Technology and Communication Universiti Utara Malaysia 06010 UUM Sintok Kedah Malaysia To whom any correspondence should be addressed Geospatial Information Science Research Centre (GIS RC) Universiti Putra Malaysia 43400 Serdang Selangor Malaysia Faculty of Computing Universiti Teknologi Malaysia 81310 UTM Skudai Johor Malaysia

This paper reviews on the 3D terrain visualisation of GIS data using game engines that are available in the market as well as open source. 3D terrain visualisation is a technique used to visualise terrain information from GIS data such as a digital elevation model (DEM), triangular irregular network (TIN) and contour. Much research has been conducted to transform the 2D view of map to 3D. There are several terrain visualisation softwares that are available for free, which include Cesium, Hftool and Landserf. This review paper will help interested users to better understand the current state of art in 3D terrain visualisation of GIS data using game engines.

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Prediction of the lithium-ion cell performance via concentration profile simulation

Prediction of the lithium-ion cell performance via concentra...

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2012 International Conference in Green and Ubiquitous technology, GUT 2012

作者： Yusof, Norzihani Basari, Abd. Samad Hasan Ibrahim, Nuzulha Khilwani Centre for Advanced Computing Technology Faculty of Information and Communication Technology UTeM Hang Tuah Jaya 76100 Durian Tunggal Malacca Malaysia

ISBN: (纸本)9781457721724

This paper presents the lithium-ion concentration profile simulation in the cathode for the half cell to predict the performance of the lithium-ion cell. By utilizing the mathematical model from the identified theoretical principles, the lithium-ion cell system in the solution phase is used to describe the discharge behavior of the rechargeable cell based on the simulated concentration profile. For this work, the cathode is the positive electrode employing LiMn2O4 as the active material. In addition, the numerical technique namely Finite Difference Method is used to solve the material balances equation of lithium-ion cell. This method is compared to other methods to identify the concentration profile. Nevertheless, the solutions in this paper merely focus on the concentration profile of lithium-ion in the cathode under galvanostatic discharge in the half cell. © 2012 IEEE.

关键词： Finite difference method

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