Search results for: Data stream analysis.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13652

Search results for: Data stream analysis.

11192 An Energy Aware Data Aggregation in Wireless Sensor Network Using Connected Dominant Set

Authors: M. Santhalakshmi, P Suganthi

Abstract:

Wireless Sensor Networks (WSNs) have many advantages. Their deployment is easier and faster than wired sensor networks or other wireless networks, as they do not need fixed infrastructure. Nodes are partitioned into many small groups named clusters to aggregate data through network organization. WSN clustering guarantees performance achievement of sensor nodes. Sensor nodes energy consumption is reduced by eliminating redundant energy use and balancing energy sensor nodes use over a network. The aim of such clustering protocols is to prolong network life. Low Energy Adaptive Clustering Hierarchy (LEACH) is a popular protocol in WSN. LEACH is a clustering protocol in which the random rotations of local cluster heads are utilized in order to distribute energy load among all sensor nodes in the network. This paper proposes Connected Dominant Set (CDS) based cluster formation. CDS aggregates data in a promising approach for reducing routing overhead since messages are transmitted only within virtual backbone by means of CDS and also data aggregating lowers the ratio of responding hosts to the hosts existing in virtual backbones. CDS tries to increase networks lifetime considering such parameters as sensors lifetime, remaining and consumption energies in order to have an almost optimal data aggregation within networks. Experimental results proved CDS outperformed LEACH regarding number of cluster formations, average packet loss rate, average end to end delay, life computation, and remaining energy computation.

Keywords: Wireless sensor network, connected dominant set, clustering, data aggregation.

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11191 A Proposal on the Educational Transactional Analysis as a Dialogical Vision of Culture: Conceptual Signposts and Practical Tools for Educators

Authors: Marina Sartor Hoffer

Abstract:

The multicultural composition of today's societies poses new challenges to educational contexts. Schools are therefore called first to develop dialogic aptitudes and communicative skills adapted to the complex reality of post-modern societies. It is indispensable for educators and for young people to learn theoretical and practical tools during their scholastic path, in order to allow the knowledge of themselves and of the others with the aim of recognizing the value of the others regardless of their culture. Dialogic Skills help to understand and manage individual differences by allowing the solution of problems and preventing conflicts. The Educational Sector of Eric Berne’s Transactional Analysis offers a range of methods and techniques for this purpose. Educational Transactional Analysis is firmly anchored in the Personalist Philosophy and deserves to be promoted as a theoretical frame suitable to face the challenges of contemporary education. The goal of this paper is therefore to outline some conceptual and methodological signposts for the education to dialogue by drawing concepts and methodologies from educational transactional analysis.

Keywords: Dialogic process, education to dialogue, educational transactional analysis, personalism, the good of the relationship.

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11190 Mediating Role of Social Responsibility on the Relationship between Consumer Awareness of Green Marketing and Purchase Intentions

Authors: Norazah Mohd Suki, Norbayah Mohd Suki

Abstract:

This research aims to examine the influence of mediating effect of corporate social responsibility on the relationship between consumer awareness of green marketing and purchase intentions in the retail setting. Data from 200 valid questionnaires was analyzed using the partial least squares (PLS) approach for the analysis of structural equation models with SmartPLS computer program version 2.0 as research data does not necessarily have a multivariate normal distribution and is less sensitive to sample size than other covariance approaches. PLS results revealed that corporate social responsibility partially mediated the link between consumer awareness of green marketing and purchase intentions of the product in the retail setting. Marketing managers should allocate a sufficient portion of their budget to appropriate corporate social responsibility activities by engaging in voluntary programs for positive return on investment leading to increased business profitability and long run business sustainability. The outcomes of the mediating effects of corporate social responsibility add a new impetus to the growing literature and preceding discoveries on consumer green marketing awareness, which is inadequately researched in the Malaysian setting. Direction for future research is also presented.

Keywords: Green marketing awareness, corporate social responsibility, partial least squares, purchase intention.

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11189 Deadline Missing Prediction for Mobile Robots through the Use of Historical Data

Authors: Edwaldo R. B. Monteiro, Patricia D. M. Plentz, Edson R. De Pieri

Abstract:

Mobile robotics is gaining an increasingly important role in modern society. Several potentially dangerous or laborious tasks for human are assigned to mobile robots, which are increasingly capable. Many of these tasks need to be performed within a specified period, i.e, meet a deadline. Missing the deadline can result in financial and/or material losses. Mechanisms for predicting the missing of deadlines are fundamental because corrective actions can be taken to avoid or minimize the losses resulting from missing the deadline. In this work we propose a simple but reliable deadline missing prediction mechanism for mobile robots through the use of historical data and we use the Pioneer 3-DX robot for experiments and simulations, one of the most popular robots in academia.

Keywords: Deadline missing, historical data, mobile robots, prediction mechanism.

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11188 Speeding up Nonlinear Time History Analysis of Base-Isolated Structures Using a Nonlinear Exponential Model

Authors: Nicolò Vaiana, Giorgio Serino

Abstract:

The nonlinear time history analysis of seismically base-isolated structures can require a significant computational effort when the behavior of each seismic isolator is predicted by adopting the widely used differential equation Bouc-Wen model. In this paper, a nonlinear exponential model, able to simulate the response of seismic isolation bearings within a relatively large displacements range, is described and adopted in order to reduce the numerical computations and speed up the nonlinear dynamic analysis. Compared to the Bouc-Wen model, the proposed one does not require the numerical solution of a nonlinear differential equation for each time step of the analysis. The seismic response of a 3d base-isolated structure with a lead rubber bearing system subjected to harmonic earthquake excitation is simulated by modeling each isolator using the proposed analytical model. The comparison of the numerical results and computational time with those obtained by modeling the lead rubber bearings using the Bouc-Wen model demonstrates the good accuracy of the proposed model and its capability to reduce significantly the computational effort of the analysis.

Keywords: Base isolation, computational efficiency, nonlinear exponential model, nonlinear time history analysis.

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11187 Analysis of Dynamic Loads Induced by Spectator Movements in Stadium

Authors: Gee-Cheol Kim, Sang-Hoon Lee, Joo-Won Kang

Abstract:

In the stadium structure, the significant dynamic responses such as resonance or similar behavior can be occurred by spectator rhythmical activities. Thus, accurate analysis and precise investigation of stadium structure that is subjected to dynamic loads are required for practical design and serviceability check of stadium structures. Moreover, it is desirable to measure and analyze the dynamic loads of spectator activities because these dynamic loads can not be easily expressed in numerical formula. In this study, various dynamic loads induced by spectator movements are measured and analyzed. These dynamic loads induced by spectators movement of stadium structure can be classified into the impact load and the periodic load. These dynamic loads can be expressed as Fourier harmonic load. And, these dynamic loads could be applied for the accurate vibration analysis of a stadium structure.

Keywords: stadium structure, spectator rhythmical activities, vibration analysis.

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11186 Molecular Characterization of Free Radicals Decomposing Genes on Plant Developmental Stages

Authors: R. Haddad, K. Morris, V. Buchanan-Wollaston

Abstract:

Biochemical and molecular analysis of some antioxidant enzyme genes revealed different level of gene expression on oilseed (Brassica napus). For molecular and biochemical analysis, leaf tissues were harvested from plants at eight different developmental stages, from young to senescence. The levels of total protein and chlorophyll were increased during maturity stages of plant, while these were decreased during the last stages of plant growth. Structural analysis (nucleotide and deduced amino acid sequence, and phylogenic tree) of a complementary DNA revealed a high level of similarity for a family of Catalase genes. The expression of the gene encoded by different Catalase isoforms was assessed during different plant growth phase. No significant difference between samples was observed, when Catalase activity was statistically analyzed at different developmental stages. EST analysis exhibited different transcripts levels for a number of other relevant antioxidant genes (different isoforms of SOD and glutathione). The high level of transcription of these genes at senescence stages was indicated that these genes are senescenceinduced genes.

Keywords: Biochemical analysis, Oilseed, Expression pattern, Growth phases

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11185 Statistical Analysis of First Order Plus Dead-time System using Operational Matrix

Authors: Pham Luu Trung Duong, Moonyong Lee

Abstract:

To increase precision and reliability of automatic control systems, we have to take into account of random factors affecting the control system. Thus, operational matrix technique is used for statistical analysis of first order plus time delay system with uniform random parameter. Examples with deterministic and stochastic disturbance are considered to demonstrate the validity of the method. Comparison with Monte Carlo method is made to show the computational effectiveness of the method.

Keywords: First order plus dead-time, Operational matrix, Statistical analysis, Walsh function.

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11184 Ensemble Approach for Predicting Student's Academic Performance

Authors: L. A. Muhammad, M. S. Argungu

Abstract:

Educational data mining (EDM) has recorded substantial considerations. Techniques of data mining in one way or the other have been proposed to dig out out-of-sight knowledge in educational data. The result of the study got assists academic institutions in further enhancing their process of learning and methods of passing knowledge to students. Consequently, the performance of students boasts and the educational products are by no doubt enhanced. This study adopted a student performance prediction model premised on techniques of data mining with Students' Essential Features (SEF). SEF are linked to the learner's interactivity with the e-learning management system. The performance of the student's predictive model is assessed by a set of classifiers, viz. Bayes Network, Logistic Regression, and Reduce Error Pruning Tree (REP). Consequently, ensemble methods of Bagging, Boosting, and Random Forest (RF) are applied to improve the performance of these single classifiers. The study reveals that the result shows a robust affinity between learners' behaviors and their academic attainment. Result from the study shows that the REP Tree and its ensemble record the highest accuracy of 83.33% using SEF. Hence, in terms of the Receiver Operating Curve (ROC), boosting method of REP Tree records 0.903, which is the best. This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, bagging, Random Forest, boosting, data mining, classifiers, machine learning.

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11183 Differences in Goal Scoring and Passing Sequences between Winning and Losing Team in UEFA-EURO Championship 2012

Authors: Muhamad S., Norasrudin S, Rahmat A.

Abstract:

The objective of current study is to investigate the differences of winning and losing teams in terms of goal scoring and passing sequences. Total of 31 matches from UEFA-EURO 2012 were analyzed and 5 matches were excluded from analysis due to matches end up drawn. There are two groups of variable used in the study which is; i. the goal scoring variable and: ii. passing sequences variable. Data were analyzed using Wilcoxon matched pair rank test with significant value set at p < 0.05. Current study found the timing of goal scored was significantly higher for winning team at 1st half (Z=-3.416, p=.001) and 2nd half (Z=-3.252, p=.001). The scoring frequency was also found to be increase as time progressed and the last 15 minutes of the game was the time interval the most goals scored. The indicators that were significantly differences between winning and losing team were the goal scored (Z=-4.578, p=.000), the head (Z=-2.500, p=.012), the right foot (Z=-3.788,p=.000), corner (Z=-.2.126,p=.033), open play (Z=-3.744,p=.000), inside the penalty box (Z=-4.174, p=.000) , attackers (Z=-2.976, p=.003) and also the midfielders (Z=-3.400, p=.001). Regarding the passing sequences, there are significance difference between both teams in short passing sequences (Z=-.4.141, p=.000). While for the long passing, there were no significance difference (Z=-.1.795, p=.073). The data gathered in present study can be used by the coaches to construct detailed training program based on their objectives.

Keywords: Football, goals scored, passing, timing.

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11182 Language Learning, Drives, and Context: A Grounded Theory of Learning Behavior

Authors: Julian Pigott

Abstract:

This paper presents the Language Learning as a Means of Drive Engagement (LLMDE) theory, derived from a grounded theory analysis of interviews with Japanese university students. According to LLMDE theory, language learning can be understood as a means of engaging one or more of four self-fulfillment drives: the drive to expand one’s horizons (perspective drive); the drive to make a success of oneself (status drive); the drive to engage in interaction with others (communication drive); and the drive to obtain intellectual and affective stimulation (entertainment drive). While many theories of learner psychology focus on conscious agency, LLMDE theory addresses the role of the unconscious. In addition, supplementary thematic analysis of the data revealed the role of context in mediating drive engagement. Unexpected memorable events, for example, play a key role in instigating and, indirectly, in regulating learning, as do institutional and cultural contexts. Given the apparent importance of such factors beyond the immediate control of the learner, and given the pervasive role of habit and drives, it is argued that the concept of motivation merits theoretical reappraisal. Rather than an underlying force determining language learning success or failure, it can be understood to emerge sporadically in consciousness to promote behavioral change, or to protect habitual behavior from disruption.

Keywords: Drives, grounded theory, motivation, significant events.

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11181 A User - Requirements Approach in Medical Devices Maintenance System Development: A Case Study from an Industry Perspective

Authors: Manar AlJazzazi, Mohammed Rawashdeh, Tariq Alshawaheen, Aktham Malkawi

Abstract:

This paper is a part of research, in which the way the biomedical engineers follow in their work is analyzed. The goal of this paper is to present a method for specification of user requirements in the medical devices maintenance process. Data Gathering Methods, Research Model Phases and Descriptive Analysis is presented. These technology and verification rules can be implemented in Medical devices maintenance management process to the maintenance process.

Keywords: Quality Function Deployment (QFD), User - requirements approach.

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11180 A Method for Evaluating the Mechanical Stress on Mandibular Advancement Devices

Authors: Tsung-yin Lin, Yi-yu Lee, Ching-hua Hung

Abstract:

This study focuses on the stress analysis of Mandibular Advancement Devices (MADs), which are considered as a standard treatment of snoring that promoted by American Academy of Sleep Medicine (AASM). Snoring is the most significant feature of sleep-disordered breathing (SDB). SDB will lead to serious problems in human health. Oral appliances are ensured in therapeutic effect and compliance, especially the MADs. This paper proposes a new MAD design, and the finite element analysis (FEA) is introduced to precede the stress simulation for this MAD.

Keywords: Finite element analysis, mandibular advancement devices, mechanical stress, snoring.

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11179 Detecting Email Forgery using Random Forests and Naïve Bayes Classifiers

Authors: Emad E Abdallah, A.F. Otoom, ArwaSaqer, Ola Abu-Aisheh, Diana Omari, Ghadeer Salem

Abstract:

As emails communications have no consistent authentication procedure to ensure the authenticity, we present an investigation analysis approach for detecting forged emails based on Random Forests and Naïve Bays classifiers. Instead of investigating the email headers, we use the body content to extract a unique writing style for all the possible suspects. Our approach consists of four main steps: (1) The cybercrime investigator extract different effective features including structural, lexical, linguistic, and syntactic evidence from previous emails for all the possible suspects, (2) The extracted features vectors are normalized to increase the accuracy rate. (3) The normalized features are then used to train the learning engine, (4) upon receiving the anonymous email (M); we apply the feature extraction process to produce a feature vector. Finally, using the machine learning classifiers the email is assigned to one of the suspects- whose writing style closely matches M. Experimental results on real data sets show the improved performance of the proposed method and the ability of identifying the authors with a very limited number of features.

Keywords: Digital investigation, cybercrimes, emails forensics, anonymous emails, writing style, and authorship analysis

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11178 Resilient Machine Learning in the Nuclear Industry: Crack Detection as a Case Study

Authors: Anita Khadka, Gregory Epiphaniou, Carsten Maple

Abstract:

There is a dramatic surge in the adoption of Machine Learning (ML) techniques in many areas, including the nuclear industry (such as fault diagnosis and fuel management in nuclear power plants), autonomous systems (including self-driving vehicles), space systems (space debris recovery, for example), medical surgery, network intrusion detection, malware detection, to name a few. Artificial Intelligence (AI) has become a part of everyday modern human life. To date, the predominant focus has been developing underpinning ML algorithms that can improve accuracy, while factors such as resiliency and robustness of algorithms have been largely overlooked. If an adversarial attack is able to compromise the learning method or data, the consequences can be fatal, especially but not exclusively in safety-critical applications. In this paper, we present an in-depth analysis of five adversarial attacks and two defence methods on a crack detection ML model. Our analysis shows that it can be dangerous to adopt ML techniques without rigorous testing, since they may be vulnerable to adversarial attacks, especially in security-critical areas such as the nuclear industry. We observed that while the adopted defence methods can effectively defend against different attacks, none of them could protect against all five adversarial attacks entirely.

Keywords: Resilient Machine Learning, attacks, defences, nuclear industry, crack detection.

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11177 Reliability Based Optimal Design of Laterally Loaded Pile with Limited Residual Strain Energy Capacity

Authors: M. Movahedi Rad

Abstract:

In this study, a general approach to the reliability based limit analysis of laterally loaded piles is presented. In engineering practice the uncertainties play a very important role. The aim of this study is to evaluate the lateral load capacity of free-head and fixed-head long pile when plastic limit analysis is considered. In addition to the plastic limit analysis to control the plastic behaviour of the structure, uncertain bound on the complementary strain energy of the residual forces is also applied. This bound has significant effect for the load parameter. The solution to reliability-based problems is obtained by a computer program which is governed by the reliability index calculation.

Keywords: Reliability, laterally loaded pile, residual strain energy, probability, limit analysis.

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11176 A Survey on Facial Feature Points Detection Techniques and Approaches

Authors: Rachid Ahdid, Khaddouj Taifi, Said Safi, Bouzid Manaut

Abstract:

Automatic detection of facial feature points plays an important role in applications such as facial feature tracking, human-machine interaction and face recognition. The majority of facial feature points detection methods using two-dimensional or three-dimensional data are covered in existing survey papers. In this article chosen approaches to the facial features detection have been gathered and described. This overview focuses on the class of researches exploiting facial feature points detection to represent facial surface for two-dimensional or three-dimensional face. In the conclusion, we discusses advantages and disadvantages of the presented algorithms.

Keywords: Facial feature points, face recognition, facial feature tracking, two-dimensional data, three-dimensional data.

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11175 Outdoor Anomaly Detection with a Spectroscopic Line Detector

Authors: O. J. G. Somsen

Abstract:

One of the tasks of optical surveillance is to detect anomalies in large amounts of image data. However, if the size of the anomaly is very small, limited information is available to distinguish it from the surrounding environment. Spectral detection provides a useful source of additional information and may help to detect anomalies with a size of a few pixels or less. Unfortunately, spectral cameras are expensive because of the difficulty of separating two spatial in addition to one spectral dimension. We investigate the possibility of modifying a simple spectral line detector for outdoor detection. This may be especially useful if the area of interest forms a line, such as the horizon. We use a monochrome CCD that also enables detection into the near infrared. A simple camera is attached to the setup to determine which part of the environment is spectrally imaged. Our preliminary results indicate that sensitive detection of very small targets is indeed possible. Spectra could be taken from the various targets by averaging columns in the line image. By imaging a set of lines of various widths we found narrow lines that could not be seen in the color image but remained visible in the spectral line image. A simultaneous analysis of the entire spectra can produce better results than visual inspection of the line spectral image. We are presently developing calibration targets for spatial and spectral focusing and alignment with the spatial camera. This will present improved results and more use in outdoor application.

Keywords: Anomaly detection, spectroscopic line imaging, image analysis.

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11174 Comparison of Phylogenetic Trees of Multiple Protein Sequence Alignment Methods

Authors: Khaddouja Boujenfa, Nadia Essoussi, Mohamed Limam

Abstract:

Multiple sequence alignment is a fundamental part in many bioinformatics applications such as phylogenetic analysis. Many alignment methods have been proposed. Each method gives a different result for the same data set, and consequently generates a different phylogenetic tree. Hence, the chosen alignment method affects the resulting tree. However in the literature, there is no evaluation of multiple alignment methods based on the comparison of their phylogenetic trees. This work evaluates the following eight aligners: ClustalX, T-Coffee, SAGA, MUSCLE, MAFFT, DIALIGN, ProbCons and Align-m, based on their phylogenetic trees (test trees) produced on a given data set. The Neighbor-Joining method is used to estimate trees. Three criteria, namely, the dNNI, the dRF and the Id_Tree are established to test the ability of different alignment methods to produce closer test tree compared to the reference one (true tree). Results show that the method which produces the most accurate alignment gives the nearest test tree to the reference tree. MUSCLE outperforms all aligners with respect to the three criteria and for all datasets, performing particularly better when sequence identities are within 10-20%. It is followed by T-Coffee at lower sequence identity (<10%), Align-m at 20-30% identity, and ClustalX and ProbCons at 30-50% identity. Also, it is noticed that when sequence identities are higher (>30%), trees scores of all methods become similar.

Keywords: Multiple alignment methods, phylogenetic trees, Neighbor-Joining method, Robinson-Foulds distance.

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11173 Comprehensive Studies on Mechanical Stress Analysis of Functionally Graded Plates

Authors: Kyung-Su Na, Ji-Hwan Kim

Abstract:

Stress analysis of functionally graded composite plates composed of ceramic, functionally graded material and metal layers is investigated using 3-D finite element method. In FGM layer, material properties are assumed to be varied continuously in the thickness direction according to a simple power law distribution in terms of the volume fraction of a ceramic and metal. The 3-D finite element model is adopted by using an 18-node solid element to analyze more accurately the variation of material properties in the thickness direction. Numerical results are compared for three types of materials. In the analysis, the tensile and the compressive stresses are summarized for various FGM thickness ratios, volume fraction distributions, geometric parameters and mechanical loads.

Keywords: Functionally graded materials, Stress analysis, 3-D finite element method

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11172 Landslide Susceptibility Mapping: A Comparison between Logistic Regression and Multivariate Adaptive Regression Spline Models in the Municipality of Oudka, Northern of Morocco

Authors: S. Benchelha, H. C. Aoudjehane, M. Hakdaoui, R. El Hamdouni, H. Mansouri, T. Benchelha, M. Layelmam, M. Alaoui

Abstract:

The logistic regression (LR) and multivariate adaptive regression spline (MarSpline) are applied and verified for analysis of landslide susceptibility map in Oudka, Morocco, using geographical information system. From spatial database containing data such as landslide mapping, topography, soil, hydrology and lithology, the eight factors related to landslides such as elevation, slope, aspect, distance to streams, distance to road, distance to faults, lithology map and Normalized Difference Vegetation Index (NDVI) were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by the two mentioned methods. Before the calculation, this database was divided into two parts, the first for the formation of the model and the second for the validation. The results of the landslide susceptibility analysis were verified using success and prediction rates to evaluate the quality of these probabilistic models. The result of this verification was that the MarSpline model is the best model with a success rate (AUC = 0.963) and a prediction rate (AUC = 0.951) higher than the LR model (success rate AUC = 0.918, rate prediction AUC = 0.901).

Keywords: Landslide susceptibility mapping, regression logistic, multivariate adaptive regression spline, Oudka, Taounate, Morocco.

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11171 New Approach to Spectral Analysis of High Bit Rate PCM Signals

Authors: J. P. Dubois

Abstract:

Pulse code modulation is a widespread technique in digital communication with significant impact on existing modern and proposed future communication technologies. Its widespread utilization is due to its simplicity and attractive spectral characteristics. In this paper, we present a new approach to the spectral analysis of PCM signals using Riemann-Stieltjes integrals, which is very accurate for high bit rates. This approach can serve as a model for similar spectral analysis of other competing modulation schemes.

Keywords: Coding, discrete Fourier, power spectral density, pulse code modulation, Riemann-Stieltjes integrals.

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11170 Unified Method to Block Pornographic Images in Websites

Authors: Sakthi Priya Balaji R., Vijayendar G.

Abstract:

This paper proposes a technique to block adult images displayed in websites. The filter is designed so as to perform even in exceptional cases such as, where face detection is not possible or improper face visibility. This is achieved by using an alternative phase to extract the MFC (Most Frequent Color) from the Human Body regions estimated using a biometric of anthropometric distances between fixed rigidly connected body locations. The logical results generated can be protected from overriding by a firewall or intrusion, by encrypting the result in a SSH data packet.

Keywords: Face detection, characteristics extraction andclassification, Component based shape analysis and classification, open source SSH V2 protocol

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11169 Mining Network Data for Intrusion Detection through Naïve Bayesian with Clustering

Authors: Dewan Md. Farid, Nouria Harbi, Suman Ahmmed, Md. Zahidur Rahman, Chowdhury Mofizur Rahman

Abstract:

Network security attacks are the violation of information security policy that received much attention to the computational intelligence society in the last decades. Data mining has become a very useful technique for detecting network intrusions by extracting useful knowledge from large number of network data or logs. Naïve Bayesian classifier is one of the most popular data mining algorithm for classification, which provides an optimal way to predict the class of an unknown example. It has been tested that one set of probability derived from data is not good enough to have good classification rate. In this paper, we proposed a new learning algorithm for mining network logs to detect network intrusions through naïve Bayesian classifier, which first clusters the network logs into several groups based on similarity of logs, and then calculates the prior and conditional probabilities for each group of logs. For classifying a new log, the algorithm checks in which cluster the log belongs and then use that cluster-s probability set to classify the new log. We tested the performance of our proposed algorithm by employing KDD99 benchmark network intrusion detection dataset, and the experimental results proved that it improves detection rates as well as reduces false positives for different types of network intrusions.

Keywords: Clustering, detection rate, false positive, naïveBayesian classifier, network intrusion detection.

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11168 Evaluation of Model Evaluation Criterion for Software Development Effort Estimation

Authors: S. K. Pillai, M. K. Jeyakumar

Abstract:

Estimation of model parameters is necessary to predict the behavior of a system. Model parameters are estimated using optimization criteria. Most algorithms use historical data to estimate model parameters. The known target values (actual) and the output produced by the model are compared. The differences between the two form the basis to estimate the parameters. In order to compare different models developed using the same data different criteria are used. The data obtained for short scale projects are used here. We consider software effort estimation problem using radial basis function network. The accuracy comparison is made using various existing criteria for one and two predictors. Then, we propose a new criterion based on linear least squares for evaluation and compared the results of one and two predictors. We have considered another data set and evaluated prediction accuracy using the new criterion. The new criterion is easy to comprehend compared to single statistic. Although software effort estimation is considered, this method is applicable for any modeling and prediction.

Keywords: Software effort estimation, accuracy, Radial Basis Function, linear least squares.

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11167 Purity Monitor Studies in Medium Liquid Argon TPC

Authors: I. Badhrees

Abstract:

This paper is an attempt to describe some of the results that had been found through a journey of study in the field of particle physics. This study consists of two parts, one about the measurement of the cross section of the decay of the Z particle in two electrons, and the other deals with the measurement of the cross section of the multi-photon absorption process using a beam of Laser in the Liquid Argon Time Projection Chamber.

The first part of the paper concerns the results based on the analysis of a data sample containing 8120 ee candidates to reconstruct the mass of the Z particle for each event where each event has an ee pair with PT(e) > 20GeV, and η(e) < 2.5. Monte Carlo templates of the reconstructed Z particle were produced as a function of the Z mass scale. The distribution of the reconstructed Z mass in the data was compared to the Monte Carlo templates, where the total cross section is calculated to be equal to 1432pb.

The second part concerns the Liquid Argon Time Projection Chamber, LAr TPC, the results of the interaction of the UV Laser, Nd-YAG with λ= 266mm, with LAr and through the study of the multi-photon ionization process as a part of the R&D at Bern University. The main result of this study was the cross section of the process of the multi-photon ionization process of the LAr, σe = 1.24±0.10stat±0.30sys.10 -56cm4.

Keywords: ATLAS, CERN, KACST, LArTPC, Particle Physics.

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11166 Regional Aircraft Selection Using Preference Analysis for Reference Ideal Solution (PARIS)

Authors: C. Ardil

Abstract:

The paper presents a multiple criteria decision making analysis process to determine the most suitable regional aircraft type according to a set of evaluation criteria. The main purpose of this study is to use different decision making methods to determine the most suitable regional aircraft for aviation operators. In this context, the nine regional aircraft types were analyzed using multiple criteria decision making analysis methods. Preference analysis for reference ideal solution (PARIS) was used in regional aircraft selection process. The findings of the proposed model show that the ranking results of the multiple criteria decision making models are consistent with each other, and the proposed method is efficient, and the results are valid. Finally, the Embraer E195-E2 model regional aircraft is chosen as the most suitable aircraft type.

Keywords: aircraft, regional aircraft selection, multiple criteria decision making, multiple criteria decision making analysis, mean weight, entropy weight, MCDMA, PARIS

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11165 Solar Seawater Desalination Still with Seawater Preheater Using Efficient Heat Transfer Oil: Numerical Investigation and Data Verification

Authors: Ahmed N. Shmroukh, Gamal Tag Abdel-Jaber, Rashed D. Aldughpassi

Abstract:

The feasibility of improving the performance of the proposed solar still unit which operated in very hot climate is investigated numerically and verified with experimental data. This solar desalination unit with proposed auxiliary device as seawater preheating system using petrol based textherm oil was used to produce pure fresh water from seawater. The effective evaporation area of basin is about 1 m2. The unit was tested in two main operation modes which are normal and with seawater preheating system. The results showed that, there is good agreement between the theoretical data and the experimental data; this means that the numerical model can be accurately dependable for predicting the proposed solar still performance and design parameters. The results also showed that the fresh water productivity of the solar still in the modified preheating case which is higher than normal case, leads to an increase in productivity of 42%.

Keywords: Improving productivity, seawater desalination, solar stills, theoretical model.

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11164 The Necessity to Standardize Procedures of Providing Engineering Geological Data for Designing Road and Railway Tunneling Projects

Authors: Atefeh Saljooghi Khoshkar, Jafar Hassanpour

Abstract:

One of the main problems of design stage relating to many tunneling projects is the lack of an appropriate standard for the provision of engineering geological data in a predefined format. In particular, this is more reflected in highway and railroad tunnels projects in which there is a number of tunnels and different professional teams involved. In this regard, a comprehensive software needs to be designed using the accepted methods in order to help engineering geologists to prepare standard reports, which contain sufficient input data for the design stage. Regarding this necessity, an applied software has been designed using macro capabilities and Visual Basic programming language (VBA) through Microsoft Excel. In this software, all of the engineering geological input data, which are required for designing different parts of tunnels such as discontinuities properties, rock mass strength parameters, rock mass classification systems, boreability classification, the penetration rate and so forth can be calculated and reported in a standard format.

Keywords: Engineering geology, rock mass classification, rock mechanic, tunnel.

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11163 Spatial Distribution and Risk Assessment of As, Hg, Co and Cr in Kaveh Industrial City, using Geostatistic and GIS

Authors: Abbas Hani

Abstract:

The concentrations of As, Hg, Co, Cr and Cd were tested for each soil sample, and their spatial patterns were analyzed by the semivariogram approach of geostatistics and geographical information system technology. Multivariate statistic approaches (principal component analysis and cluster analysis) were used to identify heavy metal sources and their spatial pattern. Principal component analysis coupled with correlation between heavy metals showed that primary inputs of As, Hg and Cd were due to anthropogenic while, Co, and Cr were associated with pedogenic factors. Ordinary kriging was carried out to map the spatial patters of heavy metals. The high pollution sources evaluated was related with usage of urban and industrial wastewater. The results of this study helpful for risk assessment of environmental pollution for decision making for industrial adjustment and remedy soil pollution.

Keywords: Geographic Information system, Geostatistics, Kaveh, Multivariate Statistical Analysis.

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