Search results for: window data envelopment analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13620

Search results for: window data envelopment analysis

10500 Research on Reservoir Lithology Prediction Based on Residual Neural Network and Squeeze-and- Excitation Neural Network

Authors: Li Kewen, Su Zhaoxin, Wang Xingmou, Zhu Jian Bing

Abstract:

Conventional reservoir prediction methods ar not sufficient to explore the implicit relation between seismic attributes, and thus data utilization is low. In order to improve the predictive classification accuracy of reservoir lithology, this paper proposes a deep learning lithology prediction method based on ResNet (Residual Neural Network) and SENet (Squeeze-and-Excitation Neural Network). The neural network model is built and trained by using seismic attribute data and lithology data of Shengli oilfield, and the nonlinear mapping relationship between seismic attribute and lithology marker is established. The experimental results show that this method can significantly improve the classification effect of reservoir lithology, and the classification accuracy is close to 70%. This study can effectively predict the lithology of undrilled area and provide support for exploration and development.

Keywords: Convolutional neural network, lithology, prediction of reservoir lithology, seismic attributes.

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10499 Attribution Theory and Perceived Reliability of Cellphones for Teaching and Learning

Authors: Mayowa A. Sofowora, Seraphim D. Eyono Obono

Abstract:

The use of information and communication technologies such as computers, mobile phones and the Internet is becoming prevalent in today’s world; and it is facilitating access to a vast amount of data, services and applications for the improvement of people’s lives. However, this prevalence of ICTs is hampered by the problem of low income levels in developing countries to the point where people cannot timeously replace or repair their ICT devices when damaged or lost; and this problem serves as a motivation for this study whose aim is to examine the perceptions of teachers on the reliability of cellphones when used for teaching and learning purposes. The research objectives unfolding this aim are of two types: Objectives on the selection and design of theories and models, and objectives on the empirical testing of these theories and models. The first type of objectives is achieved using content analysis in an extensive literature survey: and the second type of objectives is achieved through a survey of high school teachers from the ILembe and UMgungundlovu districts in the KwaZulu-Natal province of South Africa. Data collected from this questionnaire based survey is analysed in SPSS using descriptive statistics and Pearson correlations after checking the reliability and validity of the questionnaires. The main hypothesis driving this study is that there is a relationship between the demographics and the attribution identity of teachers on one hand, and their perceptions on the reliability of cellphones on the other hand, as suggested by existing literature; except that attribution identities are considered in this study under three angles: intention, knowledge and ability, and action. The results of this study confirm that the perceptions of teachers on the reliability of cellphones for teaching and learning are affected by the school location of these teachers, and by their perceptions on learners’ cellphones usage intentions and actual use.

Keywords: Attribution, Cellphones, E-learning, Reliability

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10498 HPTLC Fingerprint Profiling of Protorhus longifolia Methanolic Leaf Extract and Qualitative Analysis of Common Biomarkers

Authors: P. S. Seboletswe, Z. Mkhize, L. M. Katata-Seru

Abstract:

Protorhus longifolia is known as a medicinal plant that has been used traditionally to treat various ailments such as hemiplegic paralysis, blood clotting related diseases, diarrhoea, heartburn, etc. The study reports a High-Performance Thin Layer Chromatography (HPTLC) fingerprint profile of Protorhus longifolia methanolic extract and its qualitative analysis of gallic acid, rutin, and quercetin. HPTLC analysis was achieved using CAMAG HPTLC system equipped with CAMAG automatic TLC sampler 4, CAMAG Automatic Developing Chamber 2 (ADC2), CAMAG visualizer 2, CAMAG Thin Layer Chromatography (TLC) scanner and visionCATS CAMAG HPTLC software. Mobile phase comprising toluene, ethyl acetate, formic acid (21:15:3) was used for qualitative analysis of gallic acid and revealed eight peaks while the mobile phase containing ethyl acetate, water, glacial acetic acid, formic acid (100:26:11:11) for qualitative analysis of rutin and quercetin revealed six peaks. HPTLC sillica gel 60 F254 glass plates (10 × 10) were used as the stationary phase. Gallic acid was detected at the Rf = 0.35; while rutin and quercetin were not evident in the extract. Further studies will be performed to quantify gallic acid in Protorhus longifolia leaves and also identify other biomarkers.

Keywords: Biomarkers, fingerprint profiling, gallic acid, HPTLC, Protorhus longifolia.

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10497 A TIPSO-SVM Expert System for Efficient Classification of TSTO Surrogates

Authors: Ali Sarosh, Dong Yun-Feng, Muhammad Umer

Abstract:

Fully reusable spaceplanes do not exist as yet. This implies that design-qualification for optimized highly-integrated forebody-inlet configuration of booster-stage vehicle cannot be based on archival data of other spaceplanes. Therefore, this paper proposes a novel TIPSO-SVM expert system methodology. A non-trivial problem related to optimization and classification of hypersonic forebody-inlet configuration in conjunction with mass-model of the two-stage-to-orbit (TSTO) vehicle is solved. The hybrid-heuristic machine learning methodology is based on two-step improved particle swarm optimizer (TIPSO) algorithm and two-step support vector machine (SVM) data classification method. The efficacy of method is tested by first evolving an optimal configuration for hypersonic compression system using TIPSO algorithm; thereafter, classifying the results using two-step SVM method. In the first step extensive but non-classified mass-model training data for multiple optimized configurations is segregated and pre-classified for learning of SVM algorithm. In second step the TIPSO optimized mass-model data is classified using the SVM classification. Results showed remarkable improvement in configuration and mass-model along with sizing parameters.

Keywords: TIPSO-SVM expert system, TIPSO algorithm, two-step SVM method, aerothermodynamics, mass-modeling, TSTO vehicle.

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10496 Romanian Single-parent Families: Quality of Life

Authors: Bertha Sânduleasa, Aniela Matei, Mihaela Ghenţa, Nicolina Racoceanu

Abstract:

The increasing divorce and fertility rates outside of marriage, the changing values in the last decades have led to a high prevalence of single parent families. Currently, worldwide, singleparent families represent about a quarter of all families. Recent changes occurring in the structure of single-parent families and also the multitude of factors that influence the quality of life of these families require the development of new research tools in order to provide foundations for social policies addressed to this type of family. The purpose of this paper is to present an analysis concerning the quality of life for single parent families in Romania, based on data collected through a research methodology developed by the authors within a scientific research project funded by a national grant called Partnerships in priority areas.

Keywords: Family policies, quality of life, single-parent families, work-life balance.

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10495 Schema and Data Migration of a Relational Database RDB to the Extensible Markup Language XML

Authors: Alae El Alami, Mohamed Bahaj

Abstract:

This article discusses the passage of RDB to XML documents (schema and data) based on metadata and semantic enrichment, which makes the RDB under flattened shape and is enriched by the object concept. The integration and exploitation of the object concept in the XML uses a syntax allowing for the verification of the conformity of the document XML during the creation. The information extracted from the RDB is therefore analyzed and filtered in order to adjust according to the structure of the XML files and the associated object model. Those implemented in the XML document through a SQL query are built dynamically. A prototype was implemented to realize automatic migration, and so proves the effectiveness of this particular approach.

Keywords: RDB, XML, DTD, semantic enrichment.

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10494 The Role of Banks Funding and Promoting the Foreign Trade: Case of Turkey

Authors: Mikail Altan

Abstract:

International trust takes first place in the development of foreign trade in the country. They see an important role in ensuring that trust. Various payment methods that are developed in the banking system provide fast and reliable way to execution and promote foreign trade by financing the foreign trade. In this study, we investigate the influence of bank on foreign trade in Turkey. 26 years of data for 1990-2015 period have been used in this study. After correlation analysis, a simple regression model was established. Payment methods that are developed in the banking system make a positive contribution in Turkey’s foreign trade volume. In addition, the export of Turkey was affected positively more than import’s by these payment methods.

Keywords: Banks, export, foreign trade, import.

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10493 Estimating 3D-Position of A Stationary Random Acoustic Source Using Bispectral Analysis of 4-Point Detected Signals

Authors: Katsumi Hirata

Abstract:

To develop the useful acoustic environmental recognition system, the method of estimating 3D-position of a stationary random acoustic source using bispectral analysis of 4-point detected signals is proposed. The method uses information about amplitude attenuation and propagation delay extracted from amplitude ratios and angles of auto- and cross-bispectra of the detected signals. It is expected that using bispectral analysis affects less influence of Gaussian noises than using conventional power spectral one. In this paper, the basic principle of the method is mentioned first, and its validity and features are considered from results of the fundamental experiments assumed ideal circumstances.

Keywords: 4-point detection, a stationary random acoustic source, auto- and cross-bispectra, estimation of 3D-position.

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10492 Enhanced Character Based Algorithm for Small Parsimony

Authors: Parvinder Singh Sandhu, Sumeet Kaur Sehra, Karmjit Kaur

Abstract:

Phylogenetic tree is a graphical representation of the evolutionary relationship among three or more genes or organisms. These trees show relatedness of data sets, species or genes divergence time and nature of their common ancestors. Quality of a phylogenetic tree requires parsimony criterion. Various approaches have been proposed for constructing most parsimonious trees. This paper is concerned about calculating and optimizing the changes of state that are needed called Small Parsimony Algorithms. This paper has proposed enhanced small parsimony algorithm to give better score based on number of evolutionary changes needed to produce the observed sequence changes tree and also give the ancestor of the given input.

Keywords: Phylogenetic Analysis, Small Parsimony, EnhancedFitch Algorithm, Enhanced Sakoff Algorithm.

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10491 The Experimental and Numerical Analysis of the Joining Processes for Air Conditioning Systems

Authors: M.St. Węglowski, D. Miara, S. Błacha, J. Dworak, J. Rykała, K. Kwieciński, J. Pikuła, G. Ziobro, A. Szafron, P. Zimierska-Nowak, M. Richert, P. Noga

Abstract:

In the paper the results of welding of car’s air-conditioning elements are presented. These systems based on, mainly, the environmental unfriendly refrigerants. Thus, the producers of cars will have to stop using traditional refrigerant and to change it to carbon dioxide (R744). This refrigerant is environmental friendly. However, it should be noted that the air condition system working with R744 refrigerant operates at high temperature (up to 150 °C) and high pressure (up to 130 bar). These two parameters are much higher than for other refrigerants. Thus new materials, design as well as joining technologies are strongly needed for these systems. AISI 304 and 316L steels as well as aluminium alloys 5xxx are ranked among the prospective materials. As a joining process laser welding, plasma welding, electron beam welding as well as high rotary friction welding can be applied. In the study, the metallographic examination based on light microscopy as well as SEM was applied to estimate the quality of welded joints. The analysis of welding was supported by numerical modelling based on Sysweld software. The results indicated that using laser, plasma and electron beam welding, it is possible to obtain proper quality of welds in stainless steel. Moreover, high rotary friction welding allows to guarantee the metallic continuity in the aluminium welded area. The metallographic examination revealed that the grain growth in the heat affected zone (HAZ) in laser and electron beam welded joints were not observed. It is due to low heat input and short welding time. The grain growth and subgrains can be observed at room temperature when the solidification mode is austenitic. This caused low microstructural changes during solidification. The columnar grain structure was found in the weld metal. Meanwhile, the equiaxed grains were detected in the interface. The numerical modelling of laser welding process allowed to estimate the temperature profile in the welded joint as well as predicts the dimensions of welds. The agreement between FEM analysis and experimental data was achieved.  

Keywords: Car’s air–conditioning, microstructure, numerical modelling, welding.

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10490 The Intonation of Romanian Greetings: A Sociolinguistics Approach

Authors: Anca-Diana Bibiri, Mihaela Mocanu, Adrian Turculeț

Abstract:

In a language the inventory of greetings is dynamic with frequent input and output, although this is hardly noticed by the speakers. In this register, there are a number of constant, conservative elements that survive different language models (among them, the classic formulae: bună ziua! (good afternoon!), bună seara! (good evening!), noapte bună! (good night!), la revedere! (goodbye!) and a number of items that fail to pass the test of time, according to language use at a time (ciao!, pa!, bai!). The source of innovation depends both of internal factors (contraction, conversion, combination of classic formulae of greetings), and of external ones (borrowings and calques). Their use imposes their frequencies at once, namely the elimination of the use of others. This paper presents a sociolinguistic approach of contemporary Romanian greetings, based on prosodic surveys in two research projects: AMPRom, and SoRoEs. Romanian language presents a rich inventory of questions (especially partial interrogatives questions/WH-Q) which are used as greetings, alone or, more commonly accompanying a proper greeting. The representative of the typical formulae is Ce mai faci? (How are you?), which, unlike its English counterpart How do you do?, has not become a stereotype, but retains an obvious emotional impact, while serving as a mark of sociolinguistic group. The analyzed corpus consists of structures containing greetings recorded in the main Romanian cultural (urban) centers. From the methodological point of view, the acoustic analysis of the recorded data is performed using software tools (GoldWave, Praat), identifying intonation patterns related to three sociolinguistics variables: age, sex and level of education. The intonation patterns of the analyzed statements are at the interface between partial questions and typical greetings.

Keywords: acoustic analysis, greetings, Romanian language, sociolinguistics

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10489 A Spatial Information Network Traffic Prediction Method Based on Hybrid Model

Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

Abstract:

Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: Spatial Information Network, Traffic prediction, Wavelet decomposition, Time series model.

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10488 Evaluation of Underground Water Flow into Tabriz Metro Tunnel First Line by Hydro-Mechanical Coupling Analysis

Authors: L. Nikakhtar, S. Zare

Abstract:

One of the main practical difficulties attended with tunnel construction is related to underground water. Uncontrolled water behavior may cause extra loads on the lining, mechanical instability, and unfavorable environmental problems. Estimating underground water inflow rate to the tunnels is a complex skill. The common calculation methods are: empirical methods, analytical solutions, numerical solutions based on the equivalent continuous porous media. In this research the rate of underground water inflow to the Tabriz metro first line tunnel has been investigated by numerical finite difference method using FLAC2D software. Comparing results of Heuer analytical method and numerical simulation showed good agreement with each other. Fully coupled and one-way coupled hydro mechanical states as well as water-free conditions in the soil around the tunnel are used in numerical models and these models have been applied to evaluate the loading value on the tunnel support system. Results showed that the fully coupled hydro mechanical analysis estimated more axial forces, moments and shear forces in linings, so this type of analysis is more conservative and reliable method for design of tunnel lining system. As sensitivity analysis, inflow water rates into the tunnel were evaluated in different soil permeability, underground water levels and depths of the tunnel. Result demonstrated that water level in constant depth of the tunnel is more sensitive factor for water inflow rate to the tunnel in comparison of other parameters investigated in the sensitivity analysis.

Keywords: Coupled hydro mechanical analysis, FLAC2D, Tabriz Metro, inflow rate.

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10487 Signal Processing Approach to Study Multifractality and Singularity of Solar Wind Speed Time Series

Authors: Tushnik Sarkar, Mofazzal H. Khondekar, Subrata Banerjee

Abstract:

This paper investigates the nature of the fluctuation of the daily average Solar wind speed time series collected over a period of 2492 days, from 1st January, 1997 to 28th October, 2003. The degree of self-similarity and scalability of the Solar Wind Speed signal has been explored to characterise the signal fluctuation. Multi-fractal Detrended Fluctuation Analysis (MFDFA) method has been implemented on the signal which is under investigation to perform this task. Furthermore, the singularity spectra of the signals have been also obtained to gauge the extent of the multifractality of the time series signal.

Keywords: Detrended fluctuation analysis, generalized Hurst exponent, holder exponents, multifractal exponent, multifractal spectrum, singularity spectrum, time series analysis.

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10486 Personal Information Classification Based on Deep Learning in Automatic Form Filling System

Authors: Shunzuo Wu, Xudong Luo, Yuanxiu Liao

Abstract:

Recently, the rapid development of deep learning makes artificial intelligence (AI) penetrate into many fields, replacing manual work there. In particular, AI systems also become a research focus in the field of automatic office. To meet real needs in automatic officiating, in this paper we develop an automatic form filling system. Specifically, it uses two classical neural network models and several word embedding models to classify various relevant information elicited from the Internet. When training the neural network models, we use less noisy and balanced data for training. We conduct a series of experiments to test my systems and the results show that our system can achieve better classification results.

Keywords: Personal information, deep learning, auto fill, NLP, document analysis.

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10485 Stability Analysis of Single Inverter Fed Two Induction Motors in Parallel

Authors: R. Gunabalan, V. Subbiah

Abstract:

This paper discusses the novel graphical approach for stability analysis of multi induction motor drive controlled by a single inverter. Stability issue arises in parallel connected induction motors under unbalanced load conditions. The two powerful globally accepted modeling and simulation software packages such as MATLAB and LabVIEW are selected to perform the stability analysis. The stability investigation is performed for different load conditions and difference in stator and rotor resistances among the two motors. It is very simple and effective than the techniques presented to obtain the stability of the parallel connected induction motor drive under unbalanced load conditions. Approximate transfer functions are considered to model the induction motors, load dynamics, speed controllers and inverter. Simulink library tools are utilized to model the entire drive scheme in MATLAB. Stability study is discussed in LabVIEW using control design and simulation toolkits. Simulation results are illustrated for various running conditions to demonstrate the effectiveness of the transfer function method.

Keywords: Induction motor, Modeling, Stability analysis, Transfer function model.

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10484 Determination of the Characteristics for Ferroresonance Phenomenon in Electric Power Systems

Authors: Sezen Yildirim, Tahir Çetin Akinci, Serhat Seker, Nazmi Ekren

Abstract:

Ferroresonance is an electrical phenomenon in nonlinear character, which frequently occurs in power system due to transmission line faults and single or more-phase switching on the lines as well as usage of the saturable transformers. In this study, the ferroresonance phenomena are investigated under the modeling of the West Anatolian Electric Power Network of 380 kV in Turkey. The ferroresonance event is observed as a result of removing the loads at the end of the lines. In this sense, two different cases are considered. At first, the switching is applied at 2nd second and the ferroresonance affects are observed between 2nd and 4th seconds in the voltage variations of the phase-R. Hence the ferroresonance and nonferroresonance parts of the overall data are compared with each others using the Fourier transform techniques to show the ferroresonance affects.

Keywords: Ferroresonance, West Anatolian Electric Power System, Power System Modeling, Switching, Spectral Analysis.

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10483 An Analysis of Eco-efficiency and GHG Emission of Olive Oil Production in Northeast of Portugal

Authors: M. Feliciano, F. Maia, A. Gonçalves

Abstract:

Olive oil production sector plays an important role in Portuguese economy. It had a major growth over the last decade, increasing its weight in the overall national exports. International market penetration for Mediterranean traditional products is increasingly more demanding, especially in the Northern European markets, where consumers are looking for more sustainable products. Trying to support this growing demand this study addresses olive oil production under the environmental and eco-efficiency perspectives. The analysis considers two consecutive product life cycle stages: olive trees farming; and olive oil extraction in mills. Addressing olive farming, data collection covered two different organizations: a middle-size farm (~12ha) (F1) and a large-size farm (~100ha) (F2). Results from both farms show that olive collection activities are responsible for the largest amounts of Green House Gases (GHG) emissions. In this activities, estimate for the Carbon Footprint per olive was higher in F2 (188g CO2e/kgolive) than in F1 (148g CO2e/kgolive). Considering olive oil extraction, two different mills were considered: one using a two-phase system (2P) and other with a three-phase system (3P). Results from the study of two mills show that there is a much higher use of water in 3P. Energy intensity (EI) is similar in both mills. When evaluating the GHG generated, two conditions are evaluated: a biomass neutral condition resulting on a carbon footprint higher in 3P (184g CO2e/Lolive oil) than in 2P (92g CO2e/Lolive oil); and a non-neutral biomass condition in which 2P increase its carbon footprint to 273g CO2e/Lolive oil. When addressing the carbon footprint of possible combinations among studied subsystems, results suggest that olive harvesting is the major source for GHG.

Keywords: Carbon footprint, environmental indicators, farming subsystem, industrial subsystem, olive oil.

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10482 Fractal - Wavelet Based Techniques for Improving the Artificial Neural Network Models

Authors: Reza Bazargan Lari, Mohammad H. Fattahi

Abstract:

Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for preprocessing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based preprocessing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.

Keywords: Wavelet, de-noising, predictability, time series fractal analysis, valid length, ANN.

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10481 A Comparative Study between Displacement and Strain Based Formulated Finite Elements Applied to the Analysis of Thin Shell Structures

Authors: Djamal Hamadi, Oussama Temami, Abdallah Zatar, Sifeddine Abderrahmani

Abstract:

The analysis and design of thin shell structures is a topic of interest in a variety of engineering applications. In structural mechanics problems the analyst seeks to determine the distribution of stresses throughout the structure to be designed. It is also necessary to calculate the displacements of certain points of the structure to ensure that specified allowable values are not exceeded. In this paper a comparative study between displacement and strain based finite elements applied to the analysis of some thin shell structures is presented. The results obtained from some examples show the efficiency and the performance of the strain based approach compared to the well known displacement formulation.

Keywords: Displacement formulation, Finite elements, Strain based approach, Shell structures.

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10480 Data Hiding in Images in Discrete Wavelet Domain Using PMM

Authors: Souvik Bhattacharyya, Gautam Sanyal

Abstract:

Over last two decades, due to hostilities of environment over the internet the concerns about confidentiality of information have increased at phenomenal rate. Therefore to safeguard the information from attacks, number of data/information hiding methods have evolved mostly in spatial and transformation domain.In spatial domain data hiding techniques,the information is embedded directly on the image plane itself. In transform domain data hiding techniques the image is first changed from spatial domain to some other domain and then the secret information is embedded so that the secret information remains more secure from any attack. Information hiding algorithms in time domain or spatial domain have high capacity and relatively lower robustness. In contrast, the algorithms in transform domain, such as DCT, DWT have certain robustness against some multimedia processing.In this work the authors propose a novel steganographic method for hiding information in the transform domain of the gray scale image.The proposed approach works by converting the gray level image in transform domain using discrete integer wavelet technique through lifting scheme.This approach performs a 2-D lifting wavelet decomposition through Haar lifted wavelet of the cover image and computes the approximation coefficients matrix CA and detail coefficients matrices CH, CV, and CD.Next step is to apply the PMM technique in those coefficients to form the stego image. The aim of this paper is to propose a high-capacity image steganography technique that uses pixel mapping method in integer wavelet domain with acceptable levels of imperceptibility and distortion in the cover image and high level of overall security. This solution is independent of the nature of the data to be hidden and produces a stego image with minimum degradation.

Keywords: Cover Image, Pixel Mapping Method (PMM), StegoImage, Integer Wavelet Tranform.

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10479 Human Behavior Modeling in Video Surveillance of Conference Halls

Authors: Nour Charara, Hussein Charara, Omar Abou Khaled, Hani Abdallah, Elena Mugellini

Abstract:

In this paper, we present a human behavior modeling approach in videos scenes. This approach is used to model the normal behaviors in the conference halls. We exploited the Probabilistic Latent Semantic Analysis technique (PLSA), using the 'Bag-of-Terms' paradigm, as a tool for exploring video data to learn the model by grouping similar activities. Our term vocabulary consists of 3D spatio-temporal patch groups assigned by the direction of motion. Our video representation ensures the spatial information, the object trajectory, and the motion. The main importance of this approach is that it can be adapted to detect abnormal behaviors in order to ensure and enhance human security.

Keywords: Activity modeling, clustering, PLSA, video representation.

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10478 A Comparison of Software Analysis and Design Methods for Real Time Systems

Authors: Anthony Spiteri Staines

Abstract:

This paper examines and compares several of the most common real time methods. These methods are CORE, YSM, MASCOT, JSD, DARTS, RTSAD, ADARTS, CODARTS, HOOD, HRT-HOOD, ROOM, UML, UML-RT. The methods are compared using attributes like i) usability, ii) compositionality and iii) proper RT notations available. Finally some comparison results are given and discussed.

Keywords: Software Engineering Methods, MethodComparison, Real Time Analysis and Design.

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10477 Impact of Electronic Guest Relationship Management (e-GRM) on Brand Loyalty: The Case of Croatian Hotels

Authors: Marina Laškarin, Vlado Galičić

Abstract:

Quick adoption of e-business and emerging influence of “Electronic Word of Mouth e-WOM” communication on guests made leading hotel brands successful examples of electronic guest relationship management. Main reasons behind such success are well established procedures in collection, analysis and usage of highly valuable data available on the Internet, generated through some form of e-GRM programme. E-GRM is more than just a technology solution. It’s a system which balance respective guest demands, hotel technological capabilities and organizational culture of employees, discharging the universal approach in guest relations “same for all”. The purpose of this research derives from the necessity of determining the importance of monitoring and applying e-WOM communication as one of the methods used in managing guest relations. This paper analyses and compares different hotelier’s opinions on e-WOM communication.

Keywords: Brand loyalty, e-WOM communication, GRM programmes.

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10476 Using Textual Pre-Processing and Text Mining to Create Semantic Links

Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

Abstract:

This article offers a approach to the automatic discovery of semantic concepts and links in the domain of Oil Exploration and Production (E&P). Machine learning methods combined with textual pre-processing techniques were used to detect local patterns in texts and, thus, generate new concepts and new semantic links. Even using more specific vocabularies within the oil domain, our approach has achieved satisfactory results, suggesting that the proposal can be applied in other domains and languages, requiring only minor adjustments.

Keywords: Semantic links, data mining, linked data, SKOS.

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10475 Diffusion Analysis of a Scalable Feistel Network

Authors: Subariah Ibrahim, Mohd Aizaini Maarof

Abstract:

A generalization of the concepts of Feistel Networks (FN), known as Extended Feistel Network (EFN) is examined. EFN splits the input blocks into n > 2 sub-blocks. Like conventional FN, EFN consists of a series of rounds whereby at least one sub-block is subjected to an F function. The function plays a key role in the diffusion process due to its completeness property. It is also important to note that in EFN the F-function is the most computationally expensive operation in a round. The aim of this paper is to determine a suitable type of EFN for a scalable cipher. This is done by analyzing the threshold number of rounds for different types of EFN to achieve the completeness property as well as the number of F-function required in the network. The work focuses on EFN-Type I, Type II and Type III only. In the analysis it is found that EFN-Type II and Type III diffuses at the same rate and both are faster than Type-I EFN. Since EFN-Type-II uses less F functions as compared to EFN-Type III, therefore Type II is the most suitable EFN for use in a scalable cipher.

Keywords: Cryptography, Extended Feistel Network, Diffusion Analysis.

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10474 An AI-Based Dynamical Resource Allocation Calculation Algorithm for Unmanned Aerial Vehicle

Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

Abstract:

As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the CPU, RAM, and ROM memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles.

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10473 Simulation Method for Determining the Thermally Induced Displacement of Machine Tools – Experimental Validation and Utilization in the Design Process

Authors: G. Kehl, P. Wagner

Abstract:

A novel simulation method to determine the displacements of machine tools due to thermal factors is presented. The specific characteristic of this method is the employment of original CAD data from the design process chain, which is interpreted by an algorithm in terms of geometry-based allocation of convection and radiation parameters. Furthermore analogous models relating to the thermal behaviour of machine elements are automatically implemented, which were gained by extensive experimental testing with thermography imaging. With this a transient simulation of the thermal field and in series of the displacement of the machine tool is possible simultaneously during the design phase. This method was implemented and is already used industrially in the design of machining centres in order to improve the quality of herewith manufactured workpieces.

Keywords: Accuracy, design process, finite element analysis, machine tools, thermal simulation.

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10472 A Research on Inference from Multiple Distance Variables in Hedonic Regression – Focus on Three Variables

Authors: Yan Wang, Yasushi Asami, Yukio Sadahiro

Abstract:

In urban context, urban nodes such as amenity or hazard will certainly affect house price, while classic hedonic analysis will employ distance variables measured from each urban nodes. However, effects from distances to facilities on house prices generally do not represent the true price of the property. Distance variables measured on the same surface are suffering a problem called multicollinearity, which is usually presented as magnitude variance and mean value in regression, errors caused by instability. In this paper, we provided a theoretical framework to identify and gather the data with less bias, and also provided specific sampling method on locating the sample region to avoid the spatial multicollinerity problem in three distance variable’s case.

Keywords: Hedonic regression, urban node, distance variables, multicollinerity, collinearity.

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10471 Characterization of Novel Atrazine-Degrading Klebsiella sp. isolated from Thai Agricultural Soil

Authors: Sawangjit Sopid

Abstract:

Atrazine, a herbicide widely used in sugarcane and corn production, is a frequently detected groundwater contaminant. An atrazine-degrading bacterium, strain KB02, was obtained from long-term atrazine-treated sugarcane field soils in Kanchanaburi province of Thailand. Strain KB02 had a rod-to-coccus morphological cycle during growth. Sequence analysis of the PCR product indicated that the 16S rRNA gene in strain KB02 was ranging from 97-98% identical to the same region in Klebsiella sp. Based on biochemical, physiological analysis and 16S rDNA sequence analysis of one representative isolate, strain KB02, the isolates belong to the genus Klebsiella in the family Enterobacteriaceae. Interestingly that the various primers for atzA, B and C failed to amplify genomic DNA of strain KB02. Whereas the expected PCR product of atzA, B and C were obtained from the reference strain, Arthrobacter sp. strain KU001.

Keywords: Atrazine, atz gene, Biodegradation, bioremediation, Klebsiella

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