Search results for: Data preparation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7716

Search results for: Data preparation

7266 Modification and Characterization of Bacterial Cellulose Biopolymer as Proton Conducting Membrane

Authors: C. W. Lin, S.W. Chen

Abstract:

This study describes the preparation of a novel proton conducting membranes based on bacterial cellulose (BC) modified by grafting of 2-acrylamido-2-methyl-1 -propanesulfonic acid (AMPS) through UV-induced graft polymerization. These AMPS-g-BC membranes have been characterized by various techniques including FTIR, SEM and TGA, to find their successful grafting of AMPS on BC, surface morphology and thermal stability, respectively. Physical properties of AMPS-g-BC membranes have been assessed in terms of Lamda value( λ ), ion exchange capacity(IEC) and proton conductivity. The relationship between degree of grafting and AMPS concentration used for grafting has been determined by weight gain method. An optimum proton conductivity equal to 2.89x10-2 S cm-1 and IEC value equal to 1.79 mmol g-1 have been obtained when 20 wt% AMPS concentration is used for grafting (i.e. the corresponding membrane is notated as AMPS20-g-BC).

Keywords: Bacterial cellulose, 2-acrylamido-2-methyl-1-propanesulfonic acid, Proton conducting membrane, Self diffusioncoefficient, Fuel cell

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7265 Preparation of Homogeneous Dense Composite of Zirconia and Alumina (ZTA)using Colloidal Filtration

Authors: H. Wakily, M. Mehrali, H. S. C. Metselaar

Abstract:

Homogeneous composites of alumina and zirconia with a small amount of MgO (<1 wt %) were prepared by colloidal filtration. The object of using ZrO2 (15wt %) was to provide zirconia toughened alumina (ZTA). Suspensions of alumina and Zirconia with various solid loadings and various concentrations of Dolapix CE64 as surfactant were studied. The stability of these suspensions was investigated using rheological measurements. The optimum amount of using Dolapix was 0.8wt% for ZTA containing MgO suspension which gave low apparent viscosity in basic area (100 mPa s at shear rate of 50 s-1). The satisfactory mixtures were made into sample pallets using colloidal filtration. The process was completed with pressureless sintering in suitable temperature. Phase, grain size and qualitative compositional analysis were done using X-ray diffraction (XRD) and scanning electron microscopy (SEM) images. ZTA containing 0.05 wt% MgO shows the lowest grain size for alumina around 0.5 μm. Densification studies show that near full densities (>99%) were obtained for ZTA ceramic containing 0.05 wt% MgO in 1500 °C.

Keywords: Colloidal filtration, Dolapix, MgO, Zirconiatoughened alumina.

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7264 Factors that Contribute to the Improvement of the Sense of Self-Efficacy of Special Educators in Inclusive Settings in Greece

Authors: Sotiria Tzivinikou, Dimitra Kagkara

Abstract:

Teacher’s sense of self-efficacy can affect significantly both teacher’s and student’s performance. More specific, self-efficacy is associated with the learning outcomes as well as student’s motivation and self-efficacy. For example, teachers with high sense of self-efficacy are more open to innovations and invest more effort in teaching. In addition to this, effective inclusive education is associated with higher levels of teacher’s self-efficacy. Pre-service teachers with high levels of self-efficacy could handle student’s behavior better and more effectively assist students with special educational needs. Teacher preparation programs are also important, because teacher’s efficacy beliefs are shaped early in learning, as a result the quality of teacher’s education programs can affect the sense of self-efficacy of pre-service teachers. Usually, a number of pre-service teachers do not consider themselves well prepared to work with students with special educational needs and do not have the appropriate sense of self-efficacy. This study aims to investigate the factors that contribute to the improvement of the sense of self-efficacy of pre-service special educators by using an academic practicum training program. The sample of this study is 159 pre-service special educators, who also participated in the academic practicum training program. For the purpose of this study were used quantitative methods for data collection and analysis. Teacher’s self-efficacy was assessed by the teachers themselves with the completion of a questionnaire which was based on the scale of Teacher’s Sense of Efficacy Scale. Pre and post measurements of teacher’s self-efficacy were taken. The results of the survey are consistent with those of the international literature. The results indicate that a significant number of pre-service special educators do not hold the appropriate sense of self-efficacy regarding teaching students with special educational needs. Moreover, a quality academic training program constitutes a crucial factor for the improvement of the sense of self-efficacy of pre-service special educators, as additional for the provision of high quality inclusive education.

Keywords: Inclusive education, pre-service, self-efficacy, training program.

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7263 Analysis of Diverse Cluster Ensemble Techniques

Authors: S. Sarumathi, N. Shanthi, P. Ranjetha

Abstract:

Data mining is the procedure of determining interesting patterns from the huge amount of data. With the intention of accessing the data faster the most supporting processes needed is clustering. Clustering is the process of identifying similarity between data according to the individuality present in the data and grouping associated data objects into clusters. Cluster ensemble is the technique to combine various runs of different clustering algorithms to obtain a general partition of the original dataset, aiming for consolidation of outcomes from a collection of individual clustering outcomes. The performances of clustering ensembles are mainly affecting by two principal factors such as diversity and quality. This paper presents the overview about the different cluster ensemble algorithm along with their methods used in cluster ensemble to improve the diversity and quality in the several cluster ensemble related papers and shows the comparative analysis of different cluster ensemble also summarize various cluster ensemble methods. Henceforth this clear analysis will be very useful for the world of clustering experts and also helps in deciding the most appropriate one to determine the problem in hand.

Keywords: Cluster Ensemble, Consensus Function, CSPA, Diversity, HGPA, MCLA.

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7262 Polyacrylate Modified Copper Nanoparticles with Controlled Size

Authors: Robert Prucek, Aleš Panáček, Jan Filip, Libor Kvítek, Radek Zbořil

Abstract:

The preparation of Cu nanoparticles (NPs) through the reduction of copper ions by sodium borohydride in the presence of sodium polyacrylate with a molecular weight of 1200 is reported. Cu NPs were synthesized at a concentration of copper salt equal to 2.5, 5, and 10 mM, and at a molar ratio of copper ions and monomeric unit of polyacrylate equal to 1:2. The as-prepared Cu NPs have diameters of about 2.5–3 nm for copper concentrations of 2.5 and 5 mM, and 6 nm for copper concentration of 10 mM. Depending on the copper salt concentration and concentration of additionally added polyacrylate to Cu particle dispersion, primarily formed NPs grow through the process of aggregation and/or coalescence into clusters and/or particles with a diameter between 20–100 nm. The amount of additionally added sodium polyacrylate influences the stability of Cu particles against air oxidation. The catalytic efficiency of the prepared Cu particles for the reduction of 4-nitrophenol is discussed.

Keywords: Copper, nanoparticles, sodium polyacrylate, catalyst, 4-nitrophenol.

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7261 A Distributed Approach to Extract High Utility Itemsets from XML Data

Authors: S. Kannimuthu, K. Premalatha

Abstract:

This paper investigates a new data mining capability that entails mining of High Utility Itemsets (HUI) in a distributed environment. Existing research in data mining deals with only presence or absence of an items and do not consider the semantic measures like weight or cost of the items. Thus, HUI mining algorithm has evolved. HUI mining is the one kind of utility mining concept, aims to identify itemsets whose utility satisfies a given threshold. Although, the approach of mining HUIs in a distributed environment and mining of the same from XML data have not explored yet. In this work, a novel approach is proposed to mine HUIs from the XML based data in a distributed environment. This work utilizes Service Oriented Computing (SOC) paradigm which provides Knowledge as a Service (KaaS). The interesting patterns are provided via the web services with the help of knowledge server to answer the queries of the consumers. The performance of the approach is evaluated on various databases using execution time and memory consumption.

Keywords: Data mining, Knowledge as a Service, service oriented computing, utility mining.

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7260 On the Network Packet Loss Tolerance of SVM Based Activity Recognition

Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

Abstract:

In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces  high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: Activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss.

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7259 Performance and Availability Analyses of PV Generation Systems in Taiwan

Authors: H. S. Huang, J. C. Jao, K. L. Yen, C. T. Tsai

Abstract:

The purpose of this article applies the monthly final energy yield and failure data of 202 PV systems installed in Taiwan to analyze the PV operational performance and system availability. This data is collected by Industrial Technology Research Institute through manual records. Bad data detection and failure data estimation approaches are proposed to guarantee the quality of the received information. The performance ratio value and system availability are then calculated and compared with those of other countries. It is indicated that the average performance ratio of Taiwan-s PV systems is 0.74 and the availability is 95.7%. These results are similar with those of Germany, Switzerland, Italy and Japan.

Keywords: availability, performance ratio, PV system, Taiwan

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7258 Stealthy Network Transfer of Data

Authors: N. Veerasamy, C. J. Cheyne

Abstract:

Users of computer systems may often require the private transfer of messages/communications between parties across a network. Information warfare and the protection and dominance of information in the military context is a prime example of an application area in which the confidentiality of data needs to be maintained. The safe transportation of critical data is therefore often a vital requirement for many private communications. However, unwanted interception/sniffing of communications is also a possibility. An elementary stealthy transfer scheme is therefore proposed by the authors. This scheme makes use of encoding, splitting of a message and the use of a hashing algorithm to verify the correctness of the reconstructed message. For this proof-of-concept purpose, the authors have experimented with the random sending of encoded parts of a message and the construction thereof to demonstrate how data can stealthily be transferred across a network so as to prevent the obvious retrieval of data.

Keywords: Construction, encode, interception, stealthy.

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7257 Survey on Arabic Sentiment Analysis in Twitter

Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb

Abstract:

Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.

Keywords: Big Data, Social Networks, Sentiment Analysis.

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7256 Sensory Evaluation of Cooked Sausages with Legumes Additive

Authors: Ilze Gramatina, Jelena Zagorska, Evita Straumite, Svetlana Sarvi

Abstract:

In the meat processing industry the substitution of meat with non-meat ingredients is considered an important strategy for reducing overall production costs. The main purpose of the current research was to evaluate differences in physical-chemical composition of cooked sausage with different legumes additions. Peas (Pisum sativum), beans (Phaseolus vulgaris) and lentil (Lens culinaris) were used in preparation of sausages. The legumes at proportion of 20% of the total weight of meat were added in sausages. The whole ingredients were mixed, filled into casing, compressed, cooked and cooled. After storage the samples were sensory evaluated. The sensory evaluation was carried out using the nine point hedonic scale and line scale. Sausages without legumes flour was used as control sample. The main conclusion of the current research the legumes flour can be successfully used for cooked sausages production.

Keywords: Legumes, cooked sausages.

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7255 The Survey and the Comparison of Maximum Likelihood, Mahalanobis Distance and Minimum Distance Methods in Preparing Landuse Map in the Western Part of Isfahan Province

Authors: Ali Gholami, M.Esfadiari, M.H.Masihabadi

Abstract:

In this research three methods of Maximum Likelihood, Mahalanobis Distance and Minimum Distance were analyzed in the Western part of Isfahan province in the Iran country. For this purpose, the IRS satellite images and various land preparation uses in region including rangelands, irrigation farming, dry farming, gardens and urban areas were separated and identified. In these methods, matrix error and Kappa index were calculated and accuracy of each method, based on percentages: 53.13, 56.64 and 48.44, were obtained respectively. Considering the low accuracy of these methods to separate land uses due to spread of the land uses, it-s suggested the visual interpretation of the map, to preparing the land use map in this region. The map prepared by visual interpretation is in high accuracy if it will be accompany with the visit of the region.

Keywords: Aghche Region, land use map, MaximumLikelihood, Mahalanobis Distance and Minimum Distance.

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7254 Mean Shift-based Preprocessing Methodology for Improved 3D Buildings Reconstruction

Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

Abstract:

In this work, we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift.

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7253 The Dialectic between Effectiveness and Humanity in the Era of Open Knowledge from the Perspective of Pedagogy

Authors: Sophia Ming Lee Wen, Chao-Ching Kuo, Yu-Line Hu, Yu-Lung Ho, Chih-Cheng Huang, Yi-Hwa Lee

Abstract:

Teaching and learning should involve social issues by which effectiveness and humanity is due consideration as a guideline for sharing and co-creating knowledge. A qualitative method was used after a pioneer study to confirm pre-service teachers’ awareness of open knowledge. There are 17 in-service teacher candidates sampling from 181 schools in Taiwan. Two questions are to resolve: a) How did teachers change their educational ideas, in particular, their attitudes to meet the needs of knowledge sharing and co-creativity; and b) How did they acknowledge the necessity of working out an appropriate way between the educational efficiency and the nature of education for high performance management. This interview investigated teachers’ attitude of sharing and co-creating knowledge. The results show two facts in Taiwan: A) Individuals who must be able to express themselves will be capable of taking part in an open learning environment; and B) Teachers must lead the direction to inspire high performance and improve students’ capacity via knowledge sharing and co-creating knowledge, according to the student-centered philosophy. Collected data from interviewing showed that the teachers were well aware of changing their teaching methods and make some improvements to balance the educational efficiency and the nature of education. Almost all teachers acknowledge that ICT is helpful to motivate learning enthusiasm. Further, teaching integrated with ICT saves teachers’ time and energy on teaching preparation and promoting effectiveness. Teachers are willing to co-create knowledge with students, though using information is not easy due to the lack of operating skills of the website and ICT. Some teachers are against to co-create knowledge in the informational background since they hold that is not feasible for there being a knowledge gap between teachers and students. Technology would easily mislead teachers and students to the goal of instrumental rationality, which makes pedagogy dysfunctional and inhumane; however, any high quality of teaching should take a dialectical balance between effectiveness and humanity.

Keywords: Open knowledge, dialect between effectiveness and humanity, pedagogy, critical thinking.

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7252 Comparative Analysis of the Third Generation of Research Data for Evaluation of Solar Energy Potential

Authors: Claudineia Brazil, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Rafael Haag

Abstract:

Renewable energy sources are dependent on climatic variability, so for adequate energy planning, observations of the meteorological variables are required, preferably representing long-period series. Despite the scientific and technological advances that meteorological measurement systems have undergone in the last decades, there is still a considerable lack of meteorological observations that form series of long periods. The reanalysis is a system of assimilation of data prepared using general atmospheric circulation models, based on the combination of data collected at surface stations, ocean buoys, satellites and radiosondes, allowing the production of long period data, for a wide gamma. The third generation of reanalysis data emerged in 2010, among them is the Climate Forecast System Reanalysis (CFSR) developed by the National Centers for Environmental Prediction (NCEP), these data have a spatial resolution of 0.50 x 0.50. In order to overcome these difficulties, it aims to evaluate the performance of solar radiation estimation through alternative data bases, such as data from Reanalysis and from meteorological satellites that satisfactorily meet the absence of observations of solar radiation at global and/or regional level. The results of the analysis of the solar radiation data indicated that the reanalysis data of the CFSR model presented a good performance in relation to the observed data, with determination coefficient around 0.90. Therefore, it is concluded that these data have the potential to be used as an alternative source in locations with no seasons or long series of solar radiation, important for the evaluation of solar energy potential.

Keywords: Climate, reanalysis, renewable energy, solar radiation.

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7251 Explorative Data Mining of Constructivist Learning Experiences and Activities with Multiple Dimensions

Authors: Patrick Wessa, Bart Baesens

Abstract:

This paper discusses the use of explorative data mining tools that allow the educator to explore new relationships between reported learning experiences and actual activities, even if there are multiple dimensions with a large number of measured items. The underlying technology is based on the so-called Compendium Platform for Reproducible Computing (http://www.freestatistics.org) which was built on top the computational R Framework (http://www.wessa.net).

Keywords: Reproducible computing, data mining, explorative data analysis, compendium technology, computer assisted education

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7250 Analysis of Textual Data Based On Multiple 2-Class Classification Models

Authors: Shigeaki Sakurai, Ryohei Orihara

Abstract:

This paper proposes a new method for analyzing textual data. The method deals with items of textual data, where each item is described based on various viewpoints. The method acquires 2- class classification models of the viewpoints by applying an inductive learning method to items with multiple viewpoints. The method infers whether the viewpoints are assigned to the new items or not by using the models. The method extracts expressions from the new items classified into the viewpoints and extracts characteristic expressions corresponding to the viewpoints by comparing the frequency of expressions among the viewpoints. This paper also applies the method to questionnaire data given by guests at a hotel and verifies its effect through numerical experiments.

Keywords: Text mining, Multiple viewpoints, Differential analysis, Questionnaire data

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7249 Using Automated Database Reverse Engineering for Database Integration

Authors: M. R. Abbasifard, M. Rahgozar, A. Bayati, P. Pournemati

Abstract:

One important problem in today organizations is the existence of non-integrated information systems, inconsistency and lack of suitable correlations between legacy and modern systems. One main solution is to transfer the local databases into a global one. In this regards we need to extract the data structures from the legacy systems and integrate them with the new technology systems. In legacy systems, huge amounts of a data are stored in legacy databases. They require particular attention since they need more efforts to be normalized, reformatted and moved to the modern database environments. Designing the new integrated (global) database architecture and applying the reverse engineering requires data normalization. This paper proposes the use of database reverse engineering in order to integrate legacy and modern databases in organizations. The suggested approach consists of methods and techniques for generating data transformation rules needed for the data structure normalization.

Keywords: Reverse Engineering, Database Integration, System Integration, Data Structure Normalization

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7248 Roller Compacting Concrete “RCC” in Dams

Authors: Orod Zarrin, Mohsen Ramezan Shirazi

Abstract:

Rehabilitation of dam components such as foundations, buttresses, spillways and overtopping protection require a wide range of construction and design methodologies. Geotechnical Engineering considerations play an important role in the design and construction of foundations of new dams. Much investigation is required to assess and evaluate the existing dams. The application of roller compacting concrete (RCC) has been accepted as a new method for constructing new dams or rehabilitating old ones. In the past 40 years there have been so many changes in the usage of RCC and now it is one of most satisfactory solutions of water and hydropower resource throughout the world. The considerations of rehabilitation and construction of dams might differ due to upstream reservoir and its influence on penetrating and dewatering of downstream, operations requirements and plant layout. One of the advantages of RCC is its rapid placement which allows the dam to be operated quickly. Unlike ordinary concrete it is a drier mix, and stiffs enough for compacting by vibratory rollers. This paper evaluates some different aspects of RCC and focuses on its preparation progress.

Keywords: Spillway, Vibrating Consistency, Fly Ash, Water Tightness, Foundation.

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7247 Analysis of Cooperative Learning Behavior Based on the Data of Students' Movement

Authors: Wang Lin, Li Zhiqiang

Abstract:

The purpose of this paper is to analyze the cooperative learning behavior pattern based on the data of students' movement. The study firstly reviewed the cooperative learning theory and its research status, and briefly introduced the k-means clustering algorithm. Then, it used clustering algorithm and mathematical statistics theory to analyze the activity rhythm of individual student and groups in different functional areas, according to the movement data provided by 10 first-year graduate students. It also focused on the analysis of students' behavior in the learning area and explored the law of cooperative learning behavior. The research result showed that the cooperative learning behavior analysis method based on movement data proposed in this paper is feasible. From the results of data analysis, the characteristics of behavior of students and their cooperative learning behavior patterns could be found.

Keywords: Behavior pattern, cooperative learning, data analyze, K-means clustering algorithm.

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7246 A Security Cloud Storage Scheme Based Accountable Key-Policy Attribute-Based Encryption without Key Escrow

Authors: Ming Lun Wang, Yan Wang, Ning Ruo Sun

Abstract:

With the development of cloud computing, more and more users start to utilize the cloud storage service. However, there exist some issues: 1) cloud server steals the shared data, 2) sharers collude with the cloud server to steal the shared data, 3) cloud server tampers the shared data, 4) sharers and key generation center (KGC) conspire to steal the shared data. In this paper, we use advanced encryption standard (AES), hash algorithms, and accountable key-policy attribute-based encryption without key escrow (WOKE-AKP-ABE) to build a security cloud storage scheme. Moreover, the data are encrypted to protect the privacy. We use hash algorithms to prevent the cloud server from tampering the data uploaded to the cloud. Analysis results show that this scheme can resist conspired attacks.

Keywords: Cloud storage security, sharing storage, attributes, Hash algorithm.

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7245 Multimethod Approach to Research in Interlanguage Pragmatics

Authors: Saad Al-Gahtani, Ghassan H Al Shatter

Abstract:

Argument over the use of particular method in interlanguage pragmatics has increased recently. Researchers argued the advantages and disadvantages of each method either natural or elicited. Findings of different studies indicated that the use of one method may not provide enough data to answer all its questions. The current study investigated the validity of using multimethod approach in interlanguage pragmatics to understand the development of requests in Arabic as a second language (Arabic L2). To this end, the study adopted two methods belong to two types of data sources: the institutional discourse (natural data), and the role play (elicited data). Participants were 117 learners of Arabic L2 at the university level, representing four levels (beginners, low-intermediate, highintermediate, and advanced). Results showed that using two or more methods in interlanguage pragmatics affect the size and nature of data.

Keywords: Arabic L2, Development of requests, Interlanguage Pragmatics, Multimethod approach.

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7244 Design of Integration Security System using XML Security

Authors: Juhan Kim, Soohyung Kim, Kiyoung Moon

Abstract:

In this paper, we design an integration security system that provides authentication service, authorization service, and management service of security data and a unified interface for the management service. The interface is originated from XKMS protocol and is used to manage security data such as XACML policies, SAML assertions and other authentication security data including public keys. The system includes security services such as authentication, authorization and delegation of authentication by employing SAML and XACML based on security data such as authentication data, attributes information, assertions and polices managed with the interface in the system. It also has SAML producer that issues assertions related on the result of the authentication and the authorization services.

Keywords: XML, XML Security, XACML.

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7243 Evaluation of Beauveria bassiana Spore Compatibility with Surfactants

Authors: Sapna Mishra, Peeyush Kumar, Anushree Malik

Abstract:

The spores of entomopathogenic fungi, Beauveria bassiana was evaluated for their compatibility with four surfactants; SDS (sodium dodyl sulphate) and CABS-65 (calcium alkyl benzene sulphonate), Tween 20 (polyethylene sorbitan monolaureate) and Tween 80 (polyoxyethylene sorbitan monoleate) at six different concentrations (0.1%, 0.5%, 1%, 2.5%, 5% and 10%). Incubated spores showed decrease in concentrations due to conversion of spores to hyphae. The maximum germination recorded in 72 h incubated spores varied with surfactant concentration at 49-68% (SDS), 39- 53% (CABS), 78-92% (Tween 80) and 80-92% (Tween 20), while the optimal surfactant concentration for spore germination was found to be 2.5-5%. The surfactant effect on spores was more pronounced with SDS and CABS-65, where significant deterioration and loss in viability of the incubated spores was observed. The effect of Tween 20 and Tween 80 were comparatively less inhibiting. The results of the study would help in surfactant selection for B. bassiana emulsion preparation.

Keywords: Beauveria bassiana, spore, surfactant, compatibility, germination.

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7242 An Evaluation Model for Semantic Enablement of Virtual Research Environments

Authors: Tristan O'Neill, Trina Myers, Jarrod Trevathan

Abstract:

The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for crossdomain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.

Keywords: Virtual research environment, Semantic Web, performance analysis, tropical data hub.

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7241 Dimension Reduction of Microarray Data Based on Local Principal Component

Authors: Ali Anaissi, Paul J. Kennedy, Madhu Goyal

Abstract:

Analysis and visualization of microarraydata is veryassistantfor biologists and clinicians in the field of diagnosis and treatment of patients. It allows Clinicians to better understand the structure of microarray and facilitates understanding gene expression in cells. However, microarray dataset is a complex data set and has thousands of features and a very small number of observations. This very high dimensional data set often contains some noise, non-useful information and a small number of relevant features for disease or genotype. This paper proposes a non-linear dimensionality reduction algorithm Local Principal Component (LPC) which aims to maps high dimensional data to a lower dimensional space. The reduced data represents the most important variables underlying the original data. Experimental results and comparisons are presented to show the quality of the proposed algorithm. Moreover, experiments also show how this algorithm reduces high dimensional data whilst preserving the neighbourhoods of the points in the low dimensional space as in the high dimensional space.

Keywords: Linear Dimension Reduction, Non-Linear Dimension Reduction, Principal Component Analysis, Biologists.

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7240 Heterogeneous Attribute Reduction in Noisy System based on a Generalized Neighborhood Rough Sets Model

Authors: Siyuan Jing, Kun She

Abstract:

Neighborhood Rough Sets (NRS) has been proven to be an efficient tool for heterogeneous attribute reduction. However, most of researches are focused on dealing with complete and noiseless data. Factually, most of the information systems are noisy, namely, filled with incomplete data and inconsistent data. In this paper, we introduce a generalized neighborhood rough sets model, called VPTNRS, to deal with the problem of heterogeneous attribute reduction in noisy system. We generalize classical NRS model with tolerance neighborhood relation and the probabilistic theory. Furthermore, we use the neighborhood dependency to evaluate the significance of a subset of heterogeneous attributes and construct a forward greedy algorithm for attribute reduction based on it. Experimental results show that the model is efficient to deal with noisy data.

Keywords: attribute reduction, incomplete data, inconsistent data, tolerance neighborhood relation, rough sets

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7239 A Mobile Agent-based Clustering Data Fusion Algorithm in WSN

Authors: Xiangbin Zhu, Wenjuan Zhang

Abstract:

In wireless sensor networks,the mobile agent technology is used in data fusion. According to the node residual energy and the results of partial integration,we design the node clustering algorithm. Optimization of mobile agent in the routing within the cluster strategy for wireless sensor networks to further reduce the amount of data transfer. Through the experiments, using mobile agents in the integration process within the cluster can be reduced the path loss in some extent.

Keywords: wireless sensor networks, data fusion, mobile agent

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7238 Collision Detection Algorithm Based on Data Parallelism

Authors: Zhen Peng, Baifeng Wu

Abstract:

Modern computing technology enters the era of parallel computing with the trend of sustainable and scalable parallelism. Single Instruction Multiple Data (SIMD) is an important way to go along with the trend. It is able to gather more and more computing ability by increasing the number of processor cores without the need of modifying the program. Meanwhile, in the field of scientific computing and engineering design, many computation intensive applications are facing the challenge of increasingly large amount of data. Data parallel computing will be an important way to further improve the performance of these applications. In this paper, we take the accurate collision detection in building information modeling as an example. We demonstrate a model for constructing a data parallel algorithm. According to the model, a complex object is decomposed into the sets of simple objects; collision detection among complex objects is converted into those among simple objects. The resulting algorithm is a typical SIMD algorithm, and its advantages in parallelism and scalability is unparalleled in respect to the traditional algorithms.

Keywords: Data parallelism, collision detection, single instruction multiple data, building information modeling, continuous scalability.

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7237 Development of Energy Benchmarks Using Mandatory Energy and Emissions Reporting Data: Ontario Post-Secondary Residences

Authors: C. Xavier Mendieta, J. J McArthur

Abstract:

Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

Keywords: Building archetypes, data analysis, energy benchmarks, GHG emissions.

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