Search results for: Hierarchical Aggregate Assessment.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1790

Search results for: Hierarchical Aggregate Assessment.

1160 Residue and Ecological Risk Assessment of Polybrominated Diphenyl Ethers (PBDEs) in Sediment from CauBay River, Vietnam

Authors: Toan Vu Duc, Son Ha Viet

Abstract:

This research presents the first comprehensive survey of congener profiles (7 indicator congeners) of polybrominated diphenyl ethers (PBDEs) in sediment samples covering ten sites in CauBay River, Vietnam. Chemical analyses were carried out in gas chromatography–mass spectrometry (GC–MS) for tri- to hepta- brominated congeners. Results pointed out a non-homogenous contamination of the sediment with ∑7 PBDE values ranging from 8.93 to 25.64ng g−1, reflecting moderate to low contamination closely in conformity to other Asian aquatic environments. The general order of decreasing congener contribution to the total load was: BDE 47 > 99 > 100 > 154, similar to the distribution pattern worldwide. PBDEs had rare risks in the sediment of studied area.  However, due to the propensity of PBDEs to accumulate in various compartments of wildlife and human food webs, evaluation of biological tissues should be undertaken as a high priority. 

Keywords: Residue, Risk assessment, PBDEs, Sediment.

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1159 Collaborative and Content-based Recommender System for Social Bookmarking Website

Authors: Cheng-Lung Huang, Cheng-Wei Lin

Abstract:

This study proposes a new recommender system based on the collaborative folksonomy. The purpose of the proposed system is to recommend Internet resources (such as books, articles, documents, pictures, audio and video) to users. The proposed method includes four steps: creating the user profile based on the tags, grouping the similar users into clusters using an agglomerative hierarchical clustering, finding similar resources based on the user-s past collections by using content-based filtering, and recommending similar items to the target user. This study examines the system-s performance for the dataset collected from “del.icio.us," which is a famous social bookmarking website. Experimental results show that the proposed tag-based collaborative and content-based filtering hybridized recommender system is promising and effectiveness in the folksonomy-based bookmarking website.

Keywords: Collaborative recommendation, Folksonomy, Social tagging

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1158 Exploring SL Writing and SL Sensitivity during Writing Tasks: Poor and Advanced Writing in a Context of Second Language Other than English

Authors: S. Figueiredo, M. Alves Martins, C. Silva, C. Simões

Abstract:

This study integrates a larger research empirical project that examines second language (SL) learners’ profiles and valid procedures to perform complete and diagnostic assessment in schools. 102 learners of Portuguese as a SL aged 7 and 17 years speakers of distinct home languages were assessed in several linguistic tasks. In this article, we focused on writing performance in the specific task of narrative essay composition. The written outputs were measured using the score in six components adapted from an English SL assessment context (Alberta Education): linguistic vocabulary, grammar, syntax, strategy, socio-linguistic, and discourse. The writing processes and strategies in Portuguese language used by different immigrant students were analysed to determine features and diversity of deficits on authentic texts performed by SL writers. Differentiated performance was based on the diversity of the following variables: grades, previous schooling, home language, instruction in first language, and exposure to Portuguese as Second Language. Indo-Aryan languages speakers showed low writing scores compared to their peers and the type of language and respective cognitive mapping (such as Mandarin and Arabic) was the predictor, not linguistic distance. Home language instruction should also be prominently considered in further research to understand specificities of cognitive academic profile in a Romance languages learning context. Additionally, this study also examined the teachers’ representations that will be here addressed to understand educational implications of second language teaching in psychological distress of different minorities in schools of specific host countries.

Keywords: Second language, writing assessment, home language, immigrant students, Portuguese language.

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1157 Improved Technique of Non-viral Gene Delivery into Cancer Cells

Authors: D. Vainauska, S. Kozireva, A. Karpovs, M. Chistyakovs, M. Baryshev

Abstract:

Liposomal magnetofection is a simple, highly efficient technology for cell transfection, demonstrating better outcome than a number of other common gene delivery methods. However, aggregate complexes distribution over the cell surface is non-uniform due to the gradient of the permanent magnetic field. The aim of this study was to estimate the efficiency of liposomal magnetofection for prostate carcinoma PC3 cell line using newly designed device, “DynaFECTOR", ensuring magnetofection in a dynamic gradient magnetic field. Liposomal magnetofection in a dynamic gradient magnetic field demonstrated the highest transfection efficiency for PC3 cells – it increased for 21% in comparison with liposomal magnetofection and for 42% in comparison with lipofection alone. The optimal incubation time under dynamic magnetic field for PC3 cell line was 5 minutes and the optimal rotation frequency of magnets – 5 rpm. The new approach also revealed lower cytotoxic effect to cells than liposomal magnetofection.

Keywords: Dynamic gradient magnetic field, gene delivery, liposomal magnetofection, prostate cancer cell line

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1156 A Pattern Language for Software Debugging

Authors: Mehdi Amoui, Mohammad Zarafshan, Caro Lucas

Abstract:

In spite of all advancement in software testing, debugging remains a labor-intensive, manual, time consuming, and error prone process. A candidate solution to enhance debugging process is to fuse it with testing process. To achieve this integration, a possible solution may be categorizing common software tests and errors followed by the effort on fixing the errors through general solutions for each test/error pair. Our approach to address this issue is based on Christopher Alexander-s pattern and pattern language concepts. The patterns in this language are grouped into three major sections and connect the three concepts of test, error, and debug. These patterns and their hierarchical relationship shape a pattern language that introduces a solution to solve software errors in a known testing context. Finally, we will introduce our developed framework ADE as a sample implementation to support a pattern of proposed language, which aims to automate the whole process of evolving software design via evolutionary methods.

Keywords: Coding Errors, Software debugging, Testing, Patterns, Pattern Language

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1155 Bayesian Meta-Analysis to Account for Heterogeneity in Studies Relating Life Events to Disease

Authors: Elizabeth Stojanovski

Abstract:

Associations between life events and various forms of cancers have been identified. The purpose of a recent random-effects meta-analysis was to identify studies that examined the association between adverse events associated with changes to financial status including decreased income and breast cancer risk. The same association was studied in four separate studies which displayed traits that were not consistent between studies such as the study design, location, and time frame. It was of interest to pool information from various studies to help identify characteristics that differentiated study results. Two random-effects Bayesian meta-analysis models are proposed to combine the reported estimates of the described studies. The proposed models allow major sources of variation to be taken into account, including study level characteristics, between study variance and within study variance, and illustrate the ease with which uncertainty can be incorporated using a hierarchical Bayesian modelling approach.

Keywords: Random-effects, meta-analysis, Bayesian, variation.

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1154 Research on Urban Point of Interest Generalization Method Based on Mapping Presentation

Authors: Chengming Li, Yong Yin, Peipei Guo, Xiaoli Liu

Abstract:

Without taking account of the attribute richness of POI (point of interest) data and spatial distribution limited by roads, a POI generalization method considering both attribute information and spatial distribution has been proposed against the existing point generalization algorithm merely focusing on overall information of point groups. Hierarchical characteristic of urban POI information expression has been firstly analyzed to point out the measurement feature of the corresponding hierarchy. On this basis, an urban POI generalizing strategy has been put forward: POIs urban road network have been divided into three distribution pattern; corresponding generalization methods have been proposed according to the characteristic of POI data in different distribution patterns. Experimental results showed that the method taking into account both attribute information and spatial distribution characteristics of POI can better implement urban POI generalization in the mapping presentation.

Keywords: POI, Road network, spatial information expression, selection method, distribution pattern.

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1153 Sway Reduction on Gantry Crane System using Delayed Feedback Signal and PD-type Fuzzy Logic Controller: A Comparative Assessment

Authors: M.A. Ahmad

Abstract:

This paper presents the use of anti-sway angle control approaches for a two-dimensional gantry crane with disturbances effect in the dynamic system. Delayed feedback signal (DFS) and proportional-derivative (PD)-type fuzzy logic controller are the techniques used in this investigation to actively control the sway angle of the rope of gantry crane system. A nonlinear overhead gantry crane system is considered and the dynamic model of the system is derived using the Euler-Lagrange formulation. A complete analysis of simulation results for each technique is presented in time domain and frequency domain respectively. Performances of both controllers are examined in terms of sway angle suppression and disturbances cancellation. Finally, a comparative assessment of the impact of each controller on the system performance is presented and discussed.

Keywords: Gantry crane, anti-sway control, DFS controller, PD-type Fuzzy Logic Controller.

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1152 Water Quality Assessment Based on Operational Indicator in West Coastal Water of Malaysia

Authors: Seyedeh Belin Tavakoly Sany, H. Rosli, R. Majid, S. Aishah

Abstract:

In this study, water monitoring was performed from Nov. 2012 to Oct. 2013 to assess water quality and evaluate the spatial and temporal distribution of physicochemical and biological variables in water. Water samples were collected from 10 coastal water stations of West Port. In the case of water-quality assessment, multi-metric indices and operational indicators have been proposed to classify the trophic status at different stations. The trophic level of West Port coastal water ranges from eutrophic to hypertrophic. Chl-a concentration was used to estimate the biological response of phytoplankton biomass and indicated eutrophic conditions in West Port and mesotrophic conditions at the control site. During the study period, no eutrophication events or secondary symptoms occurred, which may be related to hydrodynamic turbulence and water exchange, which prevent the development of eutrophic conditions in the West Port.

Keywords: Water quality, multi-metric indices, operational indicator, Malaysia, West Port.

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1151 Metal Streak Analysis with different Acquisition Settings in Postoperative Spine Imaging: A Phantom Study

Authors: N. D. Osman, M. S. Salikin, M. I. Saripan

Abstract:

CT assessment of postoperative spine is challenging in the presence of metal streak artifacts that could deteriorate the quality of CT images. In this paper, we studied the influence of different acquisition parameters on the magnitude of metal streaking. A water-bath phantom was constructed with metal insertion similar with postoperative spine assessment. The phantom was scanned with different acquisition settings and acquired data were reconstructed using various reconstruction settings. Standardized ROIs were defined within streaking region for image analysis. The result shows increased kVp and mAs enhanced SNR values by reducing image noise. Sharper kernel enhanced image quality compared to smooth kernel, but produced more noise in the images with higher CT fluctuation. The noise between both kernels were significantly different (P <0.05) with increment of noise in the bone kernel images (mean difference = 54.78). The technical settings should be selected appropriately to attain the acceptable image quality with the best diagnostic value.

Keywords: Computed tomography, metal streak, noise, CT fluctuation.

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1150 Multiple Intelligence Theory with a View to Designing a Classroom for the Future

Authors: Phalaunnaphat Siriwongs

Abstract:

The classroom of the 21st century is an ever changing forum for new and innovative thoughts and ideas. With increasing technology and opportunity, students have rapid access to information that only decades ago would have taken weeks to obtain. Unfortunately, new techniques and technology is not a cure for the fundamental problems that have plagued the classroom ever since education was established. Class size has been an issue long debated in academia. While it is difficult to pin point an exact number, it is clear that in this case more does not mean better. By looking into the success and pitfalls of classroom size the true advantages of smaller classes will become clear. Previously, one class was comprised of 50 students. Being seventeen and eighteen-year-old students, sometimes it was quite difficult for them to stay focused. To help them understand and gain much knowledge, a researcher introduced “The Theory of Multiple Intelligence” and this, in fact, enabled students to learn according to their own learning preferences no matter how they were being taught. In this lesson, the researcher designed a cycle of learning activities involving all intelligences so that everyone had equal opportunities to learn.

Keywords: Multiple Intelligences, role play, performance assessment, formative assessment.

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1149 A Parametric Study: Frame Analysis Method for Masonry Arch Bridges

Authors: M. E. Rahman, D. Sujan, V. Pakrashi, P. Fanning

Abstract:

The predictability of masonry arch bridges and their behaviour is widely considered doubtful due to the lack of knowledge about the conditions of a given masonry arch bridge. The assessment methods for masonry arch bridges are MEXE, ARCHIE, RING and Frame Analysis Method. The material properties of the masonry and fill material are extremely difficult to determine accurately. Consequently, it is necessary to examine the effect of load dispersal angle through the fill material, the effect of variations in the stiffness of the masonry, the tensile strength of the masonry mortar continuum and the compressive strength of the masonry mortar continuum. It is also important to understand the effect of fill material on load dispersal angle to determine their influence on ratings. In this paper a series of parametric studies, to examine the sensitivity of assessment ratings to the various sets of input data required by the frame analysis method, are carried out.

Keywords: Arch Bridge, Frame Analyses Method, Masonry

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1148 Disaggregating and Forecasting the Total Energy Consumption of a Building: A Case Study of a High Cooling Demand Facility

Authors: Juliana Barcelos Cordeiro, Khashayar Mahani, Farbod Farzan, Mohsen A. Jafari

Abstract:

Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.  

Keywords: Energy consumption forecasting, energy efficiency, load disaggregation, pattern recognition approach.

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1147 Parametric Urban Comfort Envelope an Approach toward a Responsive Sustainable Urban Morphology

Authors: Mohamed M. Saleh, Khalid S. Al-Hagla

Abstract:

By taking advantage of computer-s processing power, an unlimited number of variations and parameters in both spatial and environmental can be provided while following the same set of rules and constraints. This paper focuses on using the tools of parametric urbanism towards a more responsive environmental and sustainable urban morphology. It presents an understanding to Parametric Urban Comfort Envelope (PUCE) as an interactive computational assessment urban model. In addition, it investigates the applicability potentials of this model to generate an optimized urban form to Borg El Arab city (a new Egyptian Community) concerning the human comfort values specially wind and solar envelopes. Finally, this paper utilizes its application outcomes -both visual and numerical- to extend the designer-s limitations by decrease the concern of controlling and manipulation of geometry, and increase the designer-s awareness about the various potentials of using the parametric tools to create relationships that generate multiple geometric alternatives.

Keywords: Assessment model, human comfort, parametric urbanism, sustainable urban morphology.

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1146 The Effects of Aggregate Sizes and Fiber Volume Fraction on Bending Toughness and Direct Tension of Steel Fiber Reinforced Concrete

Authors: Hyun-Woo Cho, Jae-Heum Moon, Jang-Hwa Lee

Abstract:

In order to supplement the brittle property of concrete, fibers are added into concrete mixtures. Compared to general concrete, various characteristics such as tensile strength, bending strength, bending toughness, and resistance to crack are superior, and even when cracks occur, improvements on toughness as well as resistance to shock are excellent due to the growth of fracture energy. Increased function of steel fiber reinforced concrete can be differentiated depending on the fiber dispersion, and sand percentage can be an important influence on the fiber dispersion. Therefore, in this research, experiments were planned on sand percentage in order to apprehend the influence of sand percentage on the bending properties and direct tension of SFRC and basic experiments were conducted on bending and direct tension in order to recognize the properties of bending properties and direct tension following the size of the aggregates and sand percentage.

Keywords: Steel Fiber Reinforced Concrete, Bending Toughness, Direct tension.

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1145 Applicability of Diatom-Based Water Quality Assessment Indices in Dari Stream, Isparta- Turkey

Authors: Hasan Kalyoncu, Burcu Şerbetci

Abstract:

Diatoms are an important group of aquatic ecosystems and diatom-based indices are increasingly becoming important tools for the assessment of ecological conditions in lotic systems. Although the studies are very limited about Turkish rivers, diatom indices were used for monitoring rivers in different basins. In the present study, we used OMNIDIA program for estimation of stream quality. Some indices have less sensitive (IDP, WAT, LOBO, GENRE, TID, CEE, PT), intermediate sensitivities (IDSE, DESCY, IPS, DI-CH, SLA, IDAP), the others higher sensitivities (SID, IBD, SHE, EPI-D). Among the investigated diatom communities, only a few taxa indicated alfa-mesosaprobity and polysaprobity. Most of the sites were characterized by a great relative contribution of eutraphent and tolerant ones as well as oligosaprobic and betamesosaprobic diatoms. In general, SID and IBD indices gave the best results. This study suggests that the structure of benthic diatom communities and diatom indices, especially SID, can be applied for monitoring rivers in Southern Turkey. 

Keywords: Diatom, Darı stream, OMNIDIA, Turkey, Water quality.

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1144 Assessment of Modern RANS Models for the C3X Vane Film Cooling Prediction

Authors: Mikhail Gritskevich, Sebastian Hohenstein

Abstract:

The paper presents the results of a detailed assessment of several modern Reynolds Averaged Navier-Stokes (RANS) turbulence models for prediction of C3X vane film cooling at various injection regimes. Three models are considered, namely the Shear Stress Transport (SST) model, the modification of the SST model accounting for the streamlines curvature (SST-CC), and the Explicit Algebraic Reynolds Stress Model (EARSM). It is shown that all the considered models face with a problem in prediction of the adiabatic effectiveness in the vicinity of the cooling holes; however, accounting for the Reynolds stress anisotropy within the EARSM model noticeably increases the solution accuracy. On the other hand, further downstream all the models provide a reasonable agreement with the experimental data for the adiabatic effectiveness and among the considered models the most accurate results are obtained with the use EARMS.

Keywords: Discrete holes film cooling, Reynolds Averaged Navier-Stokes, Reynolds stress tensor anisotropy, turbulent heat transfer.

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1143 Life Cycle Assessment of Residential Buildings: A Case Study in Canada

Authors: Venkatesh Kumar, Kasun Hewage, Rehan Sadiq

Abstract:

Residential buildings consume significant amounts of energy and produce large amount of emissions and waste. However, there is a substantial potential for energy savings in this sector which needs to be evaluated over the life cycle of residential buildings. Life Cycle Assessment (LCA) methodology has been employed to study the primary energy uses and associated environmental impacts of different phases (i.e., product, construction, use, end of life, and beyond building life) for residential buildings. Four different alternatives of residential buildings in Vancouver (BC, Canada) with a 50-year lifespan have been evaluated, including High Rise Apartment (HRA), Low Rise Apartment (LRA), Single family Attached House (SAH), and Single family Detached House (SDH). Life cycle performance of the buildings is evaluated for embodied energy, embodied environmental impacts, operational energy, operational environmental impacts, total life-cycle energy, and total life cycle environmental impacts. Estimation of operational energy and LCA are performed using DesignBuilder software and Athena Impact estimator software respectively. The study results revealed that over the life span of the buildings, the relationship between the energy use and the environmental impacts are identical. LRA is found to be the best alternative in terms of embodied energy use and embodied environmental impacts; while, HRA showed the best life-cycle performance in terms of minimum energy use and environmental impacts. Sensitivity analysis has also been carried out to study the influence of building service lifespan over 50, 75, and 100 years on the relative significance of embodied energy and total life cycle energy. The life-cycle energy requirements for SDH are found to be a significant component among the four types of residential buildings. The overall disclose that the primary operations of these buildings accounts for 90% of the total life cycle energy which far outweighs minor differences in embodied effects between the buildings.

Keywords: Building simulation, environmental impacts, life cycle assessment, life cycle energy analysis, residential buildings.

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1142 Effect of Plasticizer Additives on the Mechanical Properties of Cement Composite – A Molecular Dynamics Analysis

Authors: R. Mohan, V. Jadhav, A. Ahmed, J. Rivas, A. Kelkar

Abstract:

Cementitious materials are an excellent example of a composite material with complex hierarchical features and random features that range from nanometer (nm) to millimeter (mm) scale. Multi-scale modeling of complex material systems requires starting from fundamental building blocks to capture the scale relevant features through associated computational models. In this paper, molecular dynamics (MD) modeling is employed to predict the effect of plasticizer additive on the mechanical properties of key hydrated cement constituent calcium-silicate-hydrate (CSH) at the molecular, nanometer scale level. Due to complexity, still unknown molecular configuration of CSH, a representative configuration widely accepted in the field of mineral Jennite is employed. The effectiveness of the Molecular Dynamics modeling to understand the predictive influence of material chemistry changes based on molecular / nanoscale models is demonstrated.

Keywords: Cement composite, Mechanical Properties, Molecular Dynamics, Plasticizer additives.

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1141 Monte Carlo Analysis and Fuzzy Sets for Uncertainty Propagation in SIS Performance Assessment

Authors: Fares Innal, Yves Dutuit, Mourad Chebila

Abstract:

The object of this work is the probabilistic performance evaluation of safety instrumented systems (SIS), i.e. the average probability of dangerous failure on demand (PFDavg) and the average frequency of failure (PFH), taking into account the uncertainties related to the different parameters that come into play: failure rate (λ), common cause failure proportion (β), diagnostic coverage (DC)... This leads to an accurate and safe assessment of the safety integrity level (SIL) inherent to the safety function performed by such systems. This aim is in keeping with the requirement of the IEC 61508 standard with respect to handling uncertainty. To do this, we propose an approach that combines (1) Monte Carlo simulation and (2) fuzzy sets. Indeed, the first method is appropriate where representative statistical data are available (using pdf of the relating parameters), while the latter applies in the case characterized by vague and subjective information (using membership function). The proposed approach is fully supported with a suitable computer code.

Keywords: Fuzzy sets, Monte Carlo simulation, Safety instrumented system, Safety integrity level.

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1140 Seismic Assessment of Old Existing RC Buildings on Madinah with Masonry Infilled Using Ambient Vibration Measurements

Authors: Tarek M. Alguhane, Ayman H. Khalil, M. N. Fayed, Ayman M. Ismail

Abstract:

Early pre-code reinforced concrete structures present undetermined resistance to earthquakes. This situation is particularly unacceptable in the case of essential structures, such as healthcare structures and pilgrims' houses. Amongst these, an existing old RC building in Madinah city (KSA) is seismically evaluated with and without infill wall and their dynamic characteristics are compared with measured values in the field using ambient vibration measurements (AVM). After updating the mathematical models for this building with the experimental results, three dimensional pushover analysis (Nonlinear static analysis) was carried out using commercial structural analysis software incorporating inelastic material properties for concrete, infill and steel. The purpose of this analysis is to evaluate the expected performance of structural systems by estimating, strength and deformation demands in design, and comparing these demands to available capacities at the performance levels of interest. The results summarized and discussed.

Keywords: Seismic Assessment, Pushover Analysis, Ambient vibration, Modal update.

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1139 An Expert System for Assessment of Learning Outcomes for ABET Accreditation

Authors: M. H. Imam, Imran A. Tasadduq, Abdul-Rahim Ahmad, Fahd M. Aldosari

Abstract:

Learning outcomes of a course (CLOs) and the abilities at the time of graduation referred to as Student Outcomes (SOs) are required to be assessed for ABET accreditation. A question in an assessment must target a CLO as well as an SO and must represent a required level of competence. This paper presents the idea of an Expert System (ES) to select a proper question to satisfy ABET accreditation requirements. For ES implementation, seven attributes of a question are considered including the learning outcomes and Bloom’s Taxonomy level. A database contains all the data about a course including course content topics, course learning outcomes and the CLO-SO relationship matrix. The knowledge base of the presented ES contains a pool of questions each with tags of the specified attributes. Questions and the attributes represent expert opinions. With implicit rule base the inference engine finds the best possible question satisfying the required attributes. It is shown that the novel idea of such an ES can be implemented and applied to a course with success. An application example is presented to demonstrate the working of the proposed ES.

Keywords: Expert system, student outcomes, course learning outcomes, question attributes.

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1138 Prediction of Compressive Strength of SCC Containing Bottom Ash using Artificial Neural Networks

Authors: Yogesh Aggarwal, Paratibha Aggarwal

Abstract:

The paper presents a comparative performance of the models developed to predict 28 days compressive strengths using neural network techniques for data taken from literature (ANN-I) and data developed experimentally for SCC containing bottom ash as partial replacement of fine aggregates (ANN-II). The data used in the models are arranged in the format of six and eight input parameters that cover the contents of cement, sand, coarse aggregate, fly ash as partial replacement of cement, bottom ash as partial replacement of sand, water and water/powder ratio, superplasticizer dosage and an output parameter that is 28-days compressive strength and compressive strengths at 7 days, 28 days, 90 days and 365 days, respectively for ANN-I and ANN-II. The importance of different input parameters is also given for predicting the strengths at various ages using neural network. The model developed from literature data could be easily extended to the experimental data, with bottom ash as partial replacement of sand with some modifications.

Keywords: Self compacting concrete, bottom ash, strength, prediction, neural network, importance factor.

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1137 Impact of Government Spending on Private Consumption and on the Economy: The Case of Thailand

Authors: Paitoon Kraipornsak

Abstract:

Government spending is categorized into consumption spending and capital spending. Three categories of private consumption are used: food consumption, nonfood consumption, and services consumption. The estimated model indicates substitution effects of government consumption spending on budget shares of private nonfood consumption and of government capital spending on budget share of private food consumption. However, the results do not indicate whether the negative effects of changes in the budget shares of the nonfood and the food consumption equates to reduce total private consumption. The concept of aggregate demand comprising consumption, investment, government spending (consumption spending and capital spending), export, and import are used to estimate their relationship by using the Vector Error Correction Mechanism. The study found no effect of government capital spending on either the private consumption or the growth of GDP while the government consumption spending has negative effect on the growth of GDP.

Keywords: Complementary effect, government capital spending, government consumption spending, private consumption on food, nonfood, and services, substitution effect, vector error correction mechanism.

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1136 Effect of Model Dimension in Numerical Simulation on Assessment of Water Inflow to Tunnel in Discontinues Rock

Authors: Hadi Farhadian, Homayoon Katibeh

Abstract:

Groundwater inflow to the tunnels is one of the most important problems in tunneling operation. The objective of this study is the investigation of model dimension effects on tunnel inflow assessment in discontinuous rock masses using numerical modeling. In the numerical simulation, the model dimension has an important role in prediction of water inflow rate. When the model dimension is very small, due to low distance to the tunnel border, the model boundary conditions affect the estimated amount of groundwater flow into the tunnel and results show a very high inflow to tunnel. Hence, in this study, the two-dimensional universal distinct element code (UDEC) used and the impact of different model parameters, such as tunnel radius, joint spacing, horizontal and vertical model domain extent has been evaluated. Results show that the model domain extent is a function of the most significant parameters, which are tunnel radius and joint spacing.

Keywords: Water inflow, Tunnel, Discontinues rock, Numerical simulation.

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1135 Study of Compaction in Hot-Mix Asphalt Using Computer Simulations

Authors: Kasthurirangan Gopalakrishnan, Naga Shashidhar, Xiaoxiong Zhong

Abstract:

During the process of compaction in Hot-Mix Asphalt (HMA) mixtures, the distance between aggregate particles decreases as they come together and eliminate air-voids. By measuring the inter-particle distances in a cut-section of a HMA sample the degree of compaction can be estimated. For this, a calibration curve is generated by computer simulation technique when the gradation and asphalt content of the HMA mixture are known. A two-dimensional cross section of HMA specimen was simulated using the mixture design information (gradation, asphalt content and air-void content). Nearest neighbor distance methods such as Delaunay triangulation were used to study the changes in inter-particle distance and area distribution during the process of compaction in HMA. Such computer simulations would enable making several hundreds of repetitions in a short period of time without the necessity to compact and analyze laboratory specimens in order to obtain good statistics on the parameters defined. The distributions for the statistical parameters based on computer simulations showed similar trends as those of laboratory specimens.

Keywords: Computer simulations, Hot-Mix Asphalt (HMA), inter-particle distance, image analysis, nearest neighbor

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1134 An MADM Framework toward Hierarchical Production Planning in Hybrid MTS/MTO Environments

Authors: H. Rafiei, M. Rabbani

Abstract:

This paper proposes a new decision making structure to determine the appropriate product delivery strategy for different products in a manufacturing system among make-to-stock, make-toorder, and hybrid strategy. Given product delivery strategies for all products in the manufacturing system, the position of the Order Penetrating Point (OPP) can be located regarding the delivery strategies among which location of OPP in hybrid strategy is a cumbersome task. In this regard, we employ analytic network process, because there are varieties of interrelated driving factors involved in choosing the right location. Moreover, the proposed structure is augmented with fuzzy sets theory in order to cope with the uncertainty of judgments. Finally, applicability of the proposed structure is proven in practice through a real industrial case company. The numerical results demonstrate the efficiency of the proposed decision making structure in order partitioning and OPP location.

Keywords: Hybrid make-to-stock/make-to-order, Multi-attribute decision making, Order partitioning, Order penetration point.

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1133 Classification of Political Affiliations by Reduced Number of Features

Authors: Vesile Evrim, Aliyu Awwal

Abstract:

By the evolvement in technology, the way of expressing opinions switched direction to the digital world. The domain of politics, as one of the hottest topics of opinion mining research, merged together with the behavior analysis for affiliation determination in texts, which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 were constituted by Linguistic Inquiry and Word Count (LIWC) features were tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that the “Decision Tree”, “Rule Induction” and “M5 Rule” classifiers when used with “SVM” and “IGR” feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “Function”, as an aggregate feature of the linguistic category, was found as the most differentiating feature among the 68 features with the accuracy of 81% in classifying articles either as Republican or Democrat.

Keywords: Politics, machine learning, feature selection, LIWC.

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1132 Probabilistic Electrical Power Generation Modeling Using Decimal to Binary Conversion

Authors: Ahmed S. Al-Abdulwahab

Abstract:

Generation system reliability assessment is an important task which can be performed using deterministic or probabilistic techniques. The probabilistic approaches have significant advantages over the deterministic methods. However, more complicated modeling is required by the probabilistic approaches. Power generation model is a basic requirement for this assessment. One form of the generation models is the well known capacity outage probability table (COPT). Different analytical techniques have been used to construct the COPT. These approaches require considerable mathematical modeling of the generating units. The unit-s models are combined to build the COPT which will add more burdens on the process of creating the COPT. Decimal to Binary Conversion (DBC) technique is widely and commonly applied in electronic systems and computing This paper proposes a novel utilization of the DBC to create the COPT without engaging in analytical modeling or time consuming simulations. The simple binary representation , “0 " and “1 " is used to model the states o f generating units. The proposed technique is proven to be an effective approach to build the generation model.

Keywords: Decimal to Binary, generation, reliability.

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1131 Machine Learning Techniques in Bank Credit Analysis

Authors: Fernanda M. Assef, Maria Teresinha A. Steiner

Abstract:

The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.

Keywords: Artificial Neural Networks, ANNs, classifier algorithms, credit risk assessment, logistic regression, machine learning, support vector machines.

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