Search results for: multi regression analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30974

Search results for: multi regression analysis

30284 Analytical Solution for Multi-Segmented Toroidal Shells under Uniform Pressure

Authors: Nosakhare Enoma, Alphose Zingoni

Abstract:

The requirements for various toroidal shell forms are increasing due to new applications, available storage space and the consideration of appearance. Because of the complexity of some of these structural forms, the finite element method is nowadays mainly used for their analysis, even for simple static studies. This paper presents an easy-to-use analytical algorithm for pressurized multi-segmented toroidal shells of revolution. The membrane solution, which acts as a particular solution of the bending-theory equations, is developed based on membrane theory of shells, and a general approach is formulated for quantifying discontinuity effects at the shell junctions using the well-known Geckeler’s approximation. On superimposing these effects, and applying the ensuing solution to the problem of the pressurized toroid with four segments, closed-form stress results are obtained for the entire toroid. A numerical example is carried out using the developed method. The analytical results obtained show excellent agreement with those from the finite element method, indicating that the proposed method can be also used for complementing and verifying FEM results, and providing insights on other related problems.

Keywords: bending theory of shells, membrane hypothesis, pressurized toroid, segmented toroidal vessel, shell analysis

Procedia PDF Downloads 298
30283 Deformation Severity Prediction in Sewer Pipelines

Authors: Khalid Kaddoura, Ahmed Assad, Tarek Zayed

Abstract:

Sewer pipelines are prone to deterioration over-time. In fact, their deterioration does not follow a fixed downward pattern. This is in fact due to the defects that propagate through their service life. Sewer pipeline defects are categorized into distinct groups. However, the main two groups are the structural and operational defects. By definition, the structural defects influence the structural integrity of the sewer pipelines such as deformation, cracks, fractures, holes, etc. However, the operational defects are the ones that affect the flow of the sewer medium in the pipelines such as: roots, debris, attached deposits, infiltration, etc. Yet, the process for each defect to emerge follows a cause and effect relationship. Deformation, which is the change of the sewer pipeline geometry, is one type of an influencing defect that could be found in many sewer pipelines due to many surrounding factors. This defect could lead to collapse if the percentage exceeds 15%. Therefore, it is essential to predict the deformation percentage before confronting such a situation. Accordingly, this study will predict the percentage of the deformation defect in sewer pipelines adopting the multiple regression analysis. Several factors will be considered in establishing the model, which are expected to influence the defamation defect severity. Besides, this study will construct a time-based curve to understand how the defect would evolve overtime. Thus, this study is expected to be an asset for decision-makers as it will provide informative conclusions about the deformation defect severity. As a result, inspections will be minimized and so the budgets.

Keywords: deformation, prediction, regression analysis, sewer pipelines

Procedia PDF Downloads 168
30282 Effect of Irregularities on Seismic Performance of Building

Authors: Snehal Mevada, Darshana Bhatt, Aryan Kalthiya, Neel Parmar, Vishal Baraiya, Dhruvit Bhanderi, Tisha Patel

Abstract:

In multi-storeyed framed buildings, damage occurring from earthquake ground motion generally initiates at locations of structural weaknesses present in the lateral load-resisting frame. In some cases, these weaknesses may be created by discontinuities in stiffness, mass, plan, and torsion. Such discontinuity between storeys is often associated with sudden variations in the vertical geometric irregularities and plan irregularities. Vertical irregularities are structures with a soft storey that can further be broken down into the different types of irregularities as well as their severity for a more refined assessment tool pushover analysis which is one of the methods available for evaluating building against earthquake loads. So, it is very necessary to analyse and understand the seismic performance of the irregular structure in order to reduce the damage which occurs during an earthquake. In this project, a multi-storey (G+4) RCC building with four irregularities (stiffness, mass, plan, torsion) is studied for earthquake loads using the response spectrum method (dynamic analysis) and STADD PRO. All analyses have been done for seismic zone IV and for Medium Soil. In this study effects of different irregularities are analysed based on storey displacement, storey drift, and storey shear.

Keywords: comparison of regular and irregular structure, dynamic analysis, mass irregularity, plan irregularity, response spectrum method, stiffness irregularity, seismic performance, torsional irregularity, STAAD PRO

Procedia PDF Downloads 59
30281 Multi-Criteria Decision-Making in Ranking Drinking Water Supply Options (Case Study: Tehran City)

Authors: Mohsen Akhlaghi, Tahereh Ebrahimi

Abstract:

Considering the increasing demand for water and limited resources, there is a possibility of a water crisis in the not-so-distant future. Therefore, to prevent this crisis, other options for drinking water supply should be examined. In this regard, the application of multi-criteria decision-making methods in various aspects of water resource management and planning has always been of great interest to researchers. In this report, six options for supplying drinking water to Tehran City were considered. Then, experts' opinions were collected through matrices and questionnaires, and using the TOPSIS method, which is one of the types of multi-criteria decision-making methods, they were calculated and analyzed. In the TOPSIS method, the options were ranked by calculating their proximity to the ideal (Ci). The closer the numerical value of Ci is to one, the more desirable the option is. Based on this, the option with the optimization pattern of water consumption, with Ci = 0.9787, is the best option among the proposed options for supplying drinking water to Tehran City. The other options, in order of priority, are rainwater harvesting, wastewater reuse, increasing current water supply sources, desalination and its transfer, and transferring water from freshwater sources between basins. In conclusion, the findings of this study highlight the importance of exploring alternative drinking water supply options and utilizing multi-criteria decision-making approaches to address the potential water crisis.

Keywords: multi-criteria decision, sustainable development, topsis, water supply

Procedia PDF Downloads 48
30280 Urban Rail Transit CBTC Computer Interlocking Subsystem Relying on Multi-Template Pen Point Tracking Algorithm

Authors: Xinli Chen, Xue Su

Abstract:

In the urban rail transit CBTC system, interlocking is considered one of the most basic sys-tems, which has the characteristics of logical complexity and high-security requirements. The development and verification of traditional interlocking subsystems are entirely manual pro-cesses and rely too much on the designer, which often hides many uncertain factors. In order to solve this problem, this article is based on the multi-template nib tracking algorithm for model construction and verification, achieving the main safety attributes and using SCADE for formal verification. Experimental results show that this method helps to improve the quality and efficiency of interlocking software.

Keywords: computer interlocking subsystem, penpoint tracking, communication-based train control system, multi-template tip tracking

Procedia PDF Downloads 142
30279 Gender-Specific Association between Obstructive Sleep Apnea and Cognitive Impairment among Adults: A Population-based UK Biobank Study

Authors: Ke Qiu, Minzi Mao, Jianjun Ren, Yu Zhao

Abstract:

Although much has been done to investigate the influence of obstructive sleep apnea (OSA) on cognitive function, little attention has been paid to the role which gender differences play in this association. In the present study, we aim to explore the gender-specific association between OSA and cognitive impairment. Participants from UK biobank who have completed at least one of the five baseline cognitive tests (visuospatial memory, prospective memory, fluid intelligence, short numeric memory and reaction time) were included and were further categorized into three groups: (1) OSA, (2) self-reported snoring but without OSA, and (3) healthy controls (without OSA or snoring). Multivariable regression analysis was performed to examine the associations among snoring, OSA and performance of each of the five cognitive domains. A total of 267,889 participants (47% male, mean age: 57 years old) were included in our study. In the multivariable regression analysis, female participants in the OSA group had a higher risk of having poor prospective memory (OR: 1.24, 95% CI: 1.02~1.50, p = 0.03). Meanwhile, among female participants, OSA were inversely associated with the performances of fluid intelligence (β: -0.29, 95% CI: -0.46~-0.13, p < 0.001) and short-numeric memory (β: -0.14, 95% CI: -0.35~0.08, p = 0.02). In contrast, among male participants, no significant association was observed between OSA and impairment of the five cognitive domains. Overall, OSA was significantly associated with cognitive impairment in female participants rather than in male participants, indicating that more special attention and timely interventions should be given to female OSA patients to prevent further cognitive impairment.

Keywords: obstructive sleep apnea (OSA), cognitive impairment, gender-specific association, UK biobank

Procedia PDF Downloads 136
30278 Modelling Conceptual Quantities Using Support Vector Machines

Authors: Ka C. Lam, Oluwafunmibi S. Idowu

Abstract:

Uncertainty in cost is a major factor affecting performance of construction projects. To our knowledge, several conceptual cost models have been developed with varying degrees of accuracy. Incorporating conceptual quantities into conceptual cost models could improve the accuracy of early predesign cost estimates. Hence, the development of quantity models for estimating conceptual quantities of framed reinforced concrete structures using supervised machine learning is the aim of the current research. Using measured quantities of structural elements and design variables such as live loads and soil bearing pressures, response and predictor variables were defined and used for constructing conceptual quantities models. Twenty-four models were developed for comparison using a combination of non-parametric support vector regression, linear regression, and bootstrap resampling techniques. R programming language was used for data analysis and model implementation. Gross soil bearing pressure and gross floor loading were discovered to have a major influence on the quantities of concrete and reinforcement used for foundations. Building footprint and gross floor loading had a similar influence on beams and slabs. Future research could explore the modelling of other conceptual quantities for walls, finishes, and services using machine learning techniques. Estimation of conceptual quantities would assist construction planners in early resource planning and enable detailed performance evaluation of early cost predictions.

Keywords: bootstrapping, conceptual quantities, modelling, reinforced concrete, support vector regression

Procedia PDF Downloads 198
30277 Intelligent Agent Travel Reservation System Requirements Definitions Using the Behavioral Patterns Analysis (BPA) Approach

Authors: Assem El-Ansary

Abstract:

This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Intelligent Agent Reservation System (IARS). The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are developing the Behavioral Pattern Analysis (BPA) modeling methodology, and developing an interactive software tool (DECISION) which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, intelligent agent, reservation system, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases

Procedia PDF Downloads 468
30276 Multiscale Structures and Their Evolution in a Screen Cylinder Wake

Authors: Azlin Mohd Azmi, Tongming Zhou, Akira Rinoshika, Liang Cheng

Abstract:

The turbulent structures in the wake (x/d =10 to 60) of a screen cylinder have been reduced to understand the roles of the various structures as evolving downstream by comparing with those obtained in a solid circular cylinder wake at Reynolds number, Re of 7000. Using a wavelet multi-resolution technique, the flow structures are decomposed into a number of wavelet components based on their central frequencies. It is observed that in the solid cylinder wake, large-scale structures (of frequency f0 and 1.2 f0) make the largest contribution to the Reynolds stresses although they start to lose their roles significantly at x/d > 20. In the screen cylinder wake, the intermediate-scale structures (2f0 and 4f0) contribute the most to the Reynolds stresses at x/d =10 before being taken over by the large-scale structures (f0) further downstream.

Keywords: turbulent structure, screen cylinder, vortex, wavelet multi-resolution analysis

Procedia PDF Downloads 442
30275 Multi-Modal Visualization of Working Instructions for Assembly Operations

Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger

Abstract:

Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.

Keywords: assembly, assistive technologies, augmented reality, manufacturing, visualization

Procedia PDF Downloads 150
30274 Experimental Design and Optimization of Diesel Oil Desulfurization Process by Adsorption Processes

Authors: M. Firoz Kalam, Wilfried Schuetz, Jan Hendrik Bredehoeft

Abstract:

Thiophene sulfur compounds' removal from diesel oil by batch adsorption process using commercial powdered activated carbon was designed and optimized in two-level factorial design method. This design analysis was used to find out the effects of operating parameters directing the adsorption process, such as amount of adsorbent, temperature and stirring time. The desulfurization efficiency was considered the response or output variable. Results showed that the stirring time had the largest effects on sulfur removal efficiency as compared with other operating parameters and their interactions under the experimental ranges studied. A regression model was generated to observe the closeness between predicted and experimental values. The three-dimensional plots and contour plots of main factors were generated according to the regression results to observe the optimal points.

Keywords: activated carbon, adsorptive desulfurization, factorial design, process optimization

Procedia PDF Downloads 152
30273 Predictor Factors in Predictive Model of Soccer Talent Identification among Male Players Aged 14 to 17 Years

Authors: Muhamad Hafiz Ismail, Ahmad H., Nelfianty M. R.

Abstract:

The longitudinal study is conducted to identify predictive factors of soccer talent among male players aged 14 to 17 years. Convenience sampling involving elite respondents (n=20) and sub-elite respondents (n=20) male soccer players. Descriptive statistics were reported as frequencies and percentages. The inferential statistical analysis is used to report the status of reliability, independent samples t-test, paired samples t-test, and multiple regression analysis. Generally, there are differences in mean of height, muscular strength, muscular endurance, cardiovascular endurance, task orientation, cognitive anxiety, self-confidence, juggling skills, short pass skills, long pass skills, dribbling skills, and shooting skills for 20 elite players and sub-elite players. Accordingly, there was a significant difference between pre and post-test for thirteen variables of height, weight, fat percentage, muscle strength, muscle endurance, cardiovascular endurance, flexibility, BMI, task orientation, juggling skills, short pass skills, a long pass skills, and dribbling skills. Based on the first predictive factors (physical), second predictive factors (fitness), third predictive factors (psychological), and fourth predictive factors (skills in playing football) pledged to the soccer talent; four multiple regression models were produced. The first predictive factor (physical) contributed 53.5 percent, supported by height and percentage of fat in soccer talents. The second predictive factor (fitness) contributed 63.2 percent and the third predictive factors (psychology) contributed 66.4 percent of soccer talent. The fourth predictive factors (skills) contributed 59.0 percent of soccer talent. The four multiple regression models could be used as a guide for talent scouting for soccer players of the future.

Keywords: soccer talent identification, fitness and physical test, soccer skills test, psychological test

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30272 A New Method to Estimate the Low Income Proportion: Monte Carlo Simulations

Authors: Encarnación Álvarez, Rosa M. García-Fernández, Juan F. Muñoz

Abstract:

Estimation of a proportion has many applications in economics and social studies. A common application is the estimation of the low income proportion, which gives the proportion of people classified as poor into a population. In this paper, we present this poverty indicator and propose to use the logistic regression estimator for the problem of estimating the low income proportion. Various sampling designs are presented. Assuming a real data set obtained from the European Survey on Income and Living Conditions, Monte Carlo simulation studies are carried out to analyze the empirical performance of the logistic regression estimator under the various sampling designs considered in this paper. Results derived from Monte Carlo simulation studies indicate that the logistic regression estimator can be more accurate than the customary estimator under the various sampling designs considered in this paper. The stratified sampling design can also provide more accurate results.

Keywords: poverty line, risk of poverty, auxiliary variable, ratio method

Procedia PDF Downloads 437
30271 The Associations between Self-Determined Motivation and Physical Activity in Patients with Coronary Heart Disease

Authors: I. Hua Chu, Hsiang-Chi Yu, Hsuan Su

Abstract:

Purpose: To examine the associations between self-determined motivation and physical activity in patients with coronary heart disease (CHD) in a longitudinal study. Methods: Patients with CHD were recruited for this study. Their motivations for exercise were measured by the Behavioral Regulation in Exercise Questionnaire-2 (BREQ-2). Physical activity was assessed using the 7-day physical activity recall questionnaire. Duration and energy expenditure of moderate to vigorous physical activity (MVPA) were used in data analysis. All outcome measures were assessed at baseline and 12 months follow up. Data were analyzed using Pearson correlation analysis and regression analysis. Results: The results of the 45 participants (mean age 60.24 yr; 90.2% male) revealed that there were significant negative correlations between amotivation at baseline and duration (r=-.295, p=.049) and energy expenditure (r=-.300, p=.045) of MVPA at 12 months. In contrast, there were significant positive correlations between calculated relative autonomy index (RAI) at baseline and duration (r=.377, p=.011) and energy expenditure (r=.382, p=.010) of MVPA at 12 months. There was no significant correlation between other subscales of the BREQ-2 and duration or energy expenditure of MVPA. Regression analyses revealed that RAI was a significant predictor of duration (p=.011) and energy expenditure (p=.010) of MVPA at 12 months follow-up. Conclusions: These results suggest that the relative degree of self-determined motivation could predict long-term MVPA behaviors in CHD patients. Physical activity interventions are recommended to target enhancing one’s identified and intrinsic motivation to increase the likelihood of physical activity participation in this population.

Keywords: self-determined motivation, physical activity, coronary heart disease, relative autonomy index (RAI)

Procedia PDF Downloads 415
30270 Probabilistic-Based Design of Bridges under Multiple Hazards: Floods and Earthquakes

Authors: Kuo-Wei Liao, Jessica Gitomarsono

Abstract:

Bridge reliability against natural hazards such as floods or earthquakes is an interdisciplinary problem that involves a wide range of knowledge. Moreover, due to the global climate change, engineers have to design a structure against the multi-hazard threats. Currently, few of the practical design guideline has included such concept. The bridge foundation in Taiwan often does not have a uniform width. However, few of the researches have focused on safety evaluation of a bridge with a complex pier. Investigation of the scouring depth under such situation is very important. Thus, this study first focuses on investigating and improving the scour prediction formula for a bridge with complicated foundation via experiments and artificial intelligence. Secondly, a probabilistic design procedure is proposed using the established prediction formula for practical engineers under the multi-hazard attacks.

Keywords: bridge, reliability, multi-hazards, scour

Procedia PDF Downloads 355
30269 Real-Time Multi-Vehicle Tracking Application at Intersections Based on Feature Selection in Combination with Color Attribution

Authors: Qiang Zhang, Xiaojian Hu

Abstract:

In multi-vehicle tracking, based on feature selection, the tracking system efficiently tracks vehicles in a video with minimal error in combination with color attribution, which focuses on presenting a simple and fast, yet accurate and robust solution to the problem such as inaccurately and untimely responses of statistics-based adaptive traffic control system in the intersection scenario. In this study, a real-time tracking system is proposed for multi-vehicle tracking in the intersection scene. Considering the complexity and application feasibility of the algorithm, in the object detection step, the detection result provided by virtual loops were post-processed and then used as the input for the tracker. For the tracker, lightweight methods were designed to extract and select features and incorporate them into the adaptive color tracking (ACT) framework. And the approbatory online feature selection algorithms are integrated on the mature ACT system with good compatibility. The proposed feature selection methods and multi-vehicle tracking method are evaluated on KITTI datasets and show efficient vehicle tracking performance when compared to the other state-of-the-art approaches in the same category. And the system performs excellently on the video sequences recorded at the intersection. Furthermore, the presented vehicle tracking system is suitable for surveillance applications.

Keywords: real-time, multi-vehicle tracking, feature selection, color attribution

Procedia PDF Downloads 150
30268 Performance Evaluation of a Prioritized, Limited Multi-Server Processor-Sharing System that Includes Servers with Various Capacities

Authors: Yoshiaki Shikata, Nobutane Hanayama

Abstract:

We present a prioritized, limited multi-server processor sharing (PS) system where each server has various capacities, and N (≥2) priority classes are allowed in each PS server. In each prioritized, limited server, different service ratio is assigned to each class request, and the number of requests to be processed is limited to less than a certain number. Routing strategies of such prioritized, limited multi-server PS systems that take into account the capacity of each server are also presented, and a performance evaluation procedure for these strategies is discussed. Practical performance measures of these strategies, such as loss probability, mean waiting time, and mean sojourn time, are evaluated via simulation. In the PS server, at the arrival (or departure) of a request, the extension (shortening) of the remaining sojourn time of each request receiving service can be calculated by using the number of requests of each class and the priority ratio. Utilising a simulation program which executes these events and calculations, the performance of the proposed prioritized, limited multi-server PS rule can be analyzed. From the evaluation results, most suitable routing strategy for the loss or waiting system is clarified.

Keywords: processor sharing, multi-server, various capacity, N-priority classes, routing strategy, loss probability, mean sojourn time, mean waiting time, simulation

Procedia PDF Downloads 316
30267 Comprehensive Risk Assessment Model in Agile Construction Environment

Authors: Jolanta Tamošaitienė

Abstract:

The article focuses on a developed comprehensive model to be used in an agile environment for the risk assessment and selection based on multi-attribute methods. The model is based on a multi-attribute evaluation of risk in construction, and the determination of their optimality criterion values are calculated using complex Multiple Criteria Decision-Making methods. The model may be further applied to risk assessment in an agile construction environment. The attributes of risk in a construction project are selected by applying the risk assessment condition to the construction sector, and the construction process efficiency in the construction industry accounts for the agile environment. The paper presents the comprehensive risk assessment model in an agile construction environment. It provides a background and a description of the proposed model and the developed analysis of the comprehensive risk assessment model in an agile construction environment with the criteria.

Keywords: assessment, environment, agile, model, risk

Procedia PDF Downloads 236
30266 Transport Related Air Pollution Modeling Using Artificial Neural Network

Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

Abstract:

Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

Procedia PDF Downloads 505
30265 Multi-Objective Optimization of an Aerodynamic Feeding System Using Genetic Algorithm

Authors: Jan Busch, Peter Nyhuis

Abstract:

Considering the challenges of short product life cycles and growing variant diversity, cost minimization and manufacturing flexibility increasingly gain importance to maintain a competitive edge in today’s global and dynamic markets. In this context, an aerodynamic part feeding system for high-speed industrial assembly applications has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. The aerodynamic part feeding system outperforms conventional systems with respect to its process safety, reliability, and operating speed. In this paper, a multi-objective optimisation of the aerodynamic feeding system regarding the orientation rate, the feeding velocity and the required nozzle pressure is presented.

Keywords: aerodynamic feeding system, genetic algorithm, multi-objective optimization, workpiece orientation

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30264 Influential Factors on Woodcarvings in Traditional Malay Houses of Negeri Sembilan, Malaysia

Authors: Nurdiyana Zainal Abidin, Raja Nafida Raja Shahminan, Fawazul Khair Ibrahim

Abstract:

Timber vernacular houses in Malaysia are unique heritage buildings which can be identified through their designs, structure, architectural elements and ornamentations. Woodcarvings are common forms of ornamentations and decorations in Traditional Malay Houses and they can be found throughout Malaysia including in Negeri Sembilan. As a multi-cultural, multi-racial, and multi-religion state which uniquely practices the matrilineal social system, Negeri Sembilan has a strong connection to its’ history and heritage and in particular the distinctive vernacular architecture. The purpose of this paper is to underline the factors that influence the woodcarvings in Traditional Malay Houses in Negeri Sembilan, Malaysia. The houses studied were from the archives of measured drawings in Center of Built Environment in the Malay World (KALAM), Universiti Teknologi Malaysia (UTM). The findings indicated several factors influencing the woodcarver’s works and also the applications of the woodcarvings such as religious factors, cultural factors and political factors. These factors among several other shows that woodcarvings were predetermined before being carved and that they were not just merely placed without reason but are functioning pieces of aesthetic ornamentation.

Keywords: influences, traditional Malay houses, woodcarvings, multi-cultural

Procedia PDF Downloads 492
30263 Response of Buildings with Soil-Structure Interaction with Varying Soil Types

Authors: Shreya Thusoo, Karan Modi, Rajesh Kumar, Hitesh Madahar

Abstract:

Over the years, it has been extensively established that the practice of assuming a structure being fixed at base, leads to gross errors in evaluation of its overall response due to dynamic loadings and overestimations in design. The extent of these errors depends on a number of variables; soil type being one of the major factor. This paper studies the effect of Soil Structure Interaction (SSI) on multi-storey buildings with varying under-laying soil types after proper validation of the effect of SSI. Analysis for soft, stiff and very stiff base soils has been carried out, using a powerful Finite Element Method (FEM) software package ANSYS v14.5. Results lead to some very important conclusions regarding time period, deflection and acceleration responses.

Keywords: dynamic response, multi-storey building, soil-structure interaction, varying soil types

Procedia PDF Downloads 463
30262 Detection Efficient Enterprises via Data Envelopment Analysis

Authors: S. Turkan

Abstract:

In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: data envelopment analysis, super efficiency, logistic regression, financial ratios

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30261 Deposit Characteristics of Jakarta, Indonesia: A Stratigraphy Study of Jakarta Subsurface

Authors: Girlly Marchlina Listyono, Abdurrokhim Abdurrokhim, Emi Sukiyah, Pulung Arya Pranantya

Abstract:

Jakarta Area is composed by deposit which has various lithology characteristics. Based on its lithology types, colors, textures, mineral dan organic content from 22 wells scattered on Jakarta, lithofacies analysis and intra-wells data correlation can be done. From the analysis, it can be interpretated that Jakarta deposit deposited in marine, transition and terrestrial depositional environments. Terrestrial deposit characterized by domination of relatively coarse clastics and content of remaining roots, woods, plants, high content of quartz, lithic fragment, calcareous and oxidated appearace. The thickness of terrestrial deposit is thickening to south. Transitional deposit characterized by fine to medium clastics with dark color, high content of organic matter, various thickness in any ways. Marine deposit characterized by finer clastics, contain remain of shells, fosil, coral, limestone fragments, glauconites, calcareous. Marine deposit relatively thickening to north. Those lateral variety caused by tectonic, subsidence and stratigraphic condition. Deposition of Jakarta deposit from the data research was started on marine depositional environment which surrounded by the event of cycle of regression and transgression then ended with regression which ongoing until form shore line in north Jakarta nowadays.

Keywords: deposit, Indonesia, Jakarta, sediment, stratigraphy

Procedia PDF Downloads 236
30260 A Multi-Attribute Utility Model for Performance Evaluation of Sustainable Banking

Authors: Sonia Rebai, Mohamed Naceur Azaiez, Dhafer Saidane

Abstract:

In this study, we develop a performance evaluation model based on a multi-attribute utility approach aiming at reaching the sustainable banking (SB) status. This model is built accounting for various banks’ stakeholders in a win-win paradigm. In addition, it offers the opportunity for adopting a global measure of performance as an indication of a bank’s sustainability degree. This measure is referred to as banking sustainability performance index (BSPI). This index may constitute a basis for ranking banks. Moreover, it may constitute a bridge between the assessment types of financial and extra-financial rating agencies. A real application is performed on three French banks.

Keywords: multi-attribute utility theory, performance, sustainable banking, financial rating

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30259 Performance of the Cmip5 Models in Simulation of the Present and Future Precipitation over the Lake Victoria Basin

Authors: M. A. Wanzala, L. A. Ogallo, F. J. Opijah, J. N. Mutemi

Abstract:

The usefulness and limitations in climate information are due to uncertainty inherent in the climate system. For any given region to have sustainable development it is important to apply climate information into its socio-economic strategic plans. The overall objective of the study was to assess the performance of the Coupled Model Inter-comparison Project (CMIP5) over the Lake Victoria Basin. The datasets used included the observed point station data, gridded rainfall data from Climate Research Unit (CRU) and hindcast data from eight CMIP5. The methodology included trend analysis, spatial analysis, correlation analysis, Principal Component Analysis (PCA) regression analysis, and categorical statistical skill score. Analysis of the trends in the observed rainfall records indicated an increase in rainfall variability both in space and time for all the seasons. The spatial patterns of the individual models output from the models of MPI, MIROC, EC-EARTH and CNRM were closest to the observed rainfall patterns.

Keywords: categorical statistics, coupled model inter-comparison project, principal component analysis, statistical downscaling

Procedia PDF Downloads 354
30258 An Efficient Machine Learning Model to Detect Metastatic Cancer in Pathology Scans Using Principal Component Analysis Algorithm, Genetic Algorithm, and Classification Algorithms

Authors: Bliss Singhal

Abstract:

Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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30257 A Case Study on the Drivers of Household Water Consumption for Different Socio-Economic Classes in Selected Communities of Metro Manila, Philippines

Authors: Maria Anjelica P. Ancheta, Roberto S. Soriano, Erickson L. Llaguno

Abstract:

The main purpose of this study is to examine whether there is a significant relationship between socio-economic class and household water supply demand, through determining or verifying the factors governing water use consumption patterns of households from a sampling from different socio-economic classes in Metro Manila, the national capital region of the Philippines. This study is also an opportunity to augment the lack of local academic literature due to the very few publications on urban household water demand after 1999. In over 600 Metro Manila households, a rapid survey was conducted on their average monthly water consumption and habits on household water usage. The questions in the rapid survey were based on an extensive review of literature on urban household water demand. Sample households were divided into socio-economic classes A-B and C-D. Cluster analysis, dummy coding and outlier tests were done to prepare the data for regression analysis. Subsequently, backward stepwise regression analysis was used in order to determine different statistical models to describe the determinants of water consumption. The key finding of this study is that the socio-economic class of a household in Metro Manila is a significant factor in water consumption. A-B households consume more water in contrast to C-D families based on the mean average water consumption for A-B and C-D households are 36.75 m3 and 18.92 m3, respectively. The most significant proxy factors of socio-economic class that were related to household water consumption were examined in order to suggest improvements in policy formulation and household water demand management.

Keywords: household water uses, socio-economic classes, urban planning, urban water demand management

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30256 Multi-Band, Polarization Insensitive, Wide Angle Receptive Metamaterial Absorber for Microwave Applications

Authors: Lincy Stephen, N. Yogesh, G. Vasantharajan, V. Subramanian

Abstract:

This paper presents the design and simulation of a five band metamaterial absorber at microwave frequencies. The absorber unit cell consists of squares and strips arranged as the top layer and a metallic ground plane as the bottom layer on a dielectric substrate. Simulation results show five near perfect absorption bands at 3.15 GHz, 7.15 GHz, 11.12 GHz, 13.87 GHz, and 16.85 GHz with absorption magnitudes 99.68%, 99.05%, 96.98%, 98.36% and 99.44% respectively. Further, the proposed absorber exhibits polarization insensitivity and wide angle receptivity. The surface current analysis is presented to explain the mechanism of absorption in the structure. With these preferable features, the proposed absorber can be excellent choice for potential applications such as electromagnetic interference (EMI) shielding, radar cross section reduction.

Keywords: electromagnetic absorber, metamaterial, multi- band, polarization insensitive, wide angle receptive

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30255 Multi-Perspective Learning in a Real Production Plant Using Experiential Learning in Heterogeneous Groups to Develop System Competencies for Production System Improvements

Authors: Marlies Achenbach

Abstract:

System competencies play a key role to ensure an effective and efficient improvement of production systems. Thus, there can be observed an increasing demand for developing system competencies in industry as well as in engineering education. System competencies consist of the following two main abilities: Evaluating the current state of a production system and developing a target state. The innovative course ‘multi-perspective learning in a real production plant (multi real)’ is developed to create a learning setting that supports the development of these system competencies. Therefore, the setting combines two innovative aspects: First, the Learning takes place in heterogeneous groups formed by students as well as professionals and managers from industry. Second, the learning takes place in a real production plant. This paper presents the innovative didactic concept of ‘multi real’ in detail, which will initially be implemented in October/November 2016 in the industrial engineering, logistics and mechanical master’s program at TU Dortmund University.

Keywords: experiential learning, heterogeneous groups, improving production systems, system competencies

Procedia PDF Downloads 404