Search results for: financial models

Authors: Kristýna Pokorná, Petr Teplý

Abstract:

This paper focuses on sovereign credit risk meaning a hot topic related to the current Eurozone crisis. In the light of the recent financial crisis, market perception of the creditworthiness of individual sovereigns has changed significantly. Before the outbreak of the financial crisis, market participants did not differentiate between credit risk born by individual states despite different levels of public indebtedness. In the proceeding of the financial crisis, the market participants became aware of the worsening fiscal situation in the European countries and started to discriminate among government issuers. Concerns about the increasing sovereign risk were reflected in surging sovereign risk premium. The main of this paper is to shed light on the characteristics of the sovereign risk with the special attention paid to the mutual relation between credit spread and the CDS premium as the main measures of the sovereign risk premium.

Keywords: cointegration, credit default swap, credit risk, credit spread, sovereign risk

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1900

Authors: Edward A. Osifodunrin, Jose Manuel Dias Lopes

Abstract:

In Nigeria, enormous efforts/resources had, over the years, been expended on promoting financial inclusion (FI); however, it is seemingly discouraging that many of its self-declared targets on FI remained unachieved, especially amongst the Rural Dwellers and Actors in the Informal Sectors (RDAIS). Expectedly, many reasons had been earmarked for these failures: low literacy level, huge informal/rural sectors etc. This study posits that in spite of these truly-debilitating factors, these FI policy failures could have been avoided or mitigated if the principles of active and better-managed citizens’ participation had been strictly followed in the (re)design/implementation of its FI policies. In other words, in a bid to mitigate the prevalent financial exclusion (FE) in Nigeria, this study hypothesizes the significant positive impact of involving the RDAIS in policy-wide decision making in the FI domain, backed by a preliminary empirical validation. Also, the study introduces the RDAIS-focused Participatory Financial Inclusion Policy (PFIP) as a major FI policy regeneration/improvement tool. The three categories of respondents that served as research subjects are FI experts in Nigeria (n = 72), RDAIS from the very rural/remote village of Unguwar Dogo in Northern Nigeria (n = 43) and RDAIS from another rural village of Sekere (n = 56) in the Southern region of Nigeria. Using survey design (5-point Likert scale questionnaires), random/stratified sampling, and descriptive/inferential statistics, the study often recorded independent consensus (amongst these three categories of respondents) that RDAIS’s active participation in iterative FI policy initiation, (re)design, implementation, (re)evaluation could indeed give improved FI outcomes. However, few questionnaire items also recorded divergent opinions and various statistically (in)significant differences on the mean scores of these three categories. The PFIP (or any customized version of it) should then be carefully integrated into the NFIS of Nigeria (and possibly in the NFIS of other developing countries) to truly/fully provide FI policy integration for these excluded RDAIS and arrest the prevalence of FE.

Keywords: Citizens’ participation, development, financial inclusion, formal financial services, national financial inclusion strategy, participatory financial inclusion policy, rural dwellers and actors in the informal sectors.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 602

Authors: Anna Rogozińska-Pawełczyk

Abstract:

A psychological contract is an agreement between the employer and an employee that covers the parties’ informal and frequently non-verbalized obligations and expectations towards each other. The contract is a cognitive pattern-governing employee’s behaviour in the organization. A gap between employee’s expectations and the organizational reality may lead to difficult-to-solve conflicts or cause the employee to modify their behaviour towards organizational values and goals, if they are willing and ready to verbalize their expectations. The article discusses psychological contracts in the financial institutions in Poland. Its theoretical part outlines the types of psychological contracts in organizations (relational, transactional, and balanced) and shows the process of their verbalization. The purpose of the article is to present how the type of the psychological contract relates to employee’s readiness to verbalize it. The article ends with conclusions arising from the study.

Keywords: Customer contact staff in banks, employee expectations, financial institutions, mutual expectations, psychological contract, verbalization of the psychological contract.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1746

Authors: Neerja Bhatnagar, Ben A. Juliano, Renee S. Renner

Abstract:

This paper presents data annotation models at five levels of granularity (database, relation, column, tuple, and cell) of relational data to address the problem of unsuitability of most relational databases to express annotations. These models do not require any structural and schematic changes to the underlying database. These models are also flexible, extensible, customizable, database-neutral, and platform-independent. This paper also presents an SQL-like query language, named Annotation Query Language (AnQL), to query annotation documents. AnQL is simple to understand and exploits the already-existent wide knowledge and skill set of SQL.

Keywords: Annotation query language, data annotations, data annotation models, semantic data annotations.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1752

Authors: Dr.K.Sri Rama Krishna, J.Lakshmi Narayana, Dr.L.Pratap Reddy

Abstract:

Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that are compact and light in weight. They are generally economical to produce since they are readily adaptable to hybrid and monolithic integrated circuit (IC) fabrication technologies at RF and microwave frequencies. Although, the existing EM simulation models used for the synthesis and analysis of microstrip lines are reasonably accurate, they are computationally intensive and time consuming. Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation and optimization. After learning and abstracting from microwave data, through a process called training, neural network models are used during microwave design to provide instant answers to the task learned.This paper presents simple and accurate ANN models for the synthesis and analysis of Microstrip lines to more accurately compute the characteristic parameters and the physical dimensions respectively for the required design specifications.

Keywords: Neural Models, Algorithms, Microstrip Lines, Analysis, Synthesis

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2088

Authors: Chrysoula Karathanasi, Senad Karavdic, Angela Odero, Michèle Baumann

Abstract:

It is not only the economic determinants that impact on life conditions, but maintaining a good level of life satisfaction (LS) may also be an important challenge currently. In Luxembourg, university students receive financial aid from the government. They are then registered at the Centre for Documentation and Information on Higher Education (CEDIES). Luxembourg is built on migration with almost half its population consisting of foreigners. It is upon this basis that our research aims to analyze the associations with mental health factors (health satisfaction, psychological quality of life, worry), perceived financial situation, career attitudes (adaptability, optimism, knowledge, planning) and LS, for non-Luxembourgish and native postgraduate students. Between 2012 and 2013, postgraduates registered at CEDIES were contacted by post and asked to participate in an online survey with either the option of English or French. The study population comprised of 644 respondents. Our statistical analysis excluded: those born abroad who had Luxembourgish citizenship, or those born in Luxembourg who did not have citizenship. Two groups were formed one consisting 147 non-Luxembourgish and the other 284 natives. A single item measured LS (1=not at all satisfied to 10=very satisfied). Bivariate tests, correlations and multiple linear regression models were used in which only significant relationships (p<0.05) were integrated. Among the two groups no differences were found between LS indicators (7.8/10 non-Luxembourgish; 8.0/10 natives) as both were higher than the European indicator of 7.2/10 (for 25-34 years). In the case of non-Luxembourgish students, they were older than natives (29.3 years vs. 26.3 years) perceived their financial situation as more difficult, and a higher percentage of their parents had an education level higher than a Bachelor's degree (father 59.2% vs 44.6% for natives; mother 51.4% vs 33.7% for natives). In addition, the father’s education was related to the LS of postgraduates and the higher was the score, the greater was the contribution to LS. Whereas for native students, when their scores of health satisfaction and career optimism were higher, their LS’ score was higher. For both groups their LS was linked to mental health-related factors, perception of their financial situation, career optimism, adaptability and planning. The higher the psychological quality of life score was, the greater the LS of postgraduates’ was. Good health and positive attitudes related to the job market enhanced their LS indicator.

Keywords: Career attitudes, fathers’ education level, life satisfaction, mental health.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1440

Authors: B. A. Gobin, R. K. Subramanian

Abstract:

This paper gives an overview of how an OWL ontology has been created to represent template knowledge models defined in CML that are provided by CommonKADS. CommonKADS is a mature knowledge engineering methodology which proposes the use of template knowledge model for knowledge modelling. The aim of developing this ontology is to present the template knowledge model in a knowledge representation language that can be easily understood and shared in the knowledge engineering community. Hence OWL is used as it has become a standard for ontology and also it already has user friendly tools for viewing and editing.

Keywords: Ontology, OWL, Template Knowledge Models, CommonKADS

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1738

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, financial ratios, BCC model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 838

Authors: Pankaj K. Gupta, Krishnan V. Pagalthivarthi

Abstract:

The present work compares the performance of three turbulence modeling approach (based on the two-equation k -ε model) in predicting erosive wear in multi-size dense slurry flow through rotating channel. All three turbulence models include rotation modification to the production term in the turbulent kineticenergy equation. The two-phase flow field obtained numerically using Galerkin finite element methodology relates the local flow velocity and concentration to the wear rate via a suitable wear model. The wear models for both sliding wear and impact wear mechanisms account for the particle size dependence. Results of predicted wear rates using the three turbulence models are compared for a large number of cases spanning such operating parameters as rotation rate, solids concentration, flow rate, particle size distribution and so forth. The root-mean-square error between FE-generated data and the correlation between maximum wear rate and the operating parameters is found less than 2.5% for all the three models.

Keywords: Rotating channel, maximum wear rate, multi-sizeparticulate flow, k −ε turbulence models.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1732

Authors: K. Kamalanand, S. Srinivasan

Abstract:

Analysis of blood vessel mechanics in normal and diseased conditions is essential for disease research, medical device design and treatment planning. In this work, 3D finite element models of normal vessel and atherosclerotic vessel with 50% plaque deposition were developed. The developed models were meshed using finite number of tetrahedral elements. The developed models were simulated using actual blood pressure signals. Based on the transient analysis performed on the developed models, the parameters such as total displacement, strain energy density and entropy per unit volume were obtained. Further, the obtained parameters were used to develop artificial neural network models for analyzing normal and atherosclerotic blood vessels. In this paper, the objectives of the study, methodology and significant observations are presented.

Keywords: Blood vessel, atherosclerosis, finite element model, artificial neural networks

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2264

Authors: M. Madiajagan, B. Vijayakumar

Abstract:

The ability of information systems to operate in conjunction with each other encompassing communication protocols, hardware, software, application, and data compatibility layers. There has been considerable work in industry on the development of component interoperability models, such as CORBA, (D)COM and JavaBeans. These models are intended to reduce the complexity of software development and to facilitate reuse of off-the-shelf components. The focus of these models is syntactic interface specification, component packaging, inter-component communications, and bindings to a runtime environment. What these models lack is a consideration of architectural concerns – specifying systems of communicating components, explicitly representing loci of component interaction, and exploiting architectural styles that provide well-understood global design solutions. The development of complex business applications is now focused on an assembly of components available on a local area network or on the net. These components must be localized and identified in terms of available services and communication protocol before any request. The first part of the article introduces the base concepts of components and middleware while the following sections describe the different up-todate models of communication and interaction and the last section shows how different models can communicate among themselves.

Keywords: Interoperability, component packaging, communication technology, heterogeneous platform, component interface, middleware.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2741

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: Deep learning, artificial neural networks, energy price forecasting, Turkey.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1036

Authors: Changhyuk Jang, Keechul Jung

Abstract:

Human pose estimation can be executed using Active Shape Models. The existing techniques for applying to human-body research using Active Shape Models, such as human detection, primarily take the form of silhouette of human body. This technique is not able to estimate accurately for human pose to concern two arms and legs, as the silhouette of human body represents the shape as out of round. To solve this problem, we applied the human body model as stick-figure, “skeleton". The skeleton model of human body can give consideration to various shapes of human pose. To obtain effective estimation result, we applied background subtraction and deformed matching algorithm of primary Active Shape Models in the fitting process. The images which were used to make the model were 600 human bodies, and the model has 17 landmark points which indicate body junction and key features of human pose. The maximum iteration for the fitting process was 30 times and the execution time was less than .03 sec.

Keywords: Active shape models, skeleton, pose estimation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2367

Authors: Asfaw Gezae Daful

Abstract:

In the present study, two distinctly different approaches are followed for modeling of reactive distillation column, the equilibrium stage model and the nonequilibrium stage model. These models are simulated with a computer code developed in the present study using MATLAB programming. In the equilibrium stage models, the vapor and liquid phases are assumed to be in equilibrium and allowance is made for finite reaction rates, where as in the nonequilibrium stage models simultaneous mass transfer and reaction rates are considered. These simulated model results are validated from the experimental data reported in the literature. The simulated results of equilibrium and nonequilibrium models are compared for concentration, temperature and reaction rate profiles in a reactive distillation column for Methyl Tert Butyle Ether (MTBE) production. Both the models show similar trend for the concentration, temperature and reaction rate profiles but the nonequilibrium model predictions are higher and closer to the experimental values reported in the literature.

Keywords: Reactive Distillation, Equilibrium model, Nonequilibrium model, Methyl Tert-Butyl Ether

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4166

Authors: Andrea Bellucci, Martina Tofi

Abstract:

The aim of paper is to analyze business models of bancassurance in Italy for life business. The life insurance business is very developed in the Italian market and banks branches have 80% of the market share. Given its maturity, the life insurance market needs to consolidate its organizational form to allow for the development of non-life business, which nowadays collects few premiums but represents a great opportunity to enlarge the market share of bancassurance using its strength in the distribution channel while the market share of independent agents is decreasing. Starting with the main business model of bancassurance for life business, this paper will analyze the performances of life companies in the Italian market by balance sheet indicators and by main discriminant variables of business models. The study will observe trends from 2013 to 2015 for the Italian market by exploiting a database managed by Associazione Nazionale delle Imprese di Assicurazione (ANIA). The applied approach is based on a bottom-up analysis starting with variables and indicators to define business models’ classification. The statistical classification algorithm proposed by Ward is employed to design business models’ profiles. Results from the analysis will be a representation of the main business models built by their profile related to indicators. In that way, an unsupervised analysis is developed that has the limit of its judgmental dimension based on research opinion, but it is possible to obtain a design of effective business models.

Keywords: Balance sheet indicators, Bancassurance, business models, ward algorithm.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1223

Authors: Jihye Jeon

Abstract:

This paper analyzes the conceptual framework of three statistical methods, multiple regression, path analysis, and structural equation models. When establishing research model of the statistical modeling of complex social phenomenon, it is important to know the strengths and limitations of three statistical models. This study explored the character, strength, and limitation of each modeling and suggested some strategies for accurate explaining or predicting the causal relationships among variables. Especially, on the studying of depression or mental health, the common mistakes of research modeling were discussed.

Keywords: Multiple regression, path analysis, structural equation models, statistical modeling, social and psychological phenomenon.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9100

Authors: Edlira Donefski, Tina Donefski, Lorenc Ekonomi

Abstract:

Edgeworth Approximation, Bootstrap and Monte Carlo Simulations have a considerable impact on the achieving certain results related to different problems taken into study. In our paper, we have treated a financial case related to the effect that have the components of a Cash-Flow of one of the most successful businesses in the world, as the financial activity, operational activity and investing activity to the cash and cash equivalents at the end of the three-months period. To have a better view of this case we have created a Vector Autoregression model, and after that we have generated the impulse responses in the terms of Asymptotic Analysis (Edgeworth Approximation), Monte Carlo Simulations and Residual Bootstrap based on the standard errors of every series created. The generated results consisted of the common tendencies for the three methods applied, that consequently verified the advantage of the three methods in the optimization of the model that contains many variants.

Keywords: Autoregression, Bootstrap, Edgeworth Expansion, Monte Carlo Method.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 527

Authors: Liming Chen, Baoxin Xiu, Zhaoyun Ding, Bin Liu, Xianqiang Zhu

Abstract:

In the era of big data, public investors are faced with more complicated information related to investment decisions than ever before. To survive in the fierce competition, it has become increasingly urgent for investors to combine multi-source knowledge and evaluate the companies’ true value efficiently. For this, a rule-based ontology reasoning method is proposed to support steel companies’ value assessment. Considering the delay in financial disclosure and based on cost-benefit analysis, this paper introduces the supply chain enterprises financial analysis and constructs the ontology model used to value the value of steel company. In addition, domain knowledge is formally expressed with the help of Web Ontology Language (OWL) language and SWRL (Semantic Web Rule Language) rules. Finally, a case study on a steel company in China proved the effectiveness of the method we proposed.

Keywords: Financial ontology, steel company, supply chain, ontology reasoning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 530

Authors: Chokri Slim

Abstract:

The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.

Keywords: Neuro-fuzzy, Extended Kalman filter, nonlinear systems, financial time series.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1971

Authors: Zuraida Alwadood, Adibah Shuib, Norlida Abd Hamid

Abstract:

This paper presents the review of past studies concerning mathematical models for rescheduling passenger railway services, as part of delay management in the occurrence of railway disruption. Many past mathematical models highlighted were aimed at minimizing the service delays experienced by passengers during service disruptions. Integer programming (IP) and mixed-integer programming (MIP) models are critically discussed, focusing on the model approach, decision variables, sets and parameters. Some of them have been tested on real-life data of railway companies worldwide, while a few have been validated on fictive data. Based on selected literatures on train rescheduling, this paper is able to assist researchers in the model formulation by providing comprehensive analyses towards the model building. These analyses would be able to help in the development of new approaches in rescheduling strategies or perhaps to enhance the existing rescheduling models and make them more powerful or more applicable with shorter computing time.

Keywords: Mathematical modelling, Mixed-integer programming, Railway rescheduling, Service delays.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3191

Authors: S. Pattanapairoj, D. Chetchotsak

Abstract:

This paper proposed classification models that would be used as a proxy for hard disk drive (HDD) functional test equitant which required approximately more than two weeks to perform the HDD status classification in either “Pass" or “Fail". These models were constructed by using committee network which consisted of a number of single neural networks. This paper also included the method to solve the problem of sparseness data in failed part, which was called “enforce learning method". Our results reveal that the constructed classification models with the proposed method could perform well in the sparse data conditions and thus the models, which used a few seconds for HDD classification, could be used to substitute the HDD functional tests.

Keywords: Sparse data, Classifications, Committee network

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1694

Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand

Abstract:

Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models, on two different real-world electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.

Keywords: EHR, Machine Learning, imputation, laboratory variables, algorithmic bias.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31

Authors: M. R. Bhuiyan, S. M. M. Hossain, M. Z. Islam

Abstract:

Autism Spectrum Disorder (ASD) is the fastest growing serious developmental disorder characterized by social deficits, communicative difficulties, and repetitive behaviors. ASD is an emerging public health issue globally which is associated with huge financial burden to the family, community and the nation. The aim of this study was to assess the financial burden of family for the children with Autism spectrum Disorder. This cross-sectional study was carried out from July 2015 to June 2016 among 154 children with ASD to assess the financial burden of family. Data were collected by face-to-face interview with semi-structured questionnaire following systematic random sampling technique. Majority (73.4%) children were male and mean (±SD) age was 6.66 ± 2.97 years. Most (88.8%) of the children were from urban areas with average monthly family income Tk. 41785.71±23936.45. Average monthly direct cost of the children was Tk.17656.49 ± 9984.35, while indirect cost was Tk. 13462.90 ± 9713.54 and total treatment cost was Tk. 23076.62 ± 15341.09. Special education cost (Tk. 4871.00), cost of therapy (Tk. 4124.07) and travel cost (Tk. 3988.31) were the major types of direct cost, while loss of income (Tk.14570.18) was the chief indirect cost incurred by the families. The study found that majority (59.8%) of the children attended special schools were incurred Tk.20001-78700 as total treatment cost, which were statistically significant (p<0.001). Again, families with higher monthly family income incurred higher treatment cost (r=0.526, p<0.05). Difference between mean direct and indirect cost was found significant (t=4.190, df=61, p<0.001). According to the analysis of variance, mean difference of father’s educational status among direct cost (F=10.337, p<0.001) and total treatment cost (F=7.841, p<0.001), which were statistically significant. The study revealed that maximum children with ASD were under five years, three-fourth were male. According to monthly family income, maximum family were in middle class. The study recommends cost effective interventions and financial safety-net measures to reduce the financial burden of families for the children with ASD.

Keywords: Autism spectrum disorder, financial burden, direct cost, indirect cost, Special education.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1177

Authors: Huei-Wen Lin

Abstract:

This study explored the relationship between psychological traits, demographics and financial behavioral biases for individual investors in Taiwan stock market. By using questionnaire survey method conducted in 2010, there are 554 valid convenient samples collected to examine the determinants of three types of behavioral biases. Based on literature review, two hypothesized models are constructed and further used to evaluate the effects of big five personality traits and demographic variables on investment biases through Structural Equation Model (SEM) analysis. The results showed that investment biases of individual investors are significantly related to four personality traits as well as some demographics.

Keywords: Behavioral finance, Big Five, Disposition effect, Herding, Overconfidence, Personality traits.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3861

Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: Big data, k-NN, machine learning, traffic speed prediction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1330

Authors: Pavan K. Rallabandi, Kailash C. Patidar

Abstract:

In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence/pattern recognition/classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: Hybrid systems, Hidden Markov Models, Recurrent neural networks, Deterministic finite state automata.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2834

Authors: Y. Rhazali, Y. Hadi, A. Mouloudi

Abstract:

This paper proposes a method to automatic transformation of CIM level to PIM level respecting the MDA approach. Our proposal is based on creating a good CIM level through well-defined rules allowing as achieving rich models that contain relevant information to facilitate the task of the transformation to the PIM level. We define, thereafter, an appropriate PIM level through various UML diagram. Next, we propose set rules to move from CIM to PIM. Our method follows the MDA approach by considering the business dimension in the CIM level through the use BPMN, standard modeling business of OMG, and the use of UML in PIM advocated by MDA in this level.

Keywords: Model transformation, MDA, CIM, PIM.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3628

Authors: Ruxandra Barbulescu, Daniel Ioan, Gabriela Ciuprina

Abstract:

The saltatory conduction is the way the action potential is transmitted along a myelinated axon. The potential diffuses along the myelinated compartments and it is regenerated in the Ranvier nodes due to the ion channels allowing the flow across the membrane. For an efficient simulation of populations of neurons, it is important to use reduced order models both for myelinated compartments and for Ranvier nodes and to have control over their accuracy and inner parameters. The paper presents a reduced order model of this neural system which allows an efficient simulation method for the saltatory conduction in myelinated axons. This model is obtained by concatenating reduced order linear models of 1D myelinated compartments and nonlinear 0D models of Ranvier nodes. The models for the myelinated compartments are selected from a series of spatially distributed models developed and hierarchized according to their modeling errors. The extracted model described by a nonlinear PDE of hyperbolic type is able to reproduce the saltatory conduction with acceptable accuracy and takes into account the finite propagation speed of potential. Finally, this model is again reduced in order to make it suitable for the inclusion in large-scale neural circuits.

Keywords: Saltatory conduction, action potential, myelinated compartments, nonlinear, Ranvier nodes, reduced order models, POD.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 782

Authors: Y. Lu, X. S. Qin

Abstract:

Extensive rainfall disaggregation approaches have been developed and applied in climate change impact studies such as flood risk assessment and urban storm water management.In this study, five rainfall models that were capable ofdisaggregating daily rainfall data into hourly one were investigated for the rainfall record in theChangi Airport, Singapore. The objectives of this study were (i) to study the temporal characteristics of hourly rainfall in Singapore, and (ii) to evaluate the performance of variousdisaggregation models. The used models included: (i) Rectangular pulse Poisson model (RPPM), (ii) Bartlett-Lewis Rectangular pulse model (BLRPM), (iii) Bartlett-Lewis model with 2 cell types (BL2C), (iv) Bartlett-Lewis Rectangular with cell depth distribution dependent on duration (BLRD), and (v) Neyman-Scott Rectangular pulse model (NSRPM). All of these models werefitted using hourly rainfall data ranging from 1980 to 2005 (which was obtained from Changimeteorological station).The study results indicated that the weight scheme of inversely proportional variance could deliver more accurateoutputs for fitting rainfall patterns in tropical areas, and BLRPM performedrelatively better than other disaggregation models.

Keywords: Rainfall disaggregation, statistical properties, poisson processed, Bartlett-Lewis model, Neyman-Scott model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2244

Authors: S. S. Bhandari, N. Chakpitak, K. Meksamoot, T. Chandarasupsang

Abstract:

Under the limitation of investment budget, a utility company is required to maximize the utilization of their existing assets during their life cycle satisfying both engineering and financial requirements. However, utility does not have knowledge about the status of each asset in the portfolio neither in terms of technical nor financial values. This paper presents a knowledge based model for the utility companies in order to make an optimal decision on power transformer with their utilization. CommonKADS methodology, a structured development for knowledge and expertise representation, is utilized for designing and developing knowledge based model. A case study of One MVA power transformer of Nepal Electricity Authority is presented. The results show that the reusable knowledge can be categorized, modeled and utilized within the utility company using the proposed methodologies. Moreover, the results depict that utility company can achieve both engineering and financial benefits from its utilization.

Keywords: CommonKADS, Knowledge Engineering, LifeCycle Management, Power Transformer.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2265