1,424 research outputs found
Investment-Linked Takaful Plan Patronage: Evidence From Malaysia
Investment-linked Takaful is a recent innovation introduced in Malaysia. This study focuses on Investment-linked takaful plan selection in Malaysia. We have used a self-administered questionnaire to collect data from 143 respondents from the Klang Valley area. Data collected through the survey was analyzed through descriptive statistics, correlation and regression analysis. Results indicate that fee payment and benefits play a significant role in Takaful operator selection while coverage and benefits affect the investment-linked product selection in Malaysia. This study is unique as it provides empirical evidence on the investment-linked takaful investment which is limited in supply. Results provided by this study can be useful for takaful operators in designing the most appropriate investment-linked product for attracting customers
Analysis and classification of myocardial infarction tissue from echocardiography images based on texture analysis
Texture analysis is an important characteristic for automatic visual inspection for surface and object identification from medical images and other type of images. This paper presents an application of wavelet extension and Gray level cooccurrence matrix (GLCM) for diagnosis of myocardial infarction tissue from echocardiography images. Many of applications approach have provided good result in different fields of application, but could not implemented at all when texture samples are small dimensions caused by low quality of images. Wavelet extension procedure is used to determine the frequency bands carrying the most information about the texture by decomposition images into multiple frequency bands and to form an image approximation with higher resolution. Thus, wavelet extension procedure offers the ability to robust feature extraction in
images. The gray level co-occurrence matrices are computed for each sub-band. The feature vector of testing image and other feature vector as normal image classified by Mahalanobis distance to decide whether the test image is infarction or not
Estimating Time-Varying Effective Connectivity in High-Dimensional fMRI Data Using Regime-Switching Factor Models
Recent studies on analyzing dynamic brain connectivity rely on sliding-window
analysis or time-varying coefficient models which are unable to capture both
smooth and abrupt changes simultaneously. Emerging evidence suggests
state-related changes in brain connectivity where dependence structure
alternates between a finite number of latent states or regimes. Another
challenge is inference of full-brain networks with large number of nodes. We
employ a Markov-switching dynamic factor model in which the state-driven
time-varying connectivity regimes of high-dimensional fMRI data are
characterized by lower-dimensional common latent factors, following a
regime-switching process. It enables a reliable, data-adaptive estimation of
change-points of connectivity regimes and the massive dependencies associated
with each regime. We consider the switching VAR to quantity the dynamic
effective connectivity. We propose a three-step estimation procedure: (1)
extracting the factors using principal component analysis (PCA) and (2)
identifying dynamic connectivity states using the factor-based switching vector
autoregressive (VAR) models in a state-space formulation using Kalman filter
and expectation-maximization (EM) algorithm, and (3) constructing the
high-dimensional connectivity metrics for each state based on subspace
estimates. Simulation results show that our proposed estimator outperforms the
K-means clustering of time-windowed coefficients, providing more accurate
estimation of regime dynamics and connectivity metrics in high-dimensional
settings. Applications to analyzing resting-state fMRI data identify dynamic
changes in brain states during rest, and reveal distinct directed connectivity
patterns and modular organization in resting-state networks across different
states.Comment: 21 page
Model of a Corrosion Pit with Movement of Active Boundaries
Pitting is one of the most destructive types of localized corrosion. This paper presents the mathematical model of the early stages of pitting corrosion after its initiation stage, using a commercial finite element program. In view of the chemical and electrochemical reactions inside a single pit in steel, a two dimensional model that allows the prediction of movement of boundaries of a pit is developed
Lease Accounting in Australia: Further Empirical Evidence
Key words: Australia; Accounting standard; Efficient contracting; Lease accounting; Signalling The objective of this study is to examine the economic factors motivating Australian listed lessee firms to adopt capitalization of finance leases policy from 1985 to 1987 as permitted by the transitional provision of AAS 17. Capitalization is considered as the preferred accounting policy for finance leases compared to footnote disclosure. Adopting a joint efficient contracting and quality signaling perspective, support for the research hypotheses would be construed as suggesting that capitalization is a means for lessee firms to reduce or mitigate agency and/or political costs and concurrently as a signal to the market that they are better quality firms. The sample consists of3l4 lessee firms; 67 firms as capitalizers and 247 firms as non-capitalizers. A pooled multivariate cross—sectional analysis for 1985 to 1987 was performed incorporating sensitivity analysis to determine the “best” logistic regression model. This model was then assessed to determine its validity and predictive efficacy. the results provide evidence that lessee firms adopted the capitalization as response to the media attention as being politically visible firms and concurrently as a signal to the market that they are better quality firms. The evidence also suggests limited usefulness of a lengthy transitional period
Seven Cases Unstructured Triangulation Technique for Simplified Version of Conceptual Model of Ethylene Furnace for Radiative Heat Transfer Approximation
In this paper, we introduce a new enhanced method utilizing the approach of advancing front technique for generating unstructured meshes in the simplified version of ethylene conceptual model. The method is called as Seven Cases Unstructured Triangulation Technique (7CUTT) where it is based on seven categories of cases for element creation procedure and the layer concept for mesh gradation control. The algorithm of the mesh incorporates sensor deployment in its conceptual model to supply input for boundary values. The quality of the mesh is determined based on a measurement in GAMBIT software. 7CUTT provides the framework for the heat to be approximated using the discrete ordinate method, which is a variant of the finite volume method. Simulation results produced using FLUENT support the findings for effectively approximating the flue gas temperature distribution in the simplified furnace at the end of the study
Does socio-Demographic Variables Matter in Explaining Issues and Challenges in Islamic Microfinance? Evidence from Malaysia
Purpose - In line with the wide acceptance of the microfinance industry globally, Islamic microfinance has also evolved rapidly in the past years to cater for the demand for Shariah-compliant microfinancing schemes. Despite this, the industry is facing various issues and challenges from both the clients and microfinance institutions. This study aims to identify the issues and challenges faced by different demographic background of microentrepreneurs receiving Islamic microfinancing from Amanah Ikhtiar Malaysia (AIM). Methodology- It adopts the quantitative research methodology where primary data is collected using survey questionnaires administered on 393 women entrepreneurs who are currently clients of AIM’s Islamic microfinance scheme located in Selangor. The descriptive and cross-tabulation analyses are applied in efforts to understand the influence of socio-demographic factors (age, education level, duration with AIM, and times of receiving financing) on the following issues: cost of repayment, financing period, amount of financing, distance to AIM center, group lending mechanism, discipline among members, problematic group members, and consultation services. Findings - The study finds that clients with different socio-demographic factors perceived the issues differently, suggesting an influential role of clients’ demographic factors on the microfinance intervention. Practical implications - These findings have important implications to the microfinance industry in terms of further improving their products that are tailor-made to the socio-demographic characteristics of their clients. Originality – This research taken views of AIM’s microfinance recipients which were woman entrepreneurs in Selangor directly through a survey. Results of the research would be useful to AIM to enhance their products and services in future.
Keywords: Islamic microfinance, socio-demography, Islamic finance, Amanah Ikhtiar Malaysi
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