Abstract: Availability of different genetic tests after completion
of Human Genome Project increases the physicians’ responsibility to
keep themselves update on the potential implementation of these
genetic tests in their daily practice. However, due to numbers of
barriers, still many of physicians are not either aware of these tests or
are not willing to offer or refer their patients for genetic tests. This
study was conducted an anonymous, cross-sectional, mailed-based
survey to develop a primary data of Malaysian physicians’ level of
knowledge and perception of gene profiling. Questionnaire had 29
questions. Total scores on selected questions were used to assess the
level of knowledge. The highest possible score was 11. Descriptive
statistics, one way ANOVA and chi-squared test was used for
statistical analysis. Sixty three completed questionnaires were
returned by 27 general practitioners (GPs) and 36 medical specialists.
Responders’ age ranges from 24 to 55 years old (mean 30.2 ± 6.4).
About 40% of the participants rated themselves as having poor level
of knowledge in genetics in general whilst 60% believed that they
have fair level of knowledge; however, almost half (46%) of the
respondents felt that they were not knowledgeable about available
genetic tests. A majority (94%) of the responders were not aware of
any lab or company which is offering gene profiling services in
Malaysia. Only 4% of participants were aware of using gene profiling
for detection of dosage of some drugs. Respondents perceived greater
utility of gene profiling for breast cancer (38%) compared to the
colorectal familial cancer (3%). The score of knowledge ranged from
2 to 8 (mean 4.38 ± 1.67). Non- significant differences between score
of knowledge of GPs and specialists were observed, with score of
4.19 and 4.58 respectively. There was no significant association
between any demographic factors and level of knowledge. However,
those who graduated between years 2001 to 2005 had higher level of
knowledge. Overall, 83% of participants showed relatively high level
of perception on value of gene profiling to detect patient’s risk of
disease. However, low perception was observed for both statements
of using gene profiling for general population in order to alter their
lifestyle (25%) as well as having the full sequence of a patient
genome for the purpose of determining a patient’s best match for
treatment (18%). The lack of clinical guidelines, limited provider
knowledge and awareness, lack of time and resources to educate
patients, lack of evidence-based clinical information and cost of tests
were the most barriers of ordering gene profiling mentioned by
physicians. In conclusion Malaysian physicians who participate in
this study had mediocre level of knowledge and awareness in gene
profiling. The low exposure to the genetic questions and problems
might be a key predictor of lack of awareness and knowledge on
available genetic tests. Educational and training workshop might be useful in helping Malaysian physicians incorporate genetic profiling
into practice for eligible patients.
Abstract: This study analyzes the innovative orientation of the
Croatian entrepreneurs. Innovative orientation is represented by the
perceived extent to which an entrepreneur’s product or service or
technology is new, and no other businesses offer the same product.
The sample is extracted from the GEM Croatia Adult Population
Survey dataset for the years 2003-2013. We apply descriptive
statistics, t-test, Chi-square test and logistic regression. Findings
indicate that innovative orientations vary with personal, firm, meso
and macro level variables, and between different stages in
entrepreneurship process. Significant predictors are occupation of the
entrepreneurs, size of the firm and export aspiration for both early
stage and established entrepreneurs. In addition, fear of failure,
expecting to start a new business and seeing an entrepreneurial career
as a desirable choice are predictors of innovative orientation among
early stage entrepreneurs.
Abstract: Absorptive capacity generally facilitates the adoption
of innovation. How does this relationship change when economic
return is not the sole driver of innovation uptake? We investigate
whether absorptive capacity facilitates the adoption of green
innovation based on a survey of 79 construction companies in
Scotland. Based on the results of multiple regression analyses, we
confirm that existing knowledge utilisation (EKU), knowledge
building (KB) and external knowledge acquisition (EKA) are
significant predictors of green process GP), green administrative
(GA) and green technical innovation (GT), respectively. We discuss
the implications for theories of innovation adoption and knowledge
enhancement associated with environmentally-friendly practices.
Abstract: Estimation of model parameters is necessary to predict
the behavior of a system. Model parameters are estimated using
optimization criteria. Most algorithms use historical data to estimate
model parameters. The known target values (actual) and the output
produced by the model are compared. The differences between the
two form the basis to estimate the parameters. In order to compare
different models developed using the same data different criteria are
used. The data obtained for short scale projects are used here. We
consider software effort estimation problem using radial basis
function network. The accuracy comparison is made using various
existing criteria for one and two predictors. Then, we propose a new
criterion based on linear least squares for evaluation and compared
the results of one and two predictors. We have considered another
data set and evaluated prediction accuracy using the new criterion.
The new criterion is easy to comprehend compared to single statistic.
Although software effort estimation is considered, this method is
applicable for any modeling and prediction.
Abstract: In EFL programs, rating scales used in writing
assessment are often constructed by intuition. Intuition-based scales
tend to provide inaccurate and divisive ratings of learners’ writing
performance. Hence, following an empirical approach, this study
attempted to develop a rating scale for elementary-level writing at an
EFL program in Saudi Arabia. Towards this goal, 98 students’ essays
were scored and then coded using comprehensive taxonomy of
writing constructs and their measures. An automatic linear modeling
was run to find out which measures would best predict essay scores.
A nonparametric ANOVA, the Kruskal-Wallis test, was then used to
determine which measures could best differentiate among scoring
levels. Findings indicated that there were certain measures that could
serve as either good predictors of essay scores or differentiators
among scoring levels, or both. The main conclusion was that a rating
scale can be empirically developed using predictive and
discriminative statistical tests.
Abstract: Fuzzy systems have been successfully used for
exchange rate forecasting. However, fuzzy system is very confusing
and complex to be designed by an expert, as there is a large set of
parameters (fuzzy knowledge base) that must be selected, it is not a
simple task to select the appropriate fuzzy knowledge base for an
exchange rate forecasting. The researchers often look the effect of
fuzzy knowledge base on the performances of fuzzy system
forecasting. This paper proposes a genetic fuzzy predictor to forecast
the future value of daily US Dollar/Euro exchange rate time’s series.
A range of methodologies based on a set of fuzzy predictor’s which
allow the forecasting of the same time series, but with a different
fuzzy partition. Each fuzzy predictor is built from two stages, where
each stage is performed by a real genetic algorithm.
Abstract: Nonalcoholic fatty liver disease (NAFLD) has
increased in conjunction with obesity. The accuracy of risk factors
for detecting NAFLD in obese adolescents has not undergone a
formal evaluation. The aim of this study was to evaluate predictors of
NAFLD among Egyptian female obese adolescents. The study
included 162 obese female adolescents. All were subjected to
anthropometry, biochemical analysis and abdominal ultrasongraphic
assessment. Metabolic syndrome (MS) was diagnosed according to
the IDF criteria. Significant association between presence of MS and
NAFLD was observed. Obese adolescents with NAFLD had
significantly higher levels of ALT, triglycerides, fasting glucose,
insulin, blood pressure and HOMA-IR, whereas decreased HDL-C
levels as compared with obese cases without NAFLD. Receiver–
operating characteristic (ROC) curve analysis shows that ALT is a
sensitive predictor for NAFLD, confirming that ALT can be used as a
marker of NAFLD.
Abstract: Recent perceived climate variability raises concerns
with unprecedented hydrological phenomena and extremes.
Distribution and circulation of the waters of the Earth become
increasingly difficult to determine because of additional uncertainty
related to anthropogenic emissions. The world wide observed
changes in the large-scale hydrological cycle have been related to an
increase in the observed temperature over several decades. Although
the effect of change in climate on hydrology provides a general
picture of possible hydrological global change, new tools and
frameworks for modelling hydrological series with nonstationary
characteristics at finer scales, are required for assessing climate
change impacts. Of the downscaling techniques, dynamic
downscaling is usually based on the use of Regional Climate Models
(RCMs), which generate finer resolution output based on atmospheric
physics over a region using General Circulation Model (GCM) fields
as boundary conditions. However, RCMs are not expected to capture
the observed spatial precipitation extremes at a fine cell scale or at a
basin scale. Statistical downscaling derives a statistical or empirical
relationship between the variables simulated by the GCMs, called
predictors, and station-scale hydrologic variables, called predictands.
The main focus of the paper is on the need for using statistical
downscaling techniques for projection of local hydrometeorological
variables under climate change scenarios. The projections can be then
served as a means of input source to various hydrologic models to
obtain streamflow, evapotranspiration, soil moisture and other
hydrological variables of interest.
Abstract: This study aims to examine the role of career
advancement and job security as predictors of employee commitment
to their organization. Data was collected from 580 frontline
employees attached to two departments of 29 luxury hotels in
Peninsular Malaysia. Statistical results using Partial Least Squares
technique provided support for the proposed hypotheses. In view of
the findings, theoretical and practical implications are discussed.
Abstract: Second line antiretroviral therapy (ART) regimen is
used when patients fail their first line regimen. There are many
factors such as non-adherence, drug resistance as well as virological
and immunological failure that lead to second line highly active
antiretroviral therapy (HAART) regimen treatment failure. This study
was aimed at determining predictor factors to treatment failure with
second line HAART and analyzing median survival time.
An observational, retrospective study was conducted in Sungai
Buloh Hospital (HSB) to assess current status of HIV patients treated
with second line HAART regimen. Convenience sampling was used
and 104 patients were included based on the study’s inclusion and
exclusion criteria. Data was collected for six months i.e. from July
until December 2013. Data was then analysed using SPSS version 18.
Kaplan-Meier and Cox regression analyses were used to measure
median survival times and predictor factors for treatment failure.
The study population consisted mainly of male subjects, aged 30-
45 years, who were heterosexual, and had HIV infection for less than
6 years. The most common second line HAART regimen given was
lopinavir/ritonavir (LPV/r)-based combination. Kaplan-Meier
analysis showed that patients on LPV/r demonstrated longer median
survival times than patients on indinavir/ritonavir (IDV/r) based
combination (p
Abstract: The aims of this research are to broaden the study on the relationship between emotional intelligence and counterproductive work behavior (CWB). The study sample consisted in 441 Romanian employees from companies all over the country. Data has been collected through web surveys and processed with SPSS. The results indicated an average correlation between the two constructs and their sub variables, employees with a high level of emotional intelligence tend to be less aggressive. In addition, labeling was considered an individual difference which has the power to influence the level of employee aggression. A regression model was used to underline the importance of emotional intelligence together with labeling as predictors of CWB. Results have shown that this regression model enforces the assumption that labeling and emotional intelligence, taken together, predict CWB. Employees, who label themselves as victims and have a low degree of emotional intelligence, have a higher level of CWB.
Abstract: The aim of this research is to evaluate the effectiveness of software quality assurance approaches of Sri Lankan offshore software development organizations, and to propose a framework which could be used across all offshore software development organizations.
An empirical study was conducted using derived framework from popular software quality evaluation models. The research instrument employed was a questionnaire survey among thirty seven Sri Lankan registered offshore software development organizations.
The findings demonstrate a positive view of Effectiveness of Software Quality Assurance – the stronger predictors of Stability, Installability, Correctness, Testability and Changeability. The present study’s recommendations indicate a need for much emphasis on software quality assurance for the Sri Lankan offshore software development organizations.
Abstract: This paper deals with the novel intelligent bio-inspired control strategies, it presents a novel approach based on an optimal fuzzy immune PID parameters tuning, it is a combination of a PID controller, inspired by the human immune mechanism with fuzzy logic. Such controller offers more possibilities to deal with the delayed systems control difficulties due to the delay term. Indeed, we use an optimization approach to tune the four parameters of the controller in addition to the fuzzy function; the obtained controller is implemented in a modified Smith predictor structure, which is well known that it is the most efficient to the control of delayed systems. The application of the presented approach to control a three tank delay system shows good performances and proves the efficiency of the method.
Abstract: Metacognitive knowledge increases EFL students’ ability to be successful learners. Although this relationship has been investigated by a number of scholars, EFL teachers’ explicit awareness of their cognitive knowledge has not been sufficiently explored. The aim of this study was to examine the role of EFL teachers’ metacognitive knowledge in their pedagogical performance. Furthermore, the role played by years of their academic education and teaching experience was also studied. Fifty female EFL teachers were selected. They completed Metacognitive Awareness Inventory (MAI) that assessed six components of metacognition including procedural knowledge, declarative knowledge, conditional knowledge, planning, evaluating, and management strategies. Near the end of the academic semester, the students of each class filled in ‘the Language Teacher Characteristics Questionnaire’ to evaluate their teachers’ pedagogical performance. Four elements of MAI, declarative knowledge, planning, evaluating, and management strategies were found to be significantly correlated with EFL teachers’ pedagogical success. Significant correlation was also established between metacognitive knowledge and EFL teachers’ years of academic education and teaching experience. The findings obtained from this research have contributing implication for EFL teacher educators. The discussion concludes by setting out directions for future research.
Abstract: This paper presents a Gaussian process model-based
short-term electric load forecasting. The Gaussian process model is
a nonparametric model and the output of the model has Gaussian
distribution with mean and variance. The multiple Gaussian process
models as every hour ahead predictors are used to forecast future
electric load demands up to 24 hours ahead in accordance with the
direct forecasting approach. The separable least-squares approach that
combines the linear least-squares method and genetic algorithm is
applied to train these Gaussian process models. Simulation results
are shown to demonstrate the effectiveness of the proposed electric
load forecasting.
Abstract: Prediction of future research topics by using time series analysis either statistical or machine learning has been conducted previously by several researchers. Several methods have been proposed to combine the forecasting results into single forecast. These methods use fixed combination of individual forecast to get the final forecast result. In this paper, quite different approach is employed to select the forecasting methods, in which every point to forecast is calculated by using the best methods used by similar validation dataset. The dataset used in the experiment is time series derived from research report in Garuda, which is an online sites belongs to the Ministry of Education in Indonesia, over the past 20 years. The experimental result demonstrates that the proposed method may perform better compared to the fix combination of predictors. In addition, based on the prediction result, we can forecast emerging research topics for the next few years.
Abstract: Most of greenhouse growers desire a determined amount of yields in order to accurately meet market requirements. The purpose of this paper is to model a simple but often satisfactory supervised classification method. The original naive Bayes have a serious weakness, which is producing redundant predictors. In this paper, utilized regularization technique was used to obtain a computationally efficient classifier based on naive Bayes. The suggested construction, utilized L1-penalty, is capable of clearing redundant predictors, where a modification of the LARS algorithm is devised to solve this problem, making this method applicable to a wide range of data. In the experimental section, a study conducted to examine the effect of redundant and irrelevant predictors, and test the method on WSG data set for tomato yields, where there are many more predictors than data, and the urge need to predict weekly yield is the goal of this approach. Finally, the modified approach is compared with several naive Bayes variants and other classification algorithms (SVM and kNN), and is shown to be fairly good.
Abstract: Tinnitus is commonly defined as an aberrant
perception of sound without external stimulus. It’s a chronic
condition with consequences on the QOL. The coping strategies used
were not always effective and coping was identified as a predictor of
QOL in individuals with tinnitus, which reinforces the idea that in
health the use of effective coping styles should be promoted. This
work intend to verify relations between coping strategies assessed by
BriefCope in subjects with tinnitus and variables such as gender, age
and severity of tinnitus measured by THI and the Visual Analogue
Scale and also hearing and hyperacusis. The results indicate that there
are any statistically significant relationships between the variables
assessed in relation to the results of BriefCope except in the Visual
Analogue Scale.These results, indicating no relationship between
almost all variables, reinforce the need for further study of coping
strategies use by these patients.
Abstract: Objective: This study explored the possibility of integrating Health Belief Concepts as additional predictors of intention to adopt a recommended diet-category within the Theory of Planned Behavior (TPB). Methods: The study adopted a Sequential Exploratory Mixed Methods approach. Qualitative data were generated on attitude, subjective norm, perceived behavioral control and perceptions on predetermined diet-categories including perceived susceptibility, perceived benefits, perceived severity and cues to action. Synthesis of qualitative data was done using constant comparative approach during phase 1. A survey tool developed from qualitative results was used to collect information on the same concepts across 237 legible Type 2 diabetics. Data analysis included use of Structural Equation Modeling in Analysis of Moment Structures to explore the possibility of including perceived susceptibility, perceived benefits, perceived severity and cues to action as additional intention predictors in a single nested model. Results: Two models-one nested based on the traditional TPB model {χ2=223.3, df = 77, p = .02, χ2/df = 2.9; TLI = .93; CFI =.91; RMSEA (90CI) = .090(.039, .146)} and the newly proposed Planned Behavior Health Belief Model (PBHB) {χ2 = 743.47, df = 301, p = .019; TLI = .90; CFI=.91; RMSEA (90CI) = .079(.031, .14)} passed the goodness of fit tests based on common fit indicators used. Conclusion: The newly developed PBHB Model ranked higher than the traditional TPB model with reference made to chi-square ratios (PBHB: χ2/df = 2.47; p=0.19 against TPB: χ2/df = 2.9, p=0.02). The integrated model can be used to motivate Type 2 diabetics towards healthy eating.
Abstract: The study aimed to investigate whether cognitive emotion regulation in children varies with parenting style, family type and gender. Toward this end, cognitive emotion regulation and perceived parenting style of 206 school children were measured. Standard regression analyses of data revealed that the models were significant and explained 17.3% of the variance in adaptive emotion regulation (Adjusted R²=0.173; F=9.579, p