Abstract: Regarding heavy video game players for boys and super online chat lovers for girls as a symbolic phrase in the current adolescent culture, this project of data analysis verifies the displacement effect on deteriorating mathematics performance. To evaluate correlation or regression coefficients between a factor of playing video games or chatting online and mathematics performance compared with other factors, we use multivariate analysis technique and take gender difference into account. We find the most important reason for the negative sign of the displacement effect on mathematics performance due to students’ poor academic background. Statistical analysis methods in this project could be applied to study internet users’ academic performance from the high school education to the college education.
Abstract: Solar lentigines appear predominantly on chronically sun-exposed areas of skin, such as the face and the back of the hands. Among the several ways to lentigines treatment, quality-switched lasers are well-known effective treatment for removing solar lentigines. The present pilot study was therefore designed to assess the efficacy of quality-switched ruby laser treatment of such lentigines compare between pretreatment and posttreatment of skin brightness. Twenty-two adults with chronic sun-damaged skin (mean age 52.8 years, range 37–74 years) were treated at the Korean site. A 694 nm Q-switched ruby laser was used, with the energy density set from 1.4 to 12.5 J/cm2, to treat solar lentigines. Average brightness of skin color before ruby laser treatment was 137.3 and its skin color was brightened after ruby laser treatment by 150.5. Also, standard deviation of skin color was decreased from 17.8 to 16.4. Regarding the multivariate model, age and energy were identified as significant factors for skin color brightness change in lentigo depigmentation by ruby laser treatment. Their respective odds ratios were 1.082 (95% CI, 1.007–1.163), and 1.431 (95% CI, 1.051–1.946). Lentigo depigmentation treatment using ruby lasers resulted in a high performance in skin color brightness. Among the relative factors involve with ruby laser treatment, age and energy were the most effective factors which skin color change to brighter than pretreatment.
Abstract: The aim of this research is to study the relationship between the performance of engineering students in different math courses and their performance in specific engineering courses. The considered courses are taken mainly by engineering students during the first two years of their major. Several factors are being studied, such as gender and final grades in the math and specific engineering courses. Participants of this study comprised a sample of more than thousands of engineering students at Lebanese University during their tertiary academic years. A significant relationship tends to appear between these factors and the performance of students in engineering courses. Moreover, female students appear to outperform their male counterparts in both the math and engineering courses, and a high correlation was found between their grades in math courses and their grades in specific engineering courses. The results and implications of the study were being discussed.
Abstract: Neuromuscular control of posture as understood
through studies of responses to mechanical sudden acceleration
automatically has been previously demonstrated in individuals with
chronic ankle instability (CAI), but the presence of acute condition
has not been previously explored specially in a sudden acceleration.
The aim of this study was to determine neuromuscular control pattern
in those with and without unilateral acute ankle sprains. Design: Case
- control. Setting: University research laboratory. The sinker–card
protocol with surface translation was be used as a sudden acceleration
protocol with study of EMG upon 4 posture stabilizer muscles in two
sides of the body in response to sudden acceleration in forward and
backward directions. 20 young adult women in two groups (10 LAS;
23.9 ± 2.03 yrs and 10 normal; 26.4 ± 3.2 yrs). The data of EMG
were assessed by using multivariate test and one-way repeated
measures 2×2×4 ANOVA (P< 0.05). The results showed a significant
muscle by direction interaction. Higher TA activity of left and right
side in LAS group than normal group in forward direction
significantly be showed. Higher MGR activity in normal group than
LAS group in backward direction significantly showed. These
findings suggest that compared two sides of the body in two
directions for 4 muscles EMG activities between and within group for
neuromuscular control of posture in avoiding fall. EMG activations
of two sides of the body in lateral ankle sprain (LAS) patients were
symmetric significantly. Acute ankle instability following once ankle
sprains caused to coordinated temporal spatial patterns and strategy
selection.
Abstract: The current trends in affect recognition research are
to consider continuous observations from spontaneous natural
interactions in people using multiple feature modalities, and to
represent affect in terms of continuous dimensions, incorporate
spatio-temporal correlation among affect dimensions, and provide
fast affect predictions. These research efforts have been propelled
by a growing effort to develop affect recognition system that
can be implemented to enable seamless real-time human-computer
interaction in a wide variety of applications. Motivated by these
desired attributes of an affect recognition system, in this work
a multi-dimensional affect prediction approach is proposed by
integrating multivariate Relevance Vector Machine (MVRVM) with
a recently developed Output-associative Relevance Vector Machine
(OARVM) approach. The resulting approach can provide fast
continuous affect predictions by jointly modeling the multiple affect
dimensions and their correlations. Experiments on the RECOLA
database show that the proposed approach performs competitively
with the OARVM while providing faster predictions during testing.
Abstract: This article explains the elements and considerations taken into account when implementing and applying patent evaluation and scientometric study in the identifications of technology trends, and the tools that led to the implementation of a software application for patent revision. Univariate analysis helped recognize the technological leaders in the field of energy, and steered the way for a multivariate analysis of this sample, which allowed for a graphical description of the techniques of mature technologies, as well as the detection of emerging technologies. This article ends with a validation of the methodology as applied to the case of fuel cells.
Abstract: The purpose of this study is to investigate the efficacy of solution-focused group therapy on improving the depressed mothers of child abuser families. This study was carried out in the form of a semi-pilot, pre-test and post-test on two groups (experimental and control). Subjects include all mothers and their children that are the members of Shush and Naser Khosro child home. Beck Depression Inventory and Child Trauma Questionnaire were used to collect data. First, child abuse questionnaire was completed by children, Then Beck Depression Inventory was completed by their mothers that 22 of them were recognized as depressed and randomly divided in two groups of experimental and control. After applying pre-test for both of these groups, the intervention of solution- focused group therapy was performed in five sessions on experimental group. Finally, post-test was applied on both groups and subsequently in a month, follow-up test was performed. T-test, multivariate variance, and repeated measurement analysis of variance were used to analyze the data. According to the findings, it can be concluded that this therapy leads to the improvement of depressed mother's mood. As a result, the intervention of solution-focused group therapy is useful in order to improve the depressing mood of mothers of child abuser families.
Abstract: The social logic of 'Sequina' slum area in Alexandria details the integral measure of space syntax at the room-level of twenty-building samples. The essence of spatial structure integrates the central 'visitor' domain with the 'living' frontage of the 'children' zone against the segregated privacy of the opposite 'parent' depth. Meanwhile, the multifunctioning of shallow rooms optimizes the integral 'visitor' structure through graph and visibility dimensions in contrast to the 'inhabitant' structure of graph-tails out of sight. Common theme of the layout integrity increases in compensation to the decrease of room visibility. Despite the 'pheno-type' of collective integration, the individual layouts observe 'geno-type' structure of spatial diversity per room adjoins. In this regard, the layout integrity alternates the cross-correlation of the 'kitchen & living' rooms with the 'inhabitant & visitor' domains of 'motherhood' dynamic structure. Moreover, the added 'grandparent' restructures the integral measure to become the deepest space, but opens to the 'living' of 'household' integrity. Some isomorphic layouts change the integral structure just through the 'balcony' extension of access, visual or ignored 'ringiness' of space syntax. However, the most integrated or segregated layouts invert the 'geno-type' into a shallow 'inhabitant' centrality versus the remote 'visitor' structure. Overview of the multivariate social logic of spatial integrity could never clarify without the micro-data analysis.
Abstract: River Hindon is an important river catering the
demand of highly populated rural and industrial cluster of western
Uttar Pradesh, India. Water quality of river Hindon is deteriorating at
an alarming rate due to various industrial, municipal and agricultural
activities. The present study aimed at identifying the pollution
sources and quantifying the degree to which these sources are
responsible for the deteriorating water quality of the river. Various
water quality parameters, like pH, temperature, electrical
conductivity, total dissolved solids, total hardness, calcium, chloride,
nitrate, sulphate, biological oxygen demand, chemical oxygen
demand, and total alkalinity were assessed. Water quality data
obtained from eight study sites for one year has been subjected to the
two multivariate techniques, namely, principal component analysis
and cluster analysis. Principal component analysis was applied with
the aim to find out spatial variability and to identify the sources
responsible for the water quality of the river. Three Varifactors were
obtained after varimax rotation of initial principal components using
principal component analysis. Cluster analysis was carried out to
classify sampling stations of certain similarity, which grouped eight
different sites into two clusters. The study reveals that the
anthropogenic influence (municipal, industrial, waste water and
agricultural runoff) was the major source of river water pollution.
Thus, this study illustrates the utility of multivariate statistical
techniques for analysis and elucidation of multifaceted data sets,
recognition of pollution sources/factors and understanding
temporal/spatial variations in water quality for effective river water
quality management.
Abstract: We present probabilistic multinomial Dirichlet
classification model for multidimensional data and Gaussian process
priors. Here, we have considered efficient computational method that
can be used to obtain the approximate posteriors for latent variables
and parameters needed to define the multiclass Gaussian process
classification model. We first investigated the process of inducing a
posterior distribution for various parameters and latent function by
using the variational Bayesian approximations and important sampling
method, and next we derived a predictive distribution of latent
function needed to classify new samples. The proposed model is
applied to classify the synthetic multivariate dataset in order to verify
the performance of our model. Experiment result shows that our model
is more accurate than the other approximation methods.
Abstract: The critical concern of satellite operations is to ensure
the health and safety of satellites. The worst case in this perspective
is probably the loss of a mission, but the more common interruption
of satellite functionality can result in compromised mission
objectives. All the data acquiring from the spacecraft are known as
Telemetry (TM), which contains the wealth information related to the
health of all its subsystems. Each single item of information is
contained in a telemetry parameter, which represents a time-variant
property (i.e. a status or a measurement) to be checked. As a
consequence, there is a continuous improvement of TM monitoring
systems to reduce the time required to respond to changes in a
satellite's state of health. A fast conception of the current state of the
satellite is thus very important to respond to occurring failures.
Statistical multivariate latent techniques are one of the vital learning
tools that are used to tackle the problem above coherently.
Information extraction from such rich data sources using advanced
statistical methodologies is a challenging task due to the massive
volume of data. To solve this problem, in this paper, we present a
proposed unsupervised learning algorithm based on Principle
Component Analysis (PCA) technique. The algorithm is particularly
applied on an actual remote sensing spacecraft. Data from the
Attitude Determination and Control System (ADCS) was acquired
under two operation conditions: normal and faulty states. The models
were built and tested under these conditions, and the results show that
the algorithm could successfully differentiate between these
operations conditions. Furthermore, the algorithm provides
competent information in prediction as well as adding more insight
and physical interpretation to the ADCS operation.
Abstract: The research explores the relationship between
management responsibility and corporate governance of listed
companies in Kazakhstan. This research employs firm level data of
selected listed non-financial firms and firm level data “operational”
financial sector, consisted from banking sector, insurance companies
and accumulated pension funds using multivariate regression analysis
under fixed effect model approach. Ownership structure includes
institutional ownership, managerial ownership and private investor’s
ownership. Management responsibility of the firm is expressed by the
decision of the firm on amount of leverage. Results of the cross
sectional panel study for non-financial firms showed that only
institutional shareholding is significantly negatively correlated with
debt to equity ratio. Findings from “operational” financial sector
show that leverage is significantly affected only by the CEO/Chair
duality and the size of financial institutions, and insignificantly
affected by ownership structure. Also, the findings show, that there is
a significant negative relationship between profitability and the debt
to equity ratio for non-financial firms, which is consistent with
pecking order theory. Generally, the found results suggest that
corporate governance and a management responsibility play
important role in corporate performance of listed firms in
Kazakhstan.
Abstract: The present study aimed to determine the
effectiveness of Metaphor therapy on depression among female
students. The sample included 60 female students with depression
symptoms selected by simple sampling and randomly divided into
two equal groups (experimental and control groups). Beck
Depression Inventory was used to measure the variables. This was an
experimental study with a pre-test/post-test design with control
group. Eight metaphor therapy sessions were held for the
experimental group. A post-test was administered to both groups.
Data were analyzed using multivariate analysis of covariance
(MANCOVA). Results showed that the Metaphor therapy decreased
depression in the experimental group compared to the control group.
Abstract: Hemoglobin (HB) indicates anemia level and by
extension may reflect the nutritional level and perhaps the immunity
of an individual. Some antiretroviral drugs like Zidovudine are
known to cause anemia in people living with HIV/AIDS (PLWHA).
A cross sectional study using demographic data and blood specimen
from 218 female commercial sex workers attending antiretroviral
therapy (ART) clinics was conducted between December, 2009 and
July, 2011 to assess the effect of zidovudine on hematologic, and
RNA viral load of female sex workers receiving antiretroviral
treatment in north western Nigeria. Anemia is a common and serious
complication of both HIV infection and its treatment. In the setting of
HIV infection, anemia has been associated with decreased quality of
life, functional status, and survival. Antiretroviral therapy,
particularly the highly active antiretroviral therapy (HAART), has
been associated with a decrease in the incidence and severity of
anemia in HIV-infected patients who have received a HAART
regimen for at least 1 year. In this study, result has shown that of the
218 patients, 26 with hemoglobin count between 5.1 – 10g/dl were
observed to have the highest viral load count of 300,000 –
350,000copies/ml. It was also observed that most patients (190) with
HB of 10.1 – 15.0g/dl had viral load count of 200,000 – 250,000
copies /ml. An inverse relationship therefore exists i.e. the lower the
hemoglobin level, the higher the viral load count even though the test
statistics did not show any significance between the two (P = 0.206).
This shows that multivariate logistic regression analysis
demonstrated that anemia was associated with a CD4 + cell count
below 50/μL, female sex workers with a viral load above 100,000
copies/mL, who use zidovudine.
Severe anemia was less prevalent in this study population than in
historical comparators; however, mild to moderate anemia rates
remain high. The study therefore recommends that hematological and
virologic parameters be monitored closely in patients receiving first
line ART regimen.
Abstract: The problems arising from unbalanced data sets
generally appear in real world applications. Due to unequal class
distribution, many researchers have found that the performance of
existing classifiers tends to be biased towards the majority class. The
k-nearest neighbors’ nonparametric discriminant analysis is a method
that was proposed for classifying unbalanced classes with good
performance. In this study, the methods of discriminant analysis are
of interest in investigating misclassification error rates for classimbalanced
data of three diabetes risk groups. The purpose of this
study was to compare the classification performance between
parametric discriminant analysis and nonparametric discriminant
analysis in a three-class classification of class-imbalanced data of
diabetes risk groups. Data from a project maintaining healthy
conditions for 599 employees of a government hospital in Bangkok
were obtained for the classification problem. The employees were
divided into three diabetes risk groups: non-risk (90%), risk (5%),
and diabetic (5%). The original data including the variables of
diabetes risk group, age, gender, blood glucose, and BMI were
analyzed and bootstrapped for 50 and 100 samples, 599 observations
per sample, for additional estimation of the misclassification error
rate. Each data set was explored for the departure of multivariate
normality and the equality of covariance matrices of the three risk
groups. Both the original data and the bootstrap samples showed nonnormality
and unequal covariance matrices. The parametric linear
discriminant function, quadratic discriminant function, and the
nonparametric k-nearest neighbors’ discriminant function were
performed over 50 and 100 bootstrap samples and applied to the
original data. Searching the optimal classification rule, the choices of
prior probabilities were set up for both equal proportions (0.33: 0.33:
0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10)
and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples
indicated that the k-nearest neighbors approach when k=3 or k=4 and
the defined prior probabilities of non-risk: risk: diabetic as 0.90:
0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of
misclassification. The k-nearest neighbors approach would be
suggested for classifying a three-class-imbalanced data of diabetes
risk groups.
Abstract: Introduction: There are multiple social, individual and
cultural factors that influence an individual’s decision to adopt family
planning methods especially among non-users in patriarchal societies
like Pakistan. Non-users, if targeted efficiently, can contribute
significantly to country’s CPR. A research study showed that nonusers
if convinced to adopt lactational amenorrhea method can shift
to long term methods in future. Research shows that if non users are
targeted efficiently a 59% reduction in unintended pregnancies in
Saharan Africa and South-Central and South-East Asia is anticipated.
Methods: We did secondary data analysis on Pakistan
Demographic Heath Survey (2012-13) dataset. Use of contraception
(never-use/ever-use) was the outcome variable. At univariate level
Chi-square/Fisher Exact test was used to assess relationship of
baseline covariates with contraception use. Then variables to be
incorporated in the model were checked for multicollinearity,
confounding and interaction. Then binary logistic regression (with an
urban-rural stratification) was done to find relationship between
contraception use and baseline demographic and social variables.
Results: The multivariate analyses of the study showed that
younger women (≤ 29 years)were more prone to be never users as
compared to those who were >30 years and this trend was seen in
urban areas (AOR 1.92, CI 1.453-2.536) as well as rural areas (AOR
1.809, CI 1.421-2.303). While looking at regional variation, women
from urban Sindh (AOR 1.548, CI 1.142-2.099) and urban
Balochistan (AOR 2.403, CI 1.504-3.839) had more never users as
compared to other urban regions. Women in the rich wealth quintile
were more never users and this was seen both in urban and rural
localities (urban (AOR 1.106 CI .753-1.624); rural areas (AOR 1.162,
CI .887-1.524)) even though these were not statistically significant.
Women idealizing more children (>4) are more never users as
compared to those idealizing less children in both urban (AOR 1.854,
CI 1.275-2.697) and rural areas (AOR 2.101, CI 1.514-2.916).
Women who never lost a pregnancy were more inclined to be nonusers
in rural areas (AOR 1.394, CI 1.127-1.723) .Women familiar
with only traditional or no method had more never users in rural areas
(AOR 1.717, CI 1.127-1.723) but in urban areas it wasn’t significant.
Women unaware of Lady Health Worker’s presence in their area
were more never users especially in rural areas (AOR 1.276, CI
1.014-1.607). Women who did not visit any care provider were more
never users (urban (AOR 11.738, CI 9.112-15.121) rural areas (AOR
7.832, CI 6.243-9.826)).
Discussion/Conclusion: This study concluded that government,
policy makers and private sector family planning programs should
focus on the untapped pool of never users (younger women from underserved provinces, in higher wealth quintiles, who desire more
children.). We need to make sure to cover catchment areas where
there are less LHWs and less providers as ignorance to modern
methods and never been visited by an LHW are important
determinants of never use. This all is in sync with previous literate
from similar developing countries.
Abstract: Introduction: Researchers globally have strived to explore diverse factors that augment the continuation and uptake of family planning methods. Clients’ satisfaction is one of the core determinants facilitating continuation of family planning methods. There is a major debate yet scanty evidence to contrast public and private sectors with respect to client satisfaction. The objective of this study is to compare quality-of-care provided by public and private sectors of Pakistan through a client satisfaction lens. Methods: We used Pakistan Demographic Heath Survey 2012-13 dataset on 3133 women. Ten different multivariate models were made. to explore the relationship between client satisfaction and dependent outcome after adjusting for all known confounding factors and results are presented as OR and AOR (95% CI). Results: Multivariate analyses showed that clients were less satisfied in contraceptive provision from private sector as compared to public sector (AOR 0.92, 95% CI 0.63-1.68) even though the result was not statistically significant. Clients were more satisfied from private sector as compared to the public sector with respect to other determinants of quality-of-care follow-up care (AOR 3.29, 95% CI 1.95-5.55), infection prevention (AOR 2.41, 95% CI 1.60-3.62), counseling services (AOR 2.01, 95% CI 1.27-3.18, timely treatment (AOR 3.37, 95% CI 2.20-5.15), attitude of staff (AOR 2.23, 95% CI 1.50-3.33), punctuality of staff (AOR 2.28, 95% CI 1.92-4.13), timely referring (AOR 2.34, 95% CI 1.63-3.35), staff cooperation (AOR 1.75, 95% CI 1.22-2.51) and complications handling (AOR 2.27, 95% CI 1.56-3.29). Discussion: Public sector has successfully attained substantial satisfaction levels with respect to provision of contraceptives, but it contrasts previous literature from a multi country studies. Our study though in is concordance with a study from Tanzania where public sector was more likely to offer family planning services to clients as compared to private facilities. Conclusion: In majority of the developing countries, public sector is more involved in FP service provision; however, in Pakistan clients’ satisfaction in private sector is more, which opens doors for public-private partnerships and collaboration in the near future.
Abstract: Family has a crucial role in maintaining the
physical, social and mental health of the children. Most of the
mental and anxiety problems of children reflect the complex
interpersonal situations among family members, especially parents.
In other words, anxiety problems of the children are correlated
with deficit relationships of family members and improper
childrearing styles. The parental child rearing styles leads to
positive and negative consequences which affect the children’s
mental health. Therefore, the present research was aimed to
compare the parental childrearing styles and anxiety of children
with stuttering and normal population. It was also aimed to study
the relationship between parental child rearing styles and anxiety
of children. The research sample included 54 boys with stuttering
and 54 normal boys who were selected from the children (boys) of
Tehran, Iran in the age range of 5 to 8 years in 2013. In order to
collect data, Baum-rind Childrearing Styles Inventory and Spence
Parental Anxiety Inventory were used. Appropriate descriptive
statistical methods and multivariate variance analysis and t test for
independent groups were used to test the study hypotheses.
Statistical data analyses demonstrated that there was a significant
difference between stuttering boys and normal boys in anxiety (t =
7.601, p< 0.01); but there was no significant difference between
stuttering boys and normal boys in parental childrearing styles (F =
0.129). There was also not found significant relationship between
parental childrearing styles and children anxiety (F = 0.135, p<
0.05). It can be concluded that the influential factors of children’s
society are parents, school, teachers, peers and media. So, parental
childrearing styles are not the only influential factors on anxiety of
children, and other factors including genetic, environment and
child experiences are effective in anxiety as well. Details are
discussed.
Abstract: This paper aims to investigate the influence of quality
of education and quality of research, provided by local educational
institutions, on the adoption of Information and Communication
Technology (ICT) in managing business operations for companies in
Saudi market. A model was developed and tested using data collected
from 138 Chief Executive Officers (CEOs) of foreign companies in
diverse business sectors. The data is analyzed and managed using
multivariate approaches through standard statistical packages. The
results showed that educational quality has little contribution to the
ICT adoption while research quality seems to play a more prominent
role. These results are analyzed in terms of business environment and
market constraints and further extended to the perceived effectiveness
of applied pedagogical approaches in schools and universities.
Abstract: Pulmonary Function Tests are important non-invasive
diagnostic tests to assess respiratory impairments and provides
quantifiable measures of lung function. Spirometry is the most
frequently used measure of lung function and plays an essential role
in the diagnosis and management of pulmonary diseases. However,
the test requires considerable patient effort and cooperation,
markedly related to the age of patients resulting in incomplete data
sets. This paper presents, a nonlinear model built using Multivariate
adaptive regression splines and Random forest regression model to
predict the missing spirometric features. Random forest based feature
selection is used to enhance both the generalization capability and the
model interpretability. In the present study, flow-volume data are
recorded for N= 198 subjects. The ranked order of feature importance
index calculated by the random forests model shows that the
spirometric features FVC, FEF25, PEF, FEF25-75, FEF50 and the
demographic parameter height are the important descriptors. A
comparison of performance assessment of both models prove that, the
prediction ability of MARS with the `top two ranked features namely
the FVC and FEF25 is higher, yielding a model fit of R2= 0.96 and
R2= 0.99 for normal and abnormal subjects. The Root Mean Square
Error analysis of the RF model and the MARS model also shows that
the latter is capable of predicting the missing values of FEV1 with a
notably lower error value of 0.0191 (normal subjects) and 0.0106
(abnormal subjects) with the aforementioned input features. It is
concluded that combining feature selection with a prediction model
provides a minimum subset of predominant features to train the
model, as well as yielding better prediction performance. This
analysis can assist clinicians with a intelligence support system in the
medical diagnosis and improvement of clinical care.