Abstract: This article presents an alternative collapse capacity
intensity measure in the three elements form which is influenced by
the spectral ordinates at periods longer than that of the first mode
period at near and far source sites. A parameter, denoted by β, is
defined by which the spectral ordinate effects, up to the effective
period (2T1), on the intensity measure are taken into account. The
methodology permits to meet the hazard-levelled target extreme
event in the probabilistic and deterministic forms. A MATLAB code
is developed involving OpenSees to calculate the collapse capacities
of the 8 archetype RC structures having 2 to 20 stories for regression
process. The incremental dynamic analysis (IDA) method is used to
calculate the structure’s collapse values accounting for the element
stiffness and strength deterioration. The general near field set
presented by FEMA is used in a series of performing nonlinear
analyses. 8 linear relationships are developed for the 8structutres
leading to the correlation coefficient up to 0.93. A collapse capacity
near field prediction equation is developed taking into account the
results of regression processes obtained from the 8 structures. The
proposed prediction equation is validated against a set of actual near
field records leading to a good agreement. Implementation of the
proposed equation to the four archetype RC structures demonstrated
different collapse capacities at near field site compared to those of
FEMA. The reasons of differences are believed to be due to
accounting for the spectral shape effects.
Abstract: The knitted fabric suffers a deformation in its
dimensions due to stretching and tension factors, transverse and
longitudinal respectively, during the process in rectilinear knitting
machines so it performs a dry relaxation shrinkage procedure and
thermal action of prefixed to obtain stable conditions in the knitting.
This paper presents a dry relaxation shrinkage prediction of Bordeaux
fiber using a feed forward neural network and linear regression
models. Six operational alternatives of shrinkage were predicted. A
comparison of the results was performed finding neural network
models with higher levels of explanation of the variability and
prediction. The presence of different reposes is included. The models
were obtained through a neural toolbox of Matlab and Minitab
software with real data in a knitting company of Southern
Guanajuato. The results allow predicting dry relaxation shrinkage of
each alternative operation.
Abstract: The work reported through this paper is an
experimental work conducted on High Performance Concrete (HPC)
with super plasticizer with the aim to develop some models suitable
for prediction of compressive strength of HPC mixes. In this study,
the effect of varying proportions of fly ash (0% to 50% @ 10%
increment) on compressive strength of high performance concrete has
been evaluated. The mix designs studied were M30, M40 and M50 to
compare the effect of fly ash addition on the properties of these
concrete mixes. In all eighteen concrete mixes that have been
designed, three were conventional concretes for three grades under
discussion and fifteen were HPC with fly ash with varying
percentages of fly ash. The concrete mix designing has been done in
accordance with Indian standard recommended guidelines. All the
concrete mixes have been studied in terms of compressive strength at
7 days, 28 days, 90 days, and 365 days. All the materials used have
been kept same throughout the study to get a perfect comparison of
values of results. The models for compressive strength prediction
have been developed using Linear Regression method (LR), Artificial
Neural Network (ANN) and Leave-One-Out Validation (LOOV)
methods.
Abstract: Predicting earnings management is vital for the capital
market participants, financial analysts and managers. The aim of this
research is attempting to respond to this query: Is there a significant
difference between the regression model and neural networks’
models in predicting earnings management, and which one leads to a
superior prediction of it? In approaching this question, a Linear
Regression (LR) model was compared with two neural networks
including Multi-Layer Perceptron (MLP), and Generalized
Regression Neural Network (GRNN). The population of this study
includes 94 listed companies in Tehran Stock Exchange (TSE)
market from 2003 to 2011. After the results of all models were
acquired, ANOVA was exerted to test the hypotheses. In general, the
summary of statistical results showed that the precision of GRNN did
not exhibit a significant difference in comparison with MLP. In
addition, the mean square error of the MLP and GRNN showed a
significant difference with the multi variable LR model. These
findings support the notion of nonlinear behavior of the earnings
management. Therefore, it is more appropriate for capital market
participants to analyze earnings management based upon neural
networks techniques, and not to adopt linear regression models.
Abstract: The paper aims to evaluate the effect of online
advertising on consumer purchase behavior in Malaysian
organizations. The paper has potential to extend and refine theory. A
survey was distributed among Students of UTM university during the
winter 2014 and 160 responses were collected. Regression analysis
was used to test the hypothesized relationships of the model. Result
shows that the predictors (cost saving factor, convenience factor and
customized product or services) have positive impact on intention to
continue seeking online advertising.
Abstract: Comparative analysis of the properties of melon seed,
coconut fruit and their oil yield were evaluated in this work using
standard analytical technique AOAC. The results of the analysis
carried out revealed that the moisture contents of the samples studied
are 11.15% (melon) and 7.59% (coconut). The crude lipid content are
46.10% (melon) and 55.15% (coconut).The treatment combinations
used (leaching time, leaching temperature and solute: solvent ratio)
showed significant difference (p < 0.05) in yield between the
samples, with melon oil seed flour having a higher percentage range
of oil yield (41.30 – 52.90%) and coconut (36.25 – 49.83%). The
physical characterization of the extracted oil was also carried out.
The values gotten for refractive index are 1.487 (melon seed oil) and
1.361 (coconut oil) and viscosities are 0.008 (melon seed oil) and
0.002 (coconut oil). The chemical analysis of the extracted oils shows
acid value of 1.00mg NaOH/g oil (melon oil), 10.050mg NaOH/g oil
(coconut oil) and saponification value of 187.00mg/KOH (melon oil)
and 183.26mg/KOH (coconut oil). The iodine value of the melon oil
gave 75.00mg I2/g and 81.00mg I2/g for coconut oil. A standard
statistical package Minitab version 16.0 was used in the regression
analysis and analysis of variance (ANOVA). The statistical software
mentioned above was also used to optimize the leaching process.
Both samples gave high oil yield at the same optimal conditions. The
optimal conditions to obtain highest oil yield ≥ 52% (melon seed)
and ≥ 48% (coconut seed) are solute - solvent ratio of 40g/ml,
leaching time of 2hours and leaching temperature of 50oC. The two
samples studied have potential of yielding oil with melon seed giving
the higher yield.
Abstract: Currently, planners try to have more green travel
options to decrease economic, social and environmental problems.
Therefore, this study tries to find significant urban travel factors to be
used to increase the usage of alternative urban travel modes. This
paper attempts to identify the relationship between prominent urban
mobility indicators and daily trips by public transport in 30 cities
from various parts of the world. Different travel modes,
infrastructures and cost indicators were evaluated in this research as
mobility indicators. The results of multi-linear regression analysis
indicate that there is a significant relationship between mobility
indicators and the daily usage of public transport.
Abstract: A biosphere reserve is developed to create harmony
amongst economic development, community development, and
environmental protection, through partnership between human and
nature. Giam Siak Kecil Bukit Batu Biosphere Reserve (GSKBB BR)
in Riau Province, Indonesia, is unique in that it has peat soil
dominating the area, many springs essential for human livelihood,
high biodiversity. Furthermore, it is the only biosphere reserve
covering privately managed production forest areas. In this research, we aimed at analyzing the threat of deforestation
and forest fire, and the potential of CO2 emission at GSKBB BR. We
used Landsat image, arcView software, and ERDAS IMAGINE 8.5
Software to conduct spatial analysis of land cover and land use
changes, calculated CO2 emission based on emission potential from
each land cover and land use type, and exercised simple linear
regression to demonstrate the relation between CO2 emission
potential and deforestation. The result showed that, beside in the buffer zone and transition
area, deforestation also occurred in the core area. Spatial analysis of
land cover and land use changes from years 2010, 2012, and 2014
revealed that there were changes of land cover and land use from
natural forest and industrial plantation forest to other land use types,
such as garden, mixed garden, settlement, paddy fields, burnt areas,
and dry agricultural land. Deforestation in core area, particularly at
the Giam Siak Kecil Wildlife Reserve and Bukit Batu Wildlife
Reserve, occurred in the form of changes from natural forest in to
garden, mixed garden, shrubs, swamp shrubs, dry agricultural land,
open area, and burnt area. In the buffer zone and transition area,
changes also happened, what once swamp forest changed into garden,
mixed garden, open area, shrubs, swamp shrubs, and dry agricultural
land. Spatial analysis on land cover and land use changes indicated
that deforestation rate in the biosphere reserve from 2010 to 2014 had
reached 16 119 ha/year. Beside deforestation, threat toward the
biosphere reserve area also came from forest fire. The occurrence of forest fire in 2014 had burned 101 723 ha of the
area, in which 9 355 ha of core area, and 92 368 ha of buffer zone
and transition area. Deforestation and forest fire had increased CO2
emission as much as 24 903 855 ton/year.
Abstract: As a basic physiology need, threat to sufficient food
production is threat to human survival. Food security has been an
issue that has gained global concern. This paper looks at the food
security in Nigeria by assessing the availability of food and
accessibility of the available food. The paper employed multiple
linear regression technique and graphic trends of growth rates of
relevant variables to show the situation of food security in Nigeria.
Results of the tests revealed that population growth rate was higher
than the growth rate of food availability in Nigeria for the earlier
period of the study. Commercial bank credit to agricultural sector,
foreign exchange utilization for food and the Agricultural Credit
Guarantee Scheme Fund (ACGSF) contributed significantly to food
availability in Nigeria. Food prices grew at a faster rate than the
average income level, making it difficult to access sufficient food. It
implies that prior to the year 2012; there was insufficient food to feed
the Nigerian populace. However, continued credit to the food and
agricultural sector will ensure sustained and sufficient production of
food in Nigeria. Microfinance banks should make sufficient credit
available to smallholder farmer. Government should further control
and subsidize the rising price of food to make it more accessible by
the people.
Abstract: This paper seeks to assess the implications of bank
consolidation on the performance of small and medium scale
enterprises in the Nigerian economy. Multiple linear regression
technique and correlation matrix test were employed to measure the
extent to which small and medium scale enterprises asset size,
survival and access to credit were influenced. The result showed that
bank deposit (BD) and bank credit (L or BC) impacted on asset size
and survival of small and medium scale enterprises. None of the
variables had significant impact on SMEs access to credit. There is a
shift of focus by commercial banks away from small and medium
scale enterprises (small customers), which is evidenced by the
significant negative influence of bank credit to both the survival and
asset size of small and medium enterprises. While micro finance
banks work hard at providing funds to small and medium scale
entrepreneurs, their capacity to meet the needs of these entrepreneurs
is constrained. CBN should make policies that will boost micro
finance bank’s capital and also monitor closely the management of
the banks to ensure prudent financing of small and medium scale
investments.
Abstract: The present paper attempts to investigate the
prediction of air entrainment rate and aeration efficiency of a free
overfall jets issuing from a triangular sharp crested weir by using
regression based modelling. The empirical equations, Support vector
machine (polynomial and radial basis function) models and the linear
regression techniques were applied on the triangular sharp crested
weirs relating the air entrainment rate and the aeration efficiency to
the input parameters namely drop height, discharge, and vertex angle.
It was observed that there exists a good agreement between the
measured values and the values obtained using empirical equations,
Support vector machine (Polynomial and rbf) models and the linear
regression techniques. The test results demonstrated that the SVM
based (Poly & rbf) model also provided acceptable prediction of the
measured values with reasonable accuracy along with empirical
equations and linear regression techniques in modelling the air
entrainment rate and the aeration efficiency of a free overfall jets
issuing from triangular sharp crested weir. Further sensitivity analysis
has also been performed to study the impact of input parameter on the
output in terms of air entrainment rate and aeration efficiency.
Abstract: This study examined the mental health and behavioral
problems in early adolescence with the instrument of Achenbach
System of Empirically Based Assessment (ASEBA). The purpose of
the study was stratified sampling method was used to collect data
from 1975 participants. Multiple regression models and hierarchical
regression models were applied to examine the relations between the
background variables and internalizing problems, and the ones
between students’ performance and internalizing problems. The
results indicated that several background variables as predictors could
significantly predict the anxious/depressed problem; reading and
social study scores could significantly predict the anxious/depressed
problem. However the class as a hierarchical macro factor did not
indicate the significant effect. In brief, the majority of these models
represented that the background variables, behaviors and academic
performance were significantly related to the anxious/depressed
problem.
Abstract: In this paper, relationship between different properties
of IC concrete and water cement ratio, obtained from a
comprehensive experiment conducted on IC using local materials
(Burnt clay chips- BC) is presented. In addition, saturated SAP was
used as an IC material in some cases. Relationships have been
developed through regression analysis. The focus of this analysis is
on developing relationship between a dependent variable and an
independent variable. Different percent replacements of BC and
water cement ratios were used. Compressive strength, modulus of
elasticity, water permeability and chloride permeability were tested
and variations of these parameters were analyzed with respect to
water cement ratio.
Abstract: This paper seeks to assess the implications of
insurance to foreign direct investment inflow in Nigeria. Multiple
linear regression technique and correlation matrix test were employed
to measure the extent to which foreign direct investment was
influenced. The result showed that insurance premium (IP), asset size
of insurance industry (AS), and total investment of the industry (TI)
impacted significantly and positively on foreign direct investment
inflow in Nigeria. There should be effective risk transfer mechanism
and financial intermediation, which gives the investor confidence in
the risk management strength of the host country.
Abstract: The Multiple Intelligences theory characterizes human
intelligence as a multifaceted entity that exists in all human beings
with varying degrees. The most important contribution of this theory
to the field of English Language Teaching (ELT) is its role in
identifying individual differences and designing more learnercentered
programs. The present study aims at investigating the
relationship between different elements of multiple intelligence and
grammar scores. To this end, 63 female Iranian EFL learner selected
from among intermediate students participated in the study. The
instruments employed were a Nelson English language test, Michigan
Grammar Test, and Teele Inventory for Multiple Intelligences
(TIMI). The results of Pearson Product-Moment Correlation revealed
a significant positive correlation between grammatical accuracy and
linguistic as well as interpersonal intelligence. The results of
Stepwise Multiple Regression indicated that linguistic intelligence
contributed to the prediction of grammatical accuracy.
Abstract: Commercial banks in Nigeria adopted many strategies
to attract fresh deposits including the use of high deposit rate.
However, pricing of banking services moved in favor of the banks at
the expense of customers, resulting in their seeking other investment
alternatives rather than saving their money in the bank. Both deposit
and lending rates were greatly influenced by the Central Bank of
Nigeria (CBN) decision on interest rate. Therefore, commercial bank
effort to attract deposits via manipulation of her rates was greatly
limited, otherwise the banks will be giving out more than it earned.
The study aimed at examining the relationship between interest rate
and fixed fund deposit of commercial banks, how policy-controlled
interest rate affected commercial bank’s fixed fund deposit The
researcher employed ordinary least square technique, using, multiple
linear regression, unrestricted vector auto-regression, correlation
matrix test, granger causality and impulse response graph in the
analysis. Commercial bank’s interest rates affected commercial
bank’s fixed fund deposit significantly while policy-controlled
interest rate did not significantly transmit through the commercial
bank’s interest rates to affect fixed fund deposit. While commercial
banks seek creative ways to expand their fixed fund deposit, policy
authorities in Nigeria should better coordinate interest rate fluctuation
and induce competition in the entire financial sector.
Abstract: An approach was evaluated for the retrieval of soil
moisture of bare soil surface using bistatic scatterometer data in the
angular range of 200 to 700 at VV- and HH- polarization. The
microwave data was acquired by specially designed X-band (10
GHz) bistatic scatterometer. The linear regression analysis was done
between scattering coefficients and soil moisture content to select the
suitable incidence angle for retrieval of soil moisture content. The 250
incidence angle was found more suitable. The support vector
regression analysis was used to approximate the function described
by the input output relationship between the scattering coefficient and
corresponding measured values of the soil moisture content. The
performance of support vector regression algorithm was evaluated by
comparing the observed and the estimated soil moisture content by
statistical performance indices %Bias, root mean squared error
(RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias,
root mean squared error (RMSE) and Nash-Sutcliffe Efficiency
(NSE) were found 2.9451, 1.0986 and 0.9214 respectively at HHpolarization.
At VV- polarization, the values of %Bias, root mean
squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were
found 3.6186, 0.9373 and 0.9428 respectively.
Abstract: In recent years, honeycomb fiber reinforced plastic
(FRP) sandwich panels have been increasingly used in various
industries. Low weight, low price and high mechanical strength are
the benefits of these structures. However, their mechanical properties
and behavior have not been fully explored. The objective of this
study is to conduct a combined numerical-statistical investigation of
honeycomb FRP sandwich beams subject to torsion load. In this
paper, the effect of geometric parameters of sandwich panel on
maximum shear strain in both face and core and angle of torsion in a
honeycomb FRP sandwich structures in torsion is investigated. The
effect of Parameters including core thickness, face skin thickness,
cell shape, cell size, and cell thickness on mechanical behavior of the
structure were numerically investigated. Main effects of factors were
considered in this paper and regression equations were derived.
Taguchi method was employed as experimental design and an
optimum parameter combination for the maximum structure stiffness
has been obtained. The results showed that cell size and face skin
thickness have the most significant impacts on torsion angle,
maximum shear strain in face and core.
Abstract: Lead time is a critical measure of a supply chain's
performance. It impacts both the customer satisfactions as well as the
total cost of inventory. This paper presents the result of a study on the
analysis of the customer order lead-time for a multinational company.
In the study, the lead time was divided into three stages respectively:
order entry, order fulfillment, and order delivery. A sample of size 2,425 order lines was extracted from the
company's records to use for this study. The sample data entails
information regarding customer orders from the time of order entry
until order delivery. Data regarding the lead time of each stage for
different orders were also provided. Summary statistics on lead time
data reveals that about 30% of the orders were delivered later than the
scheduled due date. The result of the multiple linear regression
analysis technique revealed that component type, logistics parameter,
order size and the customer type have significant impacts on lead
time. Data analysis on the stages of lead time indicates that stage 2
consumed over 50% of the lead time. Pareto analysis was made to
study the reasons for the customer order delay in each stage.
Recommendation was given to resolve the problem.
Abstract: This study examined whether big five personality traits
affect game addiction with control of psychological, social, and
demographic factors. Specifically, using data from a survey of 789
game users in Korea, we conducted a regression analysis to see the
associations of psychological (loneliness/depression), social (activities
with family/friends), self-efficacy (game/general), gaming (daily
gaming time/perception), demographic (age/gender), and personality
traits (extraversion, neuroticism conscientiousness, agreeableness, &
openness) with the degree of game addiction. Results showed that
neuroticism increase game addiction with no effect of extraversion on
the addiction. General self-efficacy negatively affected game
addiction, whereas game self-efficacy increased the degree of game
addiction. Loneliness enhanced game addiction while depression
showed a negative effect on the addiction. Results and implications are
discussed.