Abstract: This paper is concerned with the single-item
continuous review inventory system in which demand is stochastic
and discrete. The budget consumed for purchasing the ordered items
is not restricted but it incurs extra cost when exceeding specific
value. The unit purchasing price depends on the quantity ordered
under the all-units discounts cost structure. In many actual systems,
the budget as a resource which is occupied by the purchased items is
limited and the system is able to confront the resource shortage by
charging more costs. Thus, considering the resource shortage costs as
a part of system costs, especially when the amount of resource
occupied by the purchased item is influenced by quantity discounts,
is well motivated by practical concerns. In this paper, an optimization
problem is formulated for finding the optimal (r, Q) policy, when the
system is influenced by the budget limitation and a discount pricing
simultaneously. Properties of the cost function are investigated and
then an algorithm based on a one-dimensional search procedure is
proposed for finding an optimal (r, Q) policy which minimizes the
expected system costs.
Abstract: This paper examines the relationship between
corporate governance rating and stock prices of 26 Turkish firms
listed in Turkish stock exchange (Borsa Istanbul) by using panel data
analysis over five-year period. The paper also investigates the stock
performance of firms with governance rating with regards to the
market portfolio (i.e. BIST 100 Index) both prior and after
governance scoring began. The empirical results show that there is no
relation between corporate governance rating and stock prices when
using panel data for annual variation in both rating score and stock
prices. Further analysis indicates surprising results that while the
selected firms outperform the market significantly prior to rating, the
same performance does not continue afterwards.
Abstract: A Rice Sheller is used for obtaining polished white
rice from paddy. There are about 3000 Rice Shellers in Punjab and
50000 in India. During the process of shelling lot of dust is emitted
from different unit operations like paddy silo, paddy shaker, bucket
elevators, huskers, paddy separator etc. These dust emissions have
adverse effect on the health of the workers and the wear and tear of
the shelling machinery is fast. All the dust emissions spewing out of
these unit operations of a rice Sheller were contained by providing
suitable hoods and enclosures while ensuring their workability. These
were sucked by providing an induced draft fan followed by a high
efficiency cyclone separator that has got an overall dust collection
efficiency of more than 90%. This cyclone separator replaced two
cyclone separators and a filter bag house, which the Rice Sheller was
already having. The dust concentration in the stack after the
installation of cyclone separator is well within the stipulated
standards. Besides controlling pollution, there is improvement in the
quality of products like bran and the life of shelling machinery has
enhanced. The payback period of this technology is less than four
shelling months.
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: Mustard leaves are rich in folates, vitamin A, K and
B-complex. Mustard greens are low in calories and fats and rich in
dietary fiber. They are rich in potassium, manganese, iron, copper,
calcium, magnesium and low in sodium. It is very rich in antioxidants
and Phytonutrients. For the optimization of process variables
(moisture content and mustard leave powder), the experiments were
conducted according to central composite Face Centered Composite
design of RSM. The mustard leaves powder was replaced with
composite flour (a combination of rice, chickpea and corn in the ratio
of 70:15:15). The extrudate was extruded in a twin screw extruder at
a barrel temperature of 120°C. The independent variables were
mustard leaves powder (2-10 %) and moisture content (12-20 %).
Responses analyzed were bulk density, water solubility index, water
absorption index, lateral expansion, antioxidant activity, total
phenolic content, and overall acceptability. The optimum conditions
obtained were 7.19 g mustard leaves powder in 100g premix having
16.8% moisture content (w.b).
Abstract: Rice bran is normally used as a raw material for rice
bran oil production or sold as feed with a low price. Conventionally,
the protein in defatted rice bran was extracted using alkaline
extraction and acid precipitation, which involves in chemical usage
and lowering some nutritious component. This study was conducted
in order to extract of rice bran protein concentrate (RBPC) from
defatted rice bran using enzymes and employing polysaccharides in a
precipitating step. The properties of RBPC obtained will be compared
to those of a control sample extracted using a conventional method.
The results showed that extraction of protein from rice bran using
enzymes exhibited the higher protein recovery compared to that
extraction with alkaline. The extraction conditions using alcalase 2%
(v/w) at 50 C, pH 9.5 gave the highest protein (2.44%) and yield
(32.09%) in extracted solution compared to other enzymes. Rice bran
protein concentrate powder prepared by a precipitation step using
alginate (protein in solution: alginate 1:0.016) exhibited the highest
protein (27.55%) and yield (6.84%). Precipitation using alginate was
better than that of acid. RBPC extracted with alkaline (ALK) or
enzyme alcalase (ALC), then precipitated with alginate (AL)
(samples RBP-ALK-AL and RBP-ALC-AL) yielded the precipitation
rate of 75% and 91.30%, respectively. Therefore, protein
precipitation using alginate was then selected. Amino acid profile of
control sample, and sample precipitated with alginate, as compared to
casein and soy protein isolated, showed that control sample showed
the highest content among all sample. Functional property study of
RBP showed that the highest nitrogen solubility occurred in pH 8-10.
There was no statically significant between emulsion capacity and
emulsion stability of control and sample precipitated by alginate.
However, control sample showed a higher of foaming capacity and
foaming stability compared to those of sample precipitated with
alginate. The finding was successful in terms of minimizing
chemicals used in extraction and precipitation steps in preparation of
rice bran protein concentrate. This research involves in a production
of value-added product in which the double amount of protein (28%)
compared to original amount (14%) contained in rice bran could be
beneficial in terms of adding to food products e.g. healthy drink with
high protein and fiber. In addition, the basic knowledge of functional
property of rice bran protein concentrate was obtained, which can be
used to appropriately select the application of this value-added
product from rice bran.
Abstract: This article aims to analyze the static stability and
pseudostatic slope by using different methods such as: Bishop
method, Junbu, Ordinary, Morgenstern-price and GLE. The two
dimensional modeling of slope stability under various loading as: the
earthquake effect, the water level and road mobile charges. The
results show that the slope is stable in the static case without water,
but in other cases, the slope lost its stability and give unstable. The
calculation of safety factor is to evaluate the stability of the slope
using the limit equilibrium method despite the difference between the
results obtained by these methods that do not rely on the same
assumptions. In the end, the results of this study illuminate well the
influence of the action of water, moving loads and the earthquake on
the stability of the slope.
Abstract: Due to today’s globalization as well as outsourcing
practices of the companies, the Supply Chain (SC) performances
have become more dependent on the efficient movement of material
among places that are geographically dispersed, where there is more
chance for disruptions. One such disruption is the quality and
delivery uncertainties of outsourcing. These uncertainties could lead
the products to be unsafe and, as is the case in a number of recent
examples, companies may have to end up in recalling their products.
As a result of these problems, there is a need to develop a
methodology for selecting suppliers globally in view of risks
associated with low quality and late delivery. Accordingly, we
developed a two-stage stochastic model that captures the risks
associated with uncertainty in quality and delivery as well as a
solution procedure for the model. The stochastic model developed
simultaneously optimizes supplier selection and purchase quantities
under price discounts over a time horizon. In particular, our target is
the study of global organizations with multiple sites and multiple
overseas suppliers, where the pricing is offered in suppliers’ local
currencies. Our proposed methodology is applied to a case study for a
US automotive company having two assembly plants and four
potential global suppliers to illustrate how the proposed model works
in practice.
Abstract: We report herein the development and preliminary mechanical characterization of fully-dense multi-wall carbon nanotube (MWCNT)-reinforced ceramics and glasses based on a completely new methodology termed High Shear Compaction (HSC). The tubes are introduced and bound to the matrix grains by aid of polymeric binders to form flexible green bodies which are sintered and densified by spark plasma sintering to unprecedentedly high densities of 100% of the pure-matrix value. The strategy was validated across a PyrexTM glass / MWCNT composite while no identifiable factors limit application to other types of matrices. Nondestructive evaluation, based on ultrasonics, of the dynamic mechanical properties of the materials including elastic, shear and bulk modulus as well as Poisson’s ratio showed optimum property improvement at 0.5 %wt tube loading while evidence of nanoscalespecific energy dissipative characteristics acting complementary to nanotube bridging and pull-out indicate a high potential in a wide range of reinforcing and multifunctional applications.
Abstract: Biomass briquette gasification is regarded as a
promising route for efficient briquette use in energy generation, fuels
and other useful chemicals. However, previous research has been
focused on briquette gasification in fixed bed gasifiers such as
updraft and downdraft gasifiers. Fluidised bed gasifier has the
potential to be effectively sized to medium or large scale. This study
investigated the use of fuel briquettes produced from blends of rice
husks and corn cobs biomass, in a bubbling fluidised bed gasifier.
The study adopted a combination of numerical equations and Aspen
Plus simulation software, to predict the product gas (syngas)
composition base on briquette density and biomass composition
(blend ratio of rice husks to corn cobs). The Aspen Plus model was
based on an experimentally validated model from the literature. The
results based on a briquette size 32 mm diameter and relaxed density
range of 500 to 650kg/m3, indicated that fluidisation air required in
the gasifier increased with increase in briquette density, and the
fluidisation air showed to be the controlling factor compared with the
actual air required for gasification of the biomass briquettes. The
mass flowrate of CO2 in the predicted syngas composition increased
with an increase in air flow, in the gasifier, while CO decreased and
H2 was almost constant. The ratio of H2 to CO for various blends of
rice husks and corn cobs did not significantly change at the designed
process air, but a significant difference of 1.0 was observed between
10/90 and 90/10 % blend of rice husks and corn cobs.
Abstract: This study examines the feasibility of indirect solar
desalination in oil producing countries in the Middle East and North
Africa (MENA) region. It relies on value engineering (VE) and costbenefit
with sensitivity analyses to identify optimal coupling
configurations of desalination and solar energy technologies. A
comparative return on investment was assessed as a function of water
costs for varied plant capacities (25,000 to 75,000 m3/day), project
lifetimes (15 to 25 years), and discount rates (5 to 15%) taking into
consideration water and energy subsidies, land cost as well as
environmental externalities in the form of carbon credit related to
greenhouse gas (GHG) emissions reduction. The results showed
reverse osmosis (RO) coupled with photovoltaic technologies (PVs)
as the most promising configuration, robust across different prices for
Brent oil, discount rates, as well as different project lifetimes.
Environmental externalities and subsidies analysis revealed that a
16% reduction in existing subsidy on water tariffs would ensure
economic viability. Additionally, while land costs affect investment
attractiveness, the viability of RO coupled with PV remains possible
for a land purchase cost
Abstract: Students' academic achievement, along with the
effects of different variables, has been a serious concern of educators
since long ago. This study was an attempt to investigate the interplay
of Locus of Control (LOC), academic achievement and biological
variables among Iranian online EFL Learners. The participants of the
study included 100 students of different age groups and genders
studying English online at Iran Language Institute (ILI), Isfahan,
Iran. The instrument used was Trice Academic LOC questionnaire
which identifies orientations of internality or externality. The
participants' Grade Point Averages (GPAs) were used as the measure
of their academic achievement. A series of independent samples ttests
were performed on the data. The results of the study showed that
(a) there were no significant differences between male and female
participants in LOC orientation, (b) there was no relationship
between LOC and academic achievement among internal males and
females, (c) external females were better achievers than external
males, (d) and the age had no significant relationship with LOC and
academic achievement. It can be concluded that the social, cultural
patterns of genders have changed. This study might help sociologists
and psychologists as well as applied linguists in that they reflect the
recent social changes and their effects on the LOC and their
consequent implications in teaching languages.
Abstract: Toddy sediment (TS) was cultured in a PDA medium
to determine initial yeast load, and also it was undergone sun, shade,
solar, dehumidified cold air (DCA) and hot air oven (at 400, 500 and
60oC) drying with a view to preserve viability of yeast. Thereafter,
this study was conducted according to two factor factorial design in
order to determine best preservation method. Therein the dried TS
from the best drying method was taken and divided into two portions.
One portion was mixed with 3: 7 ratio of TS: rice flour and the
mixture was divided in to two again. While one portion was kept
under in house condition the other was in a refrigerator. Same
procedure was followed to the rest portion of TS too but it was at the
same ratio of corn flour. All treatments were vacuum packed in triple
laminate pouches and the best preservation method was determined
in terms of leavening index (LI). The TS obtained from the best
preservation method was used to make foods (bread and hopper) and
organoleptic properties of it were evaluated against same of ordinary
foods using sensory panel with a five point hedonic scale.
Results revealed that yeast load or fresh TS was 58×106 CFU/g.
The best drying method in preserving viability of yeast was DCA
because LI of this treatment (96%) is higher than that of other three
treatments. Organoleptic properties of foods prepared from best
preservation method are as same as ordinary foods according to Duo
trio test.
Abstract: In this paper, a new concept of closed-loop design for a
product is presented. The closed-loop design model is developed by
integrating forward design and reverse design. Based on this new
concept, a closed-loop design model for sustainable manufacturing by
integrated evaluation of forward design, reverse design, and green
manufacturing using a fuzzy analytic network process is developed. In
the design stage of a product, with a given product requirement and
objective, there can be different ways to design the detailed
components and specifications. Therefore, there can be different
design cases to achieve the same product requirement and objective.
Subsequently, in the design evaluation stage, it is required to analyze
and evaluate the different design cases. The purpose of this research is
to develop a model for evaluating the design cases by integrated
evaluating the criteria in forward design, reverse design, and green
manufacturing. A fuzzy analytic network process method is presented
for integrated evaluation of the criteria in the three models. The
comparison matrices for evaluating the criteria in the three groups are
established. The total relational values among the three groups
represent the total relational effects. In applications, a super matrix
model is created and the total relational values can be used to evaluate
the design cases for decision-making to select the final design case. An
example product is demonstrated in this presentation. It shows that the
model is useful for integrated evaluation of forward design, reverse
design, and green manufacturing to achieve a closed-loop design for
sustainable manufacturing objective.
Abstract: The purpose of the paper is to estimate the US small
wind turbines market potential and forecast the small wind turbines
sales in the US. The forecasting method is based on the application of
the Bass model and the generalized Bass model of innovations
diffusion under replacement purchases. In the work an exponential
distribution is used for modeling of replacement purchases. Only one
parameter of such distribution is determined by average lifetime of
small wind turbines. The identification of the model parameters is
based on nonlinear regression analysis on the basis of the annual
sales statistics which has been published by the American Wind
Energy Association (AWEA) since 2001 up to 2012. The estimation
of the US average market potential of small wind turbines (for
adoption purchases) without account of price changes is 57080
(confidence interval from 49294 to 64866 at P = 0.95) under average
lifetime of wind turbines 15 years, and 62402 (confidence interval
from 54154 to 70648 at P = 0.95) under average lifetime of wind
turbines 20 years. In the first case the explained variance is 90,7%,
while in the second - 91,8%. The effect of the wind turbines price
changes on their sales was estimated using generalized Bass model.
This required a price forecast. To do this, the polynomial regression
function, which is based on the Berkeley Lab statistics, was used. The
estimation of the US average market potential of small wind turbines
(for adoption purchases) in that case is 42542 (confidence interval
from 32863 to 52221 at P = 0.95) under average lifetime of wind
turbines 15 years, and 47426 (confidence interval from 36092 to
58760 at P = 0.95) under average lifetime of wind turbines 20 years.
In the first case the explained variance is 95,3%, while in the second
– 95,3%.
Abstract: Background: Worldwide, at least 2.8 million people
die each year as a result of being overweight or obese, and 35.8
million (2.3%) of global DALYs are caused by overweight or
obesity. Obesity is acknowledged as one of the burning public
health problems reducing life expectancy and quality of life. The
body composition analysis of the university population is essential
in assessing the nutritional status, as well as the risk of developing
diseases associated with abnormal body fat content so as to make
nutritional recommendations. Objectives: The main aim was to
determine the prevalence of obesity and overweight in University
students using Anthropometric analysis and BIA methods. Material
and Methods: In this cross-sectional study, 283 university students
participated. The body composition analysis was undertaken by
using mainly: i) Anthropometric Measurement: Height, Weight,
BMI, waist circumference, hip circumference and skin fold
thickness, ii) Bio-electrical impedance was used for analysis of
body fat mass, fat percent and visceral fat which was measured by
Tanita SC-330P Professional Body Composition Analyzer. The
data so collected were compiled in MS Excel and analyzed for
males and females using SPSS 16. Results and Discussion: The
mean age of the male (n= 153) studied subjects was 25.37 ±2.39
years and females (n=130) was 22.53 ±2.31. The data of BIA
revealed very high mean fat per cent of the female subjects i.e.
30.3±6.5 per cent whereas mean fat per cent of the male subjects
was 15.60±6.02 per cent indicating a normal body fat range. The
findings showed high visceral fat of both males (12.92±3.02) and
females (16.86±4.98). BMI, BF% and WHR were higher among
females, and BMI was higher among males. The most evident
correlation was verified between BF% and WHR for female
students (r=0.902; p
Abstract: The US Consumer Price Indices (CPIs) measures
hundreds of items in the US economy. Many social programs
and government benefits index to the CPIs. The purpose of
this project is to modernize an existing process. This paper will
show the development of a small, visual, software product that
documents the Economic Price Adjustment (EPA) for longterm
contracts. The existing workbook does not provide the
flexibility to calculate EPAs where the base-month and the
option-month are different. Nor does the workbook provide
automated error checking. The small, visual, software product
provides the additional flexibility and error checking. This
paper presents the feedback to project.
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: A mathematical model of the additional effects of the
liquid in the hydrodynamic gap is presented in the paper. An
incompressible viscous fluid is considered. Based on computational
modeling are determined the matrices of mass, stiffness and damping.
The mathematical model is experimentally verified.
Abstract: Micro-electromechanical system (MEMS)
accelerometers and gyroscopes are suitable for the inertial navigation
system (INS) of many applications due to low price, small
dimensions and light weight. The main disadvantage in a comparison
with classic sensors is a worse long term stability. The estimation
accuracy is mostly affected by the time-dependent growth of inertial
sensor errors, especially the stochastic errors. In order to eliminate
negative effects of these random errors, they must be accurately
modeled. In this paper, the Allan variance technique will be used in
modeling the stochastic errors of the inertial sensors. By performing
a simple operation on the entire length of data, a characteristic curve
is obtained whose inspection provides a systematic characterization
of various random errors contained in the inertial-sensor output data.