Abstract: Wind energy offers a significant advantage such as no
fuel costs and no emissions from generation. However, wind energy
sources are variable and non-dispatchable. The utility grid is able to
accommodate the variability of wind in smaller proportion along with
the daily load. However, at high penetration levels, the variability can
severely impact the utility reserve requirements and the cost
associated with it. In this paper the impact of wind energy is
evaluated in detail in formulating the total utility cost. The objective
is to minimize the overall cost of generation while ensuring the
proper management of the load. Overall cost includes the curtailment
cost, reserve cost and the reliability cost, as well as any other penalty
imposed by the regulatory authority. Different levels of wind
penetrations are explored and the cost impacts are evaluated. As the
penetration level increases significantly, the reliability becomes a
critical question to be answered. Here we increase the penetration
from the wind yet keep the reliability factor within the acceptable
limit provided by NERC. This paper uses an economic dispatch (ED)
model to incorporate wind generation into the power grid. Power
system costs are analyzed at various wind penetration levels using
Linear Programming. The goal of this study is show how the
increases in wind generation will affect power system economics.
Abstract: Constructing a portfolio of investments is one of the
most significant financial decisions facing individuals and
institutions. In accordance with the modern portfolio theory
maximization of return at minimal risk should be the investment goal
of any successful investor. In addition, the costs incurred when
setting up a new portfolio or rebalancing an existing portfolio must
be included in any realistic analysis.
In this paper rebalancing an investment portfolio in the presence of
transaction costs on the Croatian capital market is analyzed. The
model applied in the paper is an extension of the standard portfolio
mean-variance optimization model in which transaction costs are
incurred to rebalance an investment portfolio. This model allows
different costs for different securities, and different costs for buying
and selling. In order to find efficient portfolio, using this model, first,
the solution of quadratic programming problem of similar size to the
Markowitz model, and then the solution of a linear programming
problem have to be found. Furthermore, in the paper the impact of
transaction costs on the efficient frontier is investigated. Moreover, it
is shown that global minimum variance portfolio on the efficient
frontier always has the same level of the risk regardless of the amount
of transaction costs. Although efficient frontier position depends of
both transaction costs amount and initial portfolio it can be concluded
that extreme right portfolio on the efficient frontier always contains
only one stock with the highest expected return and the highest risk.
Abstract: The Cone Penetration Test (CPT) is a common in-situ
test which generally investigates a much greater volume of soil more
quickly than possible from sampling and laboratory tests. Therefore,
it has the potential to realize both cost savings and assessment of soil
properties rapidly and continuously. The principle objective of this
paper is to demonstrate the feasibility and efficiency of using
artificial neural networks (ANNs) to predict the soil angle of internal
friction (Φ) and the soil modulus of elasticity (E) from CPT results
considering the uncertainties and non-linearities of the soil. In
addition, ANNs are used to study the influence of different
parameters and recommend which parameters should be included as
input parameters to improve the prediction. Neural networks discover
relationships in the input data sets through the iterative presentation
of the data and intrinsic mapping characteristics of neural topologies.
General Regression Neural Network (GRNN) is one of the powerful
neural network architectures which is utilized in this study. A large
amount of field and experimental data including CPT results, plate
load tests, direct shear box, grain size distribution and calculated data
of overburden pressure was obtained from a large project in the
United Arab Emirates. This data was used for the training and the
validation of the neural network. A comparison was made between
the obtained results from the ANN's approach, and some common
traditional correlations that predict Φ and E from CPT results with
respect to the actual results of the collected data. The results show
that the ANN is a very powerful tool. Very good agreement was
obtained between estimated results from ANN and actual measured
results with comparison to other correlations available in the
literature. The study recommends some easily available parameters
that should be included in the estimation of the soil properties to
improve the prediction models. It is shown that the use of friction
ration in the estimation of Φ and the use of fines content in the
estimation of E considerable improve the prediction models.
Abstract: The performance and analysis of speech recognition
system is illustrated in this paper. An approach to recognize the
English word corresponding to digit (0-9) spoken by 2 different
speakers is captured in noise free environment. For feature extraction,
speech Mel frequency cepstral coefficients (MFCC) has been used
which gives a set of feature vectors from recorded speech samples.
Neural network model is used to enhance the recognition
performance. Feed forward neural network with back propagation
algorithm model is used. However other speech recognition
techniques such as HMM, DTW exist. All experiments are carried
out on Matlab.
Abstract: Experimental & numeral study of temperature
distribution during milling process, is important in milling quality
and tools life aspects. In the present study the milling cross-section
temperature is determined by using Artificial Neural Networks
(ANN) according to the temperature of certain points of the work
piece and the point specifications and the milling rotational speed of
the blade. In the present work, at first three-dimensional model of the
work piece is provided and then by using the Computational Heat
Transfer (CHT) simulations, temperature in different nods of the
work piece are specified in steady-state conditions. Results obtained
from CHT are used for training and testing the ANN approach. Using
reverse engineering and setting the desired x, y, z and the milling
rotational speed of the blade as input data to the network, the milling
surface temperature determined by neural network is presented as
output data. The desired points temperature for different milling
blade rotational speed are obtained experimentally and by
extrapolation method for the milling surface temperature is obtained
and a comparison is performed among the soft programming ANN,
CHT results and experimental data and it is observed that ANN soft
programming code can be used more efficiently to determine the
temperature in a milling process.
Abstract: The ultrasound imaging is very popular to diagnosis
the disease because of its non-invasive nature. The ultrasound
imaging slowly produces low quality images due to the presence of
spackle noise and wave interferences. There are several algorithms to
be proposed for the segmentation of ultrasound carotid artery images
but it requires a certain limit of user interaction. The pixel in an
image is highly correlated so the spatial information of surrounding
pixels may be considered in the process of image segmentation which
improves the results further. When data is highly correlated, one pixel
may belong to more than one cluster with different degree of
membership. There is an important step to computerize the evaluation
of arterial disease severity using segmentation of carotid artery lumen
in 2D and 3D ultrasonography and in finding vulnerable
atherosclerotic plaques susceptible to rupture which can cause stroke.
Abstract: Nic Pizzolatto’s True Detective offers profound
mythological and philosophical ramblings for audiences with literary
sensibilities. An American Sothern Gothic with its Bayon landscape
of the Gulf Coast of Louisiana, where two detectives Rustin Cohle
and Martin Hart begin investigating the isolated murder of Dora
Lange, only to discover an entrenched network of perversion and
corruption, offers an existential outlook. The proposed research paper
shall attempt to investigate the pervasive themes of gothic and
existentialism in the music of the first season of the series.
Abstract: Formal verification is proposed to ensure the
correctness of the design and make functional verification more
efficient. As cache plays a vital role in the design of System on Chip
(SoC), and cache with Memory Management Unit (MMU) and cache
memory unit makes the state space too large for simulation to verify,
then a formal verification is presented for such system design. In the
paper, a formal model checking verification flow is suggested and a
new cache memory model which is called “exhaustive search model”
is proposed. Instead of using large size ram to denote the whole cache
memory, exhaustive search model employs just two cache blocks. For
cache system contains data cache (Dcache) and instruction cache
(Icache), Dcache memory model and Icache memory model are
established separately using the same mechanism. At last, the novel
model is employed to the verification of a cache which is module of a
custom-built SoC system that has been applied in practical, and the
result shows that the cache system is verified correctly using the
exhaustive search model, and it makes the verification much more
manageable and flexible.
Abstract: The aim of research was to define the relations
between volatile compounds, some parameters (pH, titratable acidity
(TA), total soluble solid (TSS), lactic acid bacteria count) and
consumer preference of commercial fermented milks. These relations
tend to be used for controlling and developing new fermented milk
product. Three leading commercial brands of fermented milks in
Thailand were evaluated by consumers (n=71) using hedonic scale
for four attributes (sweetness, sourness, flavour, and overall liking),
volatile compounds using headspace-solid phase microextraction
(HS-SPME) GC-MS, pH, TA, TSS and LAB count. Then the
relations were analyzed by principal component analysis (PCA). The
PCA data showed that all of four attributes liking scores were related
to each other. They were also related to TA, TSS and volatile
compounds. The related volatile compounds were mainly on
fermented produced compounds including acetic acid, furanmethanol,
furfural, octanoic acid and the volatiles known as artificial fruit
flavour (beta pinene, limonene, vanillin, and ethyl vanillin). These
compounds were provided the information about flavour addition in
commercial fermented milk in Thailand.
Abstract: Conservation works in Malaysia that is procured by
public organisation usually follow the traditional approach where the
works are tendered based on Bills of Quantities (BQ). One of the
purposes of tendering is to enable the selection of a competent
contractor that offers a competitive price. While competency of the
contractors are assessed by their technical knowledge, experience and
track records, the assessment of pricing will be dependent on the
tender amount. However, the issue currently faced by the
conservation works sector is the difficulty in assessing the
competitiveness and reasonableness of the tender amount due to the
high variance between the tenders amount. Thus, this paper discusses
the factors that cause difficulty to the tenderers in pricing
competitively in a bidding exercise for conservation tenders. Data on
tendering is collected from interviews with conservation works
contractors to gain in-depth understanding of the barriers faced in
pricing tenders of conservation works. Findings from the study lent
support to the contention that the variance of tender amount is very
high amongst tenderers. The factors identified in the survey are the
format of BQ, hidden works, experience and labour and material
costs.
Abstract: This research aimed to study about motivation for
students of Suan Sunandha Rajabhat University to follow and happily
live according to Sufficiency Economy Philosophy. Having collected
394 questionnaires, the result showed that most students had great
motivation to follow this philosophy at a high level, especially in
terms of righteousness in profession; besides, students’ determination
and intention to apply this philosophy in everyday lives was
impressive though the students’ families were not completely ready.
Each of students, in fact, consulted their families for plans of any
activities without tiredness and discouragement based on the saying,
“Where there’s a will, there’s a way.” On the part of universities life,
students interacted with society and created projects that supported
income to the community including exercises, sports, recreational
activities, and community services.
Abstract: It is likely that robots will cross the boundaries of
industry into households over the next decades. With demographic
challenges worldwide, the future ageing populations will require the
introduction of assistive technologies capable of providing, care,
human dignity and quality of life through the aging process. Robotics
technology has a high potential for being used in the areas of social
and healthcare by promoting a wide range of activities such as
entertainment, companionship, supervision or cognitive and physical
assistance. However such close Human Robotics Interaction (HRI)
encompass a rich set of ethical scenarios that need to be addressed
before Socially Assistive Robots (SARs) reach the global markets.
Such interactions with robots may seem a worthy goal for many
technical/financial reasons but inevitably require close attention to
the ethical dimensions of such interactions. This article investigates
the current HRI benchmark of social success. It revises it according
to the ethical principles of beneficence, non-maleficence and justice
aligned with social care ethos. An extension of such benchmark is
proposed based on an empirical study of HRIs conducted with elderly
groups.
Abstract: In urban area, several landmarks may affect housing
price and rents, and hedonic analysis should employ distance variables
corresponding to each landmarks. Unfortunately, the effects of
distances to landmarks on housing prices are generally not consistent
with the true price. These distance variables may cause magnitude
error in regression, pointing a problem of spatial multicollinearity. In
this paper, we provided some approaches for getting the samples with
less bias and method on locating the specific sampling area to avoid
the multicollinerity problem in two specific landmarks case.
Abstract: The eccentric connectivity index based on degree and
eccentricity of the vertices of a graph is a widely used graph invariant
in mathematics.
In this paper, we present the explicit eccentric connectivity index,
first and second Zagreb indices for a Corona graph and sub divisionrelated
corona graphs.
Abstract: In this study, an experiment was executed related to
the strength of wooden materials which have been commonly used
both in the past and present against pressure and whether fire
retardant materials used against fire have any effects or not. Totally
81 samples which included 3 different wood species, 3 different
sizes, 2 different fire retardants and 2 unprocessed samples were
prepared. Compressive pressure tests were applied to the prepared
samples, their variance analyses were executed in accordance with
the obtained results and it was aimed to determine the most
convenient wooden materials and fire-retardant coating material. It
was also determined that the species of wood and the species of
coating caused the decrease and/or increase in the resistance against
pressure.
Abstract: The paper deals with the problems of the actual
behavior, failure mechanism and load-carrying capacity of the special
bolt connection developed and intended for the assembly connections
of truss main girders of perspective railway temporary steel bridges.
Within the framework of this problem solution, several types of
structural details of assembly joints have been considered as the
conceptual structural design. Based on the preliminary evaluation of
advantages or disadvantages of these ones, in principle two basic
structural configurations – so-called “tooth” and “splice-plate”
connections have been selected for the subsequent detailed
investigation. This investigation is mainly based on the experimental
verification of the actual behavior, strain and failure mechanism and
corresponding strength of the connection, and on its numerical
modeling using FEM. This paper is focused only on the cyclic
loading (fatigue) tests results of “splice-plate” connections and their
evaluation, which have already been finished. Simultaneously with
the fatigue tests, the static loading tests have been realized too, but
these ones, as well as FEM numerical modeling, are not the subject of
this paper.
Abstract: This research was conducted in the Mae Sot
Watershed where located in the Moei River Basin at the Upper
Salween River Basin in Tak Province, Thailand. The Mae Sot
Municipality is the largest urban area in Tak Province and situated in
the midstream of the Mae Sot Watershed. It usually faces flash flood
problem after heavy rain due to poor flood management has been
reported since economic rapidly bloom up in recent years. Its
catchment can be classified as ungauged basin with lack of rainfall
data and no any stream gaging station was reported. It was attached
by most severely flood events in 2013 as the worst studied case for
all those communities in this municipality. Moreover, other problems
are also faced in this watershed, such shortage water supply for
domestic consumption and agriculture utilizations including a
deterioration of water quality and landslide as well. The research
aimed to increase capability building and strengthening the
participation of those local community leaders and related agencies to
conduct better water management in urban area was started by mean
of the data collection and illustration of the appropriated application
of some short period rainfall forecasting model as they aim for better
flood relief plan and management through the hydrologic model
system and river analysis system programs. The authors intended to
apply the global rainfall data via the integrated data viewer (IDV)
program from the Unidata with the aim for rainfall forecasting in a
short period of 7-10 days in advance during rainy season instead of
real time record. The IDV product can be present in an advance
period of rainfall with time step of 3-6 hours was introduced to the
communities. The result can be used as input data to the hydrologic
modeling system model (HEC-HMS) for synthesizing flood
hydrographs and use for flood forecasting as well. The authors
applied the river analysis system model (HEC-RAS) to present flood
flow behaviors in the reach of the Mae Sot stream via the downtown
of the Mae Sot City as flood extents as the water surface level at
every cross-sectional profiles of the stream. Both models of HMS and
RAS were tested in 2013 with observed rainfall and inflow-outflow
data from the Mae Sot Dam. The result of HMS showed fit to the
observed data at the dam and applied at upstream boundary discharge
to RAS in order to simulate flood extents and tested in the field, and
the result found satisfying. The product of rainfall from IDV was fair
while compared with observed data. However, it is an appropriate
tool to use in the ungauged catchment to use with flood hydrograph
and river analysis models for future efficient flood relief plan and
management.
Abstract: The objective of this study was to assess whether
living in proximity to a roofing fiber cement factory in southern
Thailand was associated with physical, mental, social, and spiritual
health domains measured in a self-reported health risk assessment
(HRA) questionnaire. A cross-sectional study was conducted among
community members divided into two groups: near population (living
within 0-2km of factory) and far population (living within 2-5km of
factory) (N=198). A greater proportion of those living far from the
factory (65.34%) reported physical health problems than the near
group (51.04%) (p =0.032). This study has demonstrated that the near
population group had higher proportion of participants with positive
ratings on mental assessment (30.34%) and social health impacts
(28.42%) than far population group (10.59% and 16.67%,
respectively) (p
Abstract: This study investigates the cleaning performance of
high intensity 360 kHz frequency on removal of nano-dimensional
and sub-micron particles from various surfaces, uniformity of the
cleaning tank and run to run variation of cleaning process. The
uniformity of the cleaning tank was measured by two different
methods i.e. 1. ppbTM meter and 2. Liquid Particle Counting (LPC)
technique. The result indicates that the energy was distributed more
uniformly throughout the entire cleaning vessel even at the corners
and edges of the tank when megasonic sweeping technology is
applied. The result also shows that rinsing the parts with 360 kHz
frequency at final rinse gives lower particle counts, hence higher
cleaning efficiency as compared to other frequencies. When
megasonic sweeping technology is applied each piezoelectric
transducers will operate at their optimum resonant frequency and
generates stronger acoustic cavitational force and higher acoustic
streaming velocity. These combined forces are helping to enhance the
particle removal and at the same time improve the overall cleaning
performance. The multiple extractions study was also carried out for
various frequencies to measure the cleaning potential and asymptote
value.
Abstract: Our goal is development of an algorithm capable of
predicting the directional trend of the Standard and Poor’s 500 index
(S&P 500). Extensive research has been published attempting to
predict different financial markets using historical data testing on an
in-sample and trend basis, with many authors employing excessively
complex mathematical techniques. In reviewing and evaluating these
in-sample methodologies, it became evident that this approach was
unable to achieve sufficiently reliable prediction performance for
commercial exploitation. For these reasons, we moved to an out-ofsample
strategy based on linear regression analysis of an extensive
set of financial data correlated with historical closing prices of the
S&P 500. We are pleased to report a directional trend accuracy of
greater than 55% for tomorrow (t+1) in predicting the S&P 500.