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: In this paper, an effective non-destructive, noninvasive
approach for leak detection was proposed. The process relies
on analyzing thermal images collected by an IR viewer device that
captures thermo-grams. In this study a statistical analysis of the
collected thermal images of the ground surface along the expected
leak location followed by a visual inspection of the thermo-grams
was performed in order to locate the leak. In order to verify the
applicability of the proposed approach the predicted leak location
from the developed approach was compared with the real leak
location. The results showed that the expected leak location was
successfully identified with an accuracy of more than 95%.
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: Micro-alloyed steel components are used in
automotive industry for the necessity to make the manufacturing
process cycles shorter when compared to conventional steel by
eliminating heat treatment cycles, so an important saving of costs and
energy can be reached by reducing the number of operations. Microalloying
elements like vanadium, niobium or titanium have been
added to medium carbon steels to achieve grain refinement with or
without precipitation strengthening along with uniform
microstructure throughout the matrix. Present study reports the
applicability of medium carbon vanadium micro-alloyed steel in hot
forging. Forgeability has been determined with respect to different
cooling rates, after forging in a hydraulic press at 50% diameter
reduction in temperature range of 900-11000C. Final microstructures,
hardness, tensile strength, and impact strength have been evaluated.
The friction coefficients of different lubricating conditions, viz.,
graphite in hydraulic oil, graphite in furnace oil, DF 150 (Graphite,
Water-Based) die lubricant and dry or without any lubrication were
obtained from the ring compression test for the above micro-alloyed
steel. Results of ring compression tests indicate that graphite in
hydraulic oil lubricant is preferred for free forging and dry lubricant
is preferred for die forging operation. Exceptionally good forgeability
and high resistance to fracture, especially for faster cooling rate has
been observed for fine equiaxed ferrite-pearlite grains, some amount
of bainite and fine precipitates of vanadium carbides and
carbonitrides. The results indicated that the cooling rate has a
remarkable effect on the microstructure and mechanical properties at
room temperature.
Abstract: The objectives of study are the following: To study
the way of life in terms of one hundred years co-existence of the
Muslim and local community in this area 2) To analyze factors affect
to this community with happy co-existence. The study requires
quantitative research to study a history together with the study of
humanity. The result of this study showed that the area of Petchburi
7 community is an ancient area which has owned by the Muslim for
almost 100 years. There is a sanctuary as & center of unity. Later
Bangkok becomes developed and provides more infrastructures like
motorway and other transportation: however, the owners of lands in
this community still keep their lands and build many buildings to run
business. With this purpose, there are many non-Muslim people come
to live here with co-existence. Not only are they convenient to work
but also easy to transport by sky train. There are factors that make
them live harmonious as following: 1) All Muslims in this area are
strict to follow their rules and allocate their community for business.
2) All people, who come and live here, are middle-aged and working
men and women. They, rent rooms closed to their work. 3) There are
Muslim food and desserts, especially Roti, the popular fried flour,
and local Chachak, tea originated from the south of Thailand. All
these food and desserts are famous for working men and women to
home and join after work 4) All Muslim in this area are independent
to lead their own lives although a society changes rapidly.
Abstract: This study presents the moisture variations of
unbound layers from April 2012 to January 2014 in the Interstate 40
(I-40) pavement section in New Mexico. Three moisture probes were
installed at different layers inside the pavement which measure the
continuous moisture variations of the unbound layers. Data show that
the moisture contents of unbound layers are typically constant
throughout the day and month unless there is rainfall. Moisture
contents of all unbound layers change with rainfall. Change in ground
water table may affect the moisture content of unbound layers which
has not been investigated in this study. In addition, the Level 3
predictions of moisture contents using the Pavement Mechanistic-
Empirical (ME) Design software were compared and found quite
reasonable. However, results presented in the current study may not
be applicable for pavement in other regions.
Abstract: This paper proposes a mathematical model and
examines the performance of an exact algorithm for a location–
transportation problems in humanitarian relief. The model determines
the number and location of distribution centers in a relief network,
the amount of relief supplies to be stocked at each distribution center
and the vehicles to take the supplies to meet the needs of disaster
victims under capacity restriction, transportation and budgetary
constraints. The computational experiments are conducted on the
various sizes of problems that are generated. Branch and bound
algorithm is applied for these problems. The results show that this
algorithm can solve problem sizes of up to three candidate locations
with five demand points and one candidate location with up to twenty
demand points without premature termination.
Abstract: Since “Hello Kitty” was manufactured in the market in
1974, the manufacturer, Sanrio Co., Ltd. gains high profits not only
Kitty’s products but also Kitty license, which gives us a picture of
Sanrio’s sales strategy in the global market. Kitty’s history, its
products, and Sanrio’s sales strategy are researched in this paper.
Comparing it to American Girl, and focusing on KITTYLAB, a type of
attraction where you can enjoy games with Kitty, and choose its parts
to build your own Kitty, the image of the cultural icon can be altered.
Abstract: The Blue Nile Basin is the most important tributary of
the Nile River. Egypt and Sudan are almost dependent on water
originated from the Blue Nile. This multi-dependency creates
conflicts among the three countries Egypt, Sudan, and Ethiopia
making the management of these conflicts as an international issue.
Good assessment of the water resources of the Blue Nile is an
important to help in managing such conflicts. Hydrological models
are good tool for such assessment. This paper presents a critical
review of the nature and variability of the climate and hydrology of
the Blue Nile Basin as a first step of using hydrological modeling to
assess the water resources of the Blue Nile. Many several attempts
are done to develop basin-scale hydrological modeling on the Blue
Nile. Lumped and semi distributed models used averages of
meteorological inputs and watershed characteristics in hydrological
simulation, to analyze runoff for flood control and water resource
management. Distributed models include the temporal and spatial
variability of catchment conditions and meteorological inputs to
allow better representation of the hydrological process. The main
challenge of all used models was to assess the water resources of the
basin is the shortage of the data needed for models calibration and
validation. It is recommended to use distributed model for their
higher accuracy to cope with the great variability and complexity of
the Blue Nile basin and to collect sufficient data to have more
sophisticated and accurate hydrological modeling.
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.
Abstract: The research studies the behaviors based on
sufficiency economy philosophy at individual and community
levelsas well as the satisfaction of the urban community leaders by
collecting data with purposive sampling technique. For in-depth
interviews with 26 urban community leaders, the result shows that
the urban community leaders have good knowledge and
understanding about sufficiency economy philosophy. Especially in
terms of money spending, they must consider the need for living and
be economical. The activities in the community or society should not
take advantage of the others as well as colleagues. At present, most of
the urban community leaders live in sufficient way. They often spend
time with public service, but many families are dealing with debt.
Many communities have some political conflict and high family
allowances because of living in the urban communities with rapid
social and economic changes. However, there are many communities
that leaders have applied their wisdom in development for their
people by gathering and grouping the professionals to form activities
such as making chilli sauce, textile organization, making artificial
flowers to worship the sanctity. The most prominent group is the foot
massage business in Wat Pracha Rabue Tham. This professional
group is supported continuously by the government. One of the
factors in terms of satisfaction used for evaluating community leaders
is the customary administration in brotherly, interdependent way
rather than using the absolute power or controlling power, but using
the roles of leader to perform the activities with their people intently,
determinedly and having public mind for people.
Abstract: This paper describes the tradeoffs and the design from
scratch of a self-contained, easy-to-use health dashboard software
system that provides customizable data tracking for patients in smart
homes. The system is made up of different software modules and
comprises a front-end and a back-end component. Built with HTML,
CSS, and JavaScript, the front-end allows adding users, logging into
the system, selecting metrics, and specifying health goals. The backend
consists of a NoSQL Mongo database, a Python script, and a
SimpleHTTPServer written in Python. The database stores user
profiles and health data in JSON format. The Python script makes use
of the PyMongo driver library to query the database and displays
formatted data as a daily snapshot of user health metrics against
target goals. Any number of standard and custom metrics can be
added to the system, and corresponding health data can be fed
automatically, via sensor APIs or manually, as text or picture data
files. A real-time METAR request API permits correlating weather
data with patient health, and an advanced query system is
implemented to allow trend analysis of selected health metrics over
custom time intervals. Available on the GitHub repository system,
the project is free to use for academic purposes of learning and
experimenting, or practical purposes by building on it.
Abstract: A computational fluid dynamics (CFD) model is
developed for rechargeable non-aqueous electrolyte lithium-air
batteries with a partial opening for oxygen supply to the cathode.
Multi-phase transport phenomena occurred in the battery are
considered, including dissolved lithium ions and oxygen gas in the
liquid electrolyte, solid-phase electron transfer in the porous
functional materials and liquid-phase charge transport in the
electrolyte. These transport processes are coupled with the
electrochemical reactions at the active surfaces, and effects of
discharge reaction-generated solid Li2O2 on the transport properties
and the electrochemical reaction rate are evaluated and implemented
in the model. The predicted results are discussed and analyzed in terms
of the spatial and transient distribution of various parameters, such as
local oxygen concentration, reaction rate, variable solid Li2O2 volume
fraction and porosity, as well as the effective diffusion coefficients. It
is found that the effect of the solid Li2O2 product deposited at the solid
active surfaces is significant on the transport phenomena and the
overall battery performance.
Abstract: The air transport impact on environment is more than
ever a limitative obstacle to the aeronautical industry continuous
growth. Over the last decades, considerable effort has been carried
out in order to obtain quieter aircraft solutions, whether by changing
the original design or investigating more silent maneuvers. The
noise propagated by rotating surfaces is one of the most important
sources of annoyance, being present in most aerial vehicles. Bearing
this is mind, CEIIA developed a new computational chain for
noise prediction with in-house software tools to obtain solutions in
relatively short time without using excessive computer resources. This
work is based on the new acoustic tool, which aims to predict the
rotor noise generated during steady and maneuvering flight, making
use of the flexibility of the C language and the advantages of GPU
programming in terms of velocity. The acoustic tool is based in the
Formulation 1A of Farassat, capable of predicting two important
types of noise: the loading and thickness noise. The present work
describes the most important features of the acoustic tool, presenting
its most relevant results and framework analyses for helicopters and
UAV quadrotors.
Abstract: Estimation of model parameters is necessary to predict
the behavior of a system. Model parameters are estimated using
optimization criteria. Most algorithms use historical data to estimate
model parameters. The known target values (actual) and the output
produced by the model are compared. The differences between the
two form the basis to estimate the parameters. In order to compare
different models developed using the same data different criteria are
used. The data obtained for short scale projects are used here. We
consider software effort estimation problem using radial basis
function network. The accuracy comparison is made using various
existing criteria for one and two predictors. Then, we propose a new
criterion based on linear least squares for evaluation and compared
the results of one and two predictors. We have considered another
data set and evaluated prediction accuracy using the new criterion.
The new criterion is easy to comprehend compared to single statistic.
Although software effort estimation is considered, this method is
applicable for any modeling and prediction.
Abstract: Biofuels production has come forth as a future
technology to combat the problem of depleting fossil fuels. Bio-based
ethanol production from enzymatic lignocellulosic biomass
degradation serves an efficient method and catching the eye of
scientific community. High cost of the enzyme is the major obstacle
in preventing the commercialization of this process. Thus main
objective of the present study was to optimize composition of
medium components for enhancing cellulase production by newly
isolated strain of Bacillus tequilensis. Nineteen factors were taken
into account using statistical Plackett-Burman Design. The significant
variables influencing the cellulose production were further employed
in statistical Response Surface Methodology using Central
Composite Design for maximizing cellulase production. The
optimum medium composition for cellulase production was: peptone
(4.94 g/L), ammonium chloride (4.99 g/L), yeast extract (2.00 g/L),
Tween-20 (0.53 g/L), calcium chloride (0.20 g/L) and cobalt chloride
(0.60 g/L) with pH 7, agitation speed 150 rpm and 72 h incubation at
37oC. Analysis of variance (ANOVA) revealed high coefficient of
determination (R2) of 0.99. Maximum cellulase productivity of 11.5
IU/ml was observed against the model predicted value of 13 IU/ml.
This was found to be optimally active at 60oC and pH 5.5.
Abstract: The restrained construction zoning, an important part
in the urban master plan, is a necessary planning tool to control the city
sprawl, to guarantee the reservation implementation of the various
types of protective elements, and to realize the storage of the essential
urban spatial resources. Simultaneously, owing to the diverse
constitutes of restrained construction area and the various stakeholders
involved in, its planning requires an overall consideration of all
elements from the perspective of coordination+, balance and
practicability to deal with the problems and conflicts in this process.
Taking Yangzijin Ecological Restrained Construction Area in
Yangzhou as an example, this study analyzes all the potential actors,
agencies and stakeholders in this restrained construction area, as well
as the relevant conflicts between each other. Besides, this study tries to
build up a planning procedure based on the framework of governance
theory, and proposes a possible planning method that combines
"rigidity" and "flexibility" to protect the ecological limitation
boundary, to take every interest into account, and to promote economic
development in a harmonious society.
Abstract: Load modeling is one of the central functions in
power systems operations. Electricity cannot be stored, which means
that for electric utility, the estimate of the future demand is necessary
in managing the production and purchasing in an economically
reasonable way. A majority of the recently reported approaches are
based on neural network. The attraction of the methods lies in the
assumption that neural networks are able to learn properties of the
load. However, the development of the methods is not finished, and
the lack of comparative results on different model variations is a
problem. This paper presents a new approach in order to predict the
Tunisia daily peak load. The proposed method employs a
computational intelligence scheme based on the Fuzzy neural
network (FNN) and support vector regression (SVR). Experimental
results obtained indicate that our proposed FNN-SVR technique gives
significantly good prediction accuracy compared to some classical
techniques.
Abstract: The aim of this paper is to perform experimental
modal analysis (EMA) of reinforced concrete (RC) square slabs.
EMA is the process of determining the modal parameters (Natural
Frequencies, damping factors, modal vectors) of a structure from a
set of frequency response functions FRFs (curve fitting). Although,
experimental modal analysis (or modal testing) has grown steadily in
popularity since the advent of the digital FFT spectrum analyzer in
the early 1970’s, studying all types of members and materials using
such method have not yet been well documented. Therefore, in this
work, experimental tests were conducted on RC square slab
specimens of dimensions 600mm x 600mmx 40mm. Experimental
analysis was based on freely supported boundary condition.
Moreover, impact testing as a fast and economical means of finding
the modes of vibration of a structure was used during the
experiments. In addition, Pico Scope 6 device and MATLAB
software were used to acquire data, analyze and plot Frequency
Response Function (FRF). The experimental natural frequencies
which were extracted from measurements exhibit good agreement
with analytical predictions. It is showed that EMA method can be
usefully employed to investigate the dynamic behavior of RC slabs.
Abstract: As the use of geothermal energy grows internationally
more effort is required to monitor and protect areas with rare and
important geothermal surface features. A number of approaches are
presented for developing and calibrating numerical geothermal
reservoir models that are capable of accurately representing
geothermal surface features. The approaches are discussed in the
context of cases studies of the Rotorua geothermal system and the
Orakei-korako geothermal system, both of which contain important
surface features. The results show that models are able to match the
available field data accurately and hence can be used as valuable
tools for predicting the future response of the systems to changes in
use.