Abstract: The autonomic nervous system has a regulatory
structure that helps people adapt to changes in their environment by
adjusting or modifying some functions in response to stress, and regulating involuntary function of human organs. The purpose of this
study was to investigate the effect of combined stimulation, both
far-infrared heating and chiropractic, on the autonomic nervous system
activities using thermal image and heart rate variability. Six healthy subjects participated in this test. We compared the before and after
autonomic nervous system activities through obtaining thermal image
and photoplethysmogram signal. The thermal images showed that the
combined stimulation changed subject-s body temperature more
highly and widely than before. The result of heart rate variability
indicated that LF/HF ratio decreased. We concluded that combined
stimulation activates autonomic nervous system, and expected other
possibilities of this combined stimulation.
Abstract: A new interface circuit for capacitive sensor is
presented. This paper presents the design and simulation of soil
moisture capacitive sensor interface circuit based on phase
differential technique. The circuit has been designed and fabricated
using MIMOS- 0.35"m CMOS technology. Simulation and test
results show linear characteristic from 36 – 52 degree phase
difference, representing 0 – 100% in soil moisture level. Test result
shows the circuit has sensitivity of 0.79mV/0.10 phase difference,
translating into resolution of 10% soil moisture level.
Abstract: Apparel product development is an important stage in the life cycle of a product. Shortening this stage will help to reduce the costs of a garment. The aim of this study is to examine the production parameters in knitwear apparel companies by defining the unit costs, and developing a software to calculate the unit costs of garments and make the cost estimates. In this study, with the help of a questionnaire, different companies- systems of unit cost estimating and cost calculating were tried to be analyzed. Within the scope of the questionnaire, the importance of cost estimating process for apparel companies and the expectations from a new cost estimating program were investigated. According to the results of the questionnaire, it was seen that the majority of companies which participated to the questionnaire use manual cost calculating methods or simple Microsoft Excel spreadsheets to make cost estimates. Furthermore, it was discovered that many companies meet with difficulties in archiving the cost data for future use and as a solution to that problem, it is thought that prior to making a cost estimate, sub units of garment costs which are fabric, accessory and the labor costs should be analyzed and added to the database of the programme beforehand. Another specification of the cost estimating unit prepared in this study is that the programme was designed to consist of two main units, one of which makes the product specification and the other makes the cost calculation. The programme is prepared as a web-based application in order that the supplier, the manufacturer and the customer can have the opportunity to communicate through the same platform.
Abstract: In this paper, we evaluate the choice of suitable
quantization characteristics for both the decoder messages and the
received samples in Low Density Parity Check (LDPC) coded
systems using M-QAM (Quadrature Amplitude Modulation)
schemes. The analysis involves the demapper block that provides
initial likelihood values for the decoder, by relating its quantization
strategy of the decoder. A mapping strategy refers to the grouping of
bits within a codeword, where each m-bit group is used to select a
2m-ary signal in accordance with the signal labels. Further we
evaluate the system with mapping strategies like Consecutive-Bit
(CB) and Bit-Reliability (BR). A new demapper version, based on
approximate expressions, is also presented to yield a low complexity
hardware implementation.
Abstract: Nowadays, cardiac disease is one of the most common
cause of death. Each year almost one million of angioplasty interventions and stents implantations are made all over the world.
Unfortunately, in 20-30% of cases neointimal proliferations leads to
restenosis occurring within the following period of 3-6 months. Three major factors are believed to contribute mostly to the edge
restenosis: (a) mechanical damage of the artery-s wall caused by the
stent implantation, (b) interaction between the stent and the blood constituents and (c) endothelial growth stimulation by small (lower
that 1.5 Pa) and oscillating wall shear stress. Assuming that this last actor is particularly important, a numerical model of restenosis
basing on wall shear stress distribution in the stented artery was elaborated. A numerical simulations of the development of in-stent
restenosis have been performed and realistic geometric patterns of a
progressing lumen reduction have been obtained
Abstract: In this paper, the relationship between learning
motivation and learning performance is explored by using exchange
theory. The relationship is concluded that external performance can
raise learning motivation and then increase learning performance. The
internal performance should be not completely neglected and the
external performance should be not attached important excessively.
The parents need self-study and must be also reeducated. The existing
education must be improved in raise of internal performance. The
incorrect learning thinking will mislead the students, parents, and
educators of next generation, when the students obtain good learning
performance in the learning environment with excess stimulants. Over
operation of external performance will result abnormal learning
thinking and violating learning goal. Learning is not only to obtain
performance. Learning quality and learning performance will be
limited as without learning motivation. The best learning motivation
is, the best learning performance is. The learning for reward is not
good for learning performance. Strategies of promoting life-long
learning are including the encouraging for learner, establishment of
good interaction learning environment, and the advertisement of the
merit and the importance of life-long learning, which can let the
learner with the correct learning motivation.
Abstract: Thanks to VR technology advanced, there are many
researches had used VR technology to develop a training system.
Using VR characteristics can simulate many kinds of situations to
reach our training-s goal. However, a good training system not only
considers real simulation but also considers learner-s learning
motivation. So, there are many researches started to conduct game-s
features into VR training system. We typically called this is a serious
game. It is using game-s features to engage learner-s learning
motivation. However, VR or Serious game has another important
advantage. That is simulating feature. Using this feature can create
any kinds of pressured environments. Because in the real
environment may happen any emergent situations. So, increasing the
trainees- pressure is more important when they are training. Most
pervious researches are investigated serious game-s applications and
learning performance. Seldom researches investigated how to
increase the learner-s mental workload when they are training. So, in
our study, we will introduce a real case study and create two types
training environments. Comparing the learner-s mental workload
between VR training and serious game.
Abstract: The mitigation of crop loss due to damaging freezes
requires accurate air temperature prediction models. Previous work
established that the Ward-style artificial neural network (ANN) is a
suitable tool for developing such models. The current research
focused on developing ANN models with reduced average prediction
error by increasing the number of distinct observations used in
training, adding additional input terms that describe the date of an
observation, increasing the duration of prior weather data included in
each observation, and reexamining the number of hidden nodes used
in the network. Models were created to predict air temperature at
hourly intervals from one to 12 hours ahead. Each ANN model,
consisting of a network architecture and set of associated parameters,
was evaluated by instantiating and training 30 networks and
calculating the mean absolute error (MAE) of the resulting networks
for some set of input patterns. The inclusion of seasonal input terms,
up to 24 hours of prior weather information, and a larger number of
processing nodes were some of the improvements that reduced
average prediction error compared to previous research across all
horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or
12.5%, less than the previous model. Prediction MAEs eight and 12
hours ahead improved by 0.17°C and 0.16°C, respectively,
improvements of 7.4% and 5.9% over the existing model at these
horizons. Networks instantiating the same model but with different
initial random weights often led to different prediction errors. These
results strongly suggest that ANN model developers should consider
instantiating and training multiple networks with different initial
weights to establish preferred model parameters.
Abstract: To simulate heating systems in buildings, a research oriented computer code has been developed in Sharif University of Technology in Iran where the climate, existing heating equipment in buildings, consumer behavior and their interactions are considered for simulating energy consumption in conventional systems such as heaters, radiators and fan-coils. In order to validate the computer code, the available data of five buildings was used and the computed consumed energy was compared with the estimated energy extracted from monthly bills. The initial heating system was replaced by the alternative system and the effect of this change was observed on the energy consumption. As a result, the effect of changing heating equipment on energy consumption was investigated in different climates. Changing heater to radiator renders energy conservation up to 50% in all climates and changing radiator to fan-coil decreases energy consumption in climates with cold and dry winter.
Abstract: Power system state estimation is the process of
calculating a reliable estimate of the power system state vector
composed of bus voltages' angles and magnitudes from telemetered
measurements on the system. This estimate of the state vector
provides the description of the system necessary for the operation
and security monitoring. Many methods are described in the
literature for solving the state estimation problem, the most important
of which are the classical weighted least squares method and the nondeterministic
genetic based method; however both showed
drawbacks. In this paper a modified version of the genetic
algorithm power system state estimation is introduced, Sensitivity of
the proposed algorithm to genetic operators is discussed, the
algorithm is applied to case studies and finally it is compared with
the classical weighted least squares method formulation.
Abstract: A dual-reciprocity boundary element method is presented
for the numerical solution of a class of axisymmetric elastodynamic
problems. The domain integrals that arise in the integrodifferential
formulation are converted to line integrals by using the
dual-reciprocity method together suitably constructed interpolating
functions. The second order time derivatives of the displacement
in the governing partial differential equations are suppressed by
using Laplace transformation. In the Laplace transform domain, the
problem under consideration is eventually reduced to solving a system
of linear algebraic equations. Once the linear algebraic equations are
solved, the displacement and stress fields in the physical domain can
be recovered by using a numerical technique for inverting Laplace
transforms.
Abstract: In this paper, the construction of a detailed spine
model is presented using the LifeMOD Biomechanics Modeler. The
detailed spine model is obtained by refining spine segments in
cervical, thoracic and lumbar regions into individual vertebra
segments, using bushing elements representing the intervertebral
discs, and building various ligamentous soft tissues between
vertebrae. In the sagittal plane of the spine, constant force will be
applied from the posterior to anterior during simulation to determine
dynamic characteristics of the spine. The force magnitude is
gradually increased in subsequent simulations. Based on these
recorded dynamic properties, graphs of displacement-force
relationships will be established in terms of polynomial functions by
using the least-squares method and imported into a haptic integrated
graphic environment. A thoracolumbar spine model with complex
geometry of vertebrae, which is digitized from a resin spine
prototype, will be utilized in this environment. By using the haptic
technique, surgeons can touch as well as apply forces to the spine
model through haptic devices to observe the locomotion of the spine
which is computed from the displacement-force relationship graphs.
This current study provides a preliminary picture of our ongoing
work towards building and simulating bio-fidelity scoliotic spine
models in a haptic integrated graphic environment whose dynamic
properties are obtained from LifeMOD. These models can be helpful
for surgeons to examine kinematic behaviors of scoliotic spines and
to propose possible surgical plans before spine correction operations.
Abstract: Safety Critical hard Real-Time Systems are ever
present in the avionics industry. The Model Driven Architecture
(MDA) offers different levels of model abstraction and generation.
This paper discusses our concerns relating to model development and
generation when using the MDA approach in the avionics industry.
These concerns are based on our experience when looking into
adopting the MDA as part of avionics systems development. We
place emphasis on transformations between model types and discuss
possible benefits of adopting an MDA approach as part of the
software development life cycle.
Abstract: The composite materials were prepared by sawdust, cassava starch and natural rubber latex (NR). The mixtures of 15%w/v gelatinized cassava starch and 15%w/v PVOH were used as the binder of these composite materials. The concentrated rubber latex was added to the mixtures. They were mixed rigorously to the treated sawdust in the ratio of 70:30 until achive uniform dispersion. The batters were subjected to the hot compression moulding at the temperature of 160°C and 3,000 psi pressure for 5 min. The experimental results showed that the mechanical properties of composite materials, which contained the gelatinized cassava starch and PVOH in the ratio of 2:1, 20% NR latex by weight of the dry starch and treated sawdust with 5%NaOH or 1% BPO, were the best. It contributed the maximal compression strength (341.10 + 26.11 N), puncture resistance (8.79 + 0.98 N/mm2) and flexural strength (3.99 + 0.72N/mm2). It is also found that the physicochemical and mechanical properties of composites strongly depends on the interface quality of sawdust, cassava starch and NR latex.
Abstract: Soft clays are defined as cohesive soil whose water
content is higher than its liquid limits. Thus, soil-cement mixing is
adopted to improve the ground conditions by enhancing the strength
and deformation characteristics of the soft clays. For the above
mentioned reasons, a series of laboratory tests were carried out to
study some fundamental mechanical properties of cement stabilized
soft clay. The test specimens were prepared by varying the portion of
ordinary Portland cement to the soft clay sample retrieved from the
test site of RECESS (Research Centre for Soft Soil). Comparisons
were made for both homogeneous and columnar system specimens
by relating the effects of cement stabilized clay of for 0, 5 and 10 %
cement and curing for 3, 28 and 56 days. The mechanical properties
examined included one-dimensional compressibility and undrained
shear strength. For the mechanical properties, both homogeneous and
columnar system specimens were prepared to examine the effect of
different cement contents and curing periods on the stabilized soil.
The one-dimensional compressibility test was conducted using an
oedometer, while a direct shear box was used for measuring the
undrained shear strength. The higher the value of cement content, the
greater is the enhancement of the yield stress and the decrease of
compression index. The value of cement content in a specimen is a
more active parameter than the curing period.
Abstract: Oxidative stress is considered to be the cause for onset
and the progression of type 2 diabetes mellitus (T2DM) and
complications including neuropathy. It is a deleterious process that
can be an important mediator of damage to cell structures: protein,
lipids and DNA. Data suggest that in patients with diabetes and
diabetic neuropathy DNA repair is impaired, which prevents effective
removal of lesions. Objective: The aim of our study was to evaluate
the association of the hOGG1 (326 Ser/Cys) and XRCC1 (194
Arg/Trp, 399 Arg/Gln) gene polymorphisms whose protein is
involved in the BER pathway with DNA repair efficiency in patients
with diabetes type 2 and diabetic neuropathy compared to the healthy
subjects. Genotypes were determined by PCR-RFLP analysis in 385
subjects, including 117 with type 2 diabetes, 56 with diabetic
neuropathy and 212 with normal glucose metabolism. The
polymorphisms studied include codon 326 of hOGG1 and 194, 399
of XRCC1 in the base excision repair (BER) genes. Comet assay was
carried out using peripheral blood lymphocytes from the patients and
controls. This test enabled the evaluation of DNA damage in cells
exposed to hydrogen peroxide alone and in the combination with the
endonuclease III (Nth). The results of the analysis of polymorphism
were statistically examination by calculating the odds ratio (OR) and
their 95% confidence intervals (95% CI) using the ¤ç2-tests. Our data
indicate that patients with diabetes mellitus type 2 (including those
with neuropathy) had higher frequencies of the XRCC1 399Arg/Gln
polymorphism in homozygote (GG) (OR: 1.85 [95% CI: 1.07-3.22],
P=0.3) and also increased frequency of 399Gln (G) allele (OR: 1.38
[95% CI: 1.03-1.83], P=0.3). No relation to other polymorphisms
with increased risk of diabetes or diabetic neuropathy. In T2DM
patients complicated by neuropathy, there was less efficient repair of
oxidative DNA damage induced by hydrogen peroxide in both the
presence and absence of the Nth enzyme. The results of our study
suggest that the XRCC1 399 Arg/Gln polymorphism is a significant
risk factor of T2DM in Polish population. Obtained data suggest a
decreased efficiency of DNA repair in cells from patients with
diabetes and neuropathy may be associated with oxidative stress.
Additionally, patients with neuropathy are characterized by even
greater sensitivity to oxidative damage than patients with diabetes,
which suggests participation of free radicals in the pathogenesis of
neuropathy.
Abstract: This paper reports on an effort to address the issue of
inequality in girls- and women-s access to science, engineering and
technology (SET) education and careers through raising awareness on
SET among secondary school girls in South Africa. Girls participated
in hands-on high-tech rapid prototyping environment of a fabrication
laboratory that was aimed at stimulating creativity and innovation as
part of a Fab Kids initiative. The Fab Kids intervention is about
creating a SET pipeline as part of the Young Engineers and Scientists
of Africa Initiative.The methodology was based on a real world
situation and a hands-on approach. In the process, participants
acquired a number of skills including computer-aided design,
research skills, communication skills, teamwork skills, technical
drawing skills, writing skills and problem-solving skills. Exposure to
technology enhanced the girls- confidence in being able to handle
technology-related tasks.
Abstract: Due to the three- dimensional flow pattern interacting with bed material, the process of local scour around bridge piers is complex. Modeling 3D flow field and scour hole evolution around a bridge pier is more feasible nowadays because the computational cost and computational time have significantly decreased. In order to evaluate local flow and scouring around a bridge pier, a completely three-dimensional numerical model, SSIIM program, was used. The model solves 3-D Navier-Stokes equations and a bed load conservation equation. The model was applied to simulate local flow and scouring around a bridge pier in a large natural river with four piers. Computation for 1 day of flood condition was carried out to predict the maximum local scour depth. The results show that the SSIIM program can be used efficiently for simulating the scouring in natural rivers. The results also showed that among the various turbulence models, the k-ω model gives more reasonable results.
Abstract: The preparation of good-quality Environmental Impact Assessment (EIA) reports contribute to enhancing overall effectiveness of EIA. This component of the EIA process becomes more important in situation where public participation is weak and there is lack of expertise on the part of the competent authority. In Pakistan, EIA became mandatory for every project likely to cause adverse environmental impacts from July 1994. The competent authority also formulated guidelines for preparation and review of EIA reports in 1997. However, EIA is yet to prove as a successful decision support tool to help in environmental protection. One of the several reasons of this ineffectiveness is the generally poor quality of EIA reports. This paper critically reviews EIA reports of some randomly selected projects. Interviews of EIA consultants, project proponents and concerned government officials have also been conducted to underpin the root causes of poor quality of EIA reports. The analysis reveals several inadequacies particularly in areas relating to identification, evaluation and mitigation of key impacts and consideration of alternatives. The paper identifies some opportunities and suggests measures for improving the quality of EIA reports and hence making EIA an effective tool to help in environmental protection.
Abstract: By the application of an improved back-propagation
neural network (BPNN), a model of current densities for a solid oxide
fuel cell (SOFC) with 10 layers is established in this study. To build
the learning data of BPNN, Taguchi orthogonal array is applied to
arrange the conditions of operating parameters, which totally 7 factors
act as the inputs of BPNN. Also, the average current densities
achieved by numerical method acts as the outputs of BPNN.
Comparing with the direct solution, the learning errors for all learning
data are smaller than 0.117%, and the predicting errors for 27
forecasting cases are less than 0.231%. The results show that the
presented model effectively builds a mathematical algorithm to predict
performance of a SOFC stack immediately in real time.
Also, the calculating algorithms are applied to proceed with the
optimization of the average current density for a SOFC stack. The
operating performance window of a SOFC stack is found to be
between 41137.11 and 53907.89. Furthermore, an inverse predicting
model of operating parameters of a SOFC stack is developed here by
the calculating algorithms of the improved BPNN, which is proved to
effectively predict operating parameters to achieve a desired
performance output of a SOFC stack.