Abstract: Steel corrosion in concrete is considered as a main
engineering problems for many countries and lots of expenses has been paid for their repair and maintenance annually. This problem
may occur in all engineering structures whether in coastal and offshore or other areas. Hence, concrete structures should be able to
withstand corrosion factors existing in water or soil. Reinforcing
steel corrosion enhancement can be measured by use of concrete
electrical resistance; and maintaining high electric resistivity in concrete is necessary for steel corrosion prevention. Lots of studies
devoted to different aspects of the subjects worldwide. In this paper, an evaluation of the effects of W/C ratio, cementitious materials, and
percent increase in silica fume were investigated on electric resistivity of high strength concrete. To do that, sixteen mix design
with one aggregate grading was planned. Five of them had varying amount of W/C ratio and other eleven mixes was prepared with
constant W/C ratio but different amount of cementitious materials.
Silica fume and super plasticizer were used with different proportions
in all specimens. Specimens were tested after moist curing for 28 days. A total of 80 cube specimens (50 mm) were tested for concrete
electrical resistance. Results show that concrete electric resistivity can be increased with increasing amount of cementitious materials
and silica fume.
Abstract: In this paper, we propose a method to extract the road
signs. Firstly, the grabbed image is converted into the HSV color space
to detect the road signs. Secondly, the morphological operations are
used to reduce noise. Finally, extract the road sign using the geometric
property. The feature extraction of road sign is done by using the color
information. The proposed method has been tested for the real
situations. From the experimental results, it is seen that the proposed
method can extract the road sign features effectively.
Abstract: This work concerns the topological optimization
problem for determining the optimal petroleum refinery
configuration. We are interested in further investigating and
hopefully advancing the existing optimization approaches and
strategies employing logic propositions to conceptual process
synthesis problems. In particular, we seek to contribute to this
increasingly exciting area of chemical process modeling by
addressing the following potentially important issues: (a) how the
formulation of design specifications in a mixed-logical-and-integer
optimization model can be employed in a synthesis problem to enrich
the problem representation by incorporating past design experience,
engineering knowledge, and heuristics; and (b) how structural
specifications on the interconnectivity relationships by space (states)
and by function (tasks) in a superstructure should be properly
formulated within a mixed-integer linear programming (MILP)
model. The proposed modeling technique is illustrated on a case
study involving the alternative processing routes of naphtha, in which
significant improvement in the solution quality is obtained.
Abstract: The design requirements for successful human
accommodation in urban spaces are well known; and the range of
facilities available for meeting urban water quality and quantity
requirements is also well established. Their competing requirements
must be reconciled in order for urban spaces to be successful for
both. This paper outlines the separate human and water imperatives
and their interactions in urban spaces. Stormwater management
facilities- relative potential contributions to urban spaces are
contrasted, and design choices for achieving those potentials are
described. This study uses human success of urban space as the
evaluative criterion of stormwater amenity: human values call on
stormwater facilities to contribute to successful human spaces.
Placing water-s contribution under the overall idea of successful
urban space is an evolution from previous subjective evaluations.
The information is based on photographs and notes from
approximately 1,000 stormwater facilities and urban sites collected
during the last 35 years in North America and overseas, and the
author-s experience on multi-disciplinary design teams. This
conceptual study combines the disciplinary roles of engineering,
landscape architecture, and sociology in effecting successful urban
design.
Abstract: A multi-board run-time reconfigurable (MRTR)
system for evolvable hardware (EHW) is introduced with the aim to
implement on hardware the bidirectional incremental evolution (BIE)
method. The main features of this digital intrinsic EHW solution rely
on the multi-board approach, the variable chromosome length
management and the partial configuration of the reconfigurable
circuit. These three features provide a high scalability to the solution.
The design has been written in VHDL with the concern of not being
platform dependant in order to keep a flexibility factor as high as
possible. This solution helps tackling the problem of evolving
complex task on digital configurable support.
Abstract: An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are done on the basis of the multiresolution analysis. A comparative study of the performance is also presented for Discrete Fourier Transform (DFT) based Artificial Neural Network (ANN) and Discrete Wavelet Transform (DWT). The results prove that the proposed method is an effective and efficient one in obtaining the accurate result within short duration of time by using Daubechies 4 and 9. Simulation of the power system is done using MATLAB.
Abstract: Vision-based intelligent vehicle applications often require large amounts of memory to handle video streaming and image processing, which in turn increases complexity of hardware and software. This paper presents an FPGA implement of a vision-based blind spot warning system. Using video frames, the information of the blind spot area turns into one-dimensional information. Analysis of the estimated entropy of image allows the detection of an object in time. This idea has been implemented in the XtremeDSP video starter kit. The blind spot warning system uses only 13% of its logic resources and 95k bits block memory, and its frame rate is over 30 frames per sec (fps).
Abstract: A Web-services based grid infrastructure is evolving to be readily available in the near future. In this approach, the Web services are inherited (encapsulated or functioned) into the same existing Grid services class. In practice there is not much difference between the existing Web and grid infrastructure. Grid services emerged as stateful web services. In this paper, we present the key components of web-services based grid and also how the resource discovery is performed on web-services based grid considering resource discovery, as a critical service, to be provided by any type of grid.
Abstract: Determination of nano particle size is substantial since
the nano particle size exerts a significant effect on various properties
of nano materials. Accordingly, proposing non-destructive, accurate
and rapid techniques for this aim is of high interest. There are some
conventional techniques to investigate the morphology and grain size
of nano particles such as scanning electron microscopy (SEM),
atomic force microscopy (AFM) and X-ray diffractometry (XRD).
Vibrational spectroscopy is utilized to characterize different
compounds and applied for evaluation of the average particle size
based on relationship between particle size and near infrared spectra
[1,4] , but it has never been applied in quantitative morphological
analysis of nano materials. So far, the potential application of nearinfrared
(NIR) spectroscopy with its ability in rapid analysis of
powdered materials with minimal sample preparation, has been
suggested for particle size determination of powdered
pharmaceuticals. The relationship between particle size and diffuse
reflectance (DR) spectra in near infrared region has been applied to
introduce a method for estimation of particle size. Back propagation
artificial neural network (BP-ANN) as a nonlinear model was applied
to estimate average particle size based on near infrared diffuse
reflectance spectra. Thirty five different nano TiO2 samples with
different particle size were analyzed by DR-FTNIR spectrometry and
the obtained data were processed by BP- ANN.
Abstract: The Major Depressive Disorder has been a burden of
medical expense in Taiwan as well as the situation around the world.
Major Depressive Disorder can be defined into different categories by
previous human activities. According to machine learning, we can
classify emotion in correct textual language in advance. It can help
medical diagnosis to recognize the variance in Major Depressive
Disorder automatically. Association language incremental is the
characteristic and relationship that can discovery words in sentence.
There is an overlapping-category problem for classification. In this
paper, we would like to improve the performance in classification in
principle of no overlapping-category problems. We present an
approach that to discovery words in sentence and it can find in high
frequency in the same time and can-t overlap in each category, called
Association Language Features by its Category (ALFC).
Experimental results show that ALFC distinguish well in Major
Depressive Disorder and have better performance. We also compare
the approach with baseline and mutual information that use single
words alone or correlation measure.
Abstract: The purpose of this paper is to consider the
introduction of online courses to replace the current classroom-based
staff training. The current training is practical, and must be
completed before access to the financial computer system is
authorized. The long term objective is to measure the efficacy,
effectiveness and efficiency of the training, and to establish whether
a transfer of knowledge back to the workplace has occurred. This
paper begins with an overview explaining the importance of staff
training in an evolving, competitive business environment and
defines the problem facing this particular organization. A summary
of the literature review is followed by a brief discussion of the
research methodology and objective. The implementation of the
alpha version of the online course is then described. This paper may
be of interest to those seeking insights into, or new theory regarding,
practical interventions of online learning in the real world.
Abstract: A DEA model can generally evaluate the performance
using multiple inputs and outputs for the same period. However, it is
hard to avoid the production lead time phenomenon some times, such
as long-term project or marketing activity. A couple of models have
been suggested to capture this time lag issue in the context of DEA.
This paper develops a dual-MPO model to deal with time lag effect in
evaluating efficiency. A numerical example is also given to show that
the proposed model can be used to get efficiency and reference set of
inefficient DMUs and to obtain projected target value of input
attributes for inefficient DMUs to be efficient.
Abstract: Data from 1731 Gentile di Puglia lambs, sired by 65 rams over a 5-year period were analyzed by a mixed model to estimate the variance components for heritability. The considered growth traits were: birth weight (BW), weight at 30 days of age (W30) and average daily gain from birth to 30 days of age (DG). Year of birth, sex of lamb, type of birth (single or twin), dam age at lambing and farm were significant sources of variation for all the considered growth traits. The average lamb weights were 3.85±0.16 kg at birth, 9.57±0.91 kg at 30 days of age and the average daily gain was 191±14 g. Estimates of heritability were 0.33±0.05, 0.41±0.06 and 0.16±0.05 respectively for the same traits. These values suggest there is a good opportunity to improve Gentile di Puglia lambs by selecting animals for growth traits.
Abstract: This study adopted previous fault patterns, results of
detection analysis, historical records and data, and experts-
experiences to establish fuzzy principles and estimate the failure
probability index of components of a power transformer. Considering
that actual parameters and limiting conditions of parameters may
differ, this study used the standard data of IEC, IEEE, and CIGRE as
condition parameters. According to the characteristics of each
condition parameter, relative degradation was introduced to reflect the
degree of influence of the factors on the transformer condition. The
method of fuzzy mathematics was adopted to determine the
subordinate function of the transformer condition. The calculation
used the Matlab Fuzzy Tool Box to select the condition parameters of
coil winding, iron core, bushing, OLTC, insulating oil and other
auxiliary components and factors (e.g., load records, performance
history, and maintenance records) of the transformer to establish the
fuzzy principles. Examples were presented to support the rationality
and effectiveness of the evaluation method of power transformer
performance conditions, as based on fuzzy comprehensive evaluation.
Abstract: A new strain of Type A influenza virus can cause the
transmission of H1N1 virus. This virus can spread between the
people by coughing and sneezing. Because the people are always
movement, so this virus can be easily spread. In this study, we
construct the dynamical network model of H1N1 virus by separating
the human into five groups; susceptible, exposed, infectious,
quarantine and recovered groups. The movement of people between
houses (local level) is considered. The behaviors of solutions to our
dynamical model are shown for the different parameters.
Abstract: How to effectively allocate system resource to process
the Client request by Gateway servers is a challenging problem. In
this paper, we propose an improved scheme for autonomous
performance of Gateway servers under highly dynamic traffic loads.
We devise a methodology to calculate Queue Length and Waiting
Time utilizing Gateway Server information to reduce response time
variance in presence of bursty traffic. The most widespread
contemplation is performance, because Gateway Servers must offer
cost-effective and high-availability services in the elongated period,
thus they have to be scaled to meet the expected load. Performance
measurements can be the base for performance modeling and
prediction. With the help of performance models, the performance
metrics (like buffer estimation, waiting time) can be determined at
the development process. This paper describes the possible queue
models those can be applied in the estimation of queue length to
estimate the final value of the memory size. Both simulation and
experimental studies using synthesized workloads and analysis of
real-world Gateway Servers demonstrate the effectiveness of the
proposed system.
Abstract: In Supply Chain Management (SCM), strengthening partnerships with suppliers is a significant factor for enhancing competitiveness. Hence, firms increasingly emphasize supplier evaluation processes. Supplier evaluation systems are basically developed in terms of criteria such as quality, cost, delivery, and flexibility. Because there are many variables to be analyzed, this process becomes hard to execute and needs expertise. On this account, this study aims to develop an expert system on supplier evaluation process by designing Artificial Neural Network (ANN) that is supported with Data Envelopment Analysis (DEA). The methods are applied on the data of 24 suppliers, which have longterm relationships with a medium sized company from German Iron and Steel Industry. The data of suppliers consists of variables such as material quality (MQ), discount of amount (DOA), discount of cash (DOC), payment term (PT), delivery time (DT) and annual revenue (AR). Meanwhile, the efficiency that is generated by using DEA is added to the supplier evaluation system in order to use them as system outputs.
Abstract: The problem of exponential stability and periodicity for a class of cellular neural networks (DCNNs) with time-varying delays is investigated. By dividing the network state variables into subgroups according to the characters of the neural networks, some sufficient conditions for exponential stability and periodicity are derived via the methods of variation parameters and inequality techniques. These conditions are represented by some blocks of the interconnection matrices. Compared with some previous methods, the method used in this paper does not resort to any Lyapunov function, and the results derived in this paper improve and generalize some earlier criteria established in the literature cited therein. Two examples are discussed to illustrate the main results.
Abstract: Knee joint forces are available by in vivo measurement
using an instrumented knee prosthesis for small to moderate knee
flexion but not for high flexion yet. We created a 2D mathematical
model of the lower limb incorporating several new features such as a
patello-femoral mechanism, a thigh-calf contact at high knee flexion
and co-contracting muscles' force ratio, then used it to determine knee
joint forces arising from high knee flexions in four kneeling
conditions: rising with legs in parallel, with one foot forward, with or
without arm use. With arms used, the maximum values of knee joint
force decreased to about 60% of those with arms not used. When rising
with one foot forward, if arms are not used, the forward leg sustains a
force as large as that sustained when rising with legs parallel.
Abstract: Air quality studies were carried out in the towns of
Putrajaya, Petaling Jaya and Nilai in the Malaysian Peninsular. In this
study, the variations of Ozone (O3) concentrations over a four year
period (2008-2011) were investigated using data obtained from the
Malaysian Department of the Environment (DOE). This study aims to
identify and describe the daily and monthly variations of O3
concentrations at the monitoring sites mentioned. The SPPS program
(Statistical Package for the Social Science) was used to analyze this
data in order to obtain the variations of O3 and also to clarify the
relationship between the stations. The findings of the study revealed
that the highest concentration of O3 occurred during the midday and
afternoon (between 13:00-15:00 hrs). The comparison between
stations also showed that highest O3 concentrations were recorded in
Putrajaya. The comparisons of average and maximum concentrations
of O3 for the three stations showed that the strongest significant
correlation was recorded in the Petaling Jaya station with the value
R2= 0.667. Results from this study indicate that in the urban areas of
Peninsular Malaysia, the concentration of O3 depends on the
concentration of NOx. Furthermore, HYSPLIT back trajectories
(-72h) indicated that air-mass transport patterns can also influence the
O3 concentration in the areas studied.