Abstract: Travel demand forecasting including four travel choices, i.e., trip generation, trip distribution, modal split and traffic assignment constructs the core of transportation planning. In its current application, travel demand forecasting has associated with three important issues, i.e., interface inconsistencies among four travel choices, inefficiency of commonly used solution algorithms, and undesirable multiple path solutions. In this paper, each of the three issues is extensively elaborated. An ideal unified framework for the combined model consisting of the four travel choices and variable demand functions is also suggested. Then, a few remarks are provided in the end of the paper
Abstract: Ontologies are broadly used in the context of networked home environments. With ontologies it is possible to define and store context information, as well as to model different kinds of physical environments. Ontologies are central to networked home environments as they carry the meaning. However, ontologies and the OWL language is complex. Several ontology visualization approaches have been developed to enhance the understanding of ontologies. The domain of networked home environments sets some special requirements for the ontology visualization approach. The visualization tool presented here, visualizes ontologies in a domain-specific way. It represents effectively the physical structures and spatial relationships of networked home environments. In addition, it provides extensive interaction possibilities for editing and manipulating the visualization. The tool shortens the gap from beginner to intermediate OWL ontology reader by visualizing instances in their actual locations and making OWL ontologies more interesting and concrete, and above all easier to comprehend.
Abstract: Intelligent schools are those which use IT devices and
technologies as media software, hardware and networks to improve
learning process. On the other hand management improvement is
best described as the process from which managers learn and improve
their skills not only to benefit themselves but also their employing
organizations Here, we present a model Management improvement
System that has been applied on some schools and have made strict
improvement.
Abstract: The goal of this paper is to develop a model to
integrate “pricing" and “advertisement" for short life cycle products,
such as branded fashion clothing products. To achieve this goal, we
apply the concept of “Dynamic Pricing". There are two classes of
advertisements, for the brand (regardless of product) and for a
particular product. Advertising the brand affects the demand and
price of all the products. Thus, the model considers all these products
in relation with each other. We develop two different methods to
integrate both types of advertisement and pricing. The first model is
developed within the framework of dynamic programming. However,
due to the complexity of the model, this method cannot be applicable
for large size problems. Therefore, we develop another method,
called hieratical approach, which is capable of handling the real
world problems. Finally, we show the accuracy of this method, both
theoretically and also by simulation.
Abstract: Quantitative precipitation forecast (QPF) from
atmospheric model as input to hydrological model in an integrated
hydro-meteorological flood forecasting system has been operational
in many countries worldwide. High-resolution numerical weather
prediction (NWP) models with grid cell sizes between 2 and 14 km
have great potential in contributing towards reasonably accurate QPF.
In this study the potential of two NWP models to forecast
precipitation for a flood-prone area in a tropical region is examined.
The precipitation forecasts produced from the Fifth Generation Penn
State/NCAR Mesoscale (MM5) and Weather Research and
Forecasting (WRF) models are statistically verified with the observed
rain in Kelantan River Basin, Malaysia. The statistical verification
indicates that the models have performed quite satisfactorily for low
and moderate rainfall but not very satisfactory for heavy rainfall.
Abstract: The incidences of dengue hemorrhagic disease (DHF)
over the long term exhibit a seasonal behavior. It has been
hypothesized that these behaviors are due to the seasonal climate
changes which in turn induce a seasonal variation in the incubation
period of the virus while it is developing the mosquito. The standard
dynamic analysis is applied for analysis the Susceptible-Exposed-
Infectious-Recovered (SEIR) model which includes an annual
variation in the length of the extrinsic incubation period (EIP). The
presence of both asymptomatic and symptomatic infections is
allowed in the present model. We found that dynamic behavior of the
endemic state changes as the influence of the seasonal variation of
the EIP becomes stronger. As the influence is further increased, the
trajectory exhibits sustained oscillations when it leaves the chaotic
region.
Abstract: Three dimensional analysis of thermal model in laser
full penetration welding, Nd:YAG, by transparent mode DP600 alloy
steel 1.25mm of thickness and gap of 0.1mm. Three models studied
the influence of thermal dependent temperature properties, thermal
independent temperature and the effect of peak value of specific heat
at phase transformation temperature, AC1, on the transient
temperature. Another seven models studied the influence of
discretization, meshes on the temperature distribution in weld plate.
It is shown that for the effects of thermal properties, the errors less
4% of maximum temperature in FZ and HAZ have identified. The
minimum value of discretization are at least one third increment per
radius for temporal discretization and the spatial discretization
requires two elements per radius and four elements through thickness
of the assembled plate, which therefore represent the minimum
requirements of modeling for the laser welding in order to get
minimum errors less than 5% compared to the fine mesh.
Abstract: The technique of inducing micro ecosystem
restoration is one of aquatic ecology engineering methods used to
retrieve the polluted water. Batch scale study, pilot plant study, and
field study were carried out to observe the eutrophication using the
Inducing Ecology Restorative Symbiosis Agent (IERSA) consisting
mainly degraded products by using lactobacillus, saccharomycete,
and phycomycete. The results obtained from the experiments of the
batch scale and pilot plant study allowed us to development the
parameters for the field study. A pond, 5 m to the outlet of a lake,
with an area of 500 m2 and depth of 0.6-1.2 m containing about 500
tons of water was selected as a model. After the treatment with 10
mg IERSA/L water twice a week for 70 days, the micro restoration
mechanisms consisted of three stages (i.e., restoration, impact
maintenance, and ecology recovery experiment after impact). The
COD, TN, TKN, and chlorophyll a were reduced significantly in the
first week. Although the unexpected heavy rain and contaminate
from sewage system might slow the ecology restoration. However,
the self-cleaning function continued and the chlorophyll a reduced
for 50% in one month. In the 4th week, amoeba, paramecium, rotifer,
and red wriggle worm reappeared, and the number of fish flies
appeared up to1000 fish fries/m3. Those results proved that inducing
restorative mechanism can be applied to improve the eutrophication
and to control the growth of algae in the lakes by gaining the selfcleaning
through inducing and competition of microbes. The
situation for growth of fishes also can reach an excellent result due to
the improvement of water quality.
Abstract: This paper discusses the performance modeling and availability analysis of Yarn Dyeing System of a Textile Industry. The Textile Industry is a complex and repairable engineering system. Yarn Dyeing System of Textile Industry consists of five subsystems arranged in series configuration. For performance modeling and analysis of availability, a performance evaluating model has been developed with the help of mathematical formulation based on Markov-Birth-Death Process. The differential equations have been developed on the basis of Probabilistic Approach using a Transition Diagram. These equations have further been solved using normalizing condition in order to develop the steady state availability, a performance measure of the system concerned. The system performance has been further analyzed with the help of decision matrices. These matrices provide various availability levels for different combinations of failure and repair rates for various subsystems. The findings of this paper are therefore, considered to be useful for the analysis of availability and determination of the best possible maintenance strategies which can be implemented in future to enhance the system performance.
Abstract: In hydrocyclones, the particle separation efficiency is
limited by the suspended fine particles, which are discharged with the
coarse product in the underflow. It is well known that injecting water
in the conical part of the cyclone reduces the fine particle fraction in
the underflow. This paper presents a mathematical model that
simulates the water injection in the conical component. The model
accounts for the fluid flow and the particle motion. Particle
interaction, due to hindered settling caused by increased density and
viscosity of the suspension, and fine particle entrainment by settling
coarse particles are included in the model. Water injection in the
conical part of the hydrocyclone is performed to reduce fine particle
discharge in the underflow. The model demonstrates the impact of
the injection rate, injection velocity, and injection location on the
shape of the partition curve. The simulations are compared with
experimental data of a 50-mm cyclone.
Abstract: This paper analyzes the patterns of the Monte Carlo
data for a large number of variables and minterms, in order to
characterize the circuit path length behavior. We propose models
that are determined by training process of shortest path length
derived from a wide range of binary decision diagram (BDD)
simulations. The creation of the model was done use of feed forward
neural network (NN) modeling methodology. Experimental results
for ISCAS benchmark circuits show an RMS error of 0.102 for the
shortest path length complexity estimation predicted by the NN
model (NNM). Use of such a model can help reduce the time
complexity of very large scale integrated (VLSI) circuitries and
related computer-aided design (CAD) tools that use BDDs.
Abstract: Lack of resources for road infrastructure financing is a
problem that currently affects not only eastern European economies
but also many other countries especially in relation to the impact of
global financial crisis. In this context, we are talking about the socalled
short-investment problem as a result of long-term lack of
investment resources. Based on an analysis of road infrastructure
financing in the Czech Republic this article points out at weaknesses
of current system and proposes a long-term planning methodology
supported by system approach. Within this methodology and using
created system dynamic model the article predicts the development of
short-investment problem in the Country and in reaction on the
downward trend of certain sources the article presents various
scenarios resulting from the change of the structure of financial
sources. In the discussion the article focuses more closely on the
possibility of introduction of tax on vehicles instead of taxes with
declining revenue streams and estimates its approximate price in
relation to reaching various solutions of short-investment in time.
Abstract: As the Textile Industry is the second largest industry
in Egypt and as small and medium-sized enterprises (SMEs) make up
a great portion of this industry therein it is essential to apply the
concept of Cleaner Production for the purpose of reducing pollution.
In order to achieve this goal, a case study concerned with ecofriendly
stone-washing of jeans-garments was investigated. A raw
material-substitution option was adopted whereby the toxic
potassium permanganate and sodium sulfide were replaced by the
environmentally compatible hydrogen peroxide and glucose
respectively where the concentrations of both replaced chemicals
together with the operating time were optimized. In addition, a
process-rationalization option involving four additional processes
was investigated. By means of criteria such as product quality,
effluent analysis, mass and heat balance; and cost analysis with the
aid of a statistical model, a process optimization treatment revealed
that the superior process optima were 50%, 0.15% and 50min for
H2O2 concentration, glucose concentration and time, respectively.
With these values the superior process ought to reduce the annual
cost by about EGP 105 relative to the currently used conventional
method.
Abstract: Decisions are regularly made during a project or
daily life. Some decisions are critical and have a direct impact on
project or human success. Formal evaluation is thus required,
especially for crucial decisions, to arrive at the optimal solution
among alternatives to address issues. According to microeconomic
theory, all people-s decisions can be modeled as indifference curves.
The proposed approach supports formal analysis and decision by
constructing indifference curve model from the previous experts-
decision criteria. These knowledge embedded in the system can be
reused or help naïve users select alternative solution of the similar
problem. Moreover, the method is flexible to cope with unlimited
number of factors influencing the decision-making. The preliminary
experimental results of the alternative selection are accurately
matched with the expert-s decisions.
Abstract: In text categorization problem the most used method
for documents representation is based on words frequency vectors
called VSM (Vector Space Model). This representation is based only
on words from documents and in this case loses any “word context"
information found in the document. In this article we make a
comparison between the classical method of document representation
and a method called Suffix Tree Document Model (STDM) that is
based on representing documents in the Suffix Tree format. For the
STDM model we proposed a new approach for documents
representation and a new formula for computing the similarity
between two documents. Thus we propose to build the suffix tree
only for any two documents at a time. This approach is faster, it has
lower memory consumption and use entire document representation
without using methods for disposing nodes. Also for this method is
proposed a formula for computing the similarity between documents,
which improves substantially the clustering quality. This
representation method was validated using HAC - Hierarchical
Agglomerative Clustering. In this context we experiment also the
stemming influence in the document preprocessing step and highlight
the difference between similarity or dissimilarity measures to find
“closer" documents.
Abstract: In this paper we present an autoregressive model with
neural networks modeling and standard error backpropagation
algorithm training optimization in order to predict the gross domestic
product (GDP) growth rate of four countries. Specifically we propose
a kind of weighted regression, which can be used for econometric
purposes, where the initial inputs are multiplied by the neural
networks final optimum weights from input-hidden layer after the
training process. The forecasts are compared with those of the
ordinary autoregressive model and we conclude that the proposed
regression-s forecasting results outperform significant those of
autoregressive model in the out-of-sample period. The idea behind
this approach is to propose a parametric regression with weighted
variables in order to test for the statistical significance and the
magnitude of the estimated autoregressive coefficients and
simultaneously to estimate the forecasts.
Abstract: In many cases, there are some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in evaluating the performance of organizations. Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. Multi-periods input(MpI) and Multi-periods output(MpO) models are integrate models to calculate simple efficiency considering time lag effect. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. That is, efficient DMUs can’t be discriminated because their efficiency scores are same. Thus, this paper suggests a super-efficiency model for efficiency evaluation under the consideration of time lag effect based on the MpO model. A case example using a long term research project is given to compare the suggested model with the MpO model.
Abstract: This study proposes a multi-response surface
optimization problem (MRSOP) for determining the proper choices
of a process parameter design (PPD) decision problem in a noisy
environment of a grease position process in an electronic industry.
The proposed models attempts to maximize dual process responses
on the mean of parts between failure on left and right processes. The
conventional modified simplex method and its hybridization of the
stochastic operator from the hunting search algorithm are applied to
determine the proper levels of controllable design parameters
affecting the quality performances. A numerical example
demonstrates the feasibility of applying the proposed model to the
PPD problem via two iterative methods. Its advantages are also
discussed. Numerical results demonstrate that the hybridization is
superior to the use of the conventional method. In this study, the
mean of parts between failure on left and right lines improve by
39.51%, approximately. All experimental data presented in this
research have been normalized to disguise actual performance
measures as raw data are considered to be confidential.
Abstract: Study was conducted to determine the concentration of
copper, cadmium, lead and zinc in Cabomba furcata that found
abundance in Lake Chini. This aquatic plant was collected randomly
within the lake for heavy metal determination. Water quality
measurement was undertaken in situ for temperature, pH,
conductivity and dissolved oksigen using portable multi sensor probe
YSI model 556. The C. furcata was digested using wet digestion
method and heavy metal concentrations were analysed using Atomic
Absorption Spectrometer (AAS) Perkin Elmer 4100B (flame
method). Result of water quality classify Lake Chini between class II
to class III using Malaysian Water Quality Standard. According to
this standard, Lake Chini has moderate quality, which normal for
natural lake. Heavy metal concentrations in C.furcata were low and
found to be lower than the critical toxic value in aquatic plants. Oneway
ANOVA test indicated the heavy metal concentrations in
C.furcata were significantly differ between sampling location. Water
quality and heavy metal concentrations indicates that Lake Chini was
not receives anthropogenic load from nearby activities.
Abstract: In this research we show that the dynamics of an action potential in a cell can be modeled with a linear combination of the dynamics of the gating state variables. It is shown that the modeling error is negligible. Our findings can be used for simplifying cell models and reduction of computational burden i.e. it is useful for simulating action potential propagation in large scale computations like tissue modeling. We have verified our finding with the use of several cell models.