Abstract: The aim of the study was to investigate whether there
is the promotion of product ecodesign measures as a result of
adopting ISO 14001 certification in manufacturing companies in the
Republic of Slovenia. Companies gave the most of their product
development attention to waste and energy reduction during
manufacturing process and reduction of material consumption per
unit of product. Regarding the importance of different ecodesign
criteria reduction of material consumption per unit of product was
reported as the most important criterion. Less attention is paid to endof-
life issues considering recycling or packaging. Most
manufacturing enterprises considered ISO 14001 standard as a very
useful tool or at least a useful tool helping them to accelerate and
establish product ecodesign activities. Two most frequently
considered ecodesign drivers are increased competitive advantage
and legal requirements and two most important barriers are high
development costs and insufficient market demand.
Abstract: The institutions seek to improve their performance
and quality of service, so that their patients are satisfied. This
research project aims, conduct a time study program in the area of
gynecological surgery, to determine the current level of capacity and
optimize the programming time in order to adequately respond to
demand. The system is analyzed by waiting lines and uses the
simulation using ARENA to evaluate proposals for improvement and
optimization programming time each of the surgeries.
Abstract: With the advent of DSL services, high data rates are now available over phone lines, yet higher rates are in demand. In this paper, we optimize the transmit filters that can be used over wireline channels. Results showing the bit error rates when optimized filters are used, and with a decision feedback equalizer (DFE) employed in the receiver, are given. We then show that significantly higher throughput can be achieved by modeling the channel as a multiple input multiple output (MIMO) channel. A receiver that employs a MIMO-DFE that deals jointly with several users is proposed and shown to provide significant improvement over the conventional DFE.
Abstract: The aim of this paper is to present a methodology in
three steps to forecast supply chain demand. In first step, various data
mining techniques are applied in order to prepare data for entering
into forecasting models. In second step, the modeling step, an
artificial neural network and support vector machine is presented
after defining Mean Absolute Percentage Error index for measuring
error. The structure of artificial neural network is selected based on
previous researchers' results and in this article the accuracy of
network is increased by using sensitivity analysis. The best forecast
for classical forecasting methods (Moving Average, Exponential
Smoothing, and Exponential Smoothing with Trend) is resulted based
on prepared data and this forecast is compared with result of support
vector machine and proposed artificial neural network. The results
show that artificial neural network can forecast more precisely in
comparison with other methods. Finally, forecasting methods'
stability is analyzed by using raw data and even the effectiveness of
clustering analysis is measured.
Abstract: Saudi Arabia is an arid country which depends on
costly desalination plants to satisfy the growing residential water
demand. Prediction of water demand is usually a challenging task
because the forecast model should consider variations in economic
progress, climate conditions and population growth. The task is
further complicated knowing that Mecca city is visited regularly by
large numbers during specific months in the year due to religious
occasions. In this paper, a neural networks model is proposed to
handle the prediction of the monthly and yearly water demand for
Mecca city, Saudi Arabia. The proposed model will be developed
based on historic records of water production and estimated visitors-
distribution. The driving variables for the model include annuallyvarying
variables such as household income, household density, and
city population, and monthly-varying variables such as expected
number of visitors each month and maximum monthly temperature.
Abstract: This paper presents a mathematical model and a
methodology to analyze the losses in transmission expansion
planning (TEP) under uncertainty in demand. The methodology is
based on discrete particle swarm optimization (DPSO). DPSO is a
useful and powerful stochastic evolutionary algorithm to solve the
large-scale, discrete and nonlinear optimization problems like TEP.
The effectiveness of the proposed idea is tested on an actual
transmission network of the Azerbaijan regional electric company,
Iran. The simulation results show that considering the losses even for
transmission expansion planning of a network with low load growth
is caused that operational costs decreases considerably and the
network satisfies the requirement of delivering electric power more
reliable to load centers.
Abstract: The lack of inclusive housing in Australia contributes
to the marginalization and exclusion of people with disability and
older people from family and community life. The Australian
government has handed over the responsibility of increasing the
supply of inclusive housing to the housing industry through an agreed
national access standard and a voluntary strategy. Voluntary
strategies have not been successful in other constituencies and little is
known about what would work in Australia today. Findings from a
research project into the voluntariness of the housing industry
indicate that a reliable and consistent supply is unlikely without an
equivalent increase in demand. The strategy has, however, an
important role to play in the task of changing housing industry
practices towards building more inclusive communities.
Abstract: Nowadays, several techniques such as; Fuzzy
Inference System (FIS) and Neural Network (NN) are employed for
developing of the predictive models to estimate parameters of water
quality. The main objective of this study is to compare between the
predictive ability of the Adaptive Neuro-Fuzzy Inference System
(ANFIS) model and Artificial Neural Network (ANN) model to
estimate the Biochemical Oxygen Demand (BOD) on data from 11
sampling sites of Saen Saep canal in Bangkok, Thailand. The data is
obtained from the Department of Drainage and Sewerage, Bangkok
Metropolitan Administration, during 2004-2011. The five parameters
of water quality namely Dissolved Oxygen (DO), Chemical Oxygen
Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen
(NO3N), and Total Coliform bacteria (T-coliform) are used as the
input of the models. These water quality indices affect the
biochemical oxygen demand. The experimental results indicate that
the ANN model provides a higher correlation coefficient (R=0.73)
and a lower root mean square error (RMSE=4.53) than the
corresponding ANFIS model.
Abstract: The development of sustainable utilization water resources is crucial. The ecological environment and water resources systems form the foundation of the existence and development of the social economy. The urban ecological support system depends on these resources as well. This research studies the vulnerability, criticality, and risk of climate change on water supply and demand in the main administrative district of the Taijiang Area (Tainan City). Based on the two situations set in this paper and various factors (indexes), this research adopts two kinds of weights (equal and AHP) to conduct the calculation and establish the water supply and demand risk map for the target year 2039. According to the risk analysis result, which is based on equal weight, only one district belongs to a high-grade district (Grade 4). Based on the AHP weight, 16 districts belong to a high-grade or higher-grade district (Grades 4 and 5), and from among them, two districts belong to the highest grade (Grade 5). These results show that the risk level of water supply and demand in cities is higher than that in towns. The government generally gives more attention to the adjustment strategy in the “cities." However, it should also provide proper adjustment strategies for the “towns" to be able to cope with the risks of water supply and demand.
Abstract: In this paper we propose a method for vision systems
to consistently represent functional dependencies between different
visual routines along with relational short- and long-term knowledge
about the world. Here the visual routines are bound to visual properties
of objects stored in the memory of the system. Furthermore,
the functional dependencies between the visual routines are seen
as a graph also belonging to the object-s structure. This graph is
parsed in the course of acquiring a visual property of an object to
automatically resolve the dependencies of the bound visual routines.
Using this representation, the system is able to dynamically rearrange
the processing order while keeping its functionality. Additionally, the
system is able to estimate the overall computational costs of a certain
action. We will also show that the system can efficiently use that
structure to incorporate already acquired knowledge and thus reduce
the computational demand.
Abstract: Introduction applicability of high-speed cutting stock problem (CSP) is presented in this paper. Due to the orders continued coming in from various on-line ways for a professional cutting company, to stay competitive, such a business has to focus on sustained production at high levels. In others words, operators have to keep the machine running to stay ahead of the pack. Therefore, the continuous stock cutting problem with setup is proposed to minimize the cutting time and pattern changing time to meet the on-line given demand. In this paper, a novel method is proposed to solve the problem directly by using cutting patterns directly. A major advantage of the proposed method in series on-line production is that the system can adjust the cutting plan according to the floating orders. Examples with multiple items are demonstrated. The results show considerable efficiency and reliability in high-speed cutting of CSP.
Abstract: The demand on High voltage (HV) infrastructures is growing due to the corresponding growth in industries and population. Many areas are being developed and therefore require additional electrical power to comply with the demand. Substation upgrade is one of the rapid solutions to ensure the continuous supply of power to customers. This upgrade requires civil modifications to structures and fences. The civil work requires excavation and steel works that may create unsafe touch conditions. This paper presents a brief theoretical overview of the touch voltage inside and around substations and uses CDEGS software to simulate a case study.
Abstract: In recent years, environment regulation forcing
manufactures to consider recovery activity of end-of- life products
and/or return products for refurbishing, recycling,
remanufacturing/repair and disposal in supply chain management. In
this paper, a mathematical model is formulated for single product
production-inventory system considering remanufacturing/reuse of
return products and rate of return products follows a demand like
function, dependent on purchasing price and acceptance quality level.
It is useful in decision making to determine whether to go for
remanufacturing or disposal of returned products along with newly
produced products to satisfy a stationary demand. In addition, a
modified genetic algorithm approach is proposed, inspired by particle
swarm optimization method. Numerical analysis of the case study is
carried out to validate the model.
Abstract: With the growth of electricity generation from gas
energy gas pipeline reliability can substantially impact the electric
generation. A physical disruption to pipeline or to a compressor
station can interrupt the flow of gas or reduce the pressure and lead
to loss of multiple gas-fired electric generators, which could
dramatically reduce the supplied power and threaten the power
system security. Gas pressure drops during peak loading time on
pipeline system, is a common problem in network with no enough
transportation capacity which limits gas transportation and causes
many problem for thermal domain power systems in supplying their
demand. For a feasible generation scheduling planning in networks
with no sufficient gas transportation capacity, it is required to
consider gas pipeline constraints in solving the optimization problem
and evaluate the impacts of gas consumption in power plants on gas
pipelines operating condition. This paper studies about operating of
gas fired power plants in critical conditions when the demand of gas
and electricity peak together. An integrated model of gas and electric
model is used to consider the gas pipeline constraints in the economic
dispatch problem of gas-fueled thermal generator units.
Abstract: The usage of internet is rapidly increasing and the usage of mobile agent technology in internet environment has a great demand. The security issue one of main obstacles that restrict the mobile agent technology to spread. This paper proposes Secure-Image Mechanism (SIM) as a new mechanism to protect mobile agents against malicious hosts. . SIM aims to protect mobile agent by using the symmetric encryption and hash function in cryptography science. This mechanism can prevent the eavesdropping and alteration attacks. It assists the mobile agents to continue their journey normally incase attacks occurred.
Abstract: Air conditioning is mainly use as human comfort
cooling medium. It use more in high temperatures are country such as
Malaysia. Proper estimation of cooling load will archive ideal
temperature. Without proper estimation can lead to over estimation or
under estimation. The ideal temperature should be comfort enough.
This study is to develop a program to calculate an ideal cooling load
demand, which is match with heat gain. Through this study, it is easy
to calculate cooling load estimation. Objective of this study are to
develop user-friendly and easy excess cooling load program. This is
to insure the cooling load can be estimate by any of the individual
rather than them using rule-of-thumb. Developed software is carryout
by using Matlab-GUI. These developments are only valid for
common building in Malaysia only. An office building was select as
case study to verify the applicable and accuracy of develop software.
In conclusion, the main objective has successfully where developed
software is user friendly and easily to estimate cooling load demand.
Abstract: One of object oriented software developing problem
is the difficulty of searching the appropriate and suitable objects for
starting the system. In this work, ontologies appear in the part of
supporting the object discovering in the initial of object oriented
software developing. There are many researches try to demonstrate
that there is a great potential between object model and ontologies.
Constructing ontology from object model is called ontology
engineering can be done; On the other hand, this research is aiming to
support the idea of building object model from ontology is also
promising and practical. Ontology classes are available online in any
specific areas, which can be searched by semantic search engine.
There are also many helping tools to do so; one of them which are
used in this research is Protégé ontology editor and Visual Paradigm.
To put them together give a great outcome. This research will be
shown how it works efficiently with the real case study by using
ontology classes in travel/tourism domain area. It needs to combine
classes, properties, and relationships from more than two ontologies
in order to generate the object model. In this paper presents a simple
methodology framework which explains the process of discovering
objects. The results show that this framework has great value while
there is possible for expansion. Reusing of existing ontologies offers
a much cheaper alternative than building new ones from scratch.
More ontologies are becoming available on the web, and online
ontologies libraries for storing and indexing ontologies are increasing
in number and demand. Semantic and Ontologies search engines have
also started to appear, to facilitate search and retrieval of online
ontologies.
Abstract: Today-s business has inevitably been set in the global supply chain management environment. International transportation has never played such an important role in the global supply chain network, because movement of shipments from one country to another tends to be more frequent than ever before. This paper studies international transportation problems experienced by an international transportation company. Because of the limited fleet capacity, the transportation company has to hire additional trucks from two countries in advance. However, customer-s shipment information is uncertain, and decisions have to be made before accurate information can be obtained. This paper proposes a stochastic mixed 0-1 programming model to solve the international transportation problems under uncertain demand. A series of experiments demonstrate the effectiveness of the proposed stochastic model.
Abstract: Thailand is one of the world-s leaders of rice
producers and exporters. Farmers have to increase the rice cultivation
frequency for serving the national increasing of export-s demand. It
leads to an elimination of rice residues by open burning which is the
quickest and costless management method. The open burning of rice
residue is one of the major causes of air pollutants and greenhouse
gas (GHG) emission. Under ASEAN agreement on trans-boundary
haze, Thailand set the master plan to mitigate air pollutant emission
from open burning of agricultural residues. In this master plan,
residues incorporation is promoted as alternative management
method to open burning. However, the assessment of both options in
term of GHG emission in order to investigate their contribution to
long-term global warming is still scarce or inexistent. In this study, a
method on rice residues assessment was first developed in order to
estimate and compare GHG emissions from rice cultivation under
rice residues open burning and the case with incorporation of the
same amount of rice residues, using 2006 IPCC guidelines for
emission estimation and Life Cycle Analysis technique. The
emission from rice cultivation in different preparing area practice
was also discussed.
Abstract: Supply chain consists of all stages involved, directly
or indirectly, includes all functions involved in fulfilling a customer
demand. In two stage transportation supply chain problem,
transportation costs are of a significant proportion of final product
costs. It is often crucial for successful decisions making approaches
in two stage supply chain to explicit account for non-linear
transportation costs. In this paper, deterministic demand and finite
supply of products was considered. The optimized distribution level
and the routing structure from the manufacturing plants to the
distribution centres and to the end customers is determined using
developed mathematical model and solved by proposed particle
swarm optimization based genetic algorithm. Numerical analysis of
the case study is carried out to validate the model.