Abstract: The Genetic Algorithm (GA) is one of the most important methods used to solve many combinatorial optimization problems. Therefore, many researchers have tried to improve the GA by using different methods and operations in order to find the optimal solution within reasonable time. This paper proposes an improved GA (IGA), where the new crossover operation, population reformulates operation, multi mutation operation, partial local optimal mutation operation, and rearrangement operation are used to solve the Traveling Salesman Problem. The proposed IGA was then compared with three GAs, which use different crossover operations and mutations. The results of this comparison show that the IGA can achieve better results for the solutions in a faster time.
Abstract: This paper provides an overview of auction theory literature. We present a general review on literature of various auctions and focus ourselves specifically on an English auction. We are interested in modelling bidder's behavior in an English auction environment. And hence, we present an overview of the New Zealand wool auction followed by a model that would describe a bidder's decision making behavior from the New Zealand wool auction. The mathematical assumptions in an English auction environment are demonstrated from the perspective of the New Zealand wool auction.
Abstract: The most important subtype of non-Hodgkin-s
lymphoma is the Diffuse Large B-Cell Lymphoma. Approximately
40% of the patients suffering from it respond well to therapy,
whereas the remainder needs a more aggressive treatment, in order to
better their chances of survival. Data Mining techniques have helped
to identify the class of the lymphoma in an efficient manner. Despite
that, thousands of genes should be processed to obtain the results.
This paper presents a comparison of the use of various attribute
selection methods aiming to reduce the number of genes to be
searched, looking for a more effective procedure as a whole.
Abstract: The move from cash accounting to accrual accounting, or rule-based to principle-based accounting, by many governments is part of an ongoing efforts in promoting a more business-like and performance-focused public sector. Using questionnaire responses from preparers of financial statements of public universities in Malaysia, this study examines the implementation challenges and benefits of principle-based accounting. Results from these responses suggest that most respondents perceived significant costs would be incurred in relation to staff training and recruitment of staffs with relevant technical knowledge. In addition, most respondents also perceived that there will be significant changes in the current accounting system and structure in order to comply with the principle-based accounting requirements. However, most respondents perceived that these changes might not result in significant benefits for management purposes, for example, financial management, budgeting and allocation of resources. Nevertheless, most respondents perceived that principle-based accounting information would facilitate the monitoring function of the board. The general perception is that adoption of principle-based accounting information is not significantly useful than rule-based accounting information is expected to change over time as preparers of the financial statements gradually understand and appreciate the benefits of principle-based accounting information. This infers that the perceived usefulness of different accounting system is a function of familiarity by the preparers.
Abstract: This paper discusses the implementation of a fuzzy logic based coordinated voltage control for a distribution system connected with distributed generations (DGs). The connection of DGs has created a challenge for the distribution network operators to keep the voltage in the system within its acceptable limits. Intelligent centralized or coordinated voltage control schemes have proven to be more reliable due to its ability to provide more control and coordination with the communication with other network devices. In this work, voltage control using fuzzy logic by coordinating three methods of control, power factor control, on load tap changer and generation curtailment is implemented on a distribution network test system. The results show that the fuzzy logic based coordination is able to keep the voltage within its allowable limits.
Abstract: The Mobile IP Standard has been developed to support mobility over the Internet. This standard contains several drawbacks as in the cases where packets are routed via sub-optimal paths and significant amount of signaling messages is generated due to the home registration procedure which keeps the network aware of the current location of the mobile nodes. Recently, a dynamic hierarchical mobility management strategy for mobile IP networks (DHMIP) has been proposed to reduce home registrations costs. However, this strategy induces a packet delivery delay and increases the risk of packet loss. In this paper, we propose an enhanced version of the dynamic hierarchical strategy that reduces the packet delivery delay and minimizes the risk of packet loss. Preliminary results obtained from simulations are promising. They show that the enhanced version outperforms the original dynamic hierarchical mobility management strategy version.
Abstract: To achieve competitive advantage nowadays, most of
the industrial companies are considering that success is sustained to
great product development. That is to manage the product throughout
its entire lifetime ranging from design, manufacture, operation and
destruction. Achieving this goal requires a tight collaboration
between partners from a wide variety of domains, resulting in various
product data types and formats, as well as different software tools. So
far, the lack of a meaningful unified representation for product data
semantics has slowed down efficient product development. This
paper proposes an ontology based approach to enable such semantic
interoperability. Generic and extendible product ontology is
described, gathering main concepts pertaining to the mechanical field
and the relations that hold among them. The ontology is not
exhaustive; nevertheless, it shows that such a unified representation
is possible and easily exploitable. This is illustrated thru a case study
with an example product and some semantic requests to which the
ontology responds quite easily. The study proves the efficiency of
ontologies as a support to product data exchange and information
sharing, especially in product development environments where
collaboration is not just a choice but a mandatory prerequisite.
Abstract: While to minimize the overall project cost is always
one of the objectives of construction managers, to obtain the
maximum economic return is definitely one the ultimate goals of the
project investors. As there is a trade-off relationship between the
project time and cost, and the project delivery time directly affects the
timing of economic recovery of an investment project, to provide a
method that can quantify the relationship between the project delivery
time and cost, and identify the optimal delivery time to maximize
economic return has always been the focus of researchers and
industrial practitioners. Using genetic algorithms, this study
introduces an optimization model that can quantify the relationship
between the project delivery time and cost and furthermore, determine
the optimal delivery time to maximize the economic return of the
project. The results provide objective quantification for accurately
evaluating the project delivery time and cost, and facilitate the
analysis of the economic return of a project.
Abstract: The new institutional Economics helps generalization
and expansion of new classic by adding the institution theories to
Economic. It is clear that the appropriate institution is among the
factors that lead to success in Economic programs.
If the institutional are appropriate, the society will save the source
and when we make use of time to apply the program, there will be
welfare and average revenue product will also increase. In Economy,
one should not expect the real manifestation of Economic programs
only with a model for estimating and predicting rather institutions of
the same purpose and along with production are needed to form the
process of growth and development costs.
In this research, the institution role in transaction costs, financial
markets, distribution of revenue and capital and its influence on the
process of growth and development are investigated so that
handicaps and problems of Iran Economic Institutions can be
recognized. In other words, incapability, non productivity and
ambiguity of the institution in Iran Economic are some of the factors
that handicap Economic growth and development. For example, Iran
government as an important institution while having 20 ministries,83
organizations and 60 years of programming could not go along the
growth and development but why?
Abstract: Swietenia mahagoni have been used in traditional
medicine for treatment of different diseases. Present study was
performed to evaluate anti-ulcerogenic activity of ethanol seed
extract against ethanol induced gastric mucosal injury in rats. Six
groups of rats were orally pre-treated respectively with
carboxymethyl cellulose, omeprazole 20 mg/kg, 50, 100, 200 and 400
mg/kg plant extract one hour before oral administration of absolute
ethanol to generate gastric mucosal injury. After additional hour, rats
were sacrificed and ulcer areas of gastric walls were determined.
Grossly, carboxymethyl cellulose group exhibited severe mucosal
injury, whereas pre-treatment with plant extract exhibited significant
protection of gastric mucosa. Histology, carboxymethyl cellulose
group exhibited severe damage of gastric mucosa; edema and
leucocytes infiltration of sub mucosa compared to plant extract which
showed gastric protection. Acute toxicity study did not manifest any
toxicological signs in rats. Conclusions, results suggest that S.
mahagoni promotes ulcer protection as ascertained grossly and
histologically.
Abstract: In deregulated operating regime power system security is an issue that needs due thoughtfulness from researchers in the horizon of unbundling of generation and transmission. Electric power systems are exposed to various contingencies. Network contingencies often contribute to overloading of branches, violation of voltages and also leading to problems of security/stability. To maintain the security of the systems, it is desirable to estimate the effect of contingencies and pertinent control measurement can be taken on to improve the system security. This paper presents the application of particle swarm optimization algorithm to find the optimal location of multi type FACTS devices in a power system in order to eliminate or alleviate the line over loads. The optimizations are performed on the parameters, namely the location of the devices, their types, their settings and installation cost of FACTS devices for single and multiple contingencies. TCSC, SVC and UPFC are considered and modeled for steady state analysis. The selection of UPFC and TCSC suitable location uses the criteria on the basis of improved system security. The effectiveness of the proposed method is tested for IEEE 6 bus and IEEE 30 bus test systems.
Abstract: In-situ chemical oxidation (ISCO) has been widely
used for source zone remediation of Dense Nonaqueous Phase
Liquids (DNAPLs) in subsurface environments. DNAPL source
zones for karst aquifers are generally located in epikarst where the
DNAPL mass is trapped either in karst soil or at the regolith contact
with carbonate bedrock. This study aims to investigate the
performance of oxidation of residual trichloroethylene found in such
environments by potassium permanganate. Batch and flow cell
experiments were conducted to determine the kinetics and the mass
removal rate of TCE. pH change, Cl production, TCE and MnO4
destruction were monitored routinely during experiments. Nonreactive
tracer tests were also conducted prior and after the oxidation
process to determine the influence of oxidation on flow conditions.
The results show that oxidant consumption rate of the calcareous
epikarst soil was significant and the oxidant demand was determined
to be 20 g KMnO4/kg soil. Oxidation rate of residual TCE (1.26x10-3
s-1) was faster than the oxidant consumption rate of the soil (2.54 -
2.92x10-4 s-1) at only high oxidant concentrations (> 40 mM
KMnO4). Half life of TCE oxidation ranged from 7.9 to 10.7 min.
Although highly significant fraction of residual TCE mass in the
system was destroyed by permanganate oxidation, TCE
concentration in the effluent remained above its MCL. Flow
interruption tests indicate that efficiency of ISCO was limited by the
rate of TCE dissolution and the rate-limited desorption of TCE. The
residence time and the initial concentration of the oxidant in the
source zone also controlled the efficiency of ISCO in epikarst.
Abstract: The DNA microarray technology concurrently monitors the expression levels of thousands of genes during significant biological processes and across the related samples. The better understanding of functional genomics is obtained by extracting the patterns hidden in gene expression data. It is handled by clustering which reveals natural structures and identify interesting patterns in the underlying data. In the proposed work clustering gene expression data is done through an Advanced Nelder Mead (ANM) algorithm. Nelder Mead (NM) method is a method designed for optimization process. In Nelder Mead method, the vertices of a triangle are considered as the solutions. Many operations are performed on this triangle to obtain a better result. In the proposed work, the operations like reflection and expansion is eliminated and a new operation called spread-out is introduced. The spread-out operation will increase the global search area and thus provides a better result on optimization. The spread-out operation will give three points and the best among these three points will be used to replace the worst point. The experiment results are analyzed with optimization benchmark test functions and gene expression benchmark datasets. The results show that ANM outperforms NM in both benchmarks.
Abstract: Time-Cost Optimization "TCO" is one of the greatest challenges in construction project planning and control, since the optimization of either time or cost, would usually be at the expense of the other. Since there is a hidden trade-off relationship between project and cost, it might be difficult to predict whether the total cost would increase or decrease as a result of the schedule compression. Recently third dimension in trade-off analysis is taken into consideration that is quality of the projects. Few of the existing algorithms are applied in a case of construction project with threedimensional trade-off analysis, Time-Cost-Quality relationships. The objective of this paper is to presents the development of a practical software system; that named Automatic Multi-objective Typical Construction Resource Optimization System "AMTCROS". This system incorporates the basic concepts of Line Of Balance "LOB" and Critical Path Method "CPM" in a multi-objective Genetic Algorithms "GAs" model. The main objective of this system is to provide a practical support for typical construction planners who need to optimize resource utilization in order to minimize project cost and duration while maximizing its quality simultaneously. The application of these research developments in planning the typical construction projects holds a strong promise to: 1) Increase the efficiency of resource use in typical construction projects; 2) Reduce construction duration period; 3) Minimize construction cost (direct cost plus indirect cost); and 4) Improve the quality of newly construction projects. A general description of the proposed software for the Time-Cost-Quality Trade-Off "TCQTO" is presented. The main inputs and outputs of the proposed software are outlined. The main subroutines and the inference engine of this software are detailed. The complexity analysis of the software is discussed. In addition, the verification, and complexity of the proposed software are proved and tested using a real case study.
Abstract: This paper presents the voltage regulation scheme of
D-STATCOM under three-phase faults. It consists of the voltage
detection and voltage regulation schemes in the 0dq reference. The
proposed control strategy uses the proportional controller in which
the proportional gain, kp, is appropriately adjusted by using genetic
algorithms. To verify its use, a simplified 4-bus test system is situated
by assuming a three-phase fault at bus 4. As a result, the DSTATCOM
can resume the load voltage to the desired level within
1.8 ms. This confirms that the proposed voltage regulation scheme
performs well under three-phase fault events.
Abstract: Under the variation of crude oil price and the impact of
greenhouse effect, it is urgent to find a potential alternative fuel.
Among these alternative fuels, non edible plant oils are the most
potential ones, because they don-t have the problem of food and
cropland competitions. Among the non-edible plant oils, Jatropha oil
is the most potential one. Jatropha oil is non-eatable oil and has good
oil quality and low temperature performance. It has potential to
become one of the most competitive biomass crude oils. The crude
plant oil will be blended with diesel fuel to be tested in a power
generator. The international collaboration between Taiwan and
Indonesia on the production of Jatropha in Indonesia will also be
presented in this study.
Abstract: Yogyakarta, as the capital city of Yogyakarta Province, has important roles in various sectors that require good provision of public transportation system. Ideally, a good transportation system should be able to accommodate the amount of travel demand. This research attempts to develop a trip generation model to predict the number of public transport passenger in Yogyakarta city. The model is built by using multiple linear regression analysis, which establishes relationship between trip number and socioeconomic attributes. The data consist of primary and secondary data. Primary data was collected by conducting household surveys which randomly selected. The resulted model is further applied to evaluate the existing TransJogja, a new Bus Rapid Transit system serves Yogyakarta and surrounding cities, shelters.
Abstract: Identification of cancer genes that might anticipate
the clinical behaviors from different types of cancer disease is
challenging due to the huge number of genes and small number of
patients samples. The new method is being proposed based on
supervised learning of classification like support vector machines
(SVMs).A new solution is described by the introduction of the
Maximized Margin (MM) in the subset criterion, which permits to
get near the least generalization error rate. In class prediction
problem, gene selection is essential to improve the accuracy and to
identify genes for cancer disease. The performance of the new
method was evaluated with real-world data experiment. It can give
the better accuracy for classification.
Abstract: This paper examines the available experiment data for a copper bromide vapor laser (CuBr laser), emitting at two wavelengths - 510.6 and 578.2nm. Laser output power is estimated based on 10 independent input physical parameters. A classification and regression tree (CART) model is obtained which describes 97% of data. The resulting binary CART tree specifies which input parameters influence considerably each of the classification groups. This allows for a technical assessment that indicates which of these are the most significant for the manufacture and operation of the type of laser under consideration. The predicted values of the laser output power are also obtained depending on classification. This aids the design and development processes considerably.
Abstract: Total weighted tardiness is a measure of customer
satisfaction. Minimizing it represents satisfying the general
requirement of on-time delivery. In this research, we consider an ant
colony optimization (ACO) algorithm to solve the problem of
scheduling unrelated parallel machines to minimize total weighted
tardiness. The problem is NP-hard in the strong sense. Computational
results show that the proposed ACO algorithm is giving promising
results compared to other existing algorithms.