Abstract: The distinction among urban, periurban and rural areas represents a classical example of uncertainty in land classification. Satellite images, geostatistical analysis and all kinds of spatial data are very useful in urban sprawl studies, but it is important to define precise rules in combining great amounts of data to build complex knowledge about territory. Rough Set theory may be a useful method to employ in this field. It represents a different mathematical approach to uncertainty by capturing the indiscernibility. Two different phenomena can be indiscernible in some contexts and classified in the same way when combining available information about them. This approach has been applied in a case of study, comparing the results achieved with both Map Algebra technique and Spatial Rough Set. The study case area, Potenza Province, is particularly suitable for the application of this theory, because it includes 100 municipalities with different number of inhabitants and morphologic features.
Abstract: While financial institutions have faced difficulties
over the years for a multitude of reasons, the major cause of serious
banking problems continues to be directly related to lax credit
standards for borrowers and counterparties, poor portfolio risk
management, or a lack of attention to changes in economic or other
circumstances that can lead to a deterioration in the credit standing of
a bank's counterparties. Credit risk is most simply defined as the
potential that a bank borrower or counterparty will fail to meet its
obligations in accordance with agreed terms. The goal of credit risk
management is to maximize a bank's risk-adjusted rate of return by
maintaining credit risk exposure within acceptable parameters. Banks
need to manage the credit risk inherent in the entire portfolio as well
as the risk in individual credits or transactions. Banks should also
consider the relationships between credit risk and other risks. The
effective management of credit risk is a critical component of a
comprehensive approach to risk management and essential to the
long-term success of any banking organization. In this research we
also study the relationship between credit risk indices and borrower-s
timely payback in Karafarin bank.
Abstract: This paper adopts a notion of expectation-perception
gap of systems users as information systems (IS) failure. Problems
leading to the expectation-perception gap are identified and modelled
as five interrelated discrepancies or gaps throughout the process of
information systems development (ISD). It describes an empirical
study on how systems developers and users perceive the size of each
gap and the extent to which each problematic issue contributes to the
gap. The key to achieving success in ISD is to keep the expectationperception
gap closed by closing all 5 pertaining gaps. The gap model
suggests that most factors in IS failure are related to organizational,
cognitive and social aspects of information systems design.
Organization requirement analysis, being the weakest link of IS
development, is particularly worthy of investigation.
Abstract: There is lot of work done in prediction of the fault proneness of the software systems. But, it is the severity of the faults that is more important than number of faults existing in the developed system as the major faults matters most for a developer and those major faults needs immediate attention. In this paper, we tried to predict the level of impact of the existing faults in software systems. Neuro-Fuzzy based predictor models is applied NASA-s public domain defect dataset coded in C programming language. As Correlation-based Feature Selection (CFS) evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them. So, CFS is used for the selecting the best metrics that have highly correlated with level of severity of faults. The results are compared with the prediction results of Logistic Models (LMT) that was earlier quoted as the best technique in [17]. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results show that Neuro-fuzzy based model provide a relatively better prediction accuracy as compared to other models and hence, can be used for the modeling of the level of impact of faults in function based systems.
Abstract: Among the chemicals used for ammunition production, TNT (Trinitrotoluene) play a significant role since World War I and II. Various types of military weapon utilize TNT in casting process. However, the TNT casting process for warhead is difficult to control the cooling rate of the liquid TNT. This problem occurs because the casting process lacks the equipment to detect the temperature during the casting procedure This study presents the temperature detected by infrared camera to illustrate the cooling rate and cooling zone of curing, and demonstrates the optimization of TNT condition to reduce the risk of air gap occurred in the warhead which can result in the destruction afterward. Premature initiation of explosive-filled projectiles in response to set-back forces during gunfiring cause by casting defects. Finally the study can help improving the process of the TNT casting. The operators can control the curing of TNT inside the case by rising up the heating rod at the proper time. Consequently this can reduce tremendous time of rework if the air gaps occur and increase strength to lower elastic modulus. Therefore, it can be clearly concluded that the use of Infrared Cameras in this process is another method to improve the casting procedure.
Abstract: In this paper we propose a robust environmental sound classification approach, based on spectrograms features driven from log-Gabor filters. This approach includes two methods. In the first methods, the spectrograms are passed through an appropriate log-Gabor filter banks and the outputs are averaged and underwent an optimal feature selection procedure based on a mutual information criteria. The second method uses the same steps but applied only to three patches extracted from each spectrogram.
To investigate the accuracy of the proposed methods, we conduct experiments using a large database containing 10 environmental sound classes. The classification results based on Multiclass Support Vector Machines show that the second method is the most efficient with an average classification accuracy of 89.62 %.
Abstract: The objective of this article is to discuss the potential
of economic analysis as a tool for identification and evaluation of
corruption in legislative acts. We propose that corruption be
perceived as a risk variable within the legislative process. Therefore
we find it appropriate to employ risk analysis methods, used in
various fields of economics, for the evaluation of corruption in
legislation. Furthermore we propose the incorporation of these
methods into the so called corruption impact assessment (CIA), the
general framework for detection of corruption in legislative acts. The
applications of the risk analysis methods are demonstrated on
examples of implementation of proposed CIA in the Czech Republic.
Abstract: The performance of time-reversal MUSIC algorithm will be dramatically degrades in presence of strong noise and multiple scattering (i.e. when scatterers are close to each other). This is due to error in determining the number of scatterers. The present paper provides a new approach to alleviate such a problem using an information theoretic criterion referred as minimum description length (MDL). The merits of the novel approach are confirmed by the numerical examples. The results indicate the time-reversal MUSIC yields accurate estimate of the target locations with considerable noise and multiple scattering in the received signals.
Abstract: In this paper a controller for the pitch angle of an
aircraft regarding to the elevator deflection angle is designed.
The way how the elevator angle affects pitching motion of the
aircraft is pointed out, as well as, how a pitch controller can be
applied for the aircraft to reach certain pitch angle. In this digital
optimal system, the elevator deflection angle and pitching angle
of the plane are considered to be input and output respectively.
A single input single output (SISO) system is presented. A
digital pitch aircraft control is demonstrated. A simulation for
the whole system has been performed. The optimal control
weighting vectors, Q and R have been determined.
Abstract: This paper presents a method for functional projective H∞ synchronization problem of chaotic systems with external disturbance. Based on Lyapunov theory and linear matrix inequality (LMI) formulation, the novel feedback controller is established to not only guarantee stable synchronization of both drive and response systems but also reduce the effect of external disturbance to an H∞ norm constraint.
Abstract: This paper discusses a genetic algorithm (GA) based optimal load shedding that can apply for electrical distribution networks with and without dispersed generators (DG). Also, the proposed method has the ability for considering constant and variable capacity deficiency caused by unscheduled outages in the bulked generation and transmission system of bulked power supply. The genetic algorithm (GA) is employed to search for the optimal load shedding strategy in distribution networks considering DGs in two cases of constant and variable modelling of bulked power supply of distribution networks. Electrical power distribution systems have a radial network and unidirectional power flows. With the advent of dispersed generations, the electrical distribution system has a locally looped network and bidirectional power flows. Therefore, installed DG in the electrical distribution systems can cause operational problems and impact on existing operational schemes. Introduction of DGs in electrical distribution systems has introduced many new issues in operational and planning level. Load shedding as one of operational issue has no exempt. The objective is to minimize the sum of curtailed load and also system losses within the frame-work of system operational and security constraints. The proposed method is tested on a radial distribution system with 33 load points for more practical applications.
Abstract: The objective of the research was focused on the
design, development and evaluation of a sustainable web based
network system to be used as an interoperable environment for
University process workflow and document management. In this
manner the most of the process workflows in Universities can be
entirely realized electronically and promote integrated University.
Definition of the most used University process workflows enabled
creating electronic workflows and their execution on standard
workflow execution engines. Definition or reengineering of
workflows provided increased work efficiency and helped in having
standardized process through different faculties. The concept and the
process definition as well as the solution applied as Case study are
evaluated and findings are reported.
Abstract: The information revealed by derivatives can help to
better characterize digital near-end crosstalk signatures with the
ultimate goal of identifying the specific aggressor signal.
Unfortunately, derivatives tend to be very sensitive to even low
levels of noise. In this work we approximated the derivatives of both
quiet and noisy digital signals using a wavelet-based technique. The
results are presented for Gaussian digital edges, IBIS Model digital
edges, and digital edges in oscilloscope data captured from an actual
printed circuit board. Tradeoffs between accuracy and noise
immunity are presented. The results show that the wavelet technique
can produce first derivative approximations that are accurate to
within 5% or better, even under noisy conditions. The wavelet
technique can be used to calculate the derivative of a digital signal
edge when conventional methods fail.
Abstract: The nature of consumer products causes the difficulty
in forecasting the future demands and the accuracy of the forecasts
significantly affects the overall performance of the supply chain
system. In this study, two data mining methods, artificial neural
network (ANN) and support vector machine (SVM), were utilized to
predict the demand of consumer products. The training data used was
the actual demand of six different products from a consumer product
company in Thailand. The results indicated that SVM had a better
forecast quality (in term of MAPE) than ANN in every category of
products. Moreover, another important finding was the margin
difference of MAPE from these two methods was significantly high
when the data was highly correlated.
Abstract: To study on effect of PEG and NaCl stress on
germination and early seedling stages on two cultivar of corn, two
separated experiment were laid out at physiology laboratory, faculty
of Agriculture, Razi University, Kermanshah, Iran in 2009. This
investigation was performed as factorial experiment under Complete
Randomized Design (CRD) with three replications. Cultivar factor
contains of two varieties (sweet corn SC403 and Flint corn SC704)
and five levels of stress (0, -2, -4, -6 and -8 bar). The principal aim of
current study was to compare the two varieties of maize in relative to
the stress conditions. Results indicated that significant decrease was
observed in percentage of germination, germination rate, length of
radicle and plumule and radicle and plumule dry matter. On the basis
of the results, NaCl as compared with PEG had more effect on
germination and early seedling stage and sweet corn had more
resistant than flint corn in both stress conditions.
Abstract: In this paper, the Gaussian type quadrature rules for fuzzy functions are discussed. The errors representation and convergence theorems are given. Moreover, four kinds of Gaussian type quadrature rules with error terms for approximate of fuzzy integrals are presented. The present paper complements the theoretical results of the paper by T. Allahviranloo and M. Otadi [T. Allahviranloo, M. Otadi, Gaussian quadratures for approximate of fuzzy integrals, Applied Mathematics and Computation 170 (2005) 874-885]. The obtained results are illustrated by solving some numerical examples.
Abstract: The purpose of the experiments described in this article was the comparison of integrated fixed film activated sludge (IFAS) and activated sludge (AS) system. The IFAS applied system consists of the cigarette filter rods (wasted filter in tobacco factories) as a biofilm carrier. The comparison with activated sludge was performed by two parallel treatment lines. Organic substance, ammonia and TP removal was investigated over four month period. Synthetic wastewater was prepared with ordinary tap water and glucose as the main sources of carbon and energy, plus balanced macro and micro nutrients. COD removal percentages of 94.55%, and 81.62% were achieved for IFAS and activated sludge system, respectively. Also, ammonia concentration significantly decreased by increasing the HRT in both systems. The average ammonia removal of 97.40 % and 96.34% were achieved for IFAS and activated sludge system, respectively. The removal efficiency of total phosphorus (TP-P) was 60.64%, higher than AS process by 56.63% respectively.
Abstract: In this paper, we apply the PQ theory with shunt active power filter in an unbalanced and distorted power system voltage to compensate the perturbations generated by non linear load. The power factor is also improved in the current source. The PLL system is used to extract the fundamental component of the even sequence under conditions mentioned of the power system voltage.
Abstract: Biological data has several characteristics that strongly differentiate it from typical business data. It is much more complex, usually large in size, and continuously changes. Until recently business data has been the main target for discovering trends, patterns or future expectations. However, with the recent rise in biotechnology, the powerful technology that was used for analyzing business data is now being applied to biological data. With the advanced technology at hand, the main trend in biological research is rapidly changing from structural DNA analysis to understanding cellular functions of the DNA sequences. DNA chips are now being used to perform experiments and DNA analysis processes are being used by researchers. Clustering is one of the important processes used for grouping together similar entities. There are many clustering algorithms such as hierarchical clustering, self-organizing maps, K-means clustering and so on. In this paper, we propose a clustering algorithm that imitates the ecosystem taking into account the features of biological data. We implemented the system using an Ant-Colony clustering algorithm. The system decides the number of clusters automatically. The system processes the input biological data, runs the Ant-Colony algorithm, draws the Topic Map, assigns clusters to the genes and displays the output. We tested the algorithm with a test data of 100 to1000 genes and 24 samples and show promising results for applying this algorithm to clustering DNA chip data.
Abstract: This paper presents an innovative approach within the area of Group Decision Support System (GDSS) by using tools based on intelligent agents. It introduces iGDSS, a software platform for decision support and collaboration and an application of this platform - eCollaborative Decisions - for academic environment, all these developed within a framework of a research project.