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: 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: 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.
Abstract: This paper presents a new fingerprint coding technique
based on contourlet transform and multistage vector quantization.
Wavelets have shown their ability in representing natural images that
contain smooth areas separated with edges. However, wavelets
cannot efficiently take advantage of the fact that the edges usually
found in fingerprints are smooth curves. This issue is addressed by
directional transforms, known as contourlets, which have the
property of preserving edges. The contourlet transform is a new
extension to the wavelet transform in two dimensions using
nonseparable and directional filter banks. The computation and
storage requirements are the major difficulty in implementing a
vector quantizer. In the full-search algorithm, the computation and
storage complexity is an exponential function of the number of bits
used in quantizing each frame of spectral information. The storage
requirement in multistage vector quantization is less when compared
to full search vector quantization. The coefficients of contourlet
transform are quantized by multistage vector quantization. The
quantized coefficients are encoded by Huffman coding. The results
obtained are tabulated and compared with the existing wavelet based
ones.
Abstract: A generalized unified power quality conditioner
(GUPQC) by using three single-phase three-level voltage source
converters (VSCs) connected back-to-back through a common dc
link is proposed in this paper as a new custom power device for a
three-feeder distribution system. One of the converters is connected
in shunt with one feeder for mitigation of current harmonics and
reactive power compensation, while the other two VSCs are
connected in series with the other two feeders to maintain the load
voltage sinusoidal and at constant level. A new control scheme based
on synchronous reference frame is proposed for series converters.
The simulation analysis on compensation performance of GUPQC
based on PSCAD/EMTDC is reported.
Abstract: This is a cross-cultural study that determines South
African multinational enterprises (MNEs) entry strategies as they
invest in Africa. An integrated theoretical framework comprising the
transaction cost theory, Uppsala model, eclectic paradigm and the
distance framework was adopted. A sample of 40 South African
MNEs with 415 existing FDI entries in Africa was drawn. Using an
ordered logistic regression model, the impact of culture on the choice
of degree of control by South African MNEs in Africa was
determined. Cultural distance was one of significant factors that
influenced South African MNEs- choice of degree of control.
Furthermore, South African MNEs are risk averse in all countries in
Africa but minimize the risks differently across sectors. Service
sectors chooses to own their subsidiaries 100% and avoid dealing
with the locals while manufacturing, resources and construction
choose to have a local partner to share the risk.
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: 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: The purpose of this paper is to highlight the
importance of the concept of competitiveness in the supply chain and
to present a conceptual framework for Supply Chain Competitiveness
(SCC). The framework is based on supply chain activities, which are
inputs, necessary for SCC and the benefits which are the outputs of
SCC. A literature review is conducted on key supply chain
competitiveness issues, its determinants, its various dimensions
followed by exploration for SCC. Based on the insights gained, a
conceptual framework for SCC is presented based on activities for
SCC, SCC environment and outcomes of SCC. The information flow
in the conceptual framework is bi-directional at all levels and the
activities are interrelated in a global competitive environment. The
activities include the activities of suppliers, manufacturers and
distributors, giving more emphasis on manufacturers- activities.
Further, implications of various factors such as economic, politicolegal,
technical, socio-cultural, competition, demographic etc. are
also highlighted. The SCC framework is an attempt to cover the
relatively less explored area of supply chain competitiveness. It is
expected that this work will further motivate researchers,
academicians and practitioners to work in this area and offers
conceptual help in providing a directions for supply chain
competitiveness which leads to improvement in the supply chain and
supply chain performance.
Abstract: In this paper, a new encoding algorithm of spectral envelope based on NLMS in G.729.1 for VoIP is proposed. In the TDAC part of G.729.1, the spectral envelope and MDCT coefficients extracted in the weighted CELP coding error (lower-band) and the higher-band input signal are encoded. In order to reduce allocation bits for spectral envelope coding, a new quantization algorithm based on NLMS is proposed. Also, reduced bits are used to enhance sound quality. The performance of the proposed algorithm is evaluated by sound quality and bit reduction rates in clean and frame loss conditions.
Abstract: In this paper a bank of velocity filters is devised to be
used for isolating a moving object with specific velocity in a sequence of frames. The approach used is a 3-D FFT based experimental procedure without applying any theoretical concept
from velocity filters. Accordingly, velocity filters are built using the
spectral signature of each separate moving object. Experimentation
reveals the capabilities of the constructed filter bank to separate moving objects as far as the amplitude as well as the direction of the
velocity are concerned.
Abstract: In this paper, two matrix iterative methods are presented to solve the matrix equation A1X1B1 + A2X2B2 + ... + AlXlBl = C the minimum residual problem l i=1 AiXiBi−CF = minXi∈BRni×ni l i=1 AiXiBi−CF and the matrix nearness problem [X1, X2, ..., Xl] = min[X1,X2,...,Xl]∈SE [X1,X2, ...,Xl] − [X1, X2, ..., Xl]F , where BRni×ni is the set of bisymmetric matrices, and SE is the solution set of above matrix equation or minimum residual problem. These matrix iterative methods have faster convergence rate and higher accuracy than former methods. Paige’s algorithms are used as the frame method for deriving these matrix iterative methods. The numerical example is used to illustrate the efficiency of these new methods.
Abstract: An adaptive spatial Gaussian mixture model is proposed for clustering based color image segmentation. A new clustering objective function which incorporates the spatial information is introduced in the Bayesian framework. The weighting parameter for controlling the importance of spatial information is made adaptive to the image content to augment the smoothness towards piecewisehomogeneous region and diminish the edge-blurring effect and hence the name adaptive spatial finite mixture model. The proposed approach is compared with the spatially variant finite mixture model for pixel labeling. The experimental results with synthetic and Berkeley dataset demonstrate that the proposed method is effective in improving the segmentation and it can be employed in different practical image content understanding applications.
Abstract: This paper deals with e-government issues at several
levels. Initially we look at the concept of e-government itself in order
to give it a sound framework. Than we look at the e-government
issues at three levels, first we analyse it at the global level, second we
analyse it at the level of transition economies, and finally we take a
closer look on developments in Croatia. The analysis includes actual
progress being made in selected transition economies given the Euro
area averages, along with e-government potential in future
demanding period.
Abstract: The aim of this research is to design a collaborative
framework that integrates risk analysis activities into the geospatial
database design (GDD) process. Risk analysis is rarely undertaken
iteratively as part of the present GDD methods in conformance to
requirement engineering (RE) guidelines and risk standards.
Accordingly, when risk analysis is performed during the GDD, some
foreseeable risks may be overlooked and not reach the output
specifications especially when user intentions are not systematically
collected. This may lead to ill-defined requirements and ultimately in
higher risks of geospatial data misuse. The adopted approach consists
of 1) reviewing risk analysis process within the scope of RE and
GDD, 2) analyzing the challenges of risk analysis within the context
of GDD, and 3) presenting the components of a risk-based
collaborative framework that improves the collection of the
intended/forbidden usages of the data and helps geo-IT experts to
discover implicit requirements and risks.
Abstract: Model Predictive Control (MPC) is increasingly being
proposed for real time applications and embedded systems. However
comparing to PID controller, the implementation of the MPC in
miniaturized devices like Field Programmable Gate Arrays (FPGA)
and microcontrollers has historically been very small scale due to its
complexity in implementation and its computation time requirement.
At the same time, such embedded technologies have become an
enabler for future manufacturing enterprises as well as a transformer
of organizations and markets. Recently, advances in microelectronics
and software allow such technique to be implemented in embedded
systems. In this work, we take advantage of these recent advances
in this area in the deployment of one of the most studied and
applied control technique in the industrial engineering. In fact in
this paper, we propose an efficient framework for implementation
of Generalized Predictive Control (GPC) in the performed STM32
microcontroller. The STM32 keil starter kit based on a JTAG interface
and the STM32 board was used to implement the proposed GPC
firmware. Besides the GPC, the PID anti windup algorithm was
also implemented using Keil development tools designed for ARM
processor-based microcontroller devices and working with C/Cµ
langage. A performances comparison study was done between both
firmwares. This performances study show good execution speed and
low computational burden. These results encourage to develop simple
predictive algorithms to be programmed in industrial standard hardware.
The main features of the proposed framework are illustrated
through two examples and compared with the anti windup PID
controller.
Abstract: In view of the good properties of nonstationary wavelet frames and the better flexibility of wavelets in Sobolev spaces, the nonstationary dual wavelet frames in a pair of dual Sobolev spaces are studied in this paper. We mainly give the oblique extension principle and the mixed extension principle for nonstationary dual wavelet frames in a pair of dual Sobolev spaces Hs(Rd) and H-s(Rd).
Abstract: The unanticipated brittle fracture of connection of the
steel moment resisting frame (SMRF) occurred in 1994 the Northridge
earthquake. Since then, the researches for the vulnerability of
connection of the existing SMRF and for rehabilitation of those
buildings were conducted. This paper suggests performance-based
optimal seismic retrofit technique using connection upgrade. For
optimal design, a multi-objective genetic algorithm(NSGA-II) is used.
One of the two objective functions is to minimize initial cost and
another objective function is to minimize lifetime seismic damages
cost. The optimal algorithm proposed in this paper is performed
satisfying specified performance objective based on FEMA 356. The
nonlinear static analysis is performed for structural seismic
performance evaluation. A numerical example of SAC benchmark
SMRF is provided using the performance-based optimal seismic
retrofit technique proposed in this paper
Abstract: Testable software has two inherent properties – observability and controllability. Observability facilitates observation of internal behavior of software to required degree of detail. Controllability allows creation of difficult-to-achieve states prior to execution of various tests. In this paper, we describe COTT, a Controllability and Observability Testing Tool, to create testable object-oriented software. COTT provides a framework that helps the user to instrument object-oriented software to build the required controllability and observability. During testing, the tool facilitates creation of difficult-to-achieve states required for testing of difficultto- test conditions and observation of internal details of execution at unit, integration and system levels. The execution observations are logged in a test log file, which are used for post analysis and to generate test coverage reports.
Abstract: The purpose of this study is to analyze Green IT industry in major developed countries and to suggest overall directions for IT-Energy convergence industry. Recently, IT industry is pointed out as a problem such as environmental pollution, energy exhaustion, and high energy consumption. Therefore, Green IT gets focused which concerns as solution of these problems. However, since it is a beginning stage of this convergence area, there are only a few studies of IT-Energy convergence industry. According to this, this study examined the major developed countries in terms of institution arrangements, resources, markets and companies based on Van de Ven(1999)'s social system framework that shows relationship among key components of industrial infrastructure. Subsequently, the direction of the future study of convergence on IT and Energy industry is proposed.