Abstract: Business rules and data warehouse are concepts and
technologies that impact a wide variety of organizational tasks. In
general, each area has evolved independently, impacting application
development and decision-making. Generating knowledge from data
warehouse is a complex process. This paper outlines an approach to
ease import of information and knowledge from a data warehouse
star schema through an inference class of business rules. The paper
utilizes the Oracle database for illustrating the working of the
concepts. The star schema structure and the business rules are stored
within a relational database. The approach is explained through a
prototype in Oracle-s PL/SQL Server Pages.
Abstract: This paper proposes a simple model of economic geography within the Dixit-Stiglitz-Iceberg framework that may be used to analyze migration patterns among three cities. The cost–benefit tradeoffs affecting incentives for three types of migration, including echelon migration, are discussed. This paper develops a tractable, heterogeneous-agent, general equilibrium model, where agents share constant human capital, and explores the relationship between the benefits of echelon migration and gross human capital. Using Chinese numerical solutions, we study the manifestation of echelon migration and how it responds to changes in transportation cost and elasticity of substitution. Numerical results demonstrate that (i) there are positive relationships between a migration-s benefit-and-wage ratio, (ii) there are positive relationships between gross human capital ratios and wage ratios as to origin and destination, and (iii) we identify 13 varieties of human capital convergence among cities. In particular, this model predicts population shock resulting from the processes of migration choice and echelon migration.
Abstract: The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm along with least square estimation (LSE) generates the fuzzy rules that describe the relationship between input/output data. The fuzzy rules are tuned by Adaptive Neuro-Fuzzy Inference System (ANFIS). The results show that when the pressure increases the amount of water flow rate and heat transfer rate decrease within the lower ranges of inlet dry bulb temperatures. On the other hand, and as pressure increases the amount of water flow rate and heat transfer rate increases within the higher ranges of inlet dry bulb temperatures. The inflection in the pressure effect trend occurs at lower temperatures as the inlet air humidity increases.
Abstract: Sorting appears the most attention among all computational tasks over the past years because sorted data is at the heart of many computations. Sorting is of additional importance to parallel computing because of its close relation to the task of routing data among processes, which is an essential part of many parallel algorithms. Many parallel sorting algorithms have been investigated for a variety of parallel computer architectures. In this paper, three parallel sorting algorithms have been implemented and compared in terms of their overall execution time. The algorithms implemented are the odd-even transposition sort, parallel merge sort and parallel rank sort. Cluster of Workstations or Windows Compute Cluster has been used to compare the algorithms implemented. The C# programming language is used to develop the sorting algorithms. The MPI (Message Passing Interface) library has been selected to establish the communication and synchronization between processors. The time complexity for each parallel sorting algorithm will also be mentioned and analyzed.
Abstract: Over the past years, the EMCCD has had a profound
influence on photon starved imaging applications relying on its unique
multiplication register based on the impact ionization effect in the
silicon. High signal-to-noise ratio (SNR) means high image quality.
Thus, SNR improvement is important for the EMCCD. This work
analyzes the SNR performance of an EMCCD with gain off and on. In
each mode, simplified SNR models are established for different
integration times. The SNR curves are divided into readout noise (or
CIC) region and shot noise region by integration time. Theoretical
SNR values comparing long frame integration and frame adding in
each region are presented and discussed to figure out which method is
more effective. In order to further improve the SNR performance,
pixel binning is introduced into the EMCCD. The results show that
pixel binning does obviously improve the SNR performance, but at the
expensive of the spatial resolution.
Abstract: Wavelet transform provides several important
characteristics which can be used in a texture analysis and
classification. In this work, an efficient texture classification method,
which combines concepts from wavelet and co-occurrence matrices,
is presented. An Euclidian distance classifier is used to evaluate the
various methods of classification. A comparative study is essential to
determine the ideal method. Using this conjecture, we developed a
novel feature set for texture classification and demonstrate its
effectiveness
Abstract: This paper deals with the design, development & implementation of a temperature sensor using zigbee. The main aim of the work undertaken in this paper is to sense the temperature and to display the result on the LCD using the zigbee technology. ZigBee operates in the industrial, scientific and medical (ISM) radio bands; 868 MHz in Europe, 915 MHz in the USA and 2.4 GHz in most jurisdictions worldwide. The technology is intended to be simpler and cheaper than other WPANs such as Bluetooth. The most capable ZigBee node type is said to require only about 10 % of the software of a typical Bluetooth or Wireless Internet node, while the simplest nodes are about 2 %. However, actual code sizes are much higher, more like 50 % of the Bluetooth code size. ZigBee chip vendors have announced 128-kilobyte devices. In this work undertaken in the design & development of the temperature sensor, it senses the temperature and after amplification is then fed to the micro controller, this is then connected to the zigbee module, which transmits the data and at the other end the zigbee reads the data and displays on to the LCD. The software developed is highly accurate and works at a very high speed. The method developed shows the effectiveness of the scheme employed.
Abstract: In wireless sensor network (WSN) the use of mobile
sink has been attracting more attention in recent times. Mobile sinks
are more effective means of balancing load, reducing hotspot
problem and elongating network lifetime. The sensor nodes in WSN
have limited power supply, computational capability and storage and
therefore for continuous data delivery reliability becomes high
priority in these networks. In this paper, we propose a Reliable
Energy-efficient Data Dissemination (REDD) scheme for WSNs with
multiple mobile sinks. In this strategy, sink first determines the
location of source and then directly communicates with the source
using geographical forwarding. Every forwarding node (FN) creates a
local zone comprising some sensor nodes that can act as
representative of FN when it fails. Analytical and simulation study
reveals significant improvement in energy conservation and reliable
data delivery in comparison to existing schemes.
Abstract: This paper proposes new algorithms for the computeraided
design and manufacture (CAD/CAM) of 3D woven multi-layer
textile structures. Existing commercial CAD/CAM systems are often
restricted to the design and manufacture of 2D weaves. Those
CAD/CAM systems that do support the design and manufacture of
3D multi-layer weaves are often limited to manual editing of design
paper grids on the computer display and weave retrieval from stored
archives. This complex design activity is time-consuming, tedious
and error-prone and requires considerable experience and skill of a
technical weaver. Recent research reported in the literature has
addressed some of the shortcomings of commercial 3D multi-layer
weave CAD/CAM systems. However, earlier research results have
shown the need for further work on weave specification, weave
generation, yarn path editing and layer binding. Analysis of 3D
multi-layer weaves in this research has led to the design and
development of efficient and robust algorithms for the CAD/CAM of
3D woven multi-layer textile structures. The resulting algorithmically
generated weave designs can be used as a basis for lifting plans that
can be loaded onto looms equipped with electronic shedding
mechanisms for the CAM of 3D woven multi-layer textile structures.
Abstract: The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.
Abstract: In the current research, we present an operation framework and protection mechanism to facilitate secure environment to protect mobile agents against tampering. The system depends on the presence of an authentication authority. The advantage of the proposed system is that security measures is an integral part of the design, thus common security retrofitting problems do not arise. This is due to the presence of AlGamal encryption mechanism to protect its confidential content and any collected data by the agent from the visited host . So that eavesdropping on information from the agent is no longer possible to reveal any confidential information. Also the inherent security constraints within the framework allow the system to operate as an intrusion detection system for any mobile agent environment. The mechanism is tested for most of the well known severe attacks against agents and networked systems. The scheme proved a promising performance that makes it very much recommended for the types of transactions that needs highly secure environments, e. g., business to business.
Abstract: To improve HSE standards, oil and gas industries are
interested in using remotely controlled and autonomous robots instead
of human workers on offshore platforms. In addition to earlier reason
this strategy would increase potential revenue, efficient usage of
work experts and even would allow operations in more remote areas.
This article is the presentation of a custom climbing robot, called
Walloid, designed for offshore platform topside automation. This 4
arms climbing robot with grippers is an ongoing project at University
of Oslo.
Abstract: In this paper, the modelling and design of artificial neural network architecture for load forecasting purposes is investigated. The primary pre-requisite for power system planning is to arrive at realistic estimates of future demand of power, which is known as Load Forecasting. Short Term Load Forecasting (STLF) helps in determining the economic, reliable and secure operating strategies for power system. The dependence of load on several factors makes the load forecasting a very challenging job. An over estimation of the load may cause premature investment and unnecessary blocking of the capital where as under estimation of load may result in shortage of equipment and circuits. It is always better to plan the system for the load slightly higher than expected one so that no exigency may arise. In this paper, a load-forecasting model is proposed using a multilayer neural network with an appropriately modified back propagation learning algorithm. Once the neural network model is designed and trained, it can forecast the load of the power system 24 hours ahead on daily basis and can also forecast the cumulative load on daily basis. The real load data that is used for the Artificial Neural Network training was taken from LDC, Gujarat Electricity Board, Jambuva, Gujarat, India. The results show that the load forecasting of the ANN model follows the actual load pattern more accurately throughout the forecasted period.
Abstract: The process of constructing a scale measuring the attitudes of youth toward violence on televisions is reported. A 30-item draft attitude scale was applied to a working group of 232 students attending the Faculty of Educational Sciences at Ankara University between the years 2005-2006. To introduce the construct validity and dimensionality of the scale, exploratory and confirmatory factor analysis was applied to the data. Results of the exploratory factor analysis showed that the scale had three factors that accounted for 58,44% (22,46% for the first, 22,15% for the second and 13,83% for the third factor) of the common variance. It is determined that the first factor considered issues related individual effects of violence on televisions, the second factor concerned issues related social effects of violence on televisions and the third factor concerned issues related violence on television programs. Results of the confirmatory factor analysis showed that all the items under each factor are fitting the concerning factors structure. An alpha reliability of 0,90 was estimated for the whole scale. It is concluded that the scale is valid and reliable.
Abstract: A geothermal power plant multiple simulator for
operators training is presented. The simulator is designed to be
installed in a wireless local area network and has a capacity to train
one to six operators simultaneously, each one with an independent
simulation session. The sessions must be supervised only by one
instructor. The main parts of this multiple simulator are: instructor
and operator-s stations. On the instructor station, the instructor
controls the simulation sessions, establishes training exercises and
supervises each power plant operator in individual way. This station
is hosted in a Main Personal Computer (NS) and its main functions
are: to set initial conditions, snapshots, malfunctions or faults,
monitoring trends, and process and soft-panel diagrams. On the other
hand the operators carry out their actions over the power plant
simulated on the operator-s stations; each one is also hosted in a PC.
The main software of instructor and operator-s stations are executed
on the same NS and displayed in PCs through graphical Interactive
Process Diagrams (IDP). The geothermal multiple simulator has been
installed in the Geothermal Simulation Training Center (GSTC) of
the Comisi├│n Federal de Electricidad, (Federal Commission of
Electricity, CFE), Mexico, and is being utilized as a part of the
training courses for geothermal power plant operators.
Abstract: This paper is to explore the relationship and the level
of stock market integration of the Asian countries, primarily
concentrating on Malaysia, Thailand, Indonesia, and South Korea,
with the world from January 1997 to December 2009. The degree of
short-run and long-run stock market integration of those Asian
countries are analyzed in order to determine the significance of series
of regional and world financial crises, liberalization policies and
other financial reforms in influencing the level of stock market
integration. To test for cointegration, this paper applies coefficient
correlation, univariate regression analyses, cointegration tests, and
vector autoregressive models (VAR) by using the four Asian stock
markets main indices and the MSCI World index. The empirical
findings from this work reveal that there is no long-run stock market
integration for the four countries and the world market. However,
there is short run integration.
Abstract: The inability to implement the principles of good
corporate governance (GCG) as demonstrated in the surveys is due to
a number of constraints which can be classified into three; namely internal constraints, external constraints, and constraints coming
from the structure of ownership. The issues in the internal constraints
mentioned are related to the function of several elements of the company. As a business organization, corporation is unable to
achieve its goal to successfully implement GCG principles since it is
not support by its internal elements- functions. Two of several numbers of internal elements of a company are ethical work climate
and leadership style of the top management.
To prove the correlation between internal function of organization
(in this case ethical work climate and transformational leadership)
and the successful implementation of GCG principles, this study
proposes two hypotheses to be empirically tested on thirty surveyed organizations; eleven of which are state-owned companies and
nineteen are private companies. These thirty corporations are listed in
the Jakarta Stock Exchange. All state-owned companies in the
samples are those which have been privatized.
The research showed that internal function of organization give
support to the successful implementation of GCG principle. In this
research we can prove that : (i) ethical work climate has positive
significance of correlation with the successful implementation of
social awareness principle (one of principles on GCG) and, (ii) only
at the state-owned companies, transformational leadership have
positive significance effect to forming the ethical work climate.
Abstract: Communication is an important factor and a prop in
directing corporate activities efficiently, in ensuring the flow of
knowledge which is necessary for the continuity of the institution, in
creating a common language in the institution, in transferring
corporate culture and ultimately in corporate success. The idea of
transmitting the knowledge among the workers in a healthy manner
has revived knowledge communication. Knowledge communication
can be defined as the act of mutual creation and communication of
intuitions, assessments, experiences and capabilities, as long as
maintained effectively, can provide advantages such as corporate
continuity, access to corporate objectives and making true
administrative decisions. Although the benefits of the knowledge
communication to corporations are known, and the necessary worth
and care is given, some hardships may arise which makes it difficult
or even block it. In this article, difficulties that prevent knowledge
communication will be discussed and solutions will be proposed.
Abstract: In pattern recognition applications the low level
segmentation and the high level object recognition are generally
considered as two separate steps. The paper presents a method that
bridges the gap between the low and the high level object
recognition. It is based on a Bayesian network representation and
network propagation algorithm. At the low level it uses hierarchical
structure of quadratic spline wavelet image bases. The method is
demonstrated for a simple circuit diagram component identification
problem.
Abstract: In the project FleGSens, a wireless sensor network
(WSN) for the surveillance of critical areas and properties is currently developed which incorporates mechanisms to ensure information
security. The intended prototype consists of 200 sensor nodes for
monitoring a 500m long land strip. The system is focused on ensuring
integrity and authenticity of generated alarms and availability in the
presence of an attacker who may even compromise a limited number
of sensor nodes. In this paper, two of the main protocols developed
in the project are presented, a tracking protocol to provide secure
detection of trespasses within the monitored area and a protocol for secure detection of node failures. Simulation results of networks
containing 200 and 2000 nodes as well as the results of the first prototype comprising a network of 16 nodes are presented. The focus of the simulations and prototype are functional testing of the protocols
and particularly demonstrating the impact and cost of several attacks.