Abstract: Web services are pieces of software that can be invoked via a standardized protocol. They can be combined via formalized taskflow languages. The Open Knowledge system is a fully distributed system using P2P technology, that allows users to publish the setaskflows, and programmers to register their web services or publish implementations of them, for the roles described in these workflows.Besides this, the system offers the functionality to select a peer that could coordinate such an interaction model and inform web services when it is their 'turn'. In this paper we describe the architecture and implementation of the Open Knowledge Kernel which provides the core functionality of the Open Knowledge system.
Abstract: Nowadays data backup format doesn-t cease to appear raising so the anxiety on their accessibility and their perpetuity. XML is one of the most promising formats to guarantee the integrity of data. This article suggests while showing one thing man can do with XML. Indeed XML will help to create a data backup model. The main task will consist in defining an application in JAVA able to convert information of a database in XML format and restore them later.
Abstract: The aim of this work was to detect genetic variability among the set of 40 castor genotypes using 8 RAPD markers. Amplification of genomic DNA of 40 genotypes, using RAPD analysis, yielded in 66 fragments, with an average of 8.25 polymorphic fragments per primer. Number of amplified fragments ranged from 3 to 13, with the size of amplicons ranging from 100 to 1200 bp. Values of the polymorphic information content (PIC) value ranged from 0.556 to 0.895 with an average of 0.784 and diversity index (DI) value ranged from 0.621 to 0.896 with an average of 0.798. The dendrogram based on hierarchical cluster analysis using UPGMA algorithm was prepared and analyzed genotypes were grouped into two main clusters and only two genotypes could not be distinguished. Knowledge on the genetic diversity of castor can be used for future breeding programs for increased oil production for industrial uses.
Abstract: Heart sound is an acoustic signal and many techniques
used nowadays for human recognition tasks borrow speech recognition
techniques. One popular choice for feature extraction of accoustic
signals is the Mel Frequency Cepstral Coefficients (MFCC) which
maps the signal onto a non-linear Mel-Scale that mimics the human
hearing. However the Mel-Scale is almost linear in the frequency
region of heart sounds and thus should produce similar results with
the standard cepstral coefficients (CC). In this paper, MFCC is
investigated to see if it produces superior results for PCG based
human identification system compared to CC. Results show that the
MFCC system is still superior to CC despite linear filter-banks in
the lower frequency range, giving up to 95% correct recognition rate
for MFCC and 90% for CC. Further experiments show that the high
recognition rate is due to the implementation of filter-banks and not
from Mel-Scaling.
Abstract: In this paper, we design an integration security system
that provides authentication service, authorization service, and
management service of security data and a unified interface for the
management service. The interface is originated from XKMS protocol
and is used to manage security data such as XACML policies, SAML
assertions and other authentication security data including public keys.
The system includes security services such as authentication,
authorization and delegation of authentication by employing SAML
and XACML based on security data such as authentication data,
attributes information, assertions and polices managed with the
interface in the system. It also has SAML producer that issues
assertions related on the result of the authentication and the
authorization services.
Abstract: Given a simple connected unweighted undirected graph G = (V (G), E(G)) with |V (G)| = n and |E(G)| = m, we present a new algorithm for the all-pairs shortest-path (APSP) problem. The running time of our algorithm is in O(n2 log n). This bound is an improvement over previous best known O(n2.376) time bound of Raimund Seidel (1995) for general graphs. The algorithm presented does not rely on fast matrix multiplication. Our algorithm with slight modifications, enables us to compute the APSP problem for unweighted directed graph in time O(n2 log n), improving a previous best known O(n2.575) time bound of Uri Zwick (2002).
Abstract: Among neural models the Support Vector Machine
(SVM) solutions are attracting increasing attention, mostly because
they eliminate certain crucial questions involved by neural network
construction. The main drawback of standard SVM is its high
computational complexity, therefore recently a new technique, the
Least Squares SVM (LS–SVM) has been introduced. In this paper we
present an extended view of the Least Squares Support Vector
Regression (LS–SVR), which enables us to develop new
formulations and algorithms to this regression technique. Based on
manipulating the linear equation set -which embodies all information
about the regression in the learning process- some new methods are
introduced to simplify the formulations, speed up the calculations
and/or provide better results.
Abstract: This paper shows a traceability framework for supply risk monitoring, beginning with the identification, analysis, and evaluation of the supply chain risk and focusing on the supply operations of the Health Care Institutions with oncology services in Bogota, Colombia. It includes a brief presentation of the state of the art of the Supply Chain Risk Management and traceability systems in logistics operations, and it concludes with the methodology to integrate the SCRM model with the traceability system.
Abstract: Turbine blade cooling is considered as the most
effective way of maintaining high operating temperature making use
of the available materials, and turbine systems with wet compression
have a potential for future power generation because of high efficiency
and high specific power with a relatively low cost. In this paper
performance analysis of wet-compression gas turbine cycle with
turbine blade cooling is carried out. The wet compression process is
analytically modeled based on non-equilibrium droplet evaporation.
Special attention is paid for the effects of pressure ratio and water
injection ratio on the important system variables such as ratio of
coolant fluid flow, fuel consumption, thermal efficiency and specific
power. Parametric studies show that wet compression leads to
insignificant improvement in thermal efficiency but significant
enhancement of specific power in gas turbine systems with turbine
blade cooling.
Abstract: Relational databases are often used as a basis for persistent storage of ontologies to facilitate rapid operations such as search and retrieval, and to utilize the benefits of relational databases management systems such as transaction management, security and integrity control. On the other hand, there appear more and more OWL files that contain ontologies. Therefore, this paper proposes to extract ontologies from OWL files and then store them in relational databases. A prerequisite for this storing is transformation of ontologies to relational databases, which is the purpose of this paper.
Abstract: With previous studies that examined the importance
of functional store image and CSR, this study is aimed at examining
their effects in the self-congruity model in influencing store loyalty.
In particular, this study developed and tested a structural model in the
context of retailing industry on the self-congruity theory. Whilst
much of the self-congruity studies have incorporated functional store
image, there has been lack of studies that examined social
responsibility image of retail stores in the self-congruity studies.
Findings indicate that self-congruity influence on store loyalty was
mediated by both functional store image and social responsibility
image. In influencing store loyalty, the findings have shown that
social responsibility image has a stronger influence on store loyalty
than functional store image. This study offers important findings and
implications for future research as it presents a new framework on
the importance of social responsibility image.
Abstract: At present time, competition, unpredictable fluctuations have made communication engineering education in the global sphere really difficult. Confront with new situation in the engineering education sector. Communication engineering education has to be reformed and ready to use more advanced technologies. We realized that one of the general problems of student`s education is that after graduating from their universities, they are not prepared to face the real life challenges and full skilled to work in industry. They are prepared only to think like engineers and professionals but they also need to possess some others non-technical skills. In today-s environment, technical competence alone is not sufficient for career success. Employers want employees (graduate engineers) who have good oral and written communication (soft) skills. It does require for team work, business awareness, organization, management skills, responsibility, initiative, problem solving and IT competency. This proposed curriculum brings interactive, creative, interesting, effective learning methods, which includes online education, virtual labs, practical work, problem-based learning (PBL), and lectures given by industry experts. Giving short assignments, presentations, reports, research papers and projects students can significantly improve their non-technical skills. Also, we noticed the importance of using ICT technologies in engineering education which used by students and teachers, and included that into proposed teaching and learning methods. We added collaborative learning between students through team work which builds theirs skills besides course materials. The prospective on this research that we intent to update communication engineering curriculum in order to get fully constructed engineer students to ready for real industry work.
Abstract: Recently, Northeast Asia has become one of the three
largest trade areas, covering approximately 30% of the total trade
volume of the world. However, the distribution facilities are saturated
due to the increase in the transportation volume within the area and
with the European countries. In order to accommodate the increase of
the transportation volume, the transportation networking with the
major countries in Northeast Asia and Europe is absolutely necessary.
The Eurasian Logistics Network will develop into an international
passenger transportation network covering the Northeast Asian region
and an international freight transportation network connecting across
Eurasia Continent. This paper surveys the changes and trend of the
distribution network in the Eurasian Region according to the political,
economic and environmental changes of the region, analyses the
distribution network according to the changes in the transportation
policies of the related countries, and provides the direction of the
development of composite transportation on the basis of the present
conditions of transportation means. The transportation means optimal
for the efficiency of transportation system are suggested to be train
ferries, sea & rail or sea & rail & sea. It is suggested to develop
diversified composite transportation means and routes within the
boundary of international cooperation system.
Abstract: In this paper two models using a functional network
were employed to solving classification problem. Functional networks
are generalized neural networks, which permit the specification of
their initial topology using knowledge about the problem at hand. In
this case, and after analyzing the available data and their relations, we
systematically discuss a numerical analysis method used for
functional network, and apply two functional network models to
solving XOR problem. The XOR problem that cannot be solved with
two-layered neural network can be solved by two-layered functional
network, which reveals a potent computational power of functional
networks, and the performance of the proposed model was validated
using classification problems.
Abstract: This paper proposes the analysis and design of robust
fuzzy control to Stochastic Parametrics Uncertaint Linear systems.
This system type to be controlled is partitioned into several linear
sub-models, in terms of transfer function, forming a convex polytope,
similar to LPV (Linear Parameters Varying) system. Once defined the
linear sub-models of the plant, these are organized into fuzzy Takagi-
Sugeno (TS) structure. From the Parallel Distributed Compensation
(PDC) strategy, a mathematical formulation is defined in the frequency
domain, based on the gain and phase margins specifications,
to obtain robust PI sub-controllers in accordance to the Takagi-
Sugeno fuzzy model of the plant. The main results of the paper are
based on the robust stability conditions with the proposal of one
Axiom and two Theorems.
Abstract: This paper proposes an architecture of dynamically
reconfigurable arithmetic circuit. Dynamic reconfiguration is a
technique to realize required functions by changing hardware
construction during operations. The proposed circuit is based on a
complex number multiply-accumulation circuit which is used
frequently in the field of digital signal processing. In addition, the
proposed circuit performs real number double precision arithmetic
operations. The data formats are single and double precision floating
point number based on IEEE754. The proposed circuit is designed
using VHDL, and verified the correct operation by simulations and
experiments.
Abstract: Westudy a dual-channel supply chain under
decentralized setting in which manufacturer sells to retailer and to
customers directly usingan online channel. A customer chooses the
purchase-channel based on price and service quality. Also, to buy
product from the retail store, the customer incurs a transportation cost
influenced by the fluctuating gasoline cost. Both companies are under
the revenue sharing contract. In this contract the retailer share a
portion of the revenue to the manufacturer while the manufacturer
will charge the lower wholesales price. The numerical result shows
that the effects of gasoline costs, the revenue sharing ratio and the
wholesale price play an important role in determining optimal prices.
The result shows that when the gasoline price fluctuatesthe optimal
on-line priceis relatively stable while the optimal retail price moves
in the opposite direction of the gasoline prices.
Abstract: Renewable energy resources are inexhaustible, clean as compared with conventional resources. Also, it is used to supply regions with no grid, no telephone lines, and often with difficult accessibility by common transport. Satellite earth stations which located in remote areas are the most important application of renewable energy. Neural control is a branch of the general field of intelligent control, which is based on the concept of artificial intelligence. This paper presents the mathematical modeling of satellite earth station power system which is required for simulating the system.Aswan is selected to be the site under consideration because it is a rich region with solar energy. The complete power system is simulated using MATLAB–SIMULINK.An artificial neural network (ANN) based model has been developed for the optimum operation of earth station power system. An ANN is trained using a back propagation with Levenberg–Marquardt algorithm. The best validation performance is obtained for minimum mean square error. The regression between the network output and the corresponding target is equal to 96% which means a high accuracy. Neural network controller architecture gives satisfactory results with small number of neurons, hence better in terms of memory and time are required for NNC implementation. The results indicate that the proposed control unit using ANN can be successfully used for controlling the satellite earth station power system.
Abstract: This paper reports a new and accurate method for load-flow solution of radial distribution networks with minimum data preparation. The node and branch numbering need not to be sequential like other available methods. The proposed method does not need sending-node, receiving-node and branch numbers if these are sequential. The proposed method uses the simple equation to compute the voltage magnitude and has the capability to handle composite load modelling. The proposed method uses the set of nodes of feeder, lateral(s) and sub lateral(s). The effectiveness of the proposed method is compared with other methods using two examples. The detailed load-flow results for different kind of load-modellings are also presented.
Abstract: This work concerns the evolution and the maintenance
of an ontological resource in relation with the evolution of the corpus
of texts from which it had been built.
The knowledge forming a text corpus, especially in dynamic domains,
is in continuous evolution. When a change in the corpus occurs, the
domain ontology must evolve accordingly. Most methods manage
ontology evolution independently from the corpus from which it is
built; in addition, they treat evolution just as a process of knowledge
addition, not considering other knowledge changes. We propose a
methodology for managing an evolving ontology from a text corpus
that evolves over time, while preserving the consistency and the
persistence of this ontology.
Our methodology is based on the changes made on the corpus to
reflect the evolution of the considered domain - augmented surgery
in our case. In this context, the results of text mining techniques,
as well as the ARCHONTE method slightly modified, are used to
support the evolution process.