Abstract: Network Management Systems have played a great important role in information systems. Management is very important and essential in any fields. There are many managements such as configuration management, fault management, performance management, security management, accounting management and etc. Among them, configuration, fault and security management is more important than others. Because these are essential and useful in any fields. Configuration management is to monitor and maintain the whole system or LAN. Fault management is to detect and troubleshoot the system. Security management is to control the whole system. This paper intends to increase the network management functionalities including configuration management, fault management and security management. In configuration management system, this paper specially can support the USB ports and devices to detect and read devices configuration and solve to detect hardware port and software ports. In security management system, this paper can provide the security feature for the user account setting and user management and proxy server feature. And all of the history of the security such as user account and proxy server history are kept in the java standard serializable file. So the user can view the history of the security and proxy server anytime. If the user uses this system, the user can ping the clients from the network and the user can view the result of the message in fault management system. And this system also provides to check the network card and can show the NIC card setting. This system is used RMI (Remote Method Invocation) and JNI (Java Native Interface) technology. This paper is to implement the client/server network management system using Java 2 Standard Edition (J2SE). This system can provide more than 10 clients. And then this paper intends to show data or message structure of client/server and how to work using TCP/IP protocol.
Abstract: During the last years, the genomes of more and more
species have been sequenced, providing data for phylogenetic recon-
struction based on genome rearrangement measures. A main task in
all phylogenetic reconstruction algorithms is to solve the median of
three problem. Although this problem is NP-hard even for the sim-
plest distance measures, there are exact algorithms for the breakpoint
median and the reversal median that are fast enough for practical use.
In this paper, this approach is extended to the transposition median as
well as to the weighted reversal and transposition median. Although
there is no exact polynomial algorithm known even for the pairwise
distances, we will show that it is in most cases possible to solve
these problems exactly within reasonable time by using a branch and
bound algorithm.
Abstract: This paper focuses on testing database of existing
information system. At the beginning we describe the basic problems
of implemented databases, such as data redundancy, poor design of
database logical structure or inappropriate data types in columns of
database tables. These problems are often the result of incorrect
understanding of the primary requirements for a database of an
information system. Then we propose an algorithm to compare the
conceptual model created from vague requirements for a database
with a conceptual model reconstructed from implemented database.
An algorithm also suggests steps leading to optimization of
implemented database. The proposed algorithm is verified by an
implemented prototype. The paper also describes a fuzzy system
which works with the vague requirements for a database of an
information system, procedure for creating conceptual from vague
requirements and an algorithm for reconstructing a conceptual model
from implemented database.
Abstract: Saudi Arabia in recent years has seen drastic increase
in traffic related crashes. With population of over 29 million, Saudi
Arabia is considered as a fast growing and emerging economy. The
rapid population increase and economic growth has resulted in rapid
expansion of transportation infrastructure, which has led to increase
in road crashes. Saudi Ministry of Interior reported more than 7,000
people killed and 68,000 injured in 2011 ranking Saudi Arabia to be
one of the worst worldwide in traffic safety. The traffic safety issues
in the country also result in distress to road users and cause and
economic loss exceeding 3.7 billion Euros annually. Keeping this in
view, the researchers in Saudi Arabia are investigating ways to
improve traffic safety conditions in the country. This paper presents a
multilevel approach to collect traffic safety related data required to do
traffic safety studies in the region. Two highway corridors including
King Fahd Highway 39 kilometre and Gulf Cooperation Council
Highway 42 kilometre long connecting the cities of Dammam and
Khobar were selected as a study area. Traffic data collected included
traffic counts, crash data, travel time data, and speed data. The
collected data was analysed using geographic information system to
evaluate any correlation. Further research is needed to investigate the
effectiveness of traffic safety related data when collected in a
concerted effort.
Abstract: Based on assumptions of neo-classical economics and
rational choice / public choice theory, this paper investigates the
regulation of industrial land use in Taiwan by homeowners
associations (HOAs) as opposed to traditional government
administration. The comparison, which applies the transaction cost
theory and a polynomial regression analysis, manifested that HOAs
are superior to conventional government administration in terms of
transaction costs and overall efficiency. A case study that compares
Taiwan-s commonhold industrial park, NangKang Software Park, to
traditional government counterparts using limited data on the costs
and returns was analyzed. This empirical study on the relative
efficiency of governmental and private institutions justified the
important theoretical proposition. Numerical results prove the
efficiency of the established model.
Abstract: This research explores the links between physical
development and transportation infrastructure around Kumasi,
Ghana. It utilizes census data as well as fieldwork and interviews
carried out during July and December 2005. The results suggest that
there is a weak association between transportation investments and
physical development, and that recent housing has generally occurred
in poorly accessible locations. Road investments have generally
followed physical expansion rather than the reverse. Hence policies
designed to manage the fast growth now occurring around Ghanaian
cities should not focus exclusively on improving transportation
infrastructure but also strengthening the underlying the traditional
land management structures and the official land administrative
institutions that operate within those structures.
Abstract: The benefits of rooftop greenery systems (such as
energy savings, reduction of greenhouse gas emission for mitigating
climate change and maintaining sustainable development, indoor
temperature control etc.) in buildings are well recognized, however
there remains very little research conducted for quantifying the
benefits in subtropical climates such as in Australia. This study
mainly focuses on measuring/determining temperature profile and air
conditioning energy savings by implementing rooftop greenery
systems in subtropical Central Queensland in Australia. An
experimental set-up was installed at Rockhampton campus of Central
Queensland University, where two standard shipping containers (6m
x 2.4m x 2.4m) were converted into small offices, one with green
roof and one without. These were used for temperature, humidity and
energy consumption data collection. The study found that an energy
savings of up to 11.70% and temperature difference of up to 4°C can
be achieved in March in subtropical Central Queensland climate in
Australia. It is expected that more energy can be saved in peak
summer days (December/February) as temperature difference
between green roof and non-green roof is higher in December-
February.
Abstract: Recently, in some places, optical-fibre access
networks have been used with GPON technology belonging to
organizations (in most cases public bodies) that act as neutral
operators. These operators simultaneously provide network services
to various telecommunications operators that offer integrated voice,
data and television services. This situation creates new problems
related to quality of service, since the interests of the users are
intermingled with the interests of the operators. In this paper, we
analyse this problem and consider solutions that make it possible to
provide guaranteed quality of service for voice over IP, data services
and interactive digital television.
Abstract: This paper aims at identifying and analyzing the
knowledge transmission channels in textile and clothing clusters
located in Brazil and in Europe. Primary data was obtained through
interviews with key individuals. The collection of primary data was
carried out based on a questionnaire with ten categories of indicators
of knowledge transmission. Secondary data was also collected
through a literature review and through international organizations
sites. Similarities related to the use of the main transmission channels
of knowledge are observed in all cases. The main similarities are:
influence of suppliers of machinery, equipment and raw materials;
imitation of products and best practices; training promoted by
technical institutions and businesses; and cluster companies being
open to acquire new knowledge. The main differences lie in the
relationship between companies, where in Europe the intensity of this
relationship is bigger when compared to Brazil. The differences also
occur in importance and frequency of the relationship with the
government, with the cultural environment, and with the activities of
research and development. It is also found factors that reduce the
importance of geographical proximity in transmission of knowledge,
and in generating trust and the establishment of collaborative
behavior.
Abstract: This paper includes a review of three physics simulation packages that can be used to provide researchers with a virtual ground for modeling, implementing and simulating complex models, as well as testing their control methods with less cost and time of development. The inverted pendulum model was used as a test bed for comparing ODE, DANCE and Webots, while Linear State Feedback was used to control its behavior. The packages were compared with respect to model creation, solving systems of differential equation, data storage, setting system variables, control the experiment and ease of use. The purpose of this paper is to give an overview about our experience with these environments and to demonstrate some of the benefits and drawbacks involved in practice for each package.
Abstract: The ElectroEncephaloGram (EEG) is useful for
clinical diagnosis and biomedical research. EEG signals often
contain strong ElectroOculoGram (EOG) artifacts produced
by eye movements and eye blinks especially in EEG recorded
from frontal channels. These artifacts obscure the underlying
brain activity, making its visual or automated inspection
difficult. The goal of ocular artifact removal is to remove
ocular artifacts from the recorded EEG, leaving the underlying
background signals due to brain activity. In recent times,
Independent Component Analysis (ICA) algorithms have
demonstrated superior potential in obtaining the least
dependent source components. In this paper, the independent
components are obtained by using the JADE algorithm (best
separating algorithm) and are classified into either artifact
component or neural component. Neural Network is used for
the classification of the obtained independent components.
Neural Network requires input features that exactly represent
the true character of the input signals so that the neural
network could classify the signals based on those key
characters that differentiate between various signals. In this
work, Auto Regressive (AR) coefficients are used as the input
features for classification. Two neural network approaches
are used to learn classification rules from EEG data. First, a
Polynomial Neural Network (PNN) trained by GMDH (Group
Method of Data Handling) algorithm is used and secondly,
feed-forward neural network classifier trained by a standard
back-propagation algorithm is used for classification and the
results show that JADE-FNN performs better than JADEPNN.
Abstract: This study aimed at developing visualization tools for integrating CloudSat images and Water Vapor Satellite images. KML was used for integrating data from CloudSat Satellite and GMS-6 Water Vapor Satellite. CloudSat 2D images were transformed into 3D polygons in order to achieve 3D images. Before overlaying the images on Google Earth, GMS-6 water vapor satellite images had to be rescaled into linear images. Web service was developed using webMathematica. Shoreline from GMS-6 images was compared with shoreline from LandSat images on Google Earth for evaluation. The results showed that shoreline from GMS-6 images was highly matched with the shoreline in LandSat images from Google Earth. For CloudSat images, the visualizations were compared with GMS-6 images on Google Earth. The results showed that CloudSat and GMS-6 images were highly correlated.
Abstract: The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.
Abstract: The paper proposes a new concept in developing
collaborative design system. The concept framework involves
applying simulation of supply chain management to collaborative
design called – 'SCM–Based Design Tool'. The system is developed
particularly to support design activities and to integrate all facilities
together. The system is aimed to increase design productivity and
creativity. Therefore, designers and customers can collaborate by the
system since conceptual design. JAG: Jewelry Art Generator based
on artificial intelligence techniques is integrated into the system.
Moreover, the proposed system can support users as decision tool
and data propagation. The system covers since raw material supply
until product delivery. Data management and sharing information are
visually supported to designers and customers via user interface. The
system is developed on Web–assisted product development
environment. The prototype system is presented for Thai jewelry
industry as a system prototype demonstration, but applicable for
other industry.
Abstract: In this paper, we present user pattern learning
algorithm based MDSS (Medical Decision support system) under
ubiquitous. Most of researches are focus on hardware system, hospital
management and whole concept of ubiquitous environment even
though it is hard to implement. Our objective of this paper is to design
a MDSS framework. It helps to patient for medical treatment and
prevention of the high risk patient (COPD, heart disease, Diabetes).
This framework consist database, CAD (Computer Aided diagnosis
support system) and CAP (computer aided user vital sign prediction
system). It can be applied to develop user pattern learning algorithm
based MDSS for homecare and silver town service. Especially this
CAD has wise decision making competency. It compares current vital
sign with user-s normal condition pattern data. In addition, the CAP
computes user vital sign prediction using past data of the patient. The
novel approach is using neural network method, wireless vital sign
acquisition devices and personal computer DB system. An intelligent
agent based MDSS will help elder people and high risk patients to
prevent sudden death and disease, the physician to get the online
access to patients- data, the plan of medication service priority (e.g.
emergency case).
Abstract: The modern telecommunication industry demands
higher capacity networks with high data rate. Orthogonal frequency
division multiplexing (OFDM) is a promising technique for high data
rate wireless communications at reasonable complexity in wireless
channels. OFDM has been adopted for many types of wireless
systems like wireless local area networks such as IEEE 802.11a, and
digital audio/video broadcasting (DAB/DVB). The proposed research
focuses on a concatenated coding scheme that improve the
performance of OFDM based wireless communications. It uses a
Redundant Residue Number System (RRNS) code as the outer code
and a convolutional code as the inner code. Here, a direct conversion
of analog signal to residue domain is done to reduce the conversion
complexity using sigma-delta based parallel analog-to-residue
converter. The bit error rate (BER) performances of the proposed
system under different channel conditions are investigated. These
include the effect of additive white Gaussian noise (AWGN),
multipath delay spread, peak power clipping and frame start
synchronization error. The simulation results show that the proposed
RRNS-Convolutional concatenated coding (RCCC) scheme provides
significant improvement in the system performance by exploiting the
inherent properties of RRNS.
Abstract: This study was investigated on sampling and
analyzing water quality in water reservoir & water tower installed in
two kind of residential buildings and school facilities. Data of water
quality was collected for correlation analysis with frequency of
sanitization of water reservoir through questioning managers of
building about the inspection charts recorded on equipment for water
reservoir. Statistical software packages (SPSS) were applied to the
data of two groups (cleaning frequency and water quality) for
regression analysis to determine the optimal cleaning frequency of
sanitization. The correlation coefficient (R) in this paper represented
the degree of correlation, with values of R ranging from +1 to -1.After
investigating three categories of drinking water users; this study found
that the frequency of sanitization of water reservoir significantly
influenced the water quality of drinking water. A higher frequency of
sanitization (more than four times per 1 year) implied a higher quality
of drinking water. Results indicated that sanitizing water reservoir &
water tower should at least twice annually for achieving the aim of
safety of drinking water.
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Abstract: We have measured the pressure drop and convective
heat transfer coefficient of water – based AL(25nm),AL2O3(30nm)
and CuO(50nm) Nanofluids flowing through a uniform heated
circular tube in the fully developed laminar flow regime. The
experimental results show that the data for Nanofluids friction factor
show a good agreement with analytical prediction from the Darcy's
equation for single-phase flow. After reducing the experimental
results to the form of Reynolds, Rayleigh and Nusselt numbers. The
results show the local Nusselt number and temperature have
distribution with the non-dimensional axial distance from the tube
entry. Study decided that thenNanofluid as Newtonian fluids through
the design of the linear relationship between shear stress and the rate
of stress has been the study of three chains of the Nanofluid with
different concentrations and where the AL, AL2O3 and CuO – water
ranging from (0.25 - 2.5 vol %). In addition to measuring the four
properties of the Nanofluid in practice so as to ensure the validity of
equations of properties developed by the researchers in this area and
these properties is viscosity, specific heat, and density and found that
the difference does not exceed 3.5% for the experimental equations
between them and the practical. The study also demonstrated that the
amount of the increase in heat transfer coefficient for three types of
Nano fluid is AL, AL2O3, and CuO – Water and these ratios are
respectively (45%, 32%, 25%) with insulation and without insulation
(36%, 23%, 19%), and the statement of any of the cases the best
increase in heat transfer has been proven that using insulation is
better than not using it. I have been using three types of Nano
particles and one metallic Nanoparticle and two oxide Nanoparticle
and a statement, whichever gives the best increase in heat transfer.
Abstract: One of the main advantages of the LO paradigm is to
allow the availability of good quality, shareable learning material
through the Web. The effectiveness of the retrieval process requires a
formal description of the resources (metadata) that closely fits the
user-s search criteria; in spite of the huge international efforts in this
field, educational metadata schemata often fail to fulfil this
requirement. This work aims to improve the situation, by the
definition of a metadata model capturing specific didactic features of
shareable learning resources. It classifies LOs into “teacher-oriented"
and “student-oriented" categories, in order to describe the role a LO
is to play when it is integrated into the educational process. This
article describes the model and a first experimental validation process
that has been carried out in a controlled environment.