Abstract: When binary decision diagrams are formed from
uniformly distributed Monte Carlo data for a large number of
variables, the complexity of the decision diagrams exhibits a
predictable relationship to the number of variables and minterms. In
the present work, a neural network model has been used to analyze the
pattern of shortest path length for larger number of Monte Carlo data
points. The neural model shows a strong descriptive power for the
ISCAS benchmark data with an RMS error of 0.102 for the shortest
path length complexity. Therefore, the model can be considered as a
method of predicting path length complexities; this is expected to lead
to minimum time complexity of very large-scale integrated circuitries
and related computer-aided design tools that use binary decision
diagrams.
Abstract: Phylogenies ; The evolutionary histories of groups of
species are one of the most widely used tools throughout the life
sciences, as well as objects of research with in systematic,
evolutionary biology. In every phylogenetic analysis reconstruction
produces trees. These trees represent the evolutionary histories of
many groups of organisms, bacteria due to horizontal gene transfer
and plants due to process of hybridization. The process of gene
transfer in bacteria and hybridization in plants lead to reticulate
networks, therefore, the methods of constructing trees fail in
constructing reticulate networks. In this paper a model has been
employed to reconstruct phylogenetic network in honey bee. This
network represents reticulate evolution in honey bee. The maximum
parsimony approach has been used to obtain this reticulate network.
Abstract: User-Centered Design (UCD), Usability Engineering (UE) and Participatory Design (PD) are the common Human- Computer Interaction (HCI) approaches that are practiced in the software development process, focusing towards issues and matters concerning user involvement. It overlooks the organizational perspective of HCI integration within the software development organization. The Management Information Systems (MIS) perspective of HCI takes a managerial and organizational context to view the effectiveness of integrating HCI in the software development process. The Human-Centered Design (HCD) which encompasses all of the human aspects including aesthetic and ergonomic, is claimed as to provide a better approach in strengthening the HCI approaches to strengthen the software development process. In determining the effectiveness of HCD in the software development process, this paper presents the findings of a content analysis of HCI approaches by viewing those approaches as a technology which integrates user requirements, ranging from the top management to other stake holder in the software development process. The findings obtained show that HCD approach is a technology that emphasizes on human, tools and knowledge in strengthening the HCI approaches to strengthen the software development process in the quest to produce a sustainable, usable and useful software product.
Abstract: Recently, the RFID (Radio Frequency
Identification) technology attracts the world market attention as
essential technology for ubiquitous environment. The RFID
market has focused on transponders and reader development.
But that concern has shifted to RFID software like as
high-valued e-business applications, RFID middleware and
related development tools. However, due to the high sensitivity
of data and service transaction within the RFID network,
security consideration must be addressed. In order to guarantee
trusted e-business based on RFID technology, we propose a
security enhanced RFID middleware system. Our proposal is
compliant with EPCglobal ALE (Application Level Events),
which is standard interface for middleware and its clients. We
show how to provide strengthened security and trust by
protecting transported data between middleware and its client,
and stored data in middleware. Moreover, we achieve the
identification and service access control against illegal service
abuse. Our system enables secure RFID middleware service
and trusted e-business service.
Abstract: The number of intrusions and attacks against critical
infrastructures and other information networks is increasing rapidly.
While there is no identified evidence that terrorist organizations are
currently planning a coordinated attack against the vulnerabilities of
computer systems and network connected to critical infrastructure,
and origins of the indiscriminate cyber attacks that infect computers
on network remain largely unknown. The growing trend toward the
use of more automated and menacing attack tools has also
overwhelmed some of the current methodologies used for tracking
cyber attacks. There is an ample possibility that this kind of cyber
attacks can be transform to cyberterrorism caused by illegal purposes.
Cyberterrorism is a matter of vital importance to national welfare.
Therefore, each countries and organizations have to take a proper
measure to meet the situation and consider effective legislation about
cyberterrorism.
Abstract: This paper describes a segmentation algorithm based
on the cooperation of an optical flow estimation method with edge
detection and region growing procedures.
The proposed method has been developed as a pre-processing
stage to be used in methodologies and tools for video/image indexing
and retrieval by content. The addressed problem consists in
extracting whole objects from background for producing images of
single complete objects from videos or photos. The extracted images
are used for calculating the object visual features necessary for both
indexing and retrieval processes.
The first task of the algorithm exploits the cues from motion
analysis for moving area detection. Objects and background are then
refined using respectively edge detection and region growing
procedures. These tasks are iteratively performed until objects and
background are completely resolved.
The developed method has been applied to a variety of indoor and
outdoor scenes where objects of different type and shape are
represented on variously textured background.
Abstract: Nowadays, computer worms, viruses and Trojan horse
become popular, and they are collectively called malware. Those
malware just spoiled computers by deleting or rewriting important
files a decade ago. However, recent malware seems to be born to earn
money. Some of malware work for collecting personal information so
that malicious people can find secret information such as password for
online banking, evidence for a scandal or contact address which relates
with the target. Moreover, relation between money and malware
becomes more complex. Many kinds of malware bear bots to get
springboards. Meanwhile, for ordinary internet users,
countermeasures against malware come up against a blank wall.
Pattern matching becomes too much waste of computer resources,
since matching tools have to deal with a lot of patterns derived from
subspecies. Virus making tools can automatically bear subspecies of
malware. Moreover, metamorphic and polymorphic malware are no
longer special. Recently there appears malware checking sites that
check contents in place of users' PC. However, there appears a new
type of malicious sites that avoids check by malware checking sites. In
this paper, existing protocols and methods related with the web are
reconsidered in terms of protection from current attacks, and new
protocol and method are indicated for the purpose of security of the
web.
Abstract: The vast amount of information on the World Wide
Web is created and published by many different types of providers.
Unlike books and journals, most of this information is not subject to
editing or peer review by experts. This lack of quality control and the
explosion of web sites make the task of finding quality information
on the web especially critical. Meanwhile new facilities for
producing web pages such as Blogs make this issue more significant
because Blogs have simple content management tools enabling nonexperts
to build easily updatable web diaries or online journals. On
the other hand despite a decade of active research in information
quality (IQ) there is no framework for measuring information quality
on the Blogs yet. This paper presents a novel experimental
framework for ranking quality of information on the Weblog. The
results of data analysis revealed seven IQ dimensions for the Weblog.
For each dimension, variables and related coefficients were
calculated so that presented framework is able to assess IQ of
Weblogs automatically.
Abstract: This research paper is based upon the simulation of
gradient of mathematical functions and scalar fields using MATLAB.
Scalar fields, their gradient, contours and mesh/surfaces are
simulated using different related MATLAB tools and commands for
convenient presentation and understanding. Different mathematical
functions and scalar fields are examined here by taking their
gradient, visualizing results in 3D with different color shadings and
using other necessary relevant commands. In this way the outputs of
required functions help us to analyze and understand in a better way
as compared to just theoretical study of gradient.
Abstract: Petri Net being one of the most useful graphical tools for modelling complex asynchronous systems, we have used Petri Net to model multi-track railway level crossing system. The roadway has been augmented with four half-size barriers. For better control, a three stage control mechanism has been introduced to ensure that no road-vehicle is trapped on the level crossing. Timed Petri Net is used to include the temporal nature of the signalling system. Safeness analysis has also been included in the discussion section.
Abstract: It has become crucial over the years for nations to
improve their credit scoring methods and techniques in light of the
increasing volatility of the global economy. Statistical methods or
tools have been the favoured means for this; however artificial
intelligence or soft computing based techniques are becoming
increasingly preferred due to their proficient and precise nature and
relative simplicity. This work presents a comparison between Support
Vector Machines and Artificial Neural Networks two popular soft
computing models when applied to credit scoring. Amidst the
different criteria-s that can be used for comparisons; accuracy,
computational complexity and processing times are the selected
criteria used to evaluate both models. Furthermore the German credit
scoring dataset which is a real world dataset is used to train and test
both developed models. Experimental results obtained from our study
suggest that although both soft computing models could be used with
a high degree of accuracy, Artificial Neural Networks deliver better
results than Support Vector Machines.
Abstract: Environmental micro-organisms include a large number of taxa and some species that are generally considered nonpathogenic, but can represent a risk in certain conditions, especially for elderly people and immunocompromised individuals. Chemotaxonomic identification techniques are powerful tools for environmental micro-organisms, and cellular fatty acid methyl esters (FAME) content is a powerful fingerprinting identification technique. A system based on an unsupervised artificial neural network (ANN) was set up using the fatty acid profiles of standard bacterial strains, obtained by gas-chromatography, used as learning data. We analysed 45 certified strains belonging to Acinetobacter, Aeromonas, Alcaligenes, Aquaspirillum, Arthrobacter, Bacillus, Brevundimonas, Enterobacter, Flavobacterium, Micrococcus, Pseudomonas, Serratia, Shewanella and Vibrio genera. A set of 79 bacteria isolated from a drinking water line (AMGA, the major water supply system in Genoa) were used as an example for identification compared to standard MIDI method. The resulting ANN output map was found to be a very powerful tool to identify these fresh isolates.
Abstract: Pipeline infrastructures normally represent high cost of investment and the pipeline must be free from risks that could cause environmental hazard and potential threats to personnel safety. Pipeline integrity such monitoring and management become very crucial to provide unimpeded transportation and avoiding unnecessary production deferment. Thus proper cleaning and inspection is the key to safe and reliable pipeline operation and plays an important role in pipeline integrity management program and has become a standard industry procedure. In view of this, understanding the motion (dynamic behavior), prediction and control of the PIG speed is important in executing pigging operation as it offers significant benefits, such as estimating PIG arrival time at receiving station, planning for suitable pigging operation, and improves efficiency of pigging tasks. The objective of this paper is to review recent developments in speed control system of pipeline PIGs. The review carried out would serve as an industrial application in a form of quick reference of recent developments in pipeline PIG speed control system, and further initiate others to add-in/update the list in the future leading to knowledge based data, and would attract active interest of others to share their view points.
Abstract: Within the realm of e-government, the development has moved towards testing new means for democratic decisionmaking, like e-panels, electronic discussion forums, and polls. Although such new developments seem promising, they are not problem-free, and the outcomes are seldom used in the subsequent formal political procedures. Nevertheless, process models offer promising potential when it comes to structuring and supporting transparency of decision processes in order to facilitate the integration of the public into decision-making procedures in a reasonable and manageable way. Based on real-life cases of urban planning processes in Sweden, we present an outline for an integrated framework for public decision making to: a) provide tools for citizens to organize discussion and create opinions; b) enable governments, authorities, and institutions to better analyse these opinions; and c) enable governments to account for this information in planning and societal decision making by employing a process model for structured public decision making.
Abstract: This paper is focused on issues of nonlinear dynamic process modeling and model-based predictive control of a fed-batch sugar crystallization process applying the concept of artificial neural networks as computational tools. The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. A feed forward neural network (FFNN) model of the process is first built as part of the controller structure to predict the process response over a specified (prediction) horizon. The predictions are supplied to an optimization procedure to determine the values of the control action over a specified (control) horizon that minimizes a predefined performance index. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. However, the simulation results demonstrated smooth behavior of the control actions and satisfactory reference tracking.
Abstract: The evolution of current modeling specifications gives rise to the problem of generating automated test cases from a variety of application tools. Past endeavours on behavioural testing of UML statecharts have not systematically leveraged the potential of existing graph theory for testing of objects. Therefore there exists a need for a simple, tool-independent, and effective method for automatic test generation. An architecture, codenamed ACUTE-J (Automated stateChart Unit Testing Engine for Java), for automating the unit test generation process is presented. A sequential approach for converting UML statechart diagrams to JUnit test classes is described, with the application of existing graph theory. Research byproducts such as a universal XML Schema and API for statechart-driven testing are also proposed. The result from a Java implementation of ACUTE-J is discussed in brief. The Chinese Postman algorithm is utilised as an illustration for a run-through of the ACUTE-J architecture.
Abstract: In the micro and nano-technology industry, the
«clean-rooms» dedicated to manufacturing chip, are equipped with
the most sophisticated equipment-tools. There use a large number of
resources in according to strict specifications for an optimum
working and result. The distribution of «utilities» to the production is
assured by teams who use a supervision tool.
The studies show the interest to control the various parameters of
production or/and distribution, in real time, through a reliable and
effective supervision tool. This document looks at a large part of the
functions that the supervisor must assure, with complementary
functionalities to help the diagnosis and simulation that prove very
useful in our case where the supervised installations are complexed
and in constant evolution.
Abstract: Real-time measurement of applied forces, like tension, compression, torsion, and bending moment, identifies the transferred energies being applied to the bottomhole assembly (BHA). These forces are highly detrimental to measurement/logging-while-drilling tools and downhole equipment. Real-time measurement of the dynamic downhole behavior, including weight, torque, bending on bit, and vibration, establishes a real-time feedback loop between the downhole drilling system and drilling team at the surface. This paper describes the numerical analysis of the strain data acquired by the measurement tool at different locations on the strain pockets. The strain values obtained by FEA for various loading conditions (tension, compression, torque, and bending moment) are compared against experimental results obtained from an identical experimental setup. Numerical analyses results agree with experimental data within 8% and, therefore, substantiate and validate the FEA model. This FEA model can be used to analyze the combined loading conditions that reflect the actual drilling environment.
Abstract: The emerging Semantic Web has been attracted many
researchers and developers. New applications have been developed on top of Semantic Web and many supporting tools introduced to improve its software development process. Metadata modeling is one of development process where supporting tools exists. The existing
tools are lack of readability and easiness for a domain knowledge expert to graphically models a problem in semantic model. In this paper, a metadata modeling tool called RDFGraph is proposed. This
tool is meant to solve those problems. RDFGraph is also designed to work with modern database management systems that support RDF and to improve the performance of the query execution process. The
testing result shows that the rules used in RDFGraph follows the W3C standard and the graphical model produced in this tool is properly translated and correct.
Abstract: Today Environmental Impact Assessment (EIA) is known as one of the most important tools for decision makers in the construction of civil and industrial projects towards sustainable development. In the past, projects were evaluated based on cost and benefit analysis regardless of the physical and biological environmental effects and its socio-economical impacts. According to the Department of Environment (DOE) of Iran's regulations, the construction of hydroelectric dams is an activity that requires an EIA report. In this paper the environmental impact assessment of the Gotvand hydro-electrical dam has been evaluated in the three environment elements, biological, Physical-chemical and cultural units. This dam is one of the largest dams in Iran with a volume of 4500 MCM and is going to be the last dam on the Karoon River in the south of Iran. In this paper the ICOLD (International Commission on Large Dams) technique was employed for the environmental impact assessment of the dam. The research includes all socio economical and environmental effects of the dam during the construction and operation of the hydro electric dam and Environmental management, monitoring and mitigation of negative impacts were analyzed. In this project the results led to using some techniques to protect the destructive impacts on biological aspects beside the effective long time period impacts on the biological aspects. The impacts on physical aspects are temporary and negative commonly that could be restored and rehabilitated in natural process in the long time in operation period.