Abstract: General requirements for knowledge representation in
the form of logic rules, applicable to design and control of industrial
processes, are formulated. Characteristic behavior of decision trees
(DTs) and rough sets theory (RST) in rules extraction from recorded
data is discussed and illustrated with simple examples. The
significance of the models- drawbacks was evaluated, using
simulated and industrial data sets. It is concluded that performance of
DTs may be considerably poorer in several important aspects,
compared to RST, particularly when not only a characterization of a
problem is required, but also detailed and precise rules are needed,
according to actual, specific problems to be solved.
Abstract: Mobile IP has been developed to provide the
continuous information network access to mobile users. In IP-based
mobile networks, location management is an important component of
mobility management. This management enables the system to track
the location of mobile node between consecutive communications. It
includes two important tasks- location update and call delivery.
Location update is associated with signaling load. Frequent updates
lead to degradation in the overall performance of the network and the
underutilization of the resources. It is, therefore, required to devise
the mechanism to minimize the update rate. Mobile IPv6 (MIPv6)
and Hierarchical MIPv6 (HMIPv6) have been the potential
candidates for deployments in mobile IP networks for mobility
management. HMIPv6 through studies has been shown with better
performance as compared to MIPv6. It reduces the signaling
overhead traffic by making registration process local. In this paper,
we present performance analysis of MIPv6 and HMIPv6 using an
analytical model. Location update cost function is formulated based
on fluid flow mobility model. The impact of cell residence time, cell
residence probability and user-s mobility is investigated. Numerical
results are obtained and presented in graphical form. It is shown that
HMIPv6 outperforms MIPv6 for high mobility users only and for low
mobility users; performance of both the schemes is almost equivalent
to each other.
Abstract: Recently, X. Ge and J. Qian investigated some relations between higher mathematics scores and calculus scores (resp. linear algebra scores, probability statistics scores) for Chinese university students. Based on rough-set theory, they established an information system S = (U,CuD,V, f). In this information system, higher mathematics score was taken as a decision attribute and calculus score, linear algebra score, probability statistics score were taken as condition attributes. They investigated importance of each condition attribute with respective to decision attribute and strength of each condition attribute supporting decision attribute. In this paper, we give further investigations for this issue. Based on the above information system S = (U, CU D, V, f), we analyze the decision rules between condition and decision granules. For each x E U, we obtain support (resp. strength, certainty factor, coverage factor) of the decision rule C —>x D, where C —>x D is the decision rule induced by x in S = (U, CU D, V, f). Results of this paper gives new analysis of on higher mathematics scores for Chinese university students, which can further lead Chinese university students to raise higher mathematics scores in Chinese graduate student entrance examination.
Abstract: Road transportation system is the most important
method of transporting the goods. Considering the most suitable
geographical situation of Iran to transport the goods between Europe
and Asia and placement of this country in direction of international
corridors (east- west) , (north-south) and Asian land transport to
infrastructure development “A.L.T.I.D" and Transport corridor
Europe - Caucasus - Asia “T.R.A.C.E.C.A", noticing the security of
road transportation system in this country is so important. In this
paper the main factors of accidents on the roads of Iran are
categorized regarding the rate of accidents occurred. Then apart from
studying the main reasons of accidents of every category, the main
factors of these events are studied and its strategies in Iran are
introduced.
Abstract: Concept maps can be generated manually or
automatically. It is important to recognize differences of the two
types of concept maps. The automatically generated concept maps
are dynamic, interactive, and full of associations between the terms
on the maps and the underlying documents. Through a specific
concept mapping system, Visual Concept Explorer (VCE), this paper
discusses how automatically generated concept maps are different
from manually generated concept maps and how different
applications and learning opportunities might be created with the
automatically generated concept maps. The paper presents several
examples of learning strategies that take advantages of the
automatically generated concept maps for concept learning and
exploration.
Abstract: Long term rainfall analysis and prediction is a
challenging task especially in the modern world where the impact of
global warming is creating complications in environmental issues.
These factors which are data intensive require high performance
computational modeling for accurate prediction. This research paper
describes a prototype which is designed and developed on grid
environment using a number of coupled software infrastructural
building blocks. This grid enabled system provides the demanding
computational power, efficiency, resources, user-friendly interface,
secured job submission and high throughput. The results obtained
using sequential execution and grid enabled execution shows that
computational performance has enhanced among 36% to 75%, for
decade of climate parameters. Large variation in performance can be
attributed to varying degree of computational resources available for
job execution.
Grid Computing enables the dynamic runtime selection, sharing
and aggregation of distributed and autonomous resources which plays
an important role not only in business, but also in scientific
implications and social surroundings. This research paper attempts to
explore the grid enabled computing capabilities on weather indices
from HOAPS data for climate impact modeling and change
detection.
Abstract: In ad hoc networks, the main issue about designing of protocols is quality of service, so that in wireless sensor networks the main constraint in designing protocols is limited energy of sensors. In fact, protocols which minimize the power consumption in sensors are more considered in wireless sensor networks. One approach of reducing energy consumption in wireless sensor networks is to reduce the number of packages that are transmitted in network. The technique of collecting data that combines related data and prevent transmission of additional packages in network can be effective in the reducing of transmitted packages- number. According to this fact that information processing consumes less power than information transmitting, Data Aggregation has great importance and because of this fact this technique is used in many protocols [5]. One of the Data Aggregation techniques is to use Data Aggregation tree. But finding one optimum Data Aggregation tree to collect data in networks with one sink is a NP-hard problem. In the Data Aggregation technique, related information packages are combined in intermediate nodes and form one package. So the number of packages which are transmitted in network reduces and therefore, less energy will be consumed that at last results in improvement of longevity of network. Heuristic methods are used in order to solve the NP-hard problem that one of these optimization methods is to solve Simulated Annealing problems. In this article, we will propose new method in order to build data collection tree in wireless sensor networks by using Simulated Annealing algorithm and we will evaluate its efficiency whit Genetic Algorithm.
Abstract: Nevertheless the widespread application of finite
mixture models in segmentation, finite mixture model selection is
still an important issue. In fact, the selection of an adequate number
of segments is a key issue in deriving latent segments structures and
it is desirable that the selection criteria used for this end are effective.
In order to select among several information criteria, which may
support the selection of the correct number of segments we conduct a
simulation study. In particular, this study is intended to determine
which information criteria are more appropriate for mixture model
selection when considering data sets with only categorical
segmentation base variables. The generation of mixtures of
multinomial data supports the proposed analysis. As a result, we
establish a relationship between the level of measurement of
segmentation variables and some (eleven) information criteria-s
performance. The criterion AIC3 shows better performance (it
indicates the correct number of the simulated segments- structure
more often) when referring to mixtures of multinomial segmentation
base variables.
Abstract: This paper present the harmonic elimination of hybrid
multilevel inverters (HMI) which could be increase the number of
output voltage level. Total Harmonic Distortion (THD) is one of the
most important requirements concerning performance indices.
Because of many numbers output levels of HMI, it had numerous
unknown variables of eliminate undesired individual harmonic and
THD nonlinear equations set. Optimized harmonic stepped waveform
(OHSW) is solving switching angles conventional method, but most
complicated for solving as added level. The artificial intelligent
techniques are deliberation to solve this problem. This paper presents
the Particle Swarm Optimization (PSO) technique for solving
switching angles to get minimum THD and eliminate undesired
individual harmonics of 15-levels hybrid multilevel inverters.
Consequently it had many variables and could eliminate numerous
harmonics. Both advantages including high level of inverter and
Particle Swarm Optimization (PSO) are used as powerful tools for
harmonics elimination.
Abstract: Urban disaster risks and vulnerabilities are great problems for Turkey. The annual loss of life and property through disaster in the world-s major metropolitan areas is increasing. Urban concentrations of the poor and less-informed in environmentally fragile locations suffer the impact of disaster disproportionately. Gecekondu (squatter) developments will compound the inherent risks associated with high-density environments, in appropriate technologies, and inadequate infrastructure. On the other hand, there are many geological disadvantages such as sitting on top of active tectonic plate boundaries, and why having avalanche, flood, and landslide and drought prone areas in Turkey. However, this natural formation is inevitable; the only way to survive in such a harsh geography is to be aware of importance of these natural events and to take political and physical measures. The main aim of this research is to bring up the magnitude of natural hazard risks in Izmir built-up zone, not being taken into consideration adequately. Because the dimensions of the peril are not taken seriously enough, the natural hazard risks, which are commonly well known, are not considered important or they are being forgotten after some time passes. Within this research, the magnitude of natural hazard risks for Izmir is being presented in the scope of concrete and local researches over Izmir risky areas.
Abstract: Nigerian bread is baked with vitamin A fortified wheat flour. Study aimed at determining its contribution to preschoolers- vitamin A nutriture. A cross-sectional/experimental study was carried out in four poor-urban Local Government Areas (LGAs) of Metropolitan Lagos, Nigeria. A pretested food frequency questionnaire was administered to randomly selected mothers of 1600 preschoolers (24-59 months). Retinyl Palmitate content of fourteen bread samples randomly collected from bakeries in all LGAs was analyzed at 0 and 5 days at 25oC using High Performance Liquid Chromatography. Data analysis was done at p
Abstract: Traffic Engineering (TE) is the process of controlling
how traffic flows through a network in order to facilitate efficient and
reliable network operations while simultaneously optimizing network
resource utilization and traffic performance. TE improves the
management of data traffic within a network and provides the better
utilization of network resources. Many research works considers intra
and inter Traffic Engineering separately. But in reality one influences
the other. Hence the effective network performances of both inter and
intra Autonomous Systems (AS) are not optimized properly. To
achieve a better Joint Optimization of both Intra and Inter AS TE, we
propose a joint Optimization technique by considering intra-AS
features during inter – AS TE and vice versa. This work considers the
important criterion say latency within an AS and between ASes. and
proposes a Bi-Criteria Latency optimization model. Hence an overall
network performance can be improved by considering this jointoptimization
technique in terms of Latency.
Abstract: In general, image-based 3D scenes can now be found in many popular vision systems, computer games and virtual reality tours. So, It is important to segment ROI (region of interest) from input scenes as a preprocessing step for geometric stricture detection in 3D scene. In this paper, we propose a method for segmenting ROI based on tensor voting and Dirichlet process mixture model. In particular, to estimate geometric structure information for 3D scene from a single outdoor image, we apply the tensor voting and Dirichlet process mixture model to a image segmentation. The tensor voting is used based on the fact that homogeneous region in an image are usually close together on a smooth region and therefore the tokens corresponding to centers of these regions have high saliency values. The proposed approach is a novel nonparametric Bayesian segmentation method using Gaussian Dirichlet process mixture model to automatically segment various natural scenes. Finally, our method can label regions of the input image into coarse categories: “ground", “sky", and “vertical" for 3D application. The experimental results show that our method successfully segments coarse regions in many complex natural scene images for 3D.
Abstract: Termination Mechanism is an indispensible part of the
emergency management mechanism. Despite of its importance in both
theory and practice, it is almost a brand new field for researching. The
concept of termination mechanism is proposed firstly in this paper,
and the design and implementation which are helpful to guarantee the
effect and integrity of emergency management are discussed secondly.
Starting with introduction of the problems caused by absent
termination and incorrect termination, the essence of termination
mechanism is analyzed, a model based on Optimal Stopping Theory is
constructed and the termination index is given. The model could be
applied to find the best termination time point.. Termination decision
should not only be concerned in termination stage, but also in the
whole emergency management process, which makes it a dynamic
decision making process. Besides, the main subjects and the procedure
of termination are illustrated after the termination time point is given.
Some future works are discussed lastly.
Abstract: This paper shows a simple and effective approach to
the design and implementation of Industrial Information Systems
(IIS) oriented to control the characteristics of each individual product manufactured in a production line and also their manufacturing conditions. The particular products considered in this work are large steel strips that are coiled just after their manufacturing. However, the approach is directly applicable to coiled strips in other industries, like
paper, textile, aluminum, etc. These IIS provide very detailed information of each manufactured product, which complement the general information managed by the ERP system of the production line. In spite of the high importance of this type of IIS to guarantee and improve the quality of the products manufactured in many industries, there are very few works about them in the technical literature. For this reason, this paper represents an important contribution to the development of this type of IIS, providing guidelines for their design, implementation and exploitation.
Abstract: Text categorization (the assignment of texts in natural language into predefined categories) is an important and extensively studied problem in Machine Learning. Currently, popular techniques developed to deal with this task include many preprocessing and learning algorithms, many of which in turn require tuning nontrivial internal parameters. Although partial studies are available, many authors fail to report values of the parameters they use in their experiments, or reasons why these values were used instead of others. The goal of this work then is to create a more thorough comparison of preprocessing parameters and their mutual influence, and report interesting observations and results.
Abstract: Rule Discovery is an important technique for mining knowledge from large databases. Use of objective measures for discovering interesting rules lead to another data mining problem, although of reduced complexity. Data mining researchers have studied subjective measures of interestingness to reduce the volume of discovered rules to ultimately improve the overall efficiency of KDD process. In this paper we study novelty of the discovered rules as a subjective measure of interestingness. We propose a hybrid approach that uses objective and subjective measures to quantify novelty of the discovered rules in terms of their deviations from the known rules. We analyze the types of deviation that can arise between two rules and categorize the discovered rules according to the user specified threshold. We implement the proposed framework and experiment with some public datasets. The experimental results are quite promising.
Abstract: Color Image quantization (CQ) is an important
problem in computer graphics, image and processing. The aim of
quantization is to reduce colors in an image with minimum distortion.
Clustering is a widely used technique for color quantization; all
colors in an image are grouped to small clusters. In this paper, we
proposed a new hybrid approach for color quantization using firefly
algorithm (FA) and K-means algorithm. Firefly algorithm is a swarmbased
algorithm that can be used for solving optimization problems.
The proposed method can overcome the drawbacks of both
algorithms such as the local optima converge problem in K-means
and the early converge of firefly algorithm. Experiments on three
commonly used images and the comparison results shows that the
proposed algorithm surpasses both the base-line technique k-means
clustering and original firefly algorithm.
Abstract: A large number of chemical, bio-chemical and pollution-control processes use heterogeneous fixed-bed reactors. The use of finite hollow cylindrical catalyst pellets can enhance conversion levels in such reactors. The absence of the pellet core can significantly lower the diffusional resistance associated with the solid phase. This leads to a better utilization of the catalytic material, which is reflected in the higher values for the effectiveness factor, leading ultimately to an enhanced conversion level in the reactor. It is however important to develop a rigorous heterogeneous model for the reactor incorporating the two-dimensional feature of the solid phase owing to the presence of the finite hollow cylindrical catalyst pellet. Presently, heterogeneous models reported in the literature invariably employ one-dimension solid phase models meant for spherical catalyst pellets. The objective of the paper is to present a rigorous model of the fixed-bed reactors containing finite hollow cylindrical catalyst pellets. The reaction kinetics considered here is the widely used Michaelis–Menten kinetics for the liquid-phase bio-chemical reactions. The reaction parameters used here are for the enzymatic degradation of urea. Results indicate that increasing the height to diameter ratio helps to improve the conversion level. On the other hand, decreasing the thickness is apparently not as effective. This could however be explained in terms of the higher void fraction of the bed that causes a smaller amount of the solid phase to be packed in the fixed-bed bio-chemical reactor.
Abstract: This study presents a systematic analysis of the
dynamic behaviors of a gear-bearing system with porous squeeze film
damper (PSFD) under nonlinear suspension, nonlinear oil-film force
and nonlinear gear meshing force effect. It can be found that the
system exhibits very rich forms of sub-harmonic and even the chaotic
vibrations. The bifurcation diagrams also reveal that greater values of
permeability may not only improve non-periodic motions effectively,
but also suppress dynamic amplitudes of the system. Therefore, porous
effect plays an important role to improve dynamic stability of
gear-bearing systems or other mechanical systems. The results
presented in this study provide some useful insights into the design
and development of a gear-bearing system for rotating machinery that
operates in highly rotational speed and highly nonlinear regimes.