Abstract: Data clustering is an important data exploration technique
with many applications in data mining. We present an enhanced
version of the well known single link clustering algorithm. We will
refer to this algorithm as DCBOR. The proposed algorithm alleviates
the chain effect by removing the outliers from the given dataset.
So this algorithm provides outlier detection and data clustering
simultaneously. This algorithm does not need to update the distance
matrix, since the algorithm depends on merging the most k-nearest
objects in one step and the cluster continues grow as long as possible
under specified condition. So the algorithm consists of two phases;
at the first phase, it removes the outliers from the input dataset. At
the second phase, it performs the clustering process. This algorithm
discovers clusters of different shapes, sizes, densities and requires
only one input parameter; this parameter represents a threshold for
outlier points. The value of the input parameter is ranging from 0 to
1. The algorithm supports the user in determining an appropriate
value for it. We have tested this algorithm on different datasets
contain outlier and connecting clusters by chain of density points,
and the algorithm discovers the correct clusters. The results of
our experiments demonstrate the effectiveness and the efficiency of
DCBOR.
Abstract: In this paper a new fast simplification method is presented. Such method realizes Karnough map with large number of variables. In order to accelerate the operation of the proposed method, a new approach for fast detection of group of ones is presented. Such approach implemented in the frequency domain. The search operation relies on performing cross correlation in the frequency domain rather than time one. It is proved mathematically and practically that the number of computation steps required for the presented method is less than that needed by conventional cross correlation. Simulation results using MATLAB confirm the theoretical computations. Furthermore, a powerful solution for realization of complex functions is given. The simplified functions are implemented by using a new desigen for neural networks. Neural networks are used because they are fault tolerance and as a result they can recognize signals even with noise or distortion. This is very useful for logic functions used in data and computer communications. Moreover, the implemented functions are realized with minimum amount of components. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such approach is applied to implement XOR function, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous non- modular designs, a clear reduction in the order of computations and hardware requirements is achieved.
Abstract: CTMA-bentonite and BTEA-Bentonite prepared by Na-bentonite cation exchanged with cetyltrimethylammonium(CTMA) and benzyltriethylammonium (BTEA). Products were characterized by XRD and IR techniques.The d001 spacing value of CTMA-bentonite and BTEA-bentonite are 7.54Å and 3.50Å larger than that of Na-bentonite at 100% cation exchange capacity, respectively. The IR spectrum showed that the intensities of OH stretching and bending vibrations of the two organoclays decreased greatly comparing to untreated Na-bentonite. Batch experiments were carried out at 303 K, 318 K and 333 K to obtain the sorption isotherms of Crystal violet onto the two organoclays. The results show that the sorption isothermal data could be well described by Freundlich model. The dynamical data for the two organoclays fit well with pseudo-second-order kinetic model. The adsorption capacity of CTMA-bentonite was found higher than that of BTEA-Bentonite. Thermodynamic parameters such as changes in the free energy (ΔG°), the enthalpy (ΔH°) and the entropy (ΔS°) were also evaluated. The overall adsorption process of Crystal violet onto the two organoclays were spontaneous, endothermic physisorption. The CTMA-bentonite and BTEA-Bentonite could be employed as low-cost alternatives to activated carbon in wastewater treatment for the removal of color which comes from textile dyes.
Abstract: Lately, an interest has grown greatly in the usages of
RFID in an un-presidential applications. It is shown in the adaptation
of major software companies such as Microsoft, IBM, and Oracle
the RFID capabilities in their major software products. For example
Microsoft SharePoints 2010 workflow is now fully compatible with
RFID platform. In addition, Microsoft BizTalk server is also capable
of all RFID sensors data acquisition. This will lead to applications
that required high bit rate, long range and a multimedia content in
nature. Higher frequencies of operation have been designated for
RFID tags, among them are the 2.45 and 5.8 GHz. The higher the
frequency means higher range, and higher bit rate, but the drawback
is the greater cost. In this paper we present a single layer, low
profile patch antenna operates at 5.8 GHz with pure resistive input
impedance of 50 and close to directive radiation. Also, we propose
a modification to the design in order to improve the operation band
width from 8.7 to 13.8
Abstract: Fine-grained data replication over the Internet allows duplication of frequently accessed data objects, as opposed to entire sites, to certain locations so as to improve the performance of largescale content distribution systems. In a distributed system, agents representing their sites try to maximize their own benefit since they are driven by different goals such as to minimize their communication costs, latency, etc. In this paper, we will use game theoretical techniques and in particular auctions to identify a bidding mechanism that encapsulates the selfishness of the agents, while having a controlling hand over them. In essence, the proposed game theory based mechanism is the study of what happens when independent agents act selfishly and how to control them to maximize the overall performance. A bidding mechanism asks how one can design systems so that agents- selfish behavior results in the desired system-wide goals. Experimental results reveal that this mechanism provides excellent solution quality, while maintaining fast execution time. The comparisons are recorded against some well known techniques such as greedy, branch and bound, game theoretical auctions and genetic algorithms.
Abstract: Hemorrhage Disease of Grass Carp (HDGC) is a kind
of commonly occurring illnesses in summer, and the extremely high
death rate result in colossal losses to aquaculture. As the complex
connections among each factor which influences aquiculture diseases,
there-s no quit reasonable mathematical model to solve the problem at
present.A BP neural network which with excellent nonlinear mapping
coherence was adopted to establish mathematical model;
Environmental factor, which can easily detected, such as breeding
density, water temperature, pH and light intensity was set as the main
analyzing object. 25 groups of experimental data were used for
training and test, and the accuracy of using the model to predict the
trend of HDGC was above 80%. It is demonstrated that BP neural
network for predicating diseases in HDGC has a particularly
objectivity and practicality, thus it can be spread to other aquiculture
disease.
Abstract: In this paper we develop an efficient numerical method for the finite-element model updating of damped gyroscopic systems based on incomplete complex modal measured data. It is assumed that the analytical mass and stiffness matrices are correct and only the damping and gyroscopic matrices need to be updated. By solving a constrained optimization problem, the optimal corrected symmetric damping matrix and skew-symmetric gyroscopic matrix complied with the required eigenvalue equation are found under a weighted Frobenius norm sense.
Abstract: There have been various methods created based on the regression ideas to resolve the problem of data set containing censored observations, i.e. the Buckley-James method, Miller-s method, Cox method, and Koul-Susarla-Van Ryzin estimators. Even though comparison studies show the Buckley-James method performs better than some other methods, it is still rarely used by researchers mainly because of the limited diagnostics analysis developed for the Buckley-James method thus far. Therefore, a diagnostic tool for the Buckley-James method is proposed in this paper. It is called the renovated Cook-s Distance, (RD* i ) and has been developed based on the Cook-s idea. The renovated Cook-s Distance (RD* i ) has advantages (depending on the analyst demand) over (i) the change in the fitted value for a single case, DFIT* i as it measures the influence of case i on all n fitted values Yˆ∗ (not just the fitted value for case i as DFIT* i) (ii) the change in the estimate of the coefficient when the ith case is deleted, DBETA* i since DBETA* i corresponds to the number of variables p so it is usually easier to look at a diagnostic measure such as RD* i since information from p variables can be considered simultaneously. Finally, an example using Stanford Heart Transplant data is provided to illustrate the proposed diagnostic tool.
Abstract: In the present article, a new method has been developed to enhance the application of equipment monitoring, which in turn results in improving condition-based maintenance economic impact in an automobile parts manufacturing factory. This study also describes how an effective software with a simple database can be utilized to achieve cost-effective improvements in maintenance performance. The most important results of this project are indicated here: 1. 63% reduction in direct and indirect maintenance costs. 2. Creating a proper database to analyse failures. 3. Creating a method to control system performance and develop it to similar systems. 4. Designing a software to analyse database and consequently create technical knowledge to face unusual condition of the system. Moreover, the results of this study have shown that the concept and philosophy of maintenance has not been understood in most Iranian industries. Thus, more investment is strongly required to improve maintenance conditions.
Abstract: We measured the major and trace element contents
and Rb-Sr isotopic compositions of 12 tektites from the Maoming
area, Guandong province (south China). All the samples studied are
splash-form tektites which show pitted or grooved surfaces with
schlieren structures on some surfaces. The trace element ratios Ba/Rb
(avg. 4.33), Th/Sm (avg. 2.31), Sm/Sc (avg. 0.44), Th/Sc (avg. 1.01) ,
La/Sc (avg. 2.86), Th/U (avg. 7.47), Zr/Hf (avg. 46.01) and the rare
earth elements (REE) contents of tektites of this study are similar to the
average upper continental crust. From the chemical composition, it is
suggested that tektites in this study are derived from similar parental
terrestrial sedimentary deposit which may be related to post-Archean
upper crustal rocks. The tektites from the Maoming area have high
positive εSr(0) values-ranging from 176.9~190.5 which indicate that
the parental material for these tektites have similar Sr isotopic
compositions to old terrestrial sedimentary rocks and they were not
dominantly derived from recent young sediments (such as soil or
loess). The Sr isotopic data obtained by the present study support the
conclusion proposed by Blum et al. (1992)[1] that the depositional age
of sedimentary target materials is close to 170Ma (Jurassic). Mixing
calculations based on the model proposed by Ho and Chen (1996)[2]
for various amounts and combinations of target rocks indicate that the
best fit for tektites from the Maoming area is a mixture of 40% shale,
30% greywacke, 30% quartzite.
Abstract: Automated discovery of hierarchical structures in
large data sets has been an active research area in the recent past.
This paper focuses on the issue of mining generalized rules with crisp
hierarchical structure using Genetic Programming (GP) approach to
knowledge discovery. The post-processing scheme presented in this
work uses flat rules as initial individuals of GP and discovers
hierarchical structure. Suitable genetic operators are proposed for the
suggested encoding. Based on the Subsumption Matrix(SM), an
appropriate fitness function is suggested. Finally, Hierarchical
Production Rules (HPRs) are generated from the discovered
hierarchy. Experimental results are presented to demonstrate the
performance of the proposed algorithm.
Abstract: The goals of the present research are to estimate Six Sigma implementation in Latvian commercial banks and to identify the perceived benefits of its implementation. To achieve the goals, the authors used sequential explanatory method. To obtain empirical data, the authors have developed the questionnaire and adapted it for the employees of Latvian commercial banks. The questions are related to Six Sigma implementation and its perceived benefits. The questionnaire mainly consists of closed questions, the evaluation of which is based on 5 point Likert scale. The obtained empirical data has shown that of the two hypotheses put forward in the present research – Hypothesis 1 – has to be rejected, while Hypothesis 2 has been partially confirmed. The authors have also faced some research limitations related to the fact that the participants in the questionnaire belong to different rank of the organization hierarchy.
Abstract: In this paper some procedures for building confidence intervals for the reliability in stress-strength models are discussed and empirically compared. The particular case of a bivariate normal setup is considered. The confidence intervals suggested are obtained employing approximations or asymptotic properties of maximum likelihood estimators. The coverage and the precision of these intervals are empirically checked through a simulation study. An application to real paired data is also provided.
Abstract: Nowadays, biometrical characterizations of Artemia
cysts are used as one of the most important factors in the study of
Artemia populations and intraspecific particularity; meanwhile these
characters can be used as economical indices. For example, typically
high hatching efficiency is possible due to the small diameter of
cysts (high number per gram); therefore small diameter of cysts
show someway high quality of cysts. This study was performed
during a ten year period, including two different ecological
conditions: rainy and drought. It is important from two different
aspects because it covers alteration of A. urmiana during ten years
also its variation in the best and worst environmental situations in
which salinity increased from 173.8 ppt in 1994 to 280.8 ppt in
2003/4. In this study the biometrical raw data of Artemia urmiana
cysts at seven stations from the Urmia Lake in 1994 and their seven
identical locations at 26 studied stations in 2003/4 were reanalyzed
again and compared together. Biometrical comparison of untreated
and decapsulated cysts in each of the seven similar stations showed a
highly significant variation between 1994 and 2003/4. Based on this
study, in whole stations the untreated and decapsulated cysts from
1994 were larger than cysts of 2003/4 without any exception. But
there was no logical relationship between salinity and chorion
thickness in the Urmia Lake. With regard to PCA analyses the
stations of two different studied years certainly have been separated
with factor 1 from each other. In conclusion, the interaction between
genetic and environmental factors can determine and explain
variation in the range of cysts diameter in Artemia.
Abstract: Recognizing the increasing importance of using the
Internet to conduct business, this paper looks at some related matters
associated with small businesses making a decision of whether or not
to have a Website and go online. Small businesses in Saudi Arabia
struggle to have this decision. For organizations, to fully go online,
conduct business and provide online information services, they need
to connect their database to the Web. Some issues related to doing
that might be beyond the capabilities of most small businesses in
Saudi Arabia, such as Website management, technical issues and
security concerns. Here we focus on a small business firm in Saudi
Arabia (Case Study), discussing the issues related to going online
decision and the firm's options of what to do and how to do it. The
paper suggested some valuable solutions of connecting databases to
the Web. It also discusses some of the important issues related to
online information services and e-commerce, mainly Web hosting
options and security issues.
Abstract: In the study of honeycomb crushing under quasistatic loading, two parameters are important, the mean crushing stress and the wavelength of the folding mode. The previous theoretical models did not consider the true cylindrical curvature effects and the flow stress in the folding mode of honeycomb material. The present paper introduces a modification on Wierzbicki-s model based on considering two above mentioned parameters in estimating the mean crushing stress and the wavelength through implementation of the energy method. Comparison of the results obtained by the new model and Wierzbicki-s model with existing experimental data shows better prediction by the model presented in this paper.
Abstract: The study of proteomics reached unexpected levels of
interest, as a direct consequence of its discovered influence over
some complex biological phenomena, such as problematic diseases
like cancer. This paper presents a new technique that allows for an
accurate analysis of the human interactome network. It is basically
a two-step analysis process that involves, at first, the detection of
each protein-s absolute importance through the betweenness centrality
computation. Then, the second step determines the functionallyrelated
communities of proteins. For this purpose, we use a community
detection technique that is based on the edge betweenness
calculation. The new technique was thoroughly tested on real biological
data and the results prove some interesting properties of those proteins that are involved in the carcinogenesis process. Apart from its
experimental usefulness, the novel technique is also computationally
effective in terms of execution times. Based on the analysis- results, some topological features of cancer mutated proteins are presented
and a possible optimization solution for cancer drugs design is suggested.
Abstract: Computerized lip reading has been one of the most
actively researched areas of computer vision in recent past because
of its crime fighting potential and invariance to acoustic environment.
However, several factors like fast speech, bad pronunciation,
poor illumination, movement of face, moustaches and beards make
lip reading difficult. In present work, we propose a solution for
automatic lip contour tracking and recognizing letters of English
language spoken by speakers using the information available from
lip movements. Level set method is used for tracking lip contour
using a contour velocity model and a feature vector of lip movements
is then obtained. Character recognition is performed using modified
k nearest neighbor algorithm which assigns more weight to nearer
neighbors. The proposed system has been found to have accuracy
of 73.3% for character recognition with speaker lip movements as
the only input and without using any speech recognition system in
parallel. The approach used in this work is found to significantly
solve the purpose of lip reading when size of database is small.
Abstract: Despite the fact that Arabic language is currently one
of the most common languages worldwide, there has been only a
little research on Arabic speech recognition relative to other
languages such as English and Japanese. Generally, digital speech
processing and voice recognition algorithms are of special
importance for designing efficient, accurate, as well as fast automatic
speech recognition systems. However, the speech recognition process
carried out in this paper is divided into three stages as follows: firstly,
the signal is preprocessed to reduce noise effects. After that, the
signal is digitized and hearingized. Consequently, the voice activity
regions are segmented using voice activity detection (VAD)
algorithm. Secondly, features are extracted from the speech signal
using Mel-frequency cepstral coefficients (MFCC) algorithm.
Moreover, delta and acceleration (delta-delta) coefficients have been
added for the reason of improving the recognition accuracy. Finally,
each test word-s features are compared to the training database using
dynamic time warping (DTW) algorithm. Utilizing the best set up
made for all affected parameters to the aforementioned techniques,
the proposed system achieved a recognition rate of about 98.5%
which outperformed other HMM and ANN-based approaches
available in the literature.
Abstract: National Biodiversity Database System (NBIDS) has
been developed for collecting Thai biodiversity data. The goal of this
project is to provide advanced tools for querying, analyzing,
modeling, and visualizing patterns of species distribution for
researchers and scientists. NBIDS data record two types of datasets:
biodiversity data and environmental data. Biodiversity data are
specie presence data and species status. The attributes of biodiversity
data can be further classified into two groups: universal and projectspecific
attributes. Universal attributes are attributes that are common
to all of the records, e.g. X/Y coordinates, year, and collector name.
Project-specific attributes are attributes that are unique to one or a
few projects, e.g., flowering stage. Environmental data include
atmospheric data, hydrology data, soil data, and land cover data
collecting by using GLOBE protocols. We have developed webbased
tools for data entry. Google Earth KML and ArcGIS were used
as tools for map visualization. webMathematica was used for simple
data visualization and also for advanced data analysis and
visualization, e.g., spatial interpolation, and statistical analysis.
NBIDS will be used by park rangers at Khao Nan National Park, and
researchers.