Abstract: Many supervised induction algorithms require discrete
data, even while real data often comes in a discrete
and continuous formats. Quality discretization of continuous
attributes is an important problem that has effects on speed,
accuracy and understandability of the induction models. Usually,
discretization and other types of statistical processes are applied
to subsets of the population as the entire population is practically
inaccessible. For this reason we argue that the discretization
performed on a sample of the population is only an estimate of
the entire population. Most of the existing discretization methods,
partition the attribute range into two or several intervals using
a single or a set of cut points. In this paper, we introduce a
technique by using resampling (such as bootstrap) to generate
a set of candidate discretization points and thus, improving the
discretization quality by providing a better estimation towards
the entire population. Thus, the goal of this paper is to observe
whether the resampling technique can lead to better discretization
points, which opens up a new paradigm to construction of
soft decision trees.
Abstract: This article is based on the technique which is called
Discrete Parameter Tracking (DPT). First introduced by A. A. Azab
[8] which is applicable for less order reference model. The order of
the reference model is (n-l) and n is the number of the adjustable
parameters in the physical plant.
The technique utilizes a modified gradient method [9] where the
knowledge of the exact order of the nonadaptive system is not
required, so, as to eliminate the identification problem. The
applicability of the mentioned technique (DPT) was examined
through the solution of several problems.
This article introduces the solution of a third order system with
three adjustable parameters, controlled according to second order
reference model. The adjustable parameters have great initial error
which represent condition.
Computer simulations for the solution and analysis are provided
to demonstrate the simplicity and feasibility of the technique.
Abstract: In this work, an organic compound 5,10,15,20-
Tetrakis(3,5-di-tertbutylphenyl)porphyrinatocopper(II) (TDTBPPCu)
is studied as an active material for thin film electronic devices. To
investigate the electrical properties of TDTBPPCu, junction of
TDTBPPCu with heavily doped n-Si and Al is fabricated.
TDTBPPCu film was sandwiched between Al and n-Si electrodes.
Various electrical parameters of TDTBPPCu are determined. The
current-voltage characteristics of the junction are nonlinear,
asymmetric and show rectification behavior, which gives the clue of
formation of depletion region. This behavior indicates the potential
of TDTBPPCu for electronics applications. The current-voltage and
capacitance-voltage techniques are used to find the different
electronic parameters.
Abstract: This paper presents the H-ARQ techniques comparison for OFDM systems with a new family of non-binary LDPC codes which has been developed within the EU FP7 DAVINCI project. The punctured NB-LDPC codes have been used in a simulated model of the transmission system. The link level performance has been evaluated in terms of spectral efficiency, codeword error rate and average number of retransmissions. The NB-LDPC codes can be easily and effective implemented with different methods of the retransmission needed if correct decoding of a codeword failed. Here the Optimal Symbol Selection method is proposed as a Chase Combining technique.
Abstract: In this paper a combined feature selection method is
proposed which takes advantages of sample domain filtering,
resampling and feature subset evaluation methods to reduce
dimensions of huge datasets and select reliable features. This method
utilizes both feature space and sample domain to improve the process
of feature selection and uses a combination of Chi squared with
Consistency attribute evaluation methods to seek reliable features.
This method consists of two phases. The first phase filters and
resamples the sample domain and the second phase adopts a hybrid
procedure to find the optimal feature space by applying Chi squared,
Consistency subset evaluation methods and genetic search.
Experiments on various sized datasets from UCI Repository of
Machine Learning databases show that the performance of five
classifiers (Naïve Bayes, Logistic, Multilayer Perceptron, Best First
Decision Tree and JRIP) improves simultaneously and the
classification error for these classifiers decreases considerably. The
experiments also show that this method outperforms other feature
selection methods.
Abstract: Study of soil properties like field capacity (F.C.) and permanent wilting point (P.W.P.) play important roles in study of soil moisture retention curve. Although these parameters can be measured directly, their measurement is difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. In this investigation, 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. The data set was divided into two subsets for calibration (80%) and testing (20%) of the models and their normality were tested by Kolmogorov-Smirnov method. Both multivariate regression and artificial neural network (ANN) techniques were employed to develop the appropriate PTFs for predicting soil parameters using easily measurable characteristics of clay, silt, O.C, S.P, B.D and CaCO3. The performance of the multivariate regression and ANN models was evaluated using an independent test data set. In order to evaluate the models, root mean square error (RMSE) and R2 were used. The comparison of RSME for two mentioned models showed that the ANN model gives better estimates of F.C and P.W.P than the multivariate regression model. The value of RMSE and R2 derived by ANN model for F.C and P.W.P were (2.35, 0.77) and (2.83, 0.72), respectively. The corresponding values for multivariate regression model were (4.46, 0.68) and (5.21, 0.64), respectively. Results showed that ANN with five neurons in hidden layer had better performance in predicting soil properties than multivariate regression.
Abstract: World has entered in 21st century. The technology of
computer graphics and digital cameras is prevalent. High resolution
display and printer are available. Therefore high resolution images
are needed in order to produce high quality display images and high
quality prints. However, since high resolution images are not usually
provided, there is a need to magnify the original images. One
common difficulty in the previous magnification techniques is that of
preserving details, i.e. edges and at the same time smoothing the data
for not introducing the spurious artefacts. A definitive solution to this
is still an open issue. In this paper an image magnification using
adaptive interpolation by pixel level data-dependent geometrical
shapes is proposed that tries to take into account information about
the edges (sharp luminance variations) and smoothness of the image.
It calculate threshold, classify interpolation region in the form of
geometrical shapes and then assign suitable values inside
interpolation region to the undefined pixels while preserving the
sharp luminance variations and smoothness at the same time.
The results of proposed technique has been compared qualitatively
and quantitatively with five other techniques. In which the qualitative
results show that the proposed method beats completely the Nearest
Neighbouring (NN), bilinear(BL) and bicubic(BC) interpolation. The
quantitative results are competitive and consistent with NN, BL, BC
and others.
Abstract: Space Vector Pulse Width Modulation SVPWM is
one of the most used techniques to generate sinusoidal voltage and
current due to its facility and efficiency with low harmonics
distortion. This algorithm is specially used in power electronic
applications. This paper describes simulation algorithm of SVPWM
& SPWM using MatLab/simulink environment. It also implements a
closed loop three phases DC-AC converter controlling its outputs
voltages amplitude and frequency using MatLab. Also comparison
between SVPWM & SPWM results is given.
Abstract: Two algorithms are proposed to reduce the storage requirements for mammogram images. The input image goes through a shrinking process that converts the 16-bit images to 8-bits by using pixel-depth conversion algorithm followed by enhancement process. The performance of the algorithms is evaluated objectively and subjectively. A 50% reduction in size is obtained with no loss of significant data at the breast region.
Abstract: Recommender systems are usually regarded as an
important marketing tool in the e-commerce. They use important
information about users to facilitate accurate recommendation. The
information includes user context such as location, time and interest
for personalization of mobile users. We can easily collect information
about location and time because mobile devices communicate with the
base station of the service provider. However, information about user
interest can-t be easily collected because user interest can not be
captured automatically without user-s approval process. User interest
usually represented as a need. In this study, we classify needs into two
types according to prior research. This study investigates the
usefulness of data mining techniques for classifying user need type for
recommendation systems. We employ several data mining techniques
including artificial neural networks, decision trees, case-based
reasoning, and multivariate discriminant analysis. Experimental
results show that CHAID algorithm outperforms other models for
classifying user need type. This study performs McNemar test to
examine the statistical significance of the differences of classification
results. The results of McNemar test also show that CHAID performs
better than the other models with statistical significance.
Abstract: The incessant discomfort for Voluntary Counselling and Testing (VCT) exhibited by students in some tertiary institutions in Kano State, Nigeria is capable of causing Psychological Resistance as well as jeopardizing the purpose of HIV intervention. This study investigated the Prevalence of Psychological Resistance to VCT of HIV/AIDS among students of tertiary institutions in the state. Two null hypotheses were postulated and tested. Cross- Sectional Survey Design was employed in which 1512 sample was selected from a student population of 104,841 following Stratified Random Sampling technique. A self-developed 20-item scale whose reliability coefficient is 0.83 was used for data collection. Data analyzed via Chi-square and t-test reveals a prevalence of 38% with males (Mean=0.34; SD=0.475) constituting 60% and females (Mean=0.45; SD=0.498) 40%. Also, the calculated chi-square and ttest were not significant at 0.05 as such the null hypotheses were upheld. Recommendation offered suggests the use of reinforcement and social support for students who patronize HIV/AIDS counselling.
Abstract: Void formation in underfill is considered as failure
in flip chip manufacturing process. Void formation possibly caused
by several factors such as poor soldering and flux residue during
die attach process, void entrapment due moisture contamination,
dispense pattern process and setting up the curing process. This
paper presents the comparison of single step and two steps curing
profile towards the void and black dots formation in underfill for
Hi-CTE Flip Chip Ceramic Ball Grid Array Package (FC-CBGA).
Statistic analysis was conducted to analyze how different factors
such as wafer lot, sawing technique, underfill fillet height and
curing profile recipe were affected the formation of voids and
black dots. A C-Mode Scanning Aqoustic Microscopy (C-SAM)
was used to scan the total count of voids and black dots. It was
shown that the 2 steps curing profile provided solution for void
elimination and black dots in underfill after curing process.
Abstract: In this paper a nonlinear model is presented to
demonstrate the relation between production and marketing
departments. By introducing some functions such as pricing cost and
market share loss functions it will be tried to show some aspects of
market modelling which has not been regarded before. The proposed
model will be a constrained signomial geometric programming
model. For model solving, after variables- modifications an iterative
technique based on the concept of geometric mean will be introduced
to solve the resulting non-standard posynomial model which can be
applied to a wide variety of models in non-standard posynomial
geometric programming form. At the end a numerical analysis will
be presented to accredit the validity of the mentioned model.
Abstract: Clustering techniques have been used by many intelligent software agents to group similar access patterns of the Web users into high level themes which express users intentions and interests. However, such techniques have been mostly focusing on one salient feature of the Web document visited by the user, namely the extracted keywords. The major aim of these techniques is to come up with an optimal threshold for the number of keywords needed to produce more focused themes. In this paper we focus on both keyword and similarity thresholds to generate themes with concentrated themes, and hence build a more sound model of the user behavior. The purpose of this paper is two fold: use distance based clustering methods to recognize overall themes from the Proxy log file, and suggest an efficient cut off levels for the keyword and similarity thresholds which tend to produce more optimal clusters with better focus and efficient size.
Abstract: The objective of this paper is to present a research
study of the convectors that are used for heating or cooling of the
living room or industrial halls. The key points are experimental
measurement and comprehensive numerical simulation of the flow
coming throughout the part of the convector such as heat exchanger,
input from the fan etc.. From the obtained results, the components of
the convector are optimized in sense to increase thermal power
efficiency due to improvement of heat convection or reduction of air
drag friction. Both optimized aspects are leading to the more
effective service conditions and to energy saving. The significant part
of the convector research is a design of the unique measurement
laboratory and adopting measure techniques. The new laboratory
provides possibility to measure thermal power efficiency and other
relevant parameters under specific service conditions of the
convectors.
Abstract: WLAN Positioning has been presented by many
approaches in literatures using the characteristics of Received Signal
Strength (RSS), Time of Arrival (TOA) or Time Difference of
Arrival (TDOA), Angle of Arrival (AOA) and cell ID. Among these,
RSS approach is the simplest method to implement because there is
no need of modification on both access points and client devices
whereas its accuracy is terrible due to physical environments. For
TOA or TDOA approach, the accuracy is quite acceptable but most
researches have to modify either software or hardware on existing
WLAN infrastructure. The scales of modifications are made on only
access card up to the changes in protocol of WLAN. Hence, it is an
unattractive approach to use TOA or TDOA for positioning system.
In this paper, the new concept of merging both RSS and TOA
positioning techniques is proposed. In addition, the method to
achieve TOA characteristic for positioning WLAN user without any
extra modification necessarily appended in the existing system is
presented. The measurement results confirm that the proposed
technique using both RSS and TOA characteristics provides better
accuracy than using only either RSS or TOA approach.
Abstract: In the present paper, an improved initial value
numerical technique is presented to analyze the free vibration of
symmetrically laminated rectangular plate. A combination of the
initial value method (IV) and the finite differences (FD) devices is
utilized to develop the present (IVFD) technique. The achieved
technique is applied to the equation of motion of vibrating laminated
rectangular plate under various types of boundary conditions. Three
common types of laminated symmetrically cross-ply, orthotropic and
isotropic plates are analyzed here. The convergence and accuracy of
the presented Initial Value-Finite Differences (IVFD) technique have
been examined. Also, the merits and validity of improved technique
are satisfied via comparing the obtained results with those available
in literature indicating good agreements.
Abstract: POS (also been called DGPS/IMU) technique can obtain the Exterior Orientation Elements of aerial photo, so the triangulation and DLG production using POS can save large numbers of ground control points (GCP), and this will improve the produce efficiency of DLG and reduce the cost of collecting GCP. This paper mainly research on POS technique in production of 1:10 000 scale DLG on GCP distribution. We designed 23 kinds of ground control points distribution schemes, using integrated sensor direction method to do the triangulation experiments, based on the results of triangulation, we produce a map with the scale of 1:10 000 and test its accuracy. This paper put forward appropriate GCP distributing schemes by experiments and research above, and made preparations for the application of POS technique on photogrammetry 4D data production.
Abstract: This paper proposes, implements and evaluates an original discretization method for continuous random variables, in order to estimate the reliability of systems for which stress and strength are defined as complex functions, and whose reliability is not derivable through analytic techniques. This method is compared to other two discretizing approaches appeared in literature, also through a comparative study involving four engineering applications. The results show that the proposal is very efficient in terms of closeness of the estimates to the true (simulated) reliability. In the study we analyzed both a normal and a non-normal distribution for the random variables: this method is theoretically suitable for each parametric family.
Abstract: The major objective of this study is to understand the
potential of a newly fabricated equipment to study the thermal
properties of nonwoven textile fabrics treated with aerogel at subzero
temperatures. Thermal conductivity was calculated by using the
empirical relation Fourier’s law, The relationship between the
thermal conductivity and thermal resistance of the samples were
studied at various environmental temperatures (which was set in the
clima temperature system between +25oC to -25oC). The newly
fabricated equipment was found to be a suitable for measuring at
subzero temperatures. This field of measurements is being developed
and will be the subject of further research which will be more suitable
for measurement of the various thermal characteristics.