Abstract: This paper investigates the problem of automated defect
detection for textile fabrics and proposes a new optimal filter design
method to solve this problem. Gabor Wavelet Network (GWN) is
chosen as the major technique to extract the texture features from
textile fabrics. Based on the features extracted, an optimal Gabor filter
can be designed. In view of this optimal filter, a new semi-supervised
defect detection scheme is proposed, which consists of one real-valued
Gabor filter and one smoothing filter. The performance of the scheme
is evaluated by using an offline test database with 78 homogeneous
textile images. The test results exhibit accurate defect detection with
low false alarm, thus showing the effectiveness and robustness of the
proposed scheme. To evaluate the detection scheme comprehensively,
a prototyped detection system is developed to conduct a real time test.
The experiment results obtained confirm the efficiency and
effectiveness of the proposed detection scheme.
Abstract: The objective of this study was to determine the accuracy to estimation fetal weight by Johnson-s method and compares it with actual birth weight. The sample group was 126 infants delivered in Dan KhunThot hospital from January March 2012. Fetal weight was estimated by measuring fundal height according to Johnson-s method. The information was collected by studying historical delivery records and then analyzed by using the statistics of frequency, percentage, mean, and standard deviation. Finally, the difference was analyzed by a paired t-test.The results showed had an average birth weight was 3093.57 ± 391.03 g (mean ± SD) and 3,455 ± 454.55 g average estimated fetal weight by Johnson-s method higher than average actual birth weight was 384.09 grams. When classifying the infants according to birth weight found that low birth weight ( 4000 g) actual birth weight was more than estimated fetal weight. The difference was found between actual birth weight and estimation fetal weight of the minimum weight in high birth weight ( > 4000 g) , the appropriate birth weight (2500-3999g) and low birth weight (
Abstract: In recent years, real estate prediction or valuation has
been a topic of discussion in many developed countries. Improper
hype created by investors leads to fluctuating prices of real estate,
affecting many consumers to purchase their own homes. Therefore,
scholars from various countries have conducted research in real estate
valuation and prediction. With the back-propagation neural network
that has been popular in recent years and the orthogonal array in the
Taguchi method, this study aimed to find the optimal parameter
combination at different levels of orthogonal array after the system
presented different parameter combinations, so that the artificial
neural network obtained the most accurate results. The experimental
results also demonstrated that the method presented in the study had a
better result than traditional machine learning. Finally, it also showed
that the model proposed in this study had the optimal predictive effect,
and could significantly reduce the cost of time in simulation operation.
The best predictive results could be found with a fewer number of
experiments more efficiently. Thus users could predict a real estate
transaction price that is not far from the current actual prices.
Abstract: Fluid flow in cylinders of elliptic cross-section was investigated. Fluid used is Liquefied petroleum gas (LPG). LPG found in Nigeria contains majorly butane with percentages of propane. Commercial available code FLUENT which uses finite volume method was used to solve fluid flow governing equations. There has been little attention paid to fluid flow in cylindrical elliptic pipes. The present work aims to predict the LPG gas flow in cylindrical pipes of elliptic cross-section. Results of flow parameters of velocity and pressure distributions are presented. Results show that the pressure drop in elliptic pipes is higher than circular pipe of the same cross-sectional area. This is an important result as the pressure drop is related to the pump power needed to drive the flow. Results show that the velocity increases towards centre of the pipe as the flow moves downstream, and also increases towards the outlet of the pipe.
Abstract: Nowadays the construction industry is growing specially among developing counties. Iran also has a critical role in these industries in terms of workers disorders. Work-related musculoskeletal disorders (WMSDs) assign 7% of the whole diseases in the society, which make some limitations. One of the main factors, which are ended to WMSDs, is awkward posture. Steel bar bending is considered as one of the prominent performance among construction workers. In this case study we conducted to find the major tasks of bar benders and the most important related risk factors. This study was carried out among twenty workers (18-45 years) as our volunteer samples in some construction sites with less than 6 floors in two regions of Tehran municipality. The data was gathered through in depth observation, interview and questionnaire. Also postural analysis was done by OWAS. In another part of study we used NMQ for gathering some data about psychosocial effects of work related disorders. Our findings show that 64% of workers were not aware of work risks, also about 59% of workers had troubles in their wrists, hands, and especially among workers who worked in steel bar bending. In 46% cases low back pain were prevalence. Considering with gathered data and results, awkward postures and long term tasks and its duration are known as the main risk factors in WMSDs among construction workers, so work-rest schedule and also tools design should be considered to make an ergonomic condition for the mentioned workers.
Abstract: The objective of this paper is to establish a possible relationship between sustainable business practice and firm performance. Using a field survey methodology, a sample of sixty manufacturing companies in Nigeria was studied. The firms were categorised into two groups, environmentally 'responsible' and 'irresponsible' firms. An investigation was undertaken into the possible relationship between firm performance and three selected indicators of sustainable business practice: employee health and safety (EHS), waste management (WM), and community development (CD), common within the 30 'responsible' firms. Findings from empirical results reveal that the sustainable practices of the 'responsible' firms are significantly related with firm performance. In addition, sustainable practices are inversely related with fines and penalties. The paper concludes that, within the Nigerian setting at least, sustainability affects corporate performance and sustainability may be a possible tool for corporate conflict resolution as evidenced in the reduction of fines, penalties and compensations. The paper therefore recommends research into the relationship between sustainability and conflict management.
Abstract: In this paper smooth trajectories are computed in the Lie group SO(2, 1) as a motion planning problem by assigning a Frenet frame to the rigid body system to optimize the cost function of the elastic energy which is spent to track a timelike curve in Minkowski space. A method is proposed to solve a motion planning problem that minimizes the integral of the Lorentz inner product of Darboux vector of a timelike curve. This method uses the coordinate free Maximum Principle of Optimal control and results in the theory of integrable Hamiltonian systems. The presence of several conversed quantities inherent in these Hamiltonian systems aids in the explicit computation of the rigid body motions.
Abstract: There have been numerous implementations of
security system using biometric, especially for identification and
verification cases. An example of pattern used in biometric is the iris
pattern in human eye. The iris pattern is considered unique for each
person. The use of iris pattern poses problems in encoding the human
iris.
In this research, an efficient iris recognition method is proposed.
In the proposed method the iris segmentation is based on the
observation that the pupil has lower intensity than the iris, and the
iris has lower intensity than the sclera. By detecting the boundary
between the pupil and the iris and the boundary between the iris and
the sclera, the iris area can be separated from pupil and sclera. A step
is taken to reduce the effect of eyelashes and specular reflection of
pupil. Then the four levels Coiflet wavelet transform is applied to the
extracted iris image. The modified Hamming distance is employed to
measure the similarity between two irises.
This research yields the identification success rate of 84.25% for
the CASIA version 1.0 database. The method gives an accuracy of
77.78% for the left eyes of MMU 1 database and 86.67% for the
right eyes. The time required for the encoding process, from the
segmentation until the iris code is generated, is 0.7096 seconds.
These results show that the accuracy and speed of the method is
better than many other methods.
Abstract: In this study, the problem of discriminating between interictal epileptic and non- epileptic pathological EEG cases, which present episodic loss of consciousness, investigated. We verify the accuracy of the feature extraction method of autocross-correlated coefficients which extracted and studied in previous study. For this purpose we used in one hand a suitable constructed artificial supervised LVQ1 neural network and in other a cross-correlation technique. To enforce the above verification we used a statistical procedure which based on a chi- square control. The classification and the statistical results showed that the proposed feature extraction is a significant accurate method for diagnostic discrimination cases between interictal and non-interictal EEG events and specifically the classification procedure showed that the LVQ neural method is superior than the cross-correlation one.
Abstract: This paper presents a new method for estimating the nonstationary
noise power spectral density given a noisy signal. The
method is based on averaging the noisy speech power spectrum using
time and frequency dependent smoothing factors. These factors are
adjusted based on signal-presence probability in individual frequency
bins. Signal presence is determined by computing the ratio of the
noisy speech power spectrum to its local minimum, which is updated
continuously by averaging past values of the noisy speech power
spectra with a look-ahead factor. This method adapts very quickly to
highly non-stationary noise environments. The proposed method
achieves significant improvements over a system that uses voice
activity detector (VAD) in noise estimation.
Abstract: This paper presents an on-going research work on the
implementation of feature-based machining via macro programming.
Repetitive machining features such as holes, slots, pockets etc can
readily be encapsulated in macros. Each macro consists of methods
on how to machine the shape as defined by the feature. The macro
programming technique comprises of a main program and
subprograms. The main program allows user to select several
subprograms that contain features and define their important
parameters. With macros, complex machining routines can be
implemented easily and no post processor is required. A case study
on machining of a part that comprised of planar face, hole and pocket
features using the macro programming technique was carried out. It
is envisaged that the macro programming technique can be extended
to other feature-based machining fields such as the newly developed
STEP-NC domain.
Abstract: Data clustering is an important data exploration
technique with many applications in data mining. The k-means
algorithm is well known for its efficiency in clustering large data
sets. However, this algorithm is suitable for spherical shaped clusters
of similar sizes and densities. The quality of the resulting clusters
decreases when the data set contains spherical shaped with large
variance in sizes. In this paper, we introduce a competent procedure
to overcome this problem. The proposed method is based on shifting
the center of the large cluster toward the small cluster, and recomputing
the membership of small cluster points, the experimental
results reveal that the proposed algorithm produces satisfactory
results.
Abstract: This paper aims to propose a novel, robust, and simple method for obtaining a human 3D face model and camera pose (position and orientation) from a video sequence. Given a video sequence of a face recorded from an off-the-shelf digital camera, feature points used to define facial parts are tracked using the Active- Appearance Model (AAM). Then, the face-s 3D structure and camera pose of each video frame can be simultaneously calculated from the obtained point correspondences. This proposed method is primarily based on the combined approaches of Gradient Descent and Powell-s Multidimensional Minimization. Using this proposed method, temporarily occluded point including the case of self-occlusion does not pose a problem. As long as the point correspondences displayed in the video sequence have enough parallax, these missing points can still be reconstructed.
Abstract: Horizontal platform system (HPS) is popularly applied
in offshore and earthquake technology, but it is difficult and
time-consuming for regulation. In order to understand the nonlinear
dynamic behavior of HPS and reduce the cost when using it, this paper
employs differential transformation method to study the bifurcation
behavior of HPS. The numerical results reveal a complex dynamic
behavior comprising periodic, sub-harmonic, and chaotic responses.
Furthermore, the results reveal the changes which take place in the
dynamic behavior of the HPS as the external torque is increased.
Therefore, the proposed method provides an effective means of
gaining insights into the nonlinear dynamics of horizontal platform
system.
Abstract: This paper presents the analysis of similarity between local decisions, in the process of alphanumeric hand-prints classification. From the analysis of local characteristics of handprinted numerals and characters, extracted by a zoning method, the set of classification decisions is obtained and the similarity among them is investigated. For this purpose the Similarity Index is used, which is an estimator of similarity between classifiers, based on the analysis of agreements between their decisions. The experimental tests, carried out using numerals and characters from the CEDAR and ETL database, respectively, show to what extent different parts of the patterns provide similar classification decisions.
Abstract: The rapid development of the BlackBerry games industry and its development goals were not just for entertainment, but also used for educational of students interactively. Unfortunately the development of adaptive educational games on BlackBerry in Indonesian language that interesting and entertaining for learning process is very limited. This paper shows the research of development of novel adaptive educational games for students who can adjust the difficulty level of games based on the ability of the user, so that it can motivate students to continue to play these games. We propose a method where these games can adjust the level of difficulty, based on the assessment of the results of previous problems using neural networks with three inputs in the form of percentage correct, the speed of answer and interest mode of games (animation / lessons) and 1 output. The experimental results are presented and show the adaptive games are running well on mobile devices based on BlackBerry platform
Abstract: The automatic construction of large, high-resolution
image vistas (mosaics) is an active area of research in the fields of
photogrammetry [1,2], computer vision [1,4], medical image
processing [4], computer graphics [3] and biometrics [8]. Image
stitching is one of the possible options to get image mosaics. Vista
Creation in image processing is used to construct an image with a
large field of view than that could be obtained with a single
photograph. It refers to transforming and stitching multiple images
into a new aggregate image without any visible seam or distortion in
the overlapping areas. Vista creation process aligns two partial
images over each other and blends them together. Image mosaics
allow one to compensate for differences in viewing geometry. Thus
they can be used to simplify tasks by simulating the condition in
which the scene is viewed from a fixed position with single camera.
While obtaining partial images the geometric anomalies like rotation,
scaling are bound to happen. To nullify effect of rotation of partial
images on process of vista creation, we are proposing rotation
invariant vista creation algorithm in this paper. Rotation of partial
image parts in the proposed method of vista creation may introduce
some missing region in the vista. To correct this error, that is to fill
the missing region further we have used image inpainting method on
the created vista. This missing view regeneration method also
overcomes the problem of missing view [31] in vista due to cropping,
irregular boundaries of partial image parts and errors in digitization
[35]. The method of missing view regeneration generates the missing
view of vista using the information present in vista itself.
Abstract: With increasing data in medical databases, medical
data retrieval is growing in popularity. Some of this analysis
including inducing propositional rules from databases using many
soft techniques, and then using these rules in an expert system.
Diagnostic rules and information on features are extracted from
clinical databases on diseases of congenital anomaly. This paper
explain the latest soft computing techniques and some of the
adaptive techniques encompasses an extensive group of methods
that have been applied in the medical domain and that are used for
the discovery of data dependencies, importance of features,
patterns in sample data, and feature space dimensionality
reduction. These approaches pave the way for new and interesting
avenues of research in medical imaging and represent an important
challenge for researchers.
Abstract: Voltage stability has become an important issue to many power systems around the world due to the weak systems and long line on power system networks. In this paper, MATLAB load flow program is applied to obtain the weak points in the system combined with finding the voltage stability limit. The maximum permissible loading of a system, within the voltage stability limit, is usually determined. The methods for varying tap ratio (using tap changing transformer) and applying different values of shunt capacitor injection to improve the voltage stability within the limit are also provided.
Abstract: To make the modulation classification system more suitable for signals in a wide range of signal to noise rate (SNR), a novel method of designing combined classifier based on fuzzy neural network (FNN) is presented in this paper. The method employs fuzzy neural network classifiers and interclass distance (ICD) to improve recognition reliability. Experimental results show that the proposed combined classifier has high recognition rate with large variation range of SNR (success rates are over 99.9% when SNR is not lower than 5dB).