Abstract: In this paper, we use nonlinear system identification method to predict and detect process fault of a cement rotary kiln. After selecting proper inputs and output, an input-output model is identified for the plant. To identify the various operation points in the
kiln, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOLIMOT algorithm which is an incremental treestructure
algorithm. Then, by using this method, we obtained 3
distinct models for the normal and faulty situations in the kiln. One of the models is for normal condition of the kiln with 15 minutes
prediction horizon. The other two models are for the two faulty situations in the kiln with 7 minutes prediction horizon are presented.
At the end, we detect these faults in validation data. The data collected from White Saveh Cement Company is used for in this study.
Abstract: In this article, we introduce a new approach for
analyzing UML designs to detect the inconsistencies between
multiple state diagrams and sequence diagrams. The Super State
Analysis (SSA) identifies the inconsistencies in super states, single
step transitions, and sequences. Because SSA considers multiple
UML state diagrams, it discovers inconsistencies that cannot be
discovered when considering only a single UML state diagram. We
have introduced a transition set that captures relationship information
that is not specifiable in UML diagrams. The SSA model uses the
transition set to link transitions of multiple state diagrams together.
The analysis generates three different sets automatically. These sets
are compared to the provided sets to detect the inconsistencies. SSA
identifies five types of inconsistencies: impossible super states,
unreachable super states, illegal transitions, missing transitions, and
illegal sequences.
Abstract: The transient hydrodynamics and thermal behaviors of
fluid flow in open-ended vertical parallel-plate porous microchannel are investigated semi-analytically under the effect of the hyperbolic
heat conduction model. The model that combines both the continuum approach and the possibility of slip at the boundary is adopted in the
study. The Effects of Knudsen number , Darcy number , and thermal relaxation time on the microchannel hydrodynamics and thermal behaviors are investigated using the hyperbolic heat
conduction models. It is found that as increases the slip in the hydrodynamic and thermal boundary condition increases. This slip in
the hydrodynamic boundary condition increases as increases. Also, the slip in the thermal boundary condition increases as
decreases especially the early stage of time.
Abstract: When consistently innovative business-models can
give companies a competitive advantage, longitudinal empirical
research, which can reflect dynamic business-model changes, has yet
to prove a definitive connection. This study consequently employs a
dynamic perspective in conjunction with innovation theory to examine
the relationship between the types of business-model innovation and
firm value. This study tries to examine various types of
business-model innovation in high-end and low-end technology
industries such as HTC and the 7-Eleven chain stores with research
periods of 14 years and 32 years, respectively. The empirical results
suggest that adopting radical business-model innovation in addition to
expanding new target markets can successfully lead to a competitive
advantage. Sustained advanced technological competences and
service/product innovation are the key successful factors in high-end
and low-end technology industry business-models respectively. In
sum up, the business-model innovation can yield a higher market value
and financial value in high-end technology industries than low-end
ones.
Abstract: Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of features selection methods to reduce the dimensionality of the document-representation vector. Four feature selection methods are evaluated: Random Selection, Information Gain (IG), Support Vector Machine (called SVM_FS) and Genetic Algorithm with SVM (GA_FS). We showed that the best results were obtained with SVM_FS and GA_FS methods for a relatively small dimension of the features vector comparative with the IG method that involves longer vectors, for quite similar classification accuracies. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).
Abstract: Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.
Abstract: As the majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done on time especially for the critical applications. In this paper, we have explored the different predictor models to NASA-s public domain defect dataset coded in Perl programming language. Different machine learning algorithms belonging to the different learner categories of the WEKA project including Mamdani Based Fuzzy Inference System and Neuro-fuzzy based system have been evaluated for the modeling of maintenance severity or impact of fault severity. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results show that Neuro-fuzzy based model provides relatively better prediction accuracy as compared to other models and hence, can be used for the maintenance severity prediction of the software.
Abstract: Educational institutions often implement policies with
the intention of influencing how learning and teaching occur.
Generally, such policies are not as effective as their makers would
like; changing the behavior of third-level teachers proves difficult.
Nevertheless, a policy instituted in 2006 at the Dublin Institute of
Technology has met with success: each newly hired faculty member
must have a post-graduate qualification in “Learning and Teaching"
or successfully complete one within the first two years of
employment. The intention is to build teachers- knowledge about
student-centered pedagogies and their capacity to implement them.
As a result of this policy (and associated programs that support it),
positive outcomes are readily apparent. Individual teachers who have
completed the programs have implemented significant change at the
course and program levels. This paper introduces the policy,
identifies outcomes in relation to existing theory, describes research
underway, and pinpoints areas where organizational learning has
occurred.
Abstract: The effects of equilibrium time, solution pH, and
sorption temperature of cationic methylene blue (MB) adsorption on nanoporous metallosilicoaluminophosphate ZnAPSO-34 was studied
using a batch equilibration method. UV–VIS spectroscopy was used
to obtain the adsorption isotherms at 20° C. The optimum period for
adsorption was 300 min. However, MB removal increased from
81,82 % to 94,81 %. The equilibrium adsorption data was analyzed
by using Langmuir, Freundlich and Temkin isotherm models.
Langmuir isotherm was found to be the better-fitting model and the process followed pseudo second–order kinetics. The results showed
that ZnAPSO-34 could be employed as an effective material and could be an attractive alternative for the removal of dyes and colors
from aqueous solutions.
Abstract: Extraction of edge-end-pixels is an important step for the edge linking process to achieve edge-based image segmentation. This paper presents an algorithm to extract edge-end pixels together with their directional sensitivities as an augmentation to the currently available mathematical models. The algorithm is implemented in the Java environment because of its inherent compatibility with web interfaces since its main use is envisaged to be for remote image analysis on a virtual instrumentation platform.
Abstract: The belief decision tree (BDT) approach is a decision
tree in an uncertain environment where the uncertainty is represented
through the Transferable Belief Model (TBM), one interpretation
of the belief function theory. The uncertainty can appear either in
the actual class of training objects or attribute values of objects to
classify. In this paper, we develop a post-pruning method of belief
decision trees in order to reduce size and improve classification
accuracy on unseen cases. The pruning of decision tree has a
considerable intention in the areas of machine learning.
Abstract: Detection, feature extraction and pose estimation of
people in images and video is made challenging by the variability of
human appearance, the complexity of natural scenes and the high
dimensionality of articulated body models and also the important
field in Image, Signal and Vision Computing in recent years. In this
paper, four types of people in 2D dimension image will be tested and
proposed. The system will extract the size and the advantage of them
(such as: tall fat, short fat, tall thin and short thin) from image. Fat
and thin, according to their result from the human body that has been
extract from image, will be obtained. Also the system extract every
size of human body such as length, width and shown them in output.
Abstract: This study was conducted published to investigate
there liability of the equation pressure-impulse (PI) reinforced
concrete column inprevious studies. Equation involves three different
levels of damage criteria known as D =0. 2, D =0. 5 and D =0. 8.The
damage criteria known as a minor when 0-0.2, 0.2-0.5is known as
moderate damage, high damage known as 0.5-0.8, and 0.8-1 of the
structure is considered a failure. In this study, two types of reliability
analyzes conducted. First, using pressure-impulse equation with
different parameters. The parameters involved are the concrete
strength, depth, width, and height column, the ratio of longitudinal
reinforcement and transverse reinforcement ratio. In the first analysis
of the reliability of this new equation is derived to improve the
previous equations. The second reliability analysis involves three
types of columns used to derive the PI curve diagram using the
derived equation to compare with the equation derived from other
researchers and graph minimum standoff versus weapon yield
Federal Emergency Management Agency (FEMA). The results
showed that the derived equation is more accurate with FEMA
standards than previous researchers.
Abstract: There are only limited studies that directly correlate
the increase in reinforced concrete (RC) panel structural capacities in
resisting the blast loads with different RC panel structural properties
in terms of blast loading characteristics, RC panel dimensions, steel
reinforcement ratio and concrete material strength. In this paper,
numerical analyses of dynamic response and damage of the one-way
RC panel to blast loads are carried out using the commercial software
LS-DYNA. A series of simulations are performed to predict the blast
response and damage of columns with different level and magnitude
of blast loads. The numerical results are used to develop pressureimpulse
(P-I) diagrams of one-way RC panels. Based on the
numerical results, the empirical formulae are derived to calculate the
pressure and impulse asymptotes of the P-I diagrams of RC panels.
The results presented in this paper can be used to construct P-I
diagrams of RC panels with different concrete and reinforcement
properties. The P-I diagrams are very useful to assess panel capacities
in resisting different blast loads.
Abstract: With increasing utilization of the wireless devices in
different fields such as medical devices and industrial fields, the
paper presents a method for simplify the Bluetooth packets with
throughput enhancing. The paper studies a vital issue in wireless
communications, which is the throughput of data over wireless
networks. In fact, the Bluetooth and ZigBee are a Wireless Personal
Area Network (WPAN). With taking these two systems competition
consideration, the paper proposes different schemes for improve the
throughput of Bluetooth network over a reliable channel. The
proposition depends on the Channel Quality Driven Data Rate
(CQDDR) rules, which determines the suitable packet in the
transmission process according to the channel conditions. The
proposed packet is studied over additive White Gaussian Noise
(AWGN) and fading channels. The Experimental results reveal the
capability of extension of the PL length by 8, 16, 24 bytes for classic
and EDR packets, respectively. Also, the proposed method is suitable
for the low throughput Bluetooth.
Abstract: A new code synchronization algorithm is proposed in
this paper for the secondary cell-search stage in wideband CDMA
systems. Rather than using the Cyclically Permutable (CP) code in the
Secondary Synchronization Channel (S-SCH) to simultaneously
determine the frame boundary and scrambling code group, the new
synchronization algorithm implements the same function with less
system complexity and less Mean Acquisition Time (MAT). The
Secondary Synchronization Code (SSC) is redesigned by splitting into
two sub-sequences. We treat the information of scrambling code group
as data bits and use simple time diversity BCH coding for further
reliability. It avoids involved and time-costly Reed-Solomon (RS)
code computations and comparisons. Analysis and simulation results
show that the Synchronization Error Rate (SER) yielded by the new
algorithm in Rayleigh fading channels is close to that of the
conventional algorithm in the standard. This new synchronization
algorithm reduces system complexities, shortens the average
cell-search time and can be implemented in the slot-based cell-search
pipeline. By taking antenna diversity and pipelining correlation
processes, the new algorithm also shows its flexible application in
multiple antenna systems.
Abstract: Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This article presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data and historical electric load-related data using the data from the calendar years 2001, 2002, 2003, and 2004 for training. The model tested for one week at five different seasons, typically, winter, spring, summer, Ramadan and fall seasons, and the mean absolute average error for one hour-ahead load forecasting found 1.12%.
Abstract: The use of Electronic Commerce (EC)
technologies enables Small Medium Enterprises (SMEs) to improve their efficiency and competitive position. Much of the literature proposes an extensive set of benefits for
organizations that choose to adopt and implement ECommerce
systems. Factors of Business –to-business (B2B)
E-Commerce adoption and implementation have been
extensively investigated. Despite enormous attention given to encourage Small Medium Enterprises (SMEs) to adopt and
implement E-Commerce, little research has been carried out in identifying the factors of Business-to-Consumer ECommerce adoption and implementation for SMEs. To conduct the study, Tornatsky and Fleischer model was adopted
and tested in four SMEs located in Christchurch, New
Zealand. This paper explores the factors that impact the
decision and method of adoption and implementation of ECommerce
systems in automobile industry. Automobile
industry was chosen because the product they deal with i.e.
cars are not a common commodity to be sold online, despite this fact the eCommerce penetration in automobile industry is
high. The factors that promote adoption and implementation of
E-Commerce technologies are discussed, together with the
barriers. This study will help SME owners to effectively
handle the adoption and implementation process and will also
improve the chance of successful E-Commerce
implementation. The implications of the findings for
managers, consultants, and government organizations engaged in promoting E-Commerce adoption and implementation in
small businesses and future research are discussed.
Abstract: An experiment was conducted with 80 unsexed
broilers of the Arbor Acress strain to determine the capability of a
carrot and fruit juice wastes mixture (carrot, apple, manggo, avocado,
orange, melon and Dutch egg plant) in the same proportion for
replacing corn in broiler diet. This study involved a completely
randomized design (CRD) with 5 treatments (0, 5, 10, 15, and 20% of
juice wastes mixture in diets) and 4 replicates per treatment. Diets
were isonitrogenous (22% crude protein) and isocaloric (3000 kcal/kg
diet). Measured variables were feed consumption, average daily
gain, feed conversion, as well as percentages of abdominal fat pad,
carcass, digestive organs (liver, pancreas and gizzard), and heart.
Data were analyzed by analysis of variance for CRD. Increasing
juice wastes mixture levels in diets increased feed consumption
(P
Abstract: Numerous concrete structures projects are currently running in Libya as part of a US$50 billion government funding. The
quality of concrete used in 20 different construction projects were assessed based mainly on the concrete compressive strength achieved. The projects are scattered all over the country and are at
various levels of completeness. For most of these projects, the
concrete compressive strength was obtained from test results of a
150mm standard cube mold. Statistical analysis of collected concrete
compressive strengths reveals that the data in general followed a
normal distribution pattern. The study covers comparison and assessment of concrete quality aspects such as: quality control, strength range, data standard deviation, data scatter, and ratio of minimum strength to design strength. Site quality control for these projects ranged from very good to poor according to ACI214 criteria [1]. The ranges (Rg) of the strength (max. strength – min. strength) divided by average strength are from (34% to 160%). Data scatter is
measured as the range (Rg) divided by standard deviation () and is
found to be (1.82 to 11.04), indicating that the range is ±3σ.
International construction companies working in Libya follow
different assessment criteria for concrete compressive strength in lieu
of national unified procedure. The study reveals that assessments of
concrete quality conducted by these construction companies usually
meet their adopted (internal) standards, but sometimes fail to meet
internationally known standard requirements. The assessment of
concrete presented in this paper is based on ACI, British standards
and proposed Libyan concrete strength assessment criteria.