Abstract: In this paper, multi-processors job shop scheduling problems are solved by a heuristic algorithm based on the hybrid of priority dispatching rules according to an ant colony optimization algorithm. The objective function is to minimize the makespan, i.e. total completion time, in which a simultanous presence of various kinds of ferons is allowed. By using the suitable hybrid of priority dispatching rules, the process of finding the best solution will be improved. Ant colony optimization algorithm, not only promote the ability of this proposed algorithm, but also decreases the total working time because of decreasing in setup times and modifying the working production line. Thus, the similar work has the same production lines. Other advantage of this algorithm is that the similar machines (not the same) can be considered. So, these machines are able to process a job with different processing and setup times. According to this capability and from this algorithm evaluation point of view, a number of test problems are solved and the associated results are analyzed. The results show a significant decrease in throughput time. It also shows that, this algorithm is able to recognize the bottleneck machine and to schedule jobs in an efficient way.
Abstract: In this paper we discuss on the security module for the
car appliances to prevent stealing and illegal use on other cars. We
proposed an open structure including authentication and encryption by
embed a security module in each to protect car appliances. Illegal
moving and use a car appliance with the security module without
permission will lead the appliance to useless. This paper also presents
the component identification and deal with relevant procedures. It is at
low cost to recover from destroys by the burglar. Expect this paper to
offer the new business opportunity to the automotive and technology
industry.
Abstract: A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.
Abstract: We have developed an analytic model for the radial pn-junction in a nanowire (NW) core-shell structure utilizing as a new
building block in different semiconductor devices. The potential distribution through the p-n-junction is calculated and the analytical expressions are derived to compute the depletion region widths. We
show that the widths of space charge layers, surrounding the core, are
the functions of core radius, which is the manifestation of so called classical size effect. The relationship between the depletion layer width and the built-in potential in the asymptotes of infinitely large
core radius transforms to square-root dependence specific for conventional planar p-n-junctions. The explicit equation is derived to
compute the capacitance of radial p-n-junction. The current-voltage behavior is also carefully determined taking into account the “short
base" effects.
Abstract: Modern highly automated production systems faces
problems of reliability. Machine function reliability results in
changes of productivity rate and efficiency use of expensive
industrial facilities. Predicting of reliability has become an important
research and involves complex mathematical methods and
calculation. The reliability of high productivity technological
automatic machines that consists of complex mechanical, electrical
and electronic components is important. The failure of these units
results in major economic losses of production systems. The
reliability of transport and feeding systems for automatic
technological machines is also important, because failure of transport
leads to stops of technological machines. This paper presents
reliability engineering on the feeding system and its components for
transporting a complex shape parts to automatic machines. It also
discusses about the calculation of the reliability parameters of the
feeding unit by applying the probability theory. Equations produced
for calculating the limits of the geometrical sizes of feeders and the
probability of sticking the transported parts into the chute represents
the reliability of feeders as a function of its geometrical parameters.
Abstract: The only relevant basis for the design of an educational application are objectives of learning for the content area. This study analyses the process in which the real – not only the formal – objectives could work as the starting point for the construction of an educational game. The application context is the education of perioperative nursing. The process is based on the panel discussions of nursing teachers. In the panels, the teachers elaborated the objectives. The transcribed discussions were analysed in terms of the conceptions of learning and teaching of perioperative nursing. The outcome of the study is first the elaborated objectives, which will be used in the implementation of an educational game for the needs of pre-, intra and post-operative nursing skills learning. Second, the study shows that different views of learning are necessary to be understood in order to design an appropriate educational application.
Abstract: We introduce a novel approach to measuring how
humans learn based on techniques from information theory and
apply it to the oriental game of Go. We show that the total amount
of information observable in human strategies, called the strategic
information, remains constant for populations of players of differing
skill levels for well studied patterns of play. This is despite the very
large amount of knowledge required to progress from the recreational
players at one end of our spectrum to the very best and most
experienced players in the world at the other and is in contrast to
the idea that having more knowledge might imply more 'certainty'
in what move to play next. We show this is true for very local
up to medium sized board patterns, across a variety of different
moves using 80,000 game records. Consequences for theoretical and
practical AI are outlined.
Abstract: The acoustic and articulatory properties of fricative speech sounds are being studied using magnetic resonance imaging (MRI) and acoustic recordings from a single subject. Area functions were derived from a complete set of axial and coronal MR slices using two different methods: the Mermelstein technique and the Blum transform. Area functions derived from the two techniques were shown to differ significantly in some cases. Such differences will lead to different acoustic predictions and it is important to know which is the more accurate. The vocal tract acoustic transfer function (VTTF) was derived from these area functions for each fricative and compared with measured speech signals for the same fricative and same subject. The VTTFs for /f/ in two vowel contexts and the corresponding acoustic spectra are derived here; the Blum transform appears to show a better match between prediction and measurement than the Mermelstein technique.
Abstract: Unsteady boundary layer flow of an incompressible
micropolar fluid over a stretching sheet when the sheet is stretched in
its own plane is studied in this paper. The stretching velocity is
assumed to vary linearly with the distance along the sheet. Two equal
and opposite forces are impulsively applied along the x-axis so that the
sheet is stretched, keeping the origin fixed in a micropolar fluid. The
transformed unsteady boundary layer equations are solved
numerically using the Keller-box method for the whole transient from
the initial state to final steady-state flow. Numerical results are
obtained for the velocity and microrotation distributions as well as the
skin friction coefficient for various values of the material parameter K.
It is found that there is a smooth transition from the small-time
solution to the large-time solution.
Abstract: This paper studies the effect of different compression
constraints and schemes presented in a new and flexible paradigm to
achieve high compression ratios and acceptable signal to noise ratios
of Arabic speech signals. Compression parameters are computed for
variable frame sizes of a level 5 to 7 Discrete Wavelet Transform
(DWT) representation of the signals for different analyzing mother
wavelet functions. Results are obtained and compared for Global
threshold and level dependent threshold techniques. The results
obtained also include comparisons with Signal to Noise Ratios, Peak
Signal to Noise Ratios and Normalized Root Mean Square Error.
Abstract: This study describes the relationship between motivation factors and academic performance among distance education students enrolled in a postgraduate nursing course. Students (n=96) participated in a survey that assesses student's motivational orientations from a cognitive perspective using a selfadministered questionnaire based on Pintrich-s Motivation Strategies for Learning Questionnaire (MLSQ). Results showed students- motivational factors are highest on task value (6.44, 0.71); followed by intrinsic goal orientation (6.20, 0.76), control beliefs (6.02, 0.89); extrinsic goal orientation (5.85, 1.13); self-efficacy for learning and performance (5.62, 0.84), and finally, test anxiety (4.21, 1.37). Weak positive correlations were found between academic performance and intrinsic goal orientation (r=0.13), extrinsic goal orientation (r=0.04), task value (r=0.09), control beliefs (r=0.02), and self-efficacy (r=0.05), while there was weak negative correlation with test anxiety (r=-0.04). Conclusions from the study indicate the need to focus on improving tasks and targeting intrinsic goal orientations of students to courses since these were positively correlated with academic performance and downplay the use of tests since these were negatively correlated with academic performance.
Abstract: Many studies have shown that Artificial Neural
Networks (ANN) have been widely used for forecasting financial
markets, because of many financial and economic variables are nonlinear,
and an ANN can model flexible linear or non-linear
relationship among variables.
The purpose of the study was to employ an ANN models to
predict the direction of the Istanbul Stock Exchange National 100
Indices (ISE National-100).
As a result of this study, the model forecast the direction of the
ISE National-100 to an accuracy of 74, 51%.
Abstract: Multi-Agent Systems (MAS) emerged in the pursuit to improve our standard of living, and hence can manifest complex human behaviors such as communication, decision making, negotiation and self-organization. The Social Network Services (SNSs) have attracted millions of users, many of whom have integrated these sites into their daily practices. The domains of MAS and SNS have lots of similarities such as architecture, features and functions. Exploring social network users- behavior through multiagent model is therefore our research focus, in order to generate more accurate and meaningful information to SNS users. An application of MAS is the e-Auction and e-Rental services of the Universiti Cyber AgenT(UniCAT), a Social Network for students in Universiti Tunku Abdul Rahman (UTAR), Kampar, Malaysia, built around the Belief- Desire-Intention (BDI) model. However, in spite of the various advantages of the BDI model, it has also been discovered to have some shortcomings. This paper therefore proposes a multi-agent framework utilizing a modified BDI model- Belief-Desire-Intention in Dynamic and Uncertain Situations (BDIDUS), using UniCAT system as a case study.
Abstract: This research elaborates decision models for product
innovation in the early phases, focusing on one of the most widely
implemented method in marketing research: conjoint analysis and the
related conjoint-based models with special focus on heuristics
programming techniques for the development of optimal product
innovation. The concept, potential, requirements and limitations of
conjoint analysis and its conjoint-based heuristics successors are
analysed and the development of conceptual framework of Genetic
Algorithm (GA) as one of the most widely implemented heuristic
methods for developing product innovations are discussed.
Abstract: This study aimed to explore future life orientation and
support that needed to accomplish it. A total of 258 participants are
Javanese high school student. The age of the sample ranges from 14
to 18 years old. Participants were asked about their future aspiration,
their reason of choosing them as important goals in their life, and
support that they need to accomplished their goals using open ended
questionnaire. The responses were categorized through content
analysis into four main categories. They are: (1) Self Fulfillment
(72.1%) (2) Parents and Family (16.7%) (3) Altruism (8.1%) (4)
Social and Economy Status (3.1%). Meanwhile, the categories for
support that they needed are shown as follows: (1) Affection Support
(64.7%) (2) Spiritual support (17.4%) (3) Material Support (10.9%)
(4) Guidance Support (7.0%). The research found that affection
support always gets the highest number in every future orientation
categories. It can be concluded that although Javanese adolescents
have different future orientation, they basically need affection
support.
Abstract: The grey oyster mushroom, Pleurotus sajor-caju
(PSC), is a common edible mushroom and is now grown
commercially around the world for food. This fungus has been
broadly used as food or food ingredients in various food products for
a long time. To enhance the nutritional quality and sensory attributes
of bakery-based products, PSC powder is used in the present study to
partially replace wheat flour in baked product formulations. The
nutrient content and sensory properties of rice-porridge and
unleavened bread (paratha) incorporated with various levels of PSC
powder were studied. These food items were formulated with either
0%, 2%, 4% or 6% of PSC powder. Results show PSC powder
recorded β-glucan at 3.57g/100g. In sensory evaluation, consumers
gave higher score to both rice-porridge and paratha bread containing
2-4% PSC compared to those that are not added with PSC powder.
The paratha containing 4% PSC powder can be formulated with the
intention in improving overall acceptability of paratha bread.
Meanwhile, for rice-porridge, consumers prefer the formulated
product added with 4% PSC powder. In conclusion, the addition of
PSC powder to partially wheat flour can be recommended for the
purpose of enhancing nutritional composition and maintaining the
acceptability of carbohydrate-based products.
Abstract: Grid computing provides a virtual framework for
controlled sharing of resources across institutional boundaries.
Recently, trust has been recognised as an important factor for
selection of optimal resources in a grid. We introduce a new method
that provides a quantitative trust value, based on the past interactions
and present environment characteristics. This quantitative trust value
is used to select a suitable resource for a job and eliminates run time
failures arising from incompatible user-resource pairs. The proposed
work will act as a tool to calculate the trust values of the various
components of the grid and there by improves the success rate of the
jobs submitted to the resource on the grid. The access to a resource
not only depend on the identity and behaviour of the resource but
also upon its context of transaction, time of transaction, connectivity
bandwidth, availability of the resource and load on the resource. The
quality of the recommender is also evaluated based on the accuracy
of the feedback provided about a resource. The jobs are submitted for
execution to the selected resource after finding the overall trust value
of the resource. The overall trust value is computed with respect to
the subjective and objective parameters.
Abstract: The hydrodynamics behavior of fluid flow in microconverging
plates is investigated analytically. Effects of Knudsen number () on the microchannel hydrodynamics behavior and the
coefficient of friction are investigated. It is found that as increases the slip in the hydrodynamic boundary condition increases.
Also, the coefficient of friction decreases as increases.
Abstract: The emerging Semantic Web has been attracted many
researchers and developers. New applications have been developed on top of Semantic Web and many supporting tools introduced to improve its software development process. Metadata modeling is one of development process where supporting tools exists. The existing
tools are lack of readability and easiness for a domain knowledge expert to graphically models a problem in semantic model. In this paper, a metadata modeling tool called RDFGraph is proposed. This
tool is meant to solve those problems. RDFGraph is also designed to work with modern database management systems that support RDF and to improve the performance of the query execution process. The
testing result shows that the rules used in RDFGraph follows the W3C standard and the graphical model produced in this tool is properly translated and correct.
Abstract: One problem in evaluating recent computational models of human category learning is that there is no standardized method for systematically comparing the models' assumptions or hypotheses. In the present study, a flexible general model (called GECLE) is introduced that can be used as a framework to systematically manipulate and compare the effects and descriptive validities of a limited number of assumptions at a time. Two example simulation studies are presented to show how the GECLE framework can be useful in the field of human high-order cognition research.