Abstract: Artificial Intelligence based gaming is an interesting topic in the state-of-art technology. This paper presents an automation of a tradition Omani game, called Al-Hawalees. Its related issues are resolved and implemented using artificial intelligence approach. An AI approach called mini-max procedure is incorporated to make a diverse budges of the on-line gaming. If number of moves increase, time complexity will be increased in terms of propositionally. In order to tackle the time and space complexities, we have employed a back propagation neural network (BPNN) to train in off-line to make a decision for resources required to fulfill the automation of the game. We have utilized Leverberg- Marquardt training in order to get the rapid response during the gaming. A set of optimal moves is determined by the on-line back propagation training fashioned with alpha-beta pruning. The results and analyses reveal that the proposed scheme will be easily incorporated in the on-line scenario with one player against the system.
Abstract: This paper presents a new problem solving approach
that is able to generate optimal policy solution for finite-state
stochastic sequential decision-making problems with high data
efficiency. The proposed algorithm iteratively builds and improves
an approximate Markov Decision Process (MDP) model along with
cost-to-go value approximates by generating finite length trajectories
through the state-space. The approach creates a synergy between an
approximate evolving model and approximate cost-to-go values to
produce a sequence of improving policies finally converging to the
optimal policy through an intelligent and structured search of the
policy space. The approach modifies the policy update step of the
policy iteration so as to result in a speedy and stable convergence to
the optimal policy. We apply the algorithm to a non-holonomic
mobile robot control problem and compare its performance with
other Reinforcement Learning (RL) approaches, e.g., a) Q-learning,
b) Watkins Q(λ), c) SARSA(λ).
Abstract: The quality of short term load forecasting can improve the efficiency of planning and operation of electric utilities. Artificial Neural Networks (ANNs) are employed for nonlinear short term load forecasting owing to their powerful nonlinear mapping capabilities. At present, there is no systematic methodology for optimal design and training of an artificial neural network. One has often to resort to the trial and error approach. This paper describes the process of developing three layer feed-forward large neural networks for short-term load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. Particle Swarm Optimization (PSO) is used to develop the optimum large neural network structure and connecting weights for one-day ahead electric load forecasting problem. PSO is a novel random optimization method based on swarm intelligence, which has more powerful ability of global optimization. Employing PSO algorithms on the design and training of ANNs allows the ANN architecture and parameters to be easily optimized. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. The experimental results show that the proposed method optimized by PSO can quicken the learning speed of the network and improve the forecasting precision compared with the conventional Back Propagation (BP) method. Moreover, it is not only simple to calculate, but also practical and effective. Also, it provides a greater degree of accuracy in many cases and gives lower percent errors all the time for STLF problem compared to BP method. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.
Abstract: This paper presents the effectiveness of artificial
intelligent technique to apply for pattern recognition and
classification of Partial Discharge (PD). Characteristics of PD signal
for pattern recognition and classification are computed from the
relation of the voltage phase angle, the discharge magnitude and the
repeated existing of partial discharges by using statistical and fractal
methods. The simplified fuzzy ARTMAP (SFAM) is used for pattern
recognition and classification as artificial intelligent technique. PDs
quantities, 13 parameters from statistical method and fractal method
results, are inputted to Simplified Fuzzy ARTMAP to train system
for pattern recognition and classification. The results confirm the
effectiveness of purpose technique.
Abstract: This paper deals with the design of a periodic output
feedback controller for a flexible beam structure modeled with
Timoshenko beam theory, Finite Element Method, State space
methods and embedded piezoelectrics concept. The first 3 modes are
considered in modeling the beam. The main objective of this work is
to control the vibrations of the beam when subjected to an external
force. Shear piezoelectric sensors and actuators are embedded into
the top and bottom layers of a flexible aluminum beam structure, thus
making it intelligent and self-adaptive. The composite beam is
divided into 5 finite elements and the control actuator is placed at
finite element position 1, whereas the sensor is varied from position 2
to 5, i.e., from the nearby fixed end to the free end. 4 state space
SISO models are thus developed. Periodic Output Feedback (POF)
Controllers are designed for the 4 SISO models of the same plant to
control the flexural vibrations. The effect of placing the sensor at
different locations on the beam is observed and the performance of
the controller is evaluated for vibration control. Conclusions are
finally drawn.
Abstract: In this paper we propose a novel method for human
face segmentation using the elliptical structure of the human head. It
makes use of the information present in the edge map of the image.
In this approach we use the fact that the eigenvalues of covariance
matrix represent the elliptical structure. The large and small
eigenvalues of covariance matrix are associated with major and
minor axial lengths of an ellipse. The other elliptical parameters are
used to identify the centre and orientation of the face. Since an
Elliptical Hough Transform requires 5D Hough Space, the Circular
Hough Transform (CHT) is used to evaluate the elliptical parameters.
Sparse matrix technique is used to perform CHT, as it squeeze zero
elements, and have only a small number of non-zero elements,
thereby having an advantage of less storage space and computational
time. Neighborhood suppression scheme is used to identify the valid
Hough peaks. The accurate position of the circumference pixels for
occluded and distorted ellipses is identified using Bresenham-s
Raster Scan Algorithm which uses the geometrical symmetry
properties. This method does not require the evaluation of tangents
for curvature contours, which are very sensitive to noise. The method
has been evaluated on several images with different face orientations.
Abstract: This research explores visitor-s expectations of service
quality in intelligent living space showroom – Living 3.0 in Taiwan.
Based on the five dimensions of PZB service quality, a specialist
questionnaire is utilized to establish a complete service quality
evaluation framework for Living 3.0. In this research, analysis
hierarchy process (AHP) is applied to find the relative weights among
the criteria. Finally, the service quality evaluation framework and
evaluation results can be used as a guide for Living 3.0 proprietors to
review, improve, and enhance service planning and service qualities in
the future.
Abstract: The in vitro culture procedure of purple nutsedge
(Cyperus rotundus L.) for multiple shoot induction and tuber
formation was established. Multiple shoots were significantly
induced from a single shoot of about 0.5 – 0.8 cm long, on Murashige
and Skoog (MS) medium supplemented with 4.44 μM 6-
benzyladinine (BA) alone or in combination with 2.85 μM 1-
indoleacetic acid (IAA), providing 17.6 and 15.3 shoots per explant
with 31.2 and 27.5 leaves per explant, respectively, within 6 weeks of
culturing. Moreover, MS medium supplemented with 4.44 μM BA
and 2.85 μM IAA was suitable for tuber induction, obtaining 5.9
tubers with 3.4 rhizomes per explant. In combination with ancymidol
and higher concentration of sucrose, 11.1 μM BA and 60 g/L sucrose
or 11.1 μM BA, 7.8 μM ancymidol and 60 g/L sucrose induced 3.5
tubers with 1.6 rhizomes or 3.5 tubers without rhizome, respectively.
However, MS medium containing 3.9 or 7.8 μM ancymidol in
combination with either 60 or 80 g/L sucrose enchanced significant
root formation at 20.9 – 23.6 roots per explant.
Abstract: Agropyron cristatum L. Gaertn. is a native grass of
semiarid region in Iran which is quit resistant to cool and drought
climate and withstand heavy grazing. This species has close
phylogenetic relationship with Triticum and Hordeum. In this
research, the effect of seven different concentrations of growth
regulator 2,4-D on callus production and somatic embryogenesis of
A. cristatum was investigated on Murashige and Skoog medium. The
results showed that the rate of callus, embryo and neomorph were
highest in 1 mg L-1 2,4-D. Callus production was increased in 1 mg
L-1 2,4-D but dramatically decreased at 5.5 and 9 mg L-1 2,4-D. The
somatic embryos were observed at 1 and 4 mg L-1 2,4-D but matured
embryos and plantlet were only occurred at 1 mg L-1 2,4-D. There
were significant differences between 1 mg L-1 2,4-D and other
treatments for producing globular and torpedo embryos, plantlet,
rooted callus and number of roots (p
Abstract: This study employs the use of the fourth order
Numerov scheme to determine the eigenstates and eigenvalues of
particles, electrons in particular, in single and double delta function
potentials. For the single delta potential, it is found that the
eigenstates could only be attained by using specific potential depths.
The depth of the delta potential well has a value that varies depending
on the delta strength. These depths are used for each well on the
double delta function potential and the eigenvalues are determined.
There are two bound states found in the computation, one with a
symmetric eigenstate and another one which is antisymmetric.
Abstract: We introduce an extended resource leveling model that abstracts real life projects that consider specific work ranges for each resource. Contrary to traditional resource leveling problems this model considers scarce resources and multiple objectives: the minimization of the project makespan and the leveling of each resource usage over time. We formulate this model as a multiobjective optimization problem and we propose a multiobjective genetic algorithm-based solver to optimize it. This solver consists in a two-stage process: a main stage where we obtain non-dominated solutions for all the objectives, and a postprocessing stage where we seek to specifically improve the resource leveling of these solutions. We propose an intelligent encoding for the solver that allows including domain specific knowledge in the solving mechanism. The chosen encoding proves to be effective to solve leveling problems with scarce resources and multiple objectives. The outcome of the proposed solvers represent optimized trade-offs (alternatives) that can be later evaluated by a decision maker, this multi-solution approach represents an advantage over the traditional single solution approach. We compare the proposed solver with state-of-art resource leveling methods and we report competitive and performing results.
Abstract: The OTOP Entrepreneurship that used to create
substantial source of income for local Thai communities are now in a
stage of exigent matters that required assistances from public sectors
due to over Entrepreneurship of duplicative ideas, unable to adjust
costs and prices, lack of innovation, and inadequate of quality
control. Moreover, there is a repetitive problem of middlemen who
constantly corner the OTOP market. Local OTOP producers become
easy preys since they do not know how to add more values, how to
create and maintain their own brand name, and how to create proper
packaging and labeling. The suggested solutions to local OTOP
producers are to adopt modern management techniques, to find
knowhow to add more values to products and to unravel other
marketing problems. The objectives of this research are to study the
prevalent OTOP products management and to discover direction to
manage OTOP products to enhance the effectiveness of OTOP
Entrepreneurship in Nonthaburi Province, Thailand. There were 113
participants in this study. The research tools can be divided into two
parts: First part is done by questionnaire to find responses of the
prevalent OTOP Entrepreneurship management. Second part is the
use of focus group which is conducted to encapsulate ideas and local
wisdom. Data analysis is performed by using frequency, percentage,
mean, and standard deviation as well as the synthesis of several small
group discussions. The findings reveal that 1) Business Resources:
the quality of product is most important and the marketing of product
is least important. 2) Business Management: Leadership is most
important and raw material planning is least important. 3) Business
Readiness: Communication is most important and packaging is least
important. 4) Support from public sector: Certified from the
government is most important and source of raw material is the least
important.
Abstract: Cooling with sound is a physical phenomenon allowed by Thermo-Acoustics in which acoustic energy is transformed into a negative heat transfer, in other words: into cooling! Without needing any harmful gas, the transformation is environmentally friendly and can respond to many needs in terms of air conditioning, food refrigeration for domestic use, and cooling medical samples for example. To explore the possibilities of this cooling solution on a small scale, the TACS prototype has been designed, consisting of a low cost thermoacoustic refrigerant “pipe” able to lower the temperature by a few degrees. The obtained results are providing an interesting element for possible future of thermo-acoustic refrigeration.
Abstract: There are several ways of improving the performance of a vapor compression refrigeration cycle. Use of an ejector as expansion device is one of the alternative ways. The present paper aims at evaluate the performance improvement of a vapor compression refrigeration cycle under a wide range of operating conditions. A numerical model is developed and a parametric study of important parameters such as condensation (30-50°C) and evaporation temperatures (-20-5°C), nozzle and diffuser efficiencies (0.75-0.95), subcooling and superheating degrees (0-15K) are investigated. The model verification gives a good agreement with the literature data. The simulation results revealed that condensation temperature has the highest effect (129%) on the performance improvement ratio while superheating has the lowest one (6.2%). Among ejector efficiencies, the diffuser efficiency has a significant effect on the COP of ejector expansion refrigeration cycle. The COP improvement percentage decreases from 10.9% to 4.6% as subcooling degrees increases by 15K.
Abstract: This paper presents a distributed intrusion
detection system IDS, based on the concept of specialized
distributed agents community representing agents with the
same purpose for detecting distributed attacks. The semantic of
intrusion events occurring in a predetermined network has been
defined. The correlation rules referring the process which our
proposed IDS combines the captured events that is distributed
both spatially and temporally. And then the proposed IDS tries
to extract significant and broad patterns for set of well-known
attacks. The primary goal of our work is to provide intrusion
detection and real-time prevention capability against insider
attacks in distributed and fully automated environments.
Abstract: We have proposed an information filtering system
using index word selection from a document set based on the
topics included in a set of documents. This method narrows
down the particularly characteristic words in a document set
and the topics are obtained by Sparse Non-negative Matrix
Factorization. In information filtering, a document is often
represented with the vector in which the elements correspond
to the weight of the index words, and the dimension of the
vector becomes larger as the number of documents is
increased. Therefore, it is possible that useless words as index
words for the information filtering are included. In order to
address the problem, the dimension needs to be reduced. Our
proposal reduces the dimension by selecting index words
based on the topics included in a document set. We have
applied the Sparse Non-negative Matrix Factorization to the
document set to obtain these topics. The filtering is carried out
based on a centroid of the learning document set. The centroid
is regarded as the user-s interest. In addition, the centroid is
represented with a document vector whose elements consist of
the weight of the selected index words. Using the English test
collection MEDLINE, thus, we confirm the effectiveness of
our proposal. Hence, our proposed selection can confirm the
improvement of the recommendation accuracy from the other
previous methods when selecting the appropriate number of
index words. In addition, we discussed the selected index
words by our proposal and we found our proposal was able to
select the index words covered some minor topics included in
the document set.
Abstract: In this paper, we describe a rule-based message passing method to support developing collaborative applications, in which multiple users share resources in distributed environments. Message communications of applications in collaborative environments tend to be very complex because of the necessity to manage context situations such as sharing events, access controlling of users, and network places. In this paper, we propose a message communications method based on unification of artificial intelligence and logic programming for defining rules of such context information in a procedural object-oriented programming language. We also present an implementation of the method as java classes.
Abstract: The alternative technique for sterilization of culture
medium to replace autoclaving was carried out. For sterilization of
culture medium without autoclaving, some commercial pure essential
oils, bergamot oil, betel oil, cinnamon oil, lavender oil and turmeric
oil, were tested alone or in combinations with some disinfectants,
10% povidone-iodine and 2% iodine + 2.4% potassium iodide. Each
essential oil or combination was added to 25-mL Murashige and
Skoog (MS) medium before medium was solidified in a 120-mL
container, kept for 2 weeks before evaluating sterile conditions.
Treated media, supplemented with essential oils, were compared to
control medium, autoclaved at 121 degree Celsius for 15 min. In
vitro sterile conditions were found 20 – 100% from these treated
media compared to 100% sterile condition from autoclaved medium.
Treated media obtained 100% sterile conditions were chosen for
culturing chrysanthemum shoots. It was found that 10% povidoneiodine
in combination with cinnamon oil (3:1) and 2% iodine + 2.4%
potassium iodide in combination with lavender oil (1:3) at the
concentration of 36 3L/25 mL medium provided the promising
growth of shoot explants.
Abstract: Using electrical machine in conventional vehicles, also called hybrid vehicles, has become a promising control scheme that enables some manners for fuel economy and driver assist for better stability. In this paper, vehicle stability control, fuel economy and Driving/Regeneration braking for a 4WD hybrid vehicle is investigated by using an electrical machine on each non-driven wheels. In front wheels driven vehicles, fuel economy and regenerative braking can be obtained by summing torques applied on rear wheels. On the other hand, unequal torques applied to rear wheels provides enhanced safety and path correction in steering. In this paper, a model with fourteen degrees of freedom is considered for vehicle body, tires and, suspension systems. Thereafter, powertrain subsystems are modeled. Considering an electrical machine on each rear wheel, a fuzzy controller is designed for each driving, braking, and stability conditions. Another fuzzy controller recognizes the vehicle requirements between the driving/regeneration and stability modes. Intelligent vehicle control to multi objective operation and forward simulation are the paper advantages. For reaching to these aims, power management control and yaw moment control will be done by three fuzzy controllers. Also, the above mentioned goals are weighted by another fuzzy sub-controller base on vehicle dynamic. Finally, Simulations performed in MATLAB/SIMULINK environment show that the proposed structure can enhance the vehicle performance in different modes effectively.
Abstract: Antifungal activities of ether and methanolic extracts of volatiles oils of Nigella Sativa seeds were tested against pathogenic bacterias and fungies strains.The volatile oil were found to have significant antifungal and antibacterial activities compare to tetracycline, cefuroxime and ciprofloxacin positive controls.The ether and methanolic esxtracts were compared to each other for antifungal and antibacterial activities and ether extracts showed stonger activity than methanolic one.