Abstract: Turbine blade cooling is considered as the most
effective way of maintaining high operating temperature making use
of the available materials, and turbine systems with wet compression
have a potential for future power generation because of high efficiency
and high specific power with a relatively low cost. In this paper
performance analysis of wet-compression gas turbine cycle with
turbine blade cooling is carried out. The wet compression process is
analytically modeled based on non-equilibrium droplet evaporation.
Special attention is paid for the effects of pressure ratio and water
injection ratio on the important system variables such as ratio of
coolant fluid flow, fuel consumption, thermal efficiency and specific
power. Parametric studies show that wet compression leads to
insignificant improvement in thermal efficiency but significant
enhancement of specific power in gas turbine systems with turbine
blade cooling.
Abstract: Renewable energy resources are inexhaustible, clean as compared with conventional resources. Also, it is used to supply regions with no grid, no telephone lines, and often with difficult accessibility by common transport. Satellite earth stations which located in remote areas are the most important application of renewable energy. Neural control is a branch of the general field of intelligent control, which is based on the concept of artificial intelligence. This paper presents the mathematical modeling of satellite earth station power system which is required for simulating the system.Aswan is selected to be the site under consideration because it is a rich region with solar energy. The complete power system is simulated using MATLAB–SIMULINK.An artificial neural network (ANN) based model has been developed for the optimum operation of earth station power system. An ANN is trained using a back propagation with Levenberg–Marquardt algorithm. The best validation performance is obtained for minimum mean square error. The regression between the network output and the corresponding target is equal to 96% which means a high accuracy. Neural network controller architecture gives satisfactory results with small number of neurons, hence better in terms of memory and time are required for NNC implementation. The results indicate that the proposed control unit using ANN can be successfully used for controlling the satellite earth station power system.
Abstract: Alternative energy is any energy source that is an alternative to fossil fuel. These alternatives are intended to address concerns about such fossil fuels. Today, because of the variety of energy choices and differing goals of their advocates, defining some energy types as "alternative" is highly controversial. Most of the recent and existing alternative sources of energy are discussed below
Abstract: This paper was to study the clothes dryer using waste
heat from a split type air conditioner with a capacity of 12,648 btu/h.
The drying chamber had a minimum cross section area with the size
of 0.5 x 1.0 m2. The chamber was constructed by sailcloth and was
inside folded with aluminium foil. Then, it was connected to the
condensing unit of an air conditioner. The experiment was carried out
in two aspects which were the clothes drying with and without
auxiliary fan unit. The results showed that the drying rate of clothes
in the chamber installed with and without auxiliary fan unit were
2.26 and 1.1 kg/h, respectively. In case of the chamber installed with
a auxiliary fan unit, the additional power of 0.011 kWh was
consumed and the drying rate was higher than that of clothes drying
without auxiliary fan unit. Without auxiliary fan unit installation, no
energy was required but there was a portion of hot air leaks away
through the punctured holes at the wall of the drying chamber, hence
the drying rate was dropped below. The drying rate of clothes drying
using waste heat was higher than natural indoor drying and
commercial dryer which their drying rate were 0.17 and 1.9 kg/h,
respectively. It was noted that the COP of the air conditioner did not
change during the operating of clothes drying.
Abstract: The paper presents the results of microhardness and
microstructure of low carbon steel surface melted using carbon
dioxide laser with a wavelength of 10.6μm and a maximum output
power of 2000W. The processing parameters such as the laser power,
and the scanning rate were investigated in this study. After surface
melting two distinct regions formed corresponding to the melted zone
MZ, and the heat affected zone HAZ. The laser melted region
displayed a cellular fine structures while the HAZ displayed
martensite or bainite structure. At different processing parameters,
the original microstructure of this steel (Ferrite+Pearlite) has been
transformed to new phases of martensitic and bainitic structures. The
fine structure and the high microhardness are evidence of the high
cooling rates which follow the laser melting. The melting pool and
the transformed microstructure in the laser surface melted region of
carbon steel showed clear dependence on laser power and scanning
rate.
Abstract: The article presents the whole model of IS/IT
architecture exception governance. As first, the assumptions of
presented model are set. As next, there is defined a generic
governance model that serves as a basis for the architecture exception
governance. The architecture exception definition and its attributes
follow. The model respects well known approaches to the area that
are described in the text, but it adopts higher granularity in
description and expands the process view with all the next necessary
governance components as roles, principles and policies, tools to
enable the implementation of the model into organizations. The
architecture exception process is decomposed into a set of processes
related to the architecture exception lifecycle consisting of set of
phases and architecture exception states. Finally, there is information
about my future research related to this area.
Abstract: Humic acids (HAs) have been shown to activate some
ion uptakes along with stimulating the lateral roots at effective
concentration of micronutrients. However, the effects of HA on ion
adsorption by plant roots are not easily explainable due to the
varieties of HAs that differ from origins. Therefore, this study was
aimed to investigate the effect of various concentrations of HA
obtained from the compost derived from mix manures and some
agricultural wastes on the growth of eggplant seedlings (Solanum
melongena L. cv. Chao Praya) in tissue cultures at low nutrient level.
Egg plant seeds were surfaced sterilized and germinated in ½
Murashige and Skoog medium (MS) without HA added or in ¼ MS
supplemented with 0, 25, 50, 75 and 100 ppm of HAs. Then, they
were cultured for 4 weeks under the controlled environment. The
results showed that seedlings grown on ¼MS supplemented with
HAs at the concentration of 25 and 50 ppm had the average plant
heights (2.49 and 2.28 cm, respectively) higher than the other
treatments. Both treatments also significantly showed the maximum
average fresh and dry weights (p
Abstract: The effect of the discontinuity of the rail ends and the
presence of lower modulus insulation material at the gap to the
variations of stresses in the insulated rail joint (IRJ) is presented. A
three-dimensional wheel – rail contact model in the finite element
framework is used for the analysis. It is shown that the maximum stress
occurs in the subsurface of the railhead when the wheel contact occurs
far away from the rail end and migrates to the railhead surface as the
wheel approaches the rail end; under this condition, the interface
between the rail ends and the insulation material has suffered
significantly increased levels of stress concentration. The ratio of the
elastic modulus of the railhead and insulation material is found to alter
the levels of stress concentration. Numerical result indicates that a
higher elastic modulus insulating material can reduce the stress
concentration in the railhead but will generate higher stresses in the
insulation material, leading to earlier failure of the insulation material
Abstract: Markov games are a generalization of Markov
decision process to a multi-agent setting. Two-player zero-sum
Markov game framework offers an effective platform for designing
robust controllers. This paper presents two novel controller design
algorithms that use ideas from game-theory literature to produce
reliable controllers that are able to maintain performance in presence
of noise and parameter variations. A more widely used approach for
controller design is the H∞ optimal control, which suffers from high
computational demand and at times, may be infeasible. Our approach
generates an optimal control policy for the agent (controller) via a
simple Linear Program enabling the controller to learn about the
unknown environment. The controller is facing an unknown
environment, and in our formulation this environment corresponds to
the behavior rules of the noise modeled as the opponent. Proposed
controller architectures attempt to improve controller reliability by a
gradual mixing of algorithmic approaches drawn from the game
theory literature and the Minimax-Q Markov game solution
approach, in a reinforcement-learning framework. We test the
proposed algorithms on a simulated Inverted Pendulum Swing-up
task and compare its performance against standard Q learning.
Abstract: The study of the interaction between humans and
computers has been emerging during the last few years. This
interaction will be more powerful if computers are able to perceive
and respond to human nonverbal communication such as emotions. In
this study, we present the image-based approach to emotion
classification through lower facial expression. We employ a set of
feature points in the lower face image according to the particular face
model used and consider their motion across each emotive expression
of images. The vector of displacements of all feature points input to
the Adaptive Support Vector Machines (A-SVMs) classifier that
classify it into seven basic emotions scheme, namely neutral, angry,
disgust, fear, happy, sad and surprise. The system was tested on the
Japanese Female Facial Expression (JAFFE) dataset of frontal view
facial expressions [7]. Our experiments on emotion classification
through lower facial expressions demonstrate the robustness of
Adaptive SVM classifier and verify the high efficiency of our
approach.
Abstract: Wireless Sensor Networks (WSNs) have attracted the attention of many researchers. This has resulted in their rapid integration in very different areas such as precision agriculture,environmental monitoring, object and event detection and military surveillance. Due to the current WSN characteristics this technology is specifically useful in industrial areas where security, reliability and autonomy are basic, such as nuclear power plants, chemical plants, and others. In this paper we present a system based on WSNs to monitor environmental conditions around and inside a nuclear power plant, specifically, radiation levels. Sensor nodes, equipped with radiation sensors, are deployed in fixed positions throughout the plant. In addition, plant staff are also equipped with mobile devices with higher capabilities than sensors such as for example PDAs able to monitor radiation levels and other conditions around them. The system enables communication between PDAs, which form a Mobile Ad-hoc Wireless Network (MANET), and allows workers to monitor remote conditions in the plant. It is particularly useful during stoppage periods for inspection or in the event of an accident to prevent risk situations.
Abstract: This paper proposes the novel model order
formulation scheme to design a discrete PID controller for higher
order linear time invariant discrete systems. Modified PSO (MPSO)
based model order formulation technique has used to obtain the
successful formulated second order system. PID controller is tuned to
meet the desired performance specification by using pole-zero
cancellation and proposed design procedures. Proposed PID
controller is attached with both higher order system and formulated
second order system. System specifications are tabulated and closed
loop response is observed for stabilization process. The proposed
method is illustrated through numerical examples from literature.
Abstract: Over the past decades, automatic face recognition has become a highly active research area, mainly due to the countless application possibilities in both the private as well as the public sector. Numerous algorithms have been proposed in the literature to cope with the problem of face recognition, nevertheless, a group of methods commonly referred to as appearance based have emerged as the dominant solution to the face recognition problem. Many comparative studies concerned with the performance of appearance based methods have already been presented in the literature, not rarely with inconclusive and often with contradictory results. No consent has been reached within the scientific community regarding the relative ranking of the efficiency of appearance based methods for the face recognition task, let alone regarding their susceptibility to appearance changes induced by various environmental factors. To tackle these open issues, this paper assess the performance of the three dominant appearance based methods: principal component analysis, linear discriminant analysis and independent component analysis, and compares them on equal footing (i.e., with the same preprocessing procedure, with optimized parameters for the best possible performance, etc.) in face verification experiments on the publicly available XM2VTS database. In addition to the comparative analysis on the XM2VTS database, ten degraded versions of the database are also employed in the experiments to evaluate the susceptibility of the appearance based methods on various image degradations which can occur in "real-life" operating conditions. Our experimental results suggest that linear discriminant analysis ensures the most consistent verification rates across the tested databases.
Abstract: In this paper, we proposed a method to classify each
type of natural rock texture. Our goal is to classify 26 classes of rock
textures. First, we extract five features of each class by using
principle component analysis combining with the use of applied
spatial frequency measurement. Next, the effective node number of
neural network was tested. We used the most effective neural
network in classification process. The results from this system yield
quite high in recognition rate. It is shown that high recognition rate
can be achieved in separation of 26 stone classes.
Abstract: Background: Regular physical activity contributes
positively to physical and psychological health. In the present study,
the stages of change of physical activity and the total physical
Aims: The aim of this study was to investigate the proportion of
adolescent girls in each stages of change and the causative factors
associated with physical activity such as the related social support
and self efficacy in a sample of the high school students.
Methods: In this study, Social Cognitive Theory (SCT) and the
Transtheorical Model (TTM) guided instrument development. The
data regarding the demographics, psychosocial determinants of
physical activity, stage of change and physical activity was gathered
by questionnaires. Several measures of psychosocial determinants of
physical activity were translated from English into Persian using the
back-translation technique. These translated measures were
administered to 512 ninth and tenth-grade Iranian high school
students for factor analysis.
Results: The distribution of the stage of change for physical activity
was as follow: 18/5% in precontemplation, 23.4% in contemplation,
38.2% in preparation, 4.6% in action and 15.3% in maintenance.
They were in 80.1% pre-adoption stages (precontemplation stage,
contemplation stage and preparation stage) and 19.9% post-adoption
stages (action stage and maintenance stage) of physical activity.
There was a significant relate between age and physical activity in
adolescent girls (age-related decline of physical activity) p
Abstract: this article proposed a methodology for computer
numerical control (CNC) machine scoring. The case study company
is a manufacturer of hard disk drive parts in Thailand. In this
company, sample of parts manufactured from CNC machine are
usually taken randomly for quality inspection. These inspection data
were used to make a decision to shut down the machine if it has
tendency to produce parts that are out of specification. Large amount
of data are produced in this process and data mining could be very
useful technique in analyzing them. In this research, data mining
techniques were used to construct a machine scoring model called
'machine priority assessment model (MPAM)'. This model helps to
ensure that the machine with higher risk of producing defective parts
be inspected before those with lower risk. If the defective prone
machine is identified sooner, defective part and rework could be
reduced hence improving the overall productivity. The results
showed that the proposed method can be successfully implemented
and approximately 351,000 baht of opportunity cost could have
saved in the case study company.
Abstract: To develop a process of extracting pixel values over the using of satellite remote sensing image data in Thailand. It is a very important and effective method of forecasting rainfall. This paper presents an approach for forecasting a possible rainfall area based on pixel values from remote sensing satellite images. First, a method uses an automatic extraction process of the pixel value data from the satellite image sequence. Then, a data process is designed to enable the inference of correlations between pixel value and possible rainfall occurrences. The result, when we have a high averaged pixel value of daily water vapor data, we will also have a high amount of daily rainfall. This suggests that the amount of averaged pixel values can be used as an indicator of raining events. There are some positive associations between pixel values of daily water vapor images and the amount of daily rainfall at each rain-gauge station throughout Thailand. The proposed approach was proven to be a helpful manual for rainfall forecasting from meteorologists by which using automated analyzing and interpreting process of meteorological remote sensing data.
Abstract: Quantitative Structure-Activity Relationship (QSAR)
approach for discovering novel more active Calanone derivative as
anti-leukemia compound has been conducted. There are 6
experimental activities of Calanone compounds against leukemia cell
L1210 that are used as material of the research. Calculation of
theoretical predictors (independent variables) was performed by
AM1 semiempirical method. The QSAR equation is determined by
Principle Component Regression (PCR) analysis, with Log IC50 as
dependent variable and the independent variables are atomic net
charges, dipole moment (μ), and coefficient partition of noctanol/
water (Log P). Three novel Calanone derivatives that
obtained by this research have higher activity against leukemia cell
L1210 than pure Calanone.
Abstract: The application of agro-industrial waste in Aluminum
Metal Matrix Composites has been getting more attention as they
can reinforce particles in metal matrix which enhance the strength
properties of the composites. In addition, by applying these agroindustrial
wastes in useful way not only save the manufacturing cost
of products but also reduce the pollutions on environment. This
paper represents a literature review on a range of industrial wastes
and their utilization in metal matrix composites. The paper describes
the synthesis methods of agro-industrial waste filled metal matrix
composite materials and their mechanical, wear, corrosion, and
physical properties. It also highlights the current application and
future potential of agro-industrial waste reinforced composites in
aerospace, automotive and other construction industries.
Abstract: Phytotoxicity of Daphne gnidium L. was evaluated
through the effect of incorporating leaves, stems and roots biomass
into soil (at 12.5, 25, 50g/Kg) and irrigation by their aqueous extracts
(50g/L), on the growth of two crops (Lactuca sativa L. and Raphanus
sativus L.) and two weeds (Peaganum harmala L. and Scolymus
maculatus L.). Results revealed a perceptible phytotoxic effect which
increased with dose and concentration. At the highest dose, roots and
leaves residues was the most toxic and caused total inhibition
respectively, for lettuce and thistle seedling growth. Irrigation with
aqueous extracts of D. gnidium different organs decreased also
seedlings length of all test species. Stems extract was more inhibitor
on thistle than peganum seedling growth; it induced a significant
reduction of 80% and 67%, for, respectively, roots and shoots.
Results of the present study suggest that different organs of D.
gnidium could be exploited in the management of agro-ecosystems.