Abstract: Un-doped GaN film of thickness 1.90 mm, grown on
sapphire substrate were uniformly implanted with 325 keV Mn+ ions
for various fluences varying from 1.75 x 1015 - 2.0 x 1016 ions cm-2 at
3500 C substrate temperature. The structural, morphological and
magnetic properties of Mn ion implanted gallium nitride samples
were studied using XRD, AFM and SQUID techniques. XRD of the
sample implanted with various ion fluences showed the presence of
different magnetic phases of Ga3Mn, Ga0.6Mn0.4 and Mn4N.
However, the compositions of these phases were found to be
depended on the ion fluence. AFM images of non-implanted sample
showed micrograph with rms surface roughness 2.17 nm. Whereas
samples implanted with the various fluences showed the presence of
nano clusters on the surface of GaN. The shape, size and density of
the clusters were found to vary with respect to ion fluence. Magnetic
moment versus applied field curves of the samples implanted with
various fluences exhibit the hysteresis loops. The Curie temperature
estimated from zero field cooled and field cooled curves for the
samples implanted with the fluence of 1.75 x 1015, 1.5 x 1016 and 2.0
x 1016 ions cm-2 was found to be 309 K, 342 K and 350 K
respectively.
Abstract: A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.
Abstract: The mechanical properties of granular solids are
dependent on the flow of stresses from one particle to another
through inter-particle contact. Although some experimental methods
have been used to study the inter-particle contacts in the past,
preliminary work with these techniques indicated that they do not
have the necessary resolution to distinguish between those contacts
that transmit the load and those that do not, especially for systems
with a wide distribution of particle sizes. In this research, computer
simulations are used to study the nature and distribution of contacts
in a compact with wide particle size distribution, representative of
aggregate size distribution used in asphalt pavement construction.
The packing fraction, the mean number of contacts and the
distribution of contacts were studied for different scenarios. A
methodology to distinguish and compute the fraction of load-bearing
particles and the fraction of space-filling particles (particles that do
not transmit any force) is needed for further investigation.
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: Type 2 diabetes mellitus (T2DM) is a complex
metabolic disorder that characterized by the presence of high glucose
in blood that cause from insulin resistance and insufficiency due to
deterioration β-cell Langerhans functions. T2DM is commonly
caused by the combination of inherited genetic variations as well as
our own lifestyle. Metallothionein (MT) is a known cysteine-rich
protein responsible in helping zinc homeostasis which is important in
insulin signaling and secretion as well as protection our body from
reactive oxygen species (ROS). MT scavenged ROS and free
radicals in our body happen to be one of the reasons of T2DM and its
complications. The objective of this study was to investigate the
association of MT1A and MT2A polymorphisms between T2DM and
control subjects among Malay populations. This study involved 150
T2DM and 120 Healthy individuals of Malay ethnic with mixed
genders. The genomic DNA was extracted from buccal cells and
amplified for MT1A and MT2A loci; the 347bp and 238bp banding
patterns were respectively produced by mean of the Polymerase
Chain Reaction (PCR). The PCR products were digested with Mlucl
and Tsp451 restriction enzymes respectively and producing
fragments lengths of (158/189/347bp) and (103/135/238bp)
respectively. The ANOVA test was conducted and it shown that there
was a significant difference between diabetic and control subjects for
age, BMI, WHR, SBP, FPG, HBA1C, LDL, TG, TC and family
history with (P0.05). The genotype
frequency for AA, AG and GG of MT1A polymorphisms was 72.7%,
22.7% and 4.7% in cases and 15%, 55% and 30% in control
respectively. As for MT2A, genotype frequency of GG, GC and CC
was 42.7%, 27.3% and 30% in case and 5%, 40% and 55% for
control respectively. Both polymorphisms show significant difference
between two investigated groups with (P=0.000). The Post hoc test
was conducted and shows a significant difference between the
genotypes within each polymorphism (P=0. 000). The MT1A and
MT2A polymorphisms were believed to be the reliable molecular
markers to distinguish the T2DM subjects from healthy individuals in
Malay populations.
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: 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: In the multi objective optimization, in the case when generated set of Pareto optimal solutions is large, occurs the problem to select of the best solution from this set. In this paper, is suggested a method to order of Pareto set. Ordering the Pareto optimal set carried out in conformity with the introduced distance function between each solution and selected reference point, where the reference point may be adjusted to represent the preferences of a decision making agent. Preference information about objective weights from a decision maker may be expressed imprecisely. The developed elicitation procedure provides an opportunity to obtain surrogate numerical weights for the objectives, and thus, to manage impreciseness of preference. The proposed method is a scalable to many objectives and can be used independently or as complementary to the various visualization techniques in the multidimensional case.
Abstract: In this paper, we present a system for content-based
retrieval of large database of classified satellite images, based on
user's relevance feedback (RF).Through our proposed system, we
divide each satellite image scene into small subimages, which stored
in the database. The modified radial basis functions neural network
has important role in clustering the subimages of database according
to the Euclidean distance between the query feature vector and the
other subimages feature vectors. The advantage of using RF
technique in such queries is demonstrated by analyzing the database
retrieval results.
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: 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.
Abstract: In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type-s of customers, number of plants, etc. It is nonlinear process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The developed system is applied for predicting future values of electricity consumption of Northern Cyprus. The simulation of neuro-fuzzy system has been performed.
Abstract: TiO2/MgO composite films were prepared by coating
the magnesium acetate solution in the pores of mesoporous TiO2
films using a dip coating method. Concentrations of magnesium
acetate solution were varied in a range of 1x10-4 – 1x10-1 M. The
TiO2/MgO composite films were characterized by scanning electron
microscopy (SEM), transmission electron microscropy (TEM),
electrochemical impedance spectroscopy(EIS) , transient voltage
decay and I-V test. The TiO2 films and TiO2/MgO composite films
were immersed in a 0.3 mM N719 dye solution. The Dye-sensitized
solar cells with the TiO2/MgO/N719 structure showed an optimal
concentration of magnesium acetate solution of 1x10-3 M resulting in
the MgO film estimated thickness of 0.0963 nm and giving the
maximum efficiency of 4.85%. The improved efficiency of dyesensitized
solar cell was due to the magnesium oxide film as the wide
band gap coating decays the electron back transfer to the triiodide
electrolyte and reduce charge recombination.
Abstract: Perhaps no single issue has been cited as either the root
cause and / or the greatest challenge to the restructured power system then the lack of adequate reliable transmission. Probabilistic transmission planning has become increasingly necessary and important in recent
years. The transmission planning analysis carried out by the authors,
spans a 10-year horizon, taking into consideration a value of 2 % load
increase / year at each consumer. Taking into consideration this increased
load, a probabilistic power flow was carried out, all the system components
being regarded from probabilistic point of view. Several contingencies
have been generated, for assessing the security of the power system. The results have been analyzed and several important conclusions were pointed. The objective is to achieve a network that works without limit violations for all (or most of) scenario realizations. The case study is represented by the IEEE 14 buses test power system.
Abstract: The Bayesian Optimization Algorithm (BOA) is an algorithm based on the estimation of distributions. It uses techniques from modeling data by Bayesian networks to estimating the joint distribution of promising solutions. To obtain the structure of Bayesian network, different search algorithms can be used. The key point that BOA addresses is whether the constructed Bayesian network could generate new and useful solutions (strings), which could lead the algorithm in the right direction to solve the problem. Undoubtedly, this ability is a crucial factor of the efficiency of BOA. Varied search algorithms can be used in BOA, but their performances are different. For choosing better ones, certain suitable method to present their ability difference is needed. In this paper, a greedy search algorithm and a stochastic search algorithm are used in BOA to solve certain optimization problem. A method using Kullback-Leibler (KL) Divergence to reflect their difference is described.
Abstract: The objective of this research was to find the
relationship between auspicious meaning in eastern wisdom and the
interpretation as a guideline for the design and development of
community souvenirs. The sample group included 400 customers in
Bangkok who used to buy community souvenir products. The
information was applied to design the souvenirs which were
considered for the appropriateness by 5 design specialists. The data
were analyzed to find frequency, percentage, and SD with the results
as follows. 1) The best factor referring to the auspicious meaning is
color. The application of auspicious meaning can make the value
added to the product and bring the fortune to the receivers. 2) The
effectiveness of the auspicious meaning integration on the design of
community souvenir product was in high level. When considering in
each aspect, it was found that the interpretation aspect was in high
level, the congruency of the auspicious meaning and the utility of the
product was in high level. The attractiveness and the good design
were in very high level while the potential of the value added in the
product design was in high level. The suitable application to the
design of community souvenir product was in high level.
Abstract: Stability of functionally graded beams with piezoelectric layers subjected to axial compressive load that is simply supported at both ends is studied in this paper. The displacement field of beam is assumed based on first order shear deformation beam theory. Applying the Hamilton's principle, the governing equation is established. The influences of applied voltage, dimensionless geometrical parameter, functionally graded index and piezoelectric thickness on the critical buckling load of beam are presented. To investigate the accuracy of the present analysis, a compression study is carried out with a known data.
Abstract: Drought is a phenomenon caused by
environmental and climatic changes. This phenomenon is
affected by shortage of rainfall and temperature. Dust is one
of important environmental problems caused by climate
change and drought. With recent multi-year drought, many
environmental crises caused by dust in Iran and Middle East.
Dust in the vast areas of the provinces occurs with high
frequency. By dust affecting many problems created in terms
of health, social and economic. In this study, we tried to study
the most important factors causing dust. In this way we have
used the satellite images and meteorological data. Finally,
strategies to deal with the dust will be mentioned.
Abstract: Abrasive waterjet cutting (AWJ) is a highly efficient
method for cutting almost any type of material. When holes shall be
cut the waterjet first needs to pierce the material.This paper presents a
vast experimental analysis of piercing parameters effect on piercing
time. Results from experimentation on feed rates, work piece
thicknesses, abrasive flow rates, standoff distances and water
pressure are also presented as well as studies on three methods for
dynamic piercing. It is shown that a large amount of time and
resources can be saved by choosing the piercing parameters in a
correct way. The large number of experiments puts demands on the
experimental setup. An automated experimental setup including
piercing detection is presented to enable large series of experiments
to be carried out efficiently.
Abstract: Carbon fibers are fabricated from different materials,
such as special polyacrylonitrile (PAN) fibers, rayon fibers and pitch.
Among these three groups of materials, PAN fibers are the most
widely used precursor for the manufacture of carbon fibers. The
process of fabrication carbon fibers from special PAN fibers includes
two steps; oxidative stabilization at low temperature and
carbonization at high temperatures in an inert atmosphere. Due to the
high price of raw materials (special PAN fibers), carbon fibers are
still expensive.
In the present work the main goal is making carbon fibers from
low price commercial PAN fibers with modified chemical
compositions. The results show that in case of conducting completes
stabilization process, it is possible to produce carbon fibers with
desirable tensile strength from this type of PAN fibers. To this
matter, thermal characteristics of commercial PAN fibers were
investigated and based upon the obtained results, with some changes
in conventional procedure of stabilization in terms of temperature
and time variables; the desirable conditions of complete stabilization
is achieved.