Abstract: Selection of the best possible set of suppliers has a
significant impact on the overall profitability and success of any
business. For this reason, it is usually necessary to optimize all
business processes and to make use of cost-effective alternatives for
additional savings. This paper proposes a new efficient context-aware
supplier selection model that takes into account possible changes of
the environment while significantly reducing selection costs. The
proposed model is based on data clustering techniques while
inspiring certain principles of online algorithms for an optimally
selection of suppliers. Unlike common selection models which re-run
the selection algorithm from the scratch-line for any decision-making
sub-period on the whole environment, our model considers the
changes only and superimposes it to the previously defined best set
of suppliers to obtain a new best set of suppliers. Therefore, any recomputation
of unchanged elements of the environment is avoided
and selection costs are consequently reduced significantly. A
numerical evaluation confirms applicability of this model and proves
that it is a more optimal solution compared with common static
selection models in this field.
Abstract: Predicting short term wind speed is essential in order
to prevent systems in-action from the effects of strong winds. It also
helps in using wind energy as an alternative source of energy, mainly
for Electrical power generation. Wind speed prediction has
applications in Military and civilian fields for air traffic control,
rocket launch, ship navigation etc. The wind speed in near future
depends on the values of other meteorological variables, such as
atmospheric pressure, moisture content, humidity, rainfall etc. The
values of these parameters are obtained from a nearest weather
station and are used to train various forms of neural networks. The
trained model of neural networks is validated using a similar set of
data. The model is then used to predict the wind speed, using the
same meteorological information. This paper reports an Artificial
Neural Network model for short term wind speed prediction, which
uses back propagation algorithm.
Abstract: This policy participation action research explores the
roles of Thai government units during its 2010 fiscal year on how to
create value added to recycling business in the central part of
Thailand. The research aims to a) study how the government plays a
role to support the business, and its problems and obstacles on
supporting the business, b) to design a strategic action – short,
medium, and long term plans -- to create value added to the recycling
business, particularly in local full-loop companies/organizations
licensed by Wongpanit Waste Separation Plant as well as those
licensed by the Department of Provincial Administration. Mixed
method research design, i.e., a combination of quantitative and
qualitative methods is utilized in the present study in both data
collection and analysis procedures. Quantitative data was analyzed
by frequency, percent value, mean scores, and standard deviation,
and aimed to note trend and generalizations. Qualitative data was
collected via semi-structured interviews/focus group interviews to
explore in-depth views of the operators. The sampling included 1,079
operators in eight provinces in the central part of Thailand.
Abstract: In turning hardened steel, polycrystalline cubic boron
nitride (cBN) compacts are widely used, due to their higher hardness
and higher thermal conductivity. However, in milling hardened steel,
fracture of cBN cutting tools readily occurs because they have poor
fracture toughness. Therefore, coated cemented carbide tools, which
have good fracture toughness and wear resistance, are generally
widely used. In this study, hardened steel (ASTM D2, JIS SKD11,
60HRC) was milled with three physical vapor deposition
(PVD)-coated cemented carbide end mill cutters in order to determine
effective tool materials for cutting hardened steel at high cutting
speeds. The coating films used were (Ti,W)N/(Ti,W,Si)N and
(Ti,W)N/(Ti,W,Si,Al)N coating films. (Ti,W,Si,Al)N is a new type of
coating film. The inner layer of the (Ti,W)N/(Ti,W,Si)N and
(Ti,W)N/(Ti,W,Si,Al)N coating system is (Ti,W)N coating film, and
the outer layer is (Ti,W,Si)N and (Ti,W,Si,Al)N coating films,
respectively. Furthermore, commercial (Ti,Al)N-based coating film
was also used. The following results were obtained: (1) In milling
hardened steel at a cutting speed of 3.33 m/s, the tool wear width of the
(Ti,W)N/(Ti,W,Si,Al)N-coated tool was smaller than that of the
(Ti,W)N/(Ti,W,Si)N-coated tool. And, compared with the commercial
(Ti,Al)N, the tool wear width of the (Ti,W)N/(Ti,W,Si,Al)N-coated
tool was smaller than that of the (Ti,Al)N-coated tool. (2) The tool
wear of the (Ti,W)N/(Ti,W,Si,Al)N-coated tool increased with an
increase in cutting speed. (3) The (Ti,W)N/(Ti,W,Si,Al)N-coated
cemented carbide was an effective tool material for high-speed cutting
below a cutting speed of 3.33 m/s.
Abstract: Pretreatment of oil palm empty fruit bunch (OPEFB) with N-Methylmorpholine-N-oxide (NMMO) to enhance biogas production was investigated. The pretreatments were performed at 90 and 120ºC for 1, 3, and 5 h using three different concentrations of NMMO of 73%, 79%, and 85%. The pretreated OPEFB was subsequently anaerobically digested to produce biogas. After pretreatment, there were no significant changes of the main composition of OPEFB and the maximum total solid recovery was 92%. The amorphous phase was increased up to 78% at pretreatment condition using 85% NMMO solution for 3 h at 120oC. In general, higher concentration of NMMO and higher temperature resulted in increased amorphous form and higher biogas production. The best results of biogas production reached enhancement of methane yield of 148% compared to the untreated OPEFB and increased in digestion of 94% compared to starch as reference.
Abstract: Spatial trends are one of the valuable patterns in geo
databases. They play an important role in data analysis and
knowledge discovery from spatial data. A spatial trend is a regular
change of one or more non spatial attributes when spatially moving
away from a start object. Spatial trend detection is a graph search
problem therefore heuristic methods can be good solution. Artificial
immune system (AIS) is a special method for searching and
optimizing. AIS is a novel evolutionary paradigm inspired by the
biological immune system. The models based on immune system
principles, such as the clonal selection theory, the immune network
model or the negative selection algorithm, have been finding
increasing applications in fields of science and engineering.
In this paper, we develop a novel immunological algorithm based
on clonal selection algorithm (CSA) for spatial trend detection. We
are created neighborhood graph and neighborhood path, then select
spatial trends that their affinity is high for antibody. In an
evolutionary process with artificial immune algorithm, affinity of
low trends is increased with mutation until stop condition is satisfied.
Abstract: This study determines the effect of naked and heparinbased
super-paramagnetic iron oxide nanoparticles on the human
cancer cell lines of A2780. Doxorubicin was used as the anticancer
drug, entrapped in the SPIO-NPs. This study aimed to decorate
nanoparticles with heparin, a molecular ligand for 'active' targeting
of cancerous cells and the application of modified-nanoparticles in
cancer treatment. The nanoparticles containing the anticancer drug
DOX were prepared by a solvent evaporation and emulsification
cross-linking method. The physicochemical properties of the
nanoparticles were characterized by various techniques, and uniform
nanoparticles with an average particle size of 110±15 nm with high
encapsulation efficiencies (EE) were obtained. Additionally, a
sustained release of DOX from the SPIO-NPs was successful.
Cytotoxicity tests showed that the SPIO-DOX-HP had higher cell
toxicity than the individual HP and confocal microscopy analysis
confirmed excellent cellular uptake efficiency. These results indicate
that HP based SPIO-NPs have potential uses as anticancer drug
carriers and also have an enhanced anticancer effect.
Abstract: In this paper by measuring the cutting forces the effect
of the tool shape and qualifications (sharp and worn cutting tools of
both vee and knife edge profile) and cutting conditions (depth of cut
and cutting speed) in the turning operation on the tool deflection and
cutting force is investigated. The workpiece material was mild steel
and the cutting tool was made of high speed steel. Cutting forces
were measured by a dynamometer (type P.E.I. serial No 154). The
dynamometer essentially consisted of a cantilever structure which
held the cutting tool. Deflection of the cantilever was measured by an
L.V.D.T (Mercer 122) deflection indicator. No cutting fluid was used
during the turning operations. A modern CNC lathe machine (Okuma
LH35-N) was used for the tests. It was noted that worn vee profile
tools tended to produce a greater increase in the vertical force
component than the axial component, whereas knife tools tended to
show a more pronounced increase in the axial component.
Abstract: The Niger Delta Region of Nigeria is home to about
20 million people and 40 different ethnic groups. The region has an
area of seventy thousand square kilometers (70,000 KM2) of
wetlands, formed primarily by sediments deposition and makes up
7.5 percent of Nigeria's total landmass. The notable ecological zones
in this region includes: coastal barrier islands; mangrove swamp
forests; fresh water swamps; and lowland rainforests. This incredibly
naturally-endowed ecosystem region, which contains one of the
highest concentrations of biodiversity on the planet, in addition to
supporting abundant flora and fauna, is threatened by the inhuman act
known as gas flaring. Gas flaring is the combustion of natural gas
that is associated with crude oil when it is pumped up from the
ground. In petroleum-producing areas such as the Niger Delta region
of Nigeria where insufficient investment was made in infrastructure
to utilize natural gas, flaring is employed to dispose of this associated
gas. This practice has impoverished the communities where it is
practiced, with attendant environmental, economic and health
challenges. This paper discusses the adverse environmental and
health implication associated with the practice, the role of
Government, Policy makers, Oil companies and the Local
communities aimed at bring this inhuman practice to a prompt end.
Abstract: Differentiated impact of team sports (basketball, indoor soccer, handball) on general haemodynamics and aerobic potential of students who specialize in technical subjects is detected only on the fourth year of studies in the institute of higher education. Those who play basketball and indoor soccer have shown increase of stroke and minute volume of blood indices, pumping and contractile function of the heart, oxygenation of blood and oxygen delivery to tissues, aerobic energy supply and balance of sympathetic and parasympathetic activity of the nervous regulation mechanism of the circulatory system. Those who play handball have shown these indices statistically decreased. On the whole playing basketball and indoor soccer optimizes the strategy for adaptation of students to the studying process, but playing handball does the opposite thing. The leading factor for adaptation of students is: those who play basketball have increase of minute blood volume which stipulates velocity of the system blood circulation and well-timed oxygen delivery to tissues; those who play indoor soccer have increase of power and velocity of contractile function of the heart; those who play handball have increase of resistance of thorax to the system blood flow which minimizes contractile function of the heart, blood oxygen saturation and delivery of oxygen to tissues.
Abstract: For numerical prediction of the NOX in the exhaust of
a compression ignition engine a model was developed by considering
the parameter equivalence ratio. This model was validated by
comparing the predicted results of NOX with experimental ones. The
ultimate aim of the work was to access the applicability, robustness
and performance of the improved NOX model against other NOX
models.
Abstract: The size, complexity and number of databases used
for protein information have caused bioinformatics to lag behind in
adapting to the need to handle this distributed information.
Integrating all the information from different databases into one
database is a challenging problem. Our main research is to develop a
tool which can be used to access and manipulate protein information
from difference databases. In our approach, we have integrated
difference databases such as Swiss-prot, PDB, Interpro, and EMBL
and transformed these databases in flat file format into relational
form using XML and Bioperl. As a result, we showed this tool can
search different sizes of protein information stored in relational
database and the result can be retrieved faster compared to flat file
database. A web based user interface is provided to allow user to
access or search for protein information in the local database.
Abstract: DNA shuffling is a powerful method used for in vitro
evolute molecules with specific functions and has application in areas
such as, for example, pharmaceutical, medical and agricultural
research. The success of such experiments is dependent on a variety
of parameters and conditions that, sometimes, can not be properly
pre-established. Here, two computational models predicting DNA
shuffling results is presented and their use and results are evaluated
against an empirical experiment. The in silico and in vitro results
show agreement indicating the importance of these two models and
motivating the study and development of new models.
Abstract: Wireless Sensor Networks (WSNs) are wireless
networks consisting of number of tiny, low cost and low power
sensor nodes to monitor various physical phenomena like
temperature, pressure, vibration, landslide detection, presence of any
object, etc. The major limitation in these networks is the use of nonrechargeable
battery having limited power supply. The main cause of
energy consumption WSN is communication subsystem. This paper
presents an efficient grid formation/clustering strategy known as Grid
based level Clustering and Aggregation of Data (GCAD). The
proposed clustering strategy is simple and scalable that uses low duty
cycle approach to keep non-CH nodes into sleep mode thus reducing
energy consumption. Simulation results demonstrate that our
proposed GCAD protocol performs better in various performance
metrics.
Abstract: Particle Swarm Optimization (PSO) with elite PSO
parameters has been developed for power flow analysis under
practical constrained situations. Multiple solutions of the power flow
problem are useful in voltage stability assessment of power system.
A method of determination of multiple power flow solutions is
presented using a hybrid of Particle Swarm Optimization (PSO) and
local search technique. The unique and innovative learning factors of
the PSO algorithm are formulated depending upon the node power
mismatch values to be highly adaptive with the power flow problems.
The local search is applied on the pbest solution obtained by the PSO
algorithm in each iteration. The proposed algorithm performs reliably
and provides multiple solutions when applied on standard and illconditioned
systems. The test results show that the performances of
the proposed algorithm under critical conditions are better than the
conventional methods.
Abstract: In this research it is aimed that the effect of some demographic factors on Turkish Adolescents' subjective well being is investigated. 432 adolescents who are 247 girls and 185 boys are participated in this study. They are ages 15-17, and also are high school students. The Positive and Negative Affect Scale and Life Satisfaction Scale are used for measuring adolescents' subjective well being. The ANOVA method is used in order to examine the effect of ages. For gender differences, independent t-test method is used, and finally the Pearson Correlation method is used so as to examine the effect of socio economic statues of adolescents' parents. According to results, there is no gender difference on adolescents' subjective well being. On the other hand, SES and age are effect significantly lover level on adolescents' subjective well being.
Abstract: Structural behavior of ring stiffened thick walled
cylinders made of functionally graded materials (FGMs) is
investigated in this paper. Functionally graded materials are inhomogeneous composites which are usually made from a mixture
of metal and ceramic. The gradient compositional variation of the
constituents from one surface to the other provides an elegant solution to the problem of high transverse shear stresses that are
induced when two dissimilar materials with large differences in material properties are bonded. FGM formation of the cylinder is
modeled by power-law exponent and the variation of characteristics is supposed to be in radial direction.
A finite element formulation is derived for the analysis. According to the property variation of the constituent materials in the radial
direction of the wall, it is not convenient to use conventional elements to model and analyze the structure of the stiffened FGM
cylinders. In this paper a new cylindrical super-element is used to model the finite element formulation and analyze the static and
modal behavior of stiffened FGM thick walled cylinders. By using
this super-element the number of elements, which are needed for
modeling, will reduce significantly and the process time is less in comparison with conventional finite element formulations. Results for static and modal analysis are evaluated and verified by
comparison to finite element formulation with conventional
elements. Comparison indicates a good conformity between results.
Abstract: An optimal power flow (OPF) based on particle swarm
optimization (PSO) was developed with more realistic generator
security constraint using the capability curve instead of only Pmin/Pmax
and Qmin/Qmax. Neural network (NN) was used in designing digital
capability curve and the security check algorithm. The algorithm is
very simple and flexible especially for representing non linear
generation operation limit near steady state stability limit and under
excitation operation area. In effort to avoid local optimal power flow
solution, the particle swarm optimization was implemented with
enough widespread initial population. The objective function used in
the optimization process is electric production cost which is
dominated by fuel cost. The proposed method was implemented at
Java Bali 500 kV power systems contain of 7 generators and 20
buses. The simulation result shows that the combination of generator
power output resulted from the proposed method was more economic
compared with the result using conventional constraint but operated
at more marginal operating point.
Abstract: In India, the quarrel between the budding human
populace and the planet-s unchanging supply of freshwater and
falling water tables has strained attention the reuse of gray water as
an alternative water resource in rural development. This paper
present the finest design of laboratory scale gray water treatment
plant, which is a combination of natural and physical operations such
as primary settling with cascaded water flow, aeration, agitation and
filtration, hence called as hybrid treatment process. The economical
performance of the plant for treatment of bathrooms, basins and
laundries gray water showed in terms of deduction competency of
water pollutants such as COD (83%), TDS (70%), TSS (83%), total
hardness (50%), oil and grease (97%), anions (46%) and cations
(49%). Hence, this technology could be a good alternative to treat
gray water in residential rural area.
Abstract: This paper applies Bayesian Networks to support
information extraction from unstructured, ungrammatical, and
incoherent data sources for semantic annotation. A tool has been
developed that combines ontologies, machine learning, and
information extraction and probabilistic reasoning techniques to
support the extraction process. Data acquisition is performed with the
aid of knowledge specified in the form of ontology. Due to the
variable size of information available on different data sources, it is
often the case that the extracted data contains missing values for
certain variables of interest. It is desirable in such situations to
predict the missing values. The methodology, presented in this paper,
first learns a Bayesian network from the training data and then uses it
to predict missing data and to resolve conflicts. Experiments have
been conducted to analyze the performance of the presented
methodology. The results look promising as the methodology
achieves high degree of precision and recall for information
extraction and reasonably good accuracy for predicting missing
values.