Abstract: This paper introduces the foundations of Bayesian probability theory and Bayesian decision method. The main goal of Bayesian decision theory is to minimize the expected loss of a decision or minimize the expected risk. The purposes of this study are to review the decision process on the issue of flood occurrences and to suggest possible process for decision improvement. This study examines the problem structure of flood occurrences and theoretically explicates the decision-analytic approach based on Bayesian decision theory and application to flood occurrences in Environmental Engineering. In this study, we will discuss about the flood occurrences upon an annual maximum water level in cm, 43-year record available from 1965 to 2007 at the gauging station of Sagaing on the Ayeyarwady River with the drainage area - 120193 sq km by using Bayesian decision method. As a result, we will discuss the loss and risk of vast areas of agricultural land whether which will be inundated or not in the coming year based on the two standard maximum water levels during 43 years. And also we forecast about that lands will be safe from flood water during the next 10 years.
Abstract: In this paper a combination approach of two heuristic-based algorithms: genetic algorithm and tabu search is proposed. It has been developed to obtain the least cost based on the split-pipe design of looped water distribution network. The proposed combination algorithm has been applied to solve the three well-known water distribution networks taken from the literature. The development of the combination of these two heuristic-based algorithms for optimization is aimed at enhancing their strengths and compensating their weaknesses. Tabu search is rather systematic and deterministic that uses adaptive memory in search process, while genetic algorithm is probabilistic and stochastic optimization technique in which the solution space is explored by generating candidate solutions. Split-pipe design may not be realistic in practice but in optimization purpose, optimal solutions are always achieved with split-pipe design. The solutions obtained in this study have proved that the least cost solutions obtained from the split-pipe design are always better than those obtained from the single pipe design. The results obtained from the combination approach show its ability and effectiveness to solve combinatorial optimization problems. The solutions obtained are very satisfactory and high quality in which the solutions of two networks are found to be the lowest-cost solutions yet presented in the literature. The concept of combination approach proposed in this study is expected to contribute some useful benefits in diverse problems.
Abstract: Massive use of places with strong tourist attraction
with the consequent possibility of losing place-identity produces
harmful effects on cities and their users. In order to mitigate this risk,
areas close to such places can be identified so as to widen the
visitor-s range of action and offer alternative activities integrated
with the main site. The cultural places and appropriate activities can
be identified using a method of analysis and design able to trace the
identity of the places, their characteristics and potential, and to
provide a sustainable improvement. The aim of this work is to
propose PlaceMaker as a method of urban analysis and design which
both detects elements that do not feature in traditional mapping and
which constitute the contemporary identity of the places, and
identifies appropriate project interventions. Two final complex maps
– the first of analysis and the second of design – respectively
represent the identity of places and project interventions. In order to
illustrate the method-s potential; the results of the experimentation
carried out in the Trevi-Pantheon route in Rome and the appropriate
interventions to decongest the area are illustrated.
Abstract: This paper presents a new growing neural network for
cluster analysis and market segmentation, which optimizes the size
and structure of clusters by iteratively checking them for multivariate
normality. We combine the recently published SGNN approach [8]
with the basic principle underlying the Gaussian-means algorithm
[13] and the Mardia test for multivariate normality [18, 19]. The new
approach distinguishes from existing ones by its holistic design and
its great autonomy regarding the clustering process as a whole. Its
performance is demonstrated by means of synthetic 2D data and by
real lifestyle survey data usable for market segmentation.
Abstract: In this paper, a new model predictive PID controller
design method for the slip suppression control of EVs (electric
vehicles) is proposed. The proposed method aims to improve the
maneuverability and the stability of EVs by controlling the wheel
slip ratio. The optimal control gains of PID framework are derived
by the model predictive control (MPC) algorithm. There also include
numerical simulation results to demonstrate the effectiveness of the
method.
Abstract: In this paper, applying frequency domain approach, a delayed predator-prey fishery model with prey reserve is investigated. By choosing the delay τ as a bifurcation parameter, It is found that Hopf bifurcation occurs as the bifurcation parameter τ passes a sequence of critical values. That is, a family of periodic solutions bifurcate from the equilibrium when the bifurcation parameter exceeds a critical value. The length of delay which preserves the stability of the positive equilibrium is calculated. Some numerical simulations are included to justify the theoretical analysis results. Finally, main conclusions are given.
Abstract: During last decades, developing multi-objective
evolutionary algorithms for optimization problems has found
considerable attention. Flexible job shop scheduling problem, as an
important scheduling optimization problem, has found this attention
too. However, most of the multi-objective algorithms that are
developed for this problem use nonprofessional approaches. In
another words, most of them combine their objectives and then solve
multi-objective problem through single objective approaches. Of
course, except some scarce researches that uses Pareto-based
algorithms. Therefore, in this paper, a new Pareto-based algorithm
called controlled elitism non-dominated sorting genetic algorithm
(CENSGA) is proposed for the multi-objective FJSP (MOFJSP). Our
considered objectives are makespan, critical machine work load, and
total work load of machines. The proposed algorithm is also
compared with one the best Pareto-based algorithms of the literature
on some multi-objective criteria, statistically.
Abstract: This article proposes a current-mode square-rooting
circuit using current follower transconductance amplifier (CTFA).
The amplitude of the output current can be electronically controlled
via input bias current with wide input dynamic range. The proposed
circuit consists of only single CFTA. Without any matching
conditions and external passive elements, the circuit is then
appropriate for an IC architecture. The magnitude of the output signal
is temperature-insensitive. The PSpice simulation results are
depicted, and the given results agree well with the theoretical
anticipation. The power consumption is approximately 1.96mW at
±1.5V supply voltages.
Abstract: Extensive wind tunnel tests have been conducted to
investigate the unsteady flow field over and behind a 2D model of a
660 kW wind turbine blade section in pitching motion. The surface
pressure and wake dynamic pressure variation at a distance of 1.5
chord length from trailing edge were measured by pressure
transducers during several oscillating cycles at 3 reduced frequencies
and oscillating amplitudes. Moreover, form drag and linear
momentum deficit are extracted and compared at various conditions.
The results show that the wake velocity field and surface pressure of
the model have similar behavior before and after the airfoil beyond
the static stall angle of attack. In addition, the effects of reduced
frequency and oscillation amplitudes are discussed.
Abstract: The amount and heterogeneity of data in biomedical research, notably in interdisciplinary research, requires new methods for the collection, presentation and analysis of information. Important data from laboratory experiments as well as patient trials are available but come out of distributed resources. The Charite Medical School in Berlin has established together with the German Research Foundation (DFG) a new information service center for kidney diseases and transplantation (Open European Nephrology Science Centre - OpEN.SC). The system is based on a service-oriented architecture (SOA) with main and auxiliary modules arranged in four layers. To improve the reuse and efficient arrangement of the services the functionalities are described as business processes using the standardised Business Process Execution Language (BPEL).
Abstract: The pigments covered by film-forming polymers have
opened a prospect to improve the quality of water-based printing
inks. In this study such pigments were prepared by the initiated
polymerization of styrene and methacrylate derivative monomers in
the aqueous pigment dispersions. The formation of polymer films
covering pigment cores depends on the polymerization time and the
ratio of pigment to monomers. At the time of 4 hours and the ratio of
1/10 almost pigment particles are coated by the polymer. The formed
polymer covers of pigments have the average thickness of 5.95 nm.
The size increasing percentage of the coated particles after a week is
4.5 %, about fourteen-fold lower than of the original ones. The
obtained results indicate that the coated pigments are improved
dispersion stability in water medium along with a guarantee for the
optical colour.
Abstract: This paper presents a narrative management system
for organizations to capture organization's tacit knowledge
through stories. The intention of capturing tacit knowledge is to
address the problem that comes with the mobility of workforce in
organisation. Storytelling in knowledge management context is
seen as a powerful management tool to communicate tacit
knowledge in organization. This narrative management system is
developed firstly to enable uploading of many types of knowledge
sharing stories, from general to work related-specific stories and
secondly, each video has comment functionality where knowledge
users can post comments to other knowledge users. The narrative
management system allows the stories to browse, search and view
by the users. In the system, stories are stored in a video repository.
Stories that were produced from this framework will improve
learning, knowledge transfer facilitation and tacit knowledge
quality in an organization.
Abstract: Analysis and visualization of microarraydata is veryassistantfor biologists and clinicians in the field of diagnosis and treatment of patients. It allows Clinicians to better understand the structure of microarray and facilitates understanding gene expression in cells. However, microarray dataset is a complex data set and has thousands of features and a very small number of observations. This very high dimensional data set often contains some noise, non-useful information and a small number of relevant features for disease or genotype. This paper proposes a non-linear dimensionality reduction algorithm Local Principal Component (LPC) which aims to maps high dimensional data to a lower dimensional space. The reduced data represents the most important variables underlying the original data. Experimental results and comparisons are presented to show the quality of the proposed algorithm. Moreover, experiments also show how this algorithm reduces high dimensional data whilst preserving the neighbourhoods of the points in the low dimensional space as in the high dimensional space.
Abstract: Pretreatment is an essential step in the conversion of
lignocellulosic biomass to fermentable sugar that used for biobutanol
production. Among pretreatment processes, microwave is considered
to improve pretreatment efficiency due to its high heating efficiency,
easy operation, and easily to combine with chemical reaction. The
main objectives of this work are to investigate the feasibility of
microwave pretreatment to enhance enzymatic hydrolysis of
corncobs and to determine the optimal conditions using response
surface methodology. Corncobs were pretreated via two-stage
pretreatment in dilute sodium hydroxide (2 %) followed by dilute
sulfuric acid 1 %. Pretreated corncobs were subjected to enzymatic
hydrolysis to produce reducing sugar. Statistical experimental design
was used to optimize pretreatment parameters including temperature,
residence time and solid-to-liquid ratio to achieve the highest amount
of glucose. The results revealed that solid-to-liquid ratio and
temperature had a significant effect on the amount of glucose.
Abstract: Student-s movements have been going increasing in
last decades. International students can have different psychological
and sociological problems in their adaptation process. Depression is
one of the most important problems in this procedure. This research
purposed to reveal level of foreign students- depression, kinds of
interpersonal communication networks (host/ethnic interpersonal
communication) and media usage (host/ethnic media usage).
Additionally study aimed to display the relationship between
depression and communication (host/ethnic interpersonal
communication and host/ethnic media usage) among foreign
university students. A field research was performed among 283
foreign university students who have been attending 8 different
universities in Turkey. A purposeful sampling technique was used in
this research cause of data collect facilities. Results indicated that
58.3% of foreign students- depression stage was “intermediate" while
33.2% of foreign students- depression level was “low". Add to this,
host interpersonal communication behaviors and Turkish web sites
usages were negatively and significantly correlated with depression.
Abstract: This paper proposes a novel approach to the question of lithofacies classification based on an assessment of the uncertainty in the classification results. The proposed approach has multiple neural networks (NN), and interval neutrosophic sets (INS) are used to classify the input well log data into outputs of multiple classes of lithofacies. A pair of n-class neural networks are used to predict n-degree of truth memberships and n-degree of false memberships. Indeterminacy memberships or uncertainties in the predictions are estimated using a multidimensional interpolation method. These three memberships form the INS used to support the confidence in results of multiclass classification. Based on the experimental data, our approach improves the classification performance as compared to an existing technique applied only to the truth membership. In addition, our approach has the capability to provide a measure of uncertainty in the problem of multiclass classification.
Abstract: The passive electrical properties of a tissue depends
on the intrinsic constituents and its structure, therefore by measuring
the complex electrical impedance of the tissue it might be possible to
obtain indicators of the tissue state or physiological activity [1].
Complete bio-impedance information relative to physiology and
pathology of a human body and functional states of the body tissue or
organs can be extracted by using a technique containing a fourelectrode
measurement setup. This work presents the estimation
measurement setup based on the four-electrode technique. First, the
complex impedance is estimated by three different estimation
techniques: Fourier, Sine Correlation and Digital De-convolution and
then estimation errors for the magnitude, phase, reactance and
resistance are calculated and analyzed for different levels of
disturbances in the observations. The absolute values of relative
errors are plotted and the graphical performance of each technique is
compared.
Abstract: Among the technologies available to reduce methane
emitted from the pig industry, biofiltration seems to be an effective
and inexpensive solution. In methane (CH4) biofiltration, nitrogen is
an important macronutrient for the microorganisms growth. The
objective of this research project was to study the effect of
ammonium (NH4
+) on the performance, the biomass production and
the nitrogen conversion of a biofilter treating methane. For NH4
+
concentrations ranging from 0.05 to 0.5 gN-NH4
+/L, the CH4 removal
efficiency and the dioxide carbon production rate decreased linearly
from 68 to 11.8 % and from 7.1 to 0.5 g/(m3-h), respectively. The dry
biomass content varied from 4.1 to 5.8 kg/(m3 filter bed). For the
same range of concentrations, the ammonium conversion decreased
while the specific nitrate production rate increased. The specific
nitrate production rate presented negative values indicating
denitrification in the biofilter.
Abstract: To investigate some relations between higher mathe¬matics scores in Chinese graduate student entrance examination and calculus (resp. linear algebra, probability statistics) scores in subject's completion examination of Chinese university, we select 20 students as a sample, take higher mathematics score as a decision attribute and take calculus score, linear algebra score, probability statistics score as condition attributes. In this paper, we are based on rough-set theory (Rough-set theory is a logic-mathematical method proposed by Z. Pawlak. In recent years, this theory has been widely implemented in the many fields of natural science and societal science.) to investigate importance of condition attributes with respective to decision attribute and strength of condition attributes supporting decision attribute. Results of this investigation will be helpful for university students to raise higher mathematics scores in Chinese graduate student entrance examination.
Abstract: This study evaluated the microbiological quality
and the sensory characteristics of carp fillets processed by the
sousvide method when stored at 2 and 10 °C. Four different
combinations of sauced–storage were studied then stored at 2 or 10
°C was evaluate periodically sensory, microbiological and
chemical quality. Batches stored at 2 °C had lower growth rates of
mesophiles and psychrotrophs. Moreover, these counts decreased
by increasing the heating temperature and time. Staphylococcus
aureus, Bacillus cereus, Clostridium perfringens and Listeria
monocytogenes were not found in any of the samples. The heat
treatment of 90 °C for 15 min and sauced was the most effective to
ensure the safety and extend the shelf-life of sousvide carp
preserving its sensory characteristics. This study establishes the
microbiological quality of sous vide carp and emphasizes the
relevance of the raw materials, heat treatment and storage
temperature to ensure the safety of the product.