Abstract: Nowadays, precipitation prediction is required for proper planning and management of water resources. Prediction with neural network models has received increasing interest in various research and application domains. However, it is difficult to determine the best neural network architecture for prediction since it is not immediately obvious how many input or hidden nodes are used in the model. In this paper, neural network model is used as a forecasting tool. The major aim is to evaluate a suitable neural network model for monthly precipitation mapping of Myanmar. Using 3-layerd neural network models, 100 cases are tested by changing the number of input and hidden nodes from 1 to 10 nodes, respectively, and only one outputnode used. The optimum model with the suitable number of nodes is selected in accordance with the minimum forecast error. In measuring network performance using Root Mean Square Error (RMSE), experimental results significantly show that 3 inputs-10 hiddens-1 output architecture model gives the best prediction result for monthly precipitation in Myanmar.
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: In this paper, a block code to minimize the peak-toaverage
power ratio (PAPR) of orthogonal frequency division
multiplexing (OFDM) signals is proposed. It is shown that cyclic
shift and codeword inversion cause not change to peak envelope
power. The encoding rule for the proposed code comprises of
searching for a seed codeword, shifting the register elements, and
determining codeword inversion, eliminating the look-up table for
one-to-one correspondence between the source and the coded data.
Simulation results show that OFDM systems with the proposed code
always have the minimum PAPR.
Abstract: Our objectives were to evaluate the effects of sire
breed, type of protein supplement, level of supplementation and sex
on wool spinning fineness (SF), its correlations with other wool
characteristics and prediction accuracy in F1 Merino crossbred lambs.
Texel, Coopworth, White Suffolk, East Friesian and Dorset rams
were mated with 500 purebred Merino dams at a ratio of 1:100 in
separate paddocks within a single management system. The F1
progeny were raised on ryegrass pasture until weaning, before forty
lambs were randomly allocated to treatments in a 5 x 2 x 2 x 2
factorial experimental design representing 5 sire breeds, 2
supplementary feeds (canola or lupins), 2 levels of supplementation
(1% or 2% of liveweight) and sex (wethers or ewes). Lambs were
supplemented for six weeks after an initial three weeks of adjustment,
wool sampled at the commencement and conclusion of the feeding
trial and analyzed for SF, mean fibre diameter (FD), coefficient of
variation (CV), standard deviation, comfort factor (CF), fibre
curvature (CURV), and clean fleece yield. Data were analyzed using
mixed linear model procedures with sire fitted as a random effect,
and sire breed, sex, supplementary feed type, level of
supplementation and their second-order interactions as fixed effects.
Sire breed (P
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: 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: Sedimentation in reservoirs lowers the quality of
consumed water, reduce the volume of reservoir, lowers the
controllable amount of flood, increases the risk of water overflow
during possible floods and the risk of reversal and reduction of dam's
useful life. So in all stages of dam establishment such as cognitive
studies, phase-1 studies of design, control, construction and
maintenance, the problem of sedimentation in reservoir should be
considered. What engineers need to do is examine and develop the
methods to keep effective capacity of a reservoir, however engineers
should also consider the influences of the methods on the flood
disaster, functions of water use facilities and environmental
issues.This article first examines the sedimentation in reservoirs and
shows how to control it and then discusses the studies about the
sedimens in Siazakh Dam.
Abstract: This study was a part of the three-year longitudinal
research on setting up an math learning model for the disadvantaged
students in Taiwan. A target 2nd grade class with 10 regular students
and 6 disadvantaged students at a disadvantaged area in Taipei
participated in this study. Two units of a market basal math textbook
concerning fractions, three-dimensional figures, weight and capacity
were adapted to enhance their math learning motivations, confidences
and effects. The findings were (1) curriculum adaptation was effective
on enhancing students- learning motivations, confidences and effects;
(2) story-type problems and illustrations decreased difficulties on
understanding math language for students from new immigrant
families and students with special needs; (3) “concrete –
semiconcrete – abstract" teaching strategies and hands-on activities
were essential to raise students learning interests and effects; and (4)
curriculum adaptation knowledge and skills needed to be included in
the pre- and in-service teacher training programs.
Abstract: One of the most important secrets of succesful companies is the fact that cooperation with NGOs will create a good reputation for them so that they can be immunized to economic crisis. The performance of the most admired companies in the world based on the ratings of Forbes and Fortune show us that most of these firms also have close relationships with their NGOs. Today, if companies do something wrong this information spreads very quickly to do the society. If people do not like the activities of a company, it can find itself in public relations nightmare that can threaten its repuation. Since the cost of communication has dropped dramatically due to the vast use of internet, the increase in communication among stakeholders via internet makes companies more visible. These multiple and interdependent interactions among the network of stakeholders is called as the network relationships. NGOs play the role of catalyst among the stakeholders of a firm to enhance the awareness. Succesful firms are aware of this fact that NGOs have a central role in today-s business world. Firms are also aware of the fact that they can enhance their corporate reputation via cooperation with the NGOs. This fact will be illustrated in this paper by examining some of the actions of the most succesful companies in terms of their cooperations with the NGOs.
Abstract: The ability to predict an accurate temperature
distribution requires the knowledge of the losses, the thermal
characteristics of the materials, and the cooling conditions, all of
which are very difficult to quantify. In this paper, the impact of the
effects of iron and copper losses are investigated separately and
their effects on the heating in various points of the stator of an
induction motor, is highlighted by using two simple tests. In addition,
the effect of a defect, such as an open circuit in a phase of the stator,
on the heating is also obtained by a no-load test.
The squirrel cage induction motor is rated at 2.2 kW; 380 V; 5.2
A; Δ connected; 50 Hz; 1420 rpm and the class of insulation F, has
been thermally tested under several load conditions. Several
thermocouples were placed in strategic points of the stator.
Abstract: The objective of this research intends to create a suitable model of distance training for community leaders in the upper northeastern region of Thailand. The implementation of the research process is divided into four steps: The first step is to analyze relevant documents. The second step deals with an interview in depth with experts. The third step is concerned with constructing a model. And the fourth step takes aim at model validation by expert assessments. The findings reveal the two important components for constructing an appropriate model of distance training for community leaders in the upper northeastern region. The first component consists of the context of technology management, e.g., principle, policy and goals. The second component can be viewed in two ways. Firstly, there are elements comprising input, process, output and feedback. Secondly, the sub-components include steps and process in training. The result of expert assessments informs that the researcher-s constructed model is consistent and suitable and overall the most appropriate.
Abstract: A higher order spline interpolated contour obtained
with up-sampling of homogenously distributed coordinates for
segmentation of kidney region in different classes of ultrasound
kidney images has been developed and presented in this paper. The
performance of the proposed method is measured and compared with
modified snake model contour, Markov random field contour and
expert outlined contour. The validation of the method is made in
correspondence with expert outlined contour using maximum coordinate
distance, Hausdorff distance and mean radial distance
metrics. The results obtained reveal that proposed scheme provides
optimum contour that agrees well with expert outlined contour.
Moreover this technique helps to preserve the pixels-of-interest
which in specific defines the functional characteristic of kidney. This
explores various possibilities in implementing computer-aided
diagnosis system exclusively for US kidney images.
Abstract: In this study the integration of an absorption heat
pump (AHP) with the concentration section of an industrial pulp and
paper process is investigated using pinch technology. The optimum
design of the proposed water-lithium bromide AHP is then achieved
by minimizing the total annual cost. A comprehensive optimization is
carried out by relaxation of all stream pressure drops as well as heat
exchanger areas involving in AHP structure. It is shown that by
applying genetic algorithm optimizer, the total annual cost of the
proposed AHP is decreased by 18% compared to one resulted from
simulation.
Abstract: This paper describes a low-power second-order filter
for a continuous-time chopper stabilized capacitive sensor interface,
integrated with a fully differential post-CMOS surface-micromachined
MEMS pressure sensor. The circuit uses a single-ended
folded-cascode operational amplifier and two GM-C filters connected
in cascade. The circuit is realized in a 0.18 μm CMOS process and
offers differential to single-ended conversion. The novelty of the
scheme is the cascade of two GM-C filters to achieve a second-order
filter while minimizing power dissipation. The simulated filter cutoff
frequency is 1.14 kHz at common-mode voltage 1.65 V,
operating from a 3.3 V supply while dissipating 172μW of power.
The filter achieves an operating range of 1V for an output load of
1MOhm and 10pF.
Abstract: There has been a growing interest in implementing humanoid avatars in networked virtual environment. However, most existing avatar communication systems do not take avatars- social backgrounds into consideration. This paper proposes a novel humanoid avatar animation system to represent personalities and facial emotions of avatars based on culture, profession, mood, age, taste, and so forth. We extract semantic keywords from the input text through natural language processing, and then the animations of personalized avatars are retrieved and displayed according to the order of the keywords. Our primary work is focused on giving avatars runtime instruction from multiple natural languages. Experiments with Chinese, Japanese and English input based on the prototype show that interactive avatar animations can be displayed in real time and be made available online. This system provides a more natural and interesting means of human communication, and therefore is expected to be used for cross-cultural communication, multiuser online games, and other entertainment applications.
Abstract: We develop a three-step fuzzy logic-based algorithm for clustering categorical attributes, and we apply it to analyze cultural data. In the first step the algorithm employs an entropy-based clustering scheme, which initializes the cluster centers. In the second step we apply the fuzzy c-modes algorithm to obtain a fuzzy partition of the data set, and the third step introduces a novel cluster validity index, which decides the final number of clusters.
Abstract: With a development of Hybrid Electric Vehicle(HEV),
A photovoltaic(PV) generation system is used for charging batteries in many cases. A dc/dc converter using PV power for a battery charger
requires a high efficiency. In this paper, A ZVS boost converter using the renewable energies for HEV charger is proposed. Through the theoretical analysis and experimental result, operation modes and characteristics of the proposed topology are verified.