Abstract: In this paper we introduce new data oriented modeling
of uniform random variable well-matched with computing systems. Due to this conformity with current computers structure, this modeling will be efficiently used in statistical inference.
Abstract: Facing the concern of the population to its environment and to climatic change, city planners are now considering the urban climate in their choices of planning. The urban climate, representing different urban morphologies across central Bangkok metropolitan area (BMA), are used to investigates the effects of both the composition and configuration of variables of urban morphology indicators on the summer diurnal range of urban climate, using correlation analyses and multiple linear regressions. Results show first indicate that approximately 92.6% of the variation in the average maximum daytime near-surface air temperature (Ta) was explained jointly by the two composition variables of urban morphology indicators including open space ratio (OSR) and floor area ratio (FAR). It has been possible to determine the membership of sample areas to the local climate zones (LCZs) using these urban morphology descriptors automatically computed with GIS and remote sensed data. Finally result found the temperature differences among zones of large separation, such as the city center could be respectively from 35.48±1.04ºC (Mean±S.D.) warmer than the outskirt of Bangkok on average for maximum daytime near surface temperature to 28.27±0.21ºC for extreme event and, can exceed as 8ºC. A spatially disaggregation of urban thermal responsiveness map would be helpful for several reasons. First, it would localize urban areas concerned by different climate behavior over summer daytime and be a good indicator of urban climate variability. Second, when overlaid with a land cover map, this map may contribute to identify possible urban management strategies to reduce heat wave effects in BMA.
Abstract: Because of its global reach, reduction of time
restraints, and ability to reduce costs and increase sales, use of the
Internet, the World Wide Web (WWW), and related technologies
can be a competitive tool in the arsenal of small and medium-sized
enterprises (SMEs). Countries the world over are interested in the
successful adoption of the Internet by SMEs. Because a vast
majority of jobs come from that sector, greater financial success of
SMEs translates into greater job growth and, subsequently, higher
tax revenue to the government. This research investigated the level
of Internet usage for business solutions by small and medium
enterprises in Jordan. Through the survey of a random sample of
100 firms with less than 500 employees and from data obtained
from this survey that formed the basis for our study, we found that
a majority of respondents use the Internet in business activities ,
the adoption of the Internet as a business tool is limited to a
brochure where Web site which primarily provides one way. As
such, there wasn't interactive information about the company and
its products and services.
Abstract: In a competitive energy market, system reliability
should be maintained at all times. Power system operation being of
online in nature, the energy balance requirements must be satisfied to
ensure reliable operation the system. To achieve this, information
regarding the expected status of the system, the scheduled
transactions and the relevant inputs necessary to make either a
transaction contract or a transmission contract operational, have to be
made available in real time. The real time procedure proposed,
facilitates this. This paper proposes a quadratic curve learning
procedure, which enables a generator-s contribution to the retailer
demand, power loss of transaction in a line at the retail end and its
associated losses for an oncoming operating scenario to be predicted.
Matlab program was used to test in on a 24-bus IEE Reliability Test
System, and the results are found to be acceptable.
Abstract: Generation system reliability assessment is an
important task which can be performed using deterministic or
probabilistic techniques. The probabilistic approaches have
significant advantages over the deterministic methods. However,
more complicated modeling is required by the probabilistic
approaches. Power generation model is a basic requirement for this
assessment. One form of the generation models is the well known
capacity outage probability table (COPT). Different analytical
techniques have been used to construct the COPT. These approaches
require considerable mathematical modeling of the generating units.
The unit-s models are combined to build the COPT which will add
more burdens on the process of creating the COPT. Decimal to
Binary Conversion (DBC) technique is widely and commonly applied
in electronic systems and computing This paper proposes a novel
utilization of the DBC to create the COPT without engaging in
analytical modeling or time consuming simulations. The simple
binary representation , “0 " and “1 " is used to model the states o f
generating units. The proposed technique is proven to be an effective
approach to build the generation model.
Abstract: Post-anthesis drought stress is the most important
problem affecting wheat production in dryland fields, specially in
Mediterranean regions. The main objective of this research was to
evaluate drought tolerance indices in dryland wheat genotypes under
post-anthesis drought stress. The research was including two different
experiments. In each experiment, twenty dryland bread wheat
genotypes were sown in a randomized complete blocks design
(RCBD) with three replications. One of experiments belonged to
rain-fed conditions (post-anthesis drought stress) and other
experiment was under non-stress conditions (with supplemental
irrigation). Different drought tolerance indices include Stress
Tolerance (Tol), Mean Productivity (MP), Geometric Mean
Productivity (GMP), Stress Susceptibility Index (SSI), Stress
Tolerance Index (STI), Harmonic Mean (HAM), Yield Index (YI)
and Yield Stability Index (YSI) were evaluate based on grain yield
under rain-fed (Ys) and supplemental irrigation (Yp) environments.
G10 and G12 were the most tolerant genotypes based on TOL and
SSI. But, based on MP, GMP, STI, HAM and YI indices, G1 and G2
were selected. STI, GMP and MP indices had high correlation with
grain yield under rain-fed and supplementary irrigation conditions
and were recognized as appropriate indices to identify genotypes with
high grain yield and low sensitivity to drought stress environments.
Abstract: The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for crossdomain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.
Abstract: Raw wood vinegar was purified by both standing and
filtering methods. Toxicity tests were conducted under laboratory
conditions by the topical application method (contact poison) and
feeding method (stomach poison). Larvicidal activities of wood
vinegar at four different concentrations (10, 15, 20, 25 and 30 %)
were studied against second instar larvae of housefly (Musca
domestica L.). Four replicates were maintained for all treatments and
controls. Larval mortality was recorded up to 96 hours and compared
with the larval survivability by two methods of larvicidal bioassay.
Percent pupation and percent adult emergence were observed in
treated M. domestica. The study revealed that the feeding method
gave higher efficiency compared with the topical application method.
Larval mortality increased with increasing concentration of wood
vinegar and the duration of exposure. No mortality was found in
treated M. domestica larvae at minimum 10% concentration of wood
vinegar through the experiments. The treated larvae were maintained
up to pupa and adult emergence. At 30% maximum concentration
larval duration was extended to 11 days in M. domestica for topical
application method and 9 days for feeding method. Similarly the
pupal durations were also increased with increased concentrations
(16 and 24 days for topical application method and feeding method
respectively at 30% concentration) of the treatments.
Abstract: In this paper, we propose a solution to the motion
control problem of a 2-link revolute manipulator arm. We require the
end-effector of the arm to move safely to its designated target in a
priori known workspace cluttered with fixed circular obstacles of
arbitrary position and sizes. Firstly a unique velocity algorithm is
used to move the end-effector to its target. Secondly, for obstacle
avoidance a turning angle is designed, which when incorporated into
the control laws ensures that the entire robot arm avoids any number
of fixed obstacles along its path enroute the target. The control laws
proposed in this paper also ensure that the equilibrium point of the
system is asymptotically stable. Computer simulations of the
proposed technique are presented.
Abstract: In this paper, genetic algorithm (GA) opmization technique is applied to design Flexible AC Transmission System (FACTS)-based damping controllers. Two types of controller structures, namely a proportional-integral (PI) and a lead-lag (LL) are considered. The design problem of the proposed controllers is formulated as an optimization problem and GA is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The proposed controllers are tested on a weakly connected power system subjected to different disturbances. The non-linear simulation results are presented to show the effectiveness of the proposed controller and their ability to provide efficient damping of low frequency oscillations. It is also observed that the proposed SSSC-based controllers improve greatly the voltage profile of the system under severe disturbances. Further, the dynamic performances of both the PI and LL structured FACTS-controller are analyzed at different loading conditions and under various disturbance condition as well as under unbalanced fault conditions..
Abstract: This study aimed to develop and initially validate an instrument that measures social competency among tertiary level faculty members. A review of extant literature on social competence was done. The review of extant literature led to the writing of the items in the initial instrument which was evaluated by 11 Subject Matter Experts (SMEs). The SMEs were either educators or psychologists. The results of the evaluations done by the SMEs served as bases for the creation of the pre-try-out instrument used in the first trial-run. Insights from the first trial-run participants led to the development of the main try-out instrument used in the final test administration. One Hundred Forty-one participants from five private Higher Education Institutions (HEIs) in the National Capital Region (NCR) and five private HEIs in Central Luzon in the Philippines participated in the final test administration. The reliability of the instrument was evaluated using Cronbach-s Coefficient Alpha formula and had a Cronbach-s Alpha of 0.92. On the other hand, Factor Analysis was used to evaluate the validity of the instrument and six factors were identified. The development of the final instrument was based on the results of the evaluation of the instrument-s reliability and validity. For purposes of recognition, the instrument was named “Social Competency Inventory for Tertiary Level Faculty Members (SCI-TLFM)."
Abstract: The leisure boatbuilding industry has tight profit margins that demand that boats are created to a high quality but with low cost. This requirement means reduced design times combined with increased use of design for production can lead to large benefits. The evolutionary nature of the boatbuilding industry can lead to a large usage of previous vessels in new designs. With the increase in automated tools for concurrent engineering within structural design it is important that these tools can reuse this information while subsequently feeding this to designers. The ability to accurately gather this materials and parts data is also a key component to these tools. This paper therefore aims to develop an architecture made up of neural networks and databases to feed information effectively to the designers based on previous design experience.
Abstract: A Finite Volume method based on Characteristic Fluxes for compressible fluids is developed. An explicit cell-centered resolution is adopted, where second and third order accuracy is provided by using two different MUSCL schemes with Minmod, Sweby or Superbee limiters for the hyperbolic part. Few different times integrator is used and be describe in this paper. Resolution is performed on a generic unstructured Cartesian grid, where solid boundaries are handled by a Cut-Cell method. Interfaces are explicitely advected in a non-diffusive way, ensuring local mass conservation. An improved cell cutting has been developed to handle boundaries of arbitrary geometrical complexity. Instead of using a polygon clipping algorithm, we use the Voxel traversal algorithm coupled with a local floodfill scanline to intersect 2D or 3D boundary surface meshes with the fixed Cartesian grid. Small cells stability problem near the boundaries is solved using a fully conservative merging method. Inflow and outflow conditions are also implemented in the model. The solver is validated on 2D academic test cases, such as the flow past a cylinder. The latter test cases are performed both in the frame of the body and in a fixed frame where the body is moving across the mesh. Adaptive Cartesian grid is provided by Paramesh without complex geometries for the moment.
Abstract: Data mining and knowledge engineering have become a tough task due to the availability of large amount of data in the web nowadays. Validity and reliability of data also become a main debate in knowledge acquisition. Besides, acquiring knowledge from different languages has become another concern. There are many language translators and corpora developed but the function of these translators and corpora are usually limited to certain languages and domains. Furthermore, search results from engines with traditional 'keyword' approach are no longer satisfying. More intelligent knowledge engineering agents are needed. To address to these problems, a system known as Multilingual Word Semantic Network is proposed. This system adapted semantic network to organize words according to concepts and relations. The system also uses open source as the development philosophy to enable the native language speakers and experts to contribute their knowledge to the system. The contributed words are then defined and linked using lexical and semantic relations. Thus, related words and derivatives can be identified and linked. From the outcome of the system implementation, it contributes to the development of semantic web and knowledge engineering.
Abstract: A large section of the society in Urban India is unable
to afford a basic dwelling unit. Housing shortage due to the rising unafforability makes it logical to consider alternative technologies more seriously for their application How far do these alternative
technologies match up with the conventional techniques? How do these integrate with the present-day need for urban amenities and
facilities? Are the owners of bamboo dwellings, for instance, a part of
the mainstream housing sector, having the same rights and privileges
as those enjoyed by other property owners? Will they have access to loans for building, improving, renovating or repairing their
dwellings? Why do we still hesitate to build a bamboo house for ourselves? Is our policy framework and political resolve in place, to
welcome such alternative technologies? It is time we found these answers, in order to explore the reasons for large-scale nonacceptance,
of a technology proven for its worthiness.
Abstract: This study discusses the effect of uncertainty on
production levels of a petrochemical complex. Uncertainly or
variations in some model parameters, such as prices, supply and
demand of materials, can affect the optimality or the efficiency of any
chemical process. For any petrochemical complex with many plants,
there are many sources of uncertainty and frequent variations which
require more attention. Many optimization approaches are proposed
in the literature to incorporate uncertainty within the model in order
to obtain a robust solution. In this work, a stability analysis approach
is applied to a deterministic LP model of a petrochemical complex
consists of ten plants to investigate the effect of such variations on
the obtained optimal production levels. The proposed approach can
determinate the allowable variation ranges of some parameters,
mainly objective or RHS coefficients, before the system lose its
optimality. Parameters with relatively narrow range of variations, i.e.
stability limits, are classified as sensitive parameters or constraints
that need accurate estimate or intensive monitoring. These stability
limits offer easy-to-use information to the decision maker and help in
understanding the interaction between some model parameters and
deciding when the system need to be re-optimize. The study shows
that maximum production of ethylene and the prices of intermediate
products are the most sensitive factors that affect the stability of the
optimum solution
Abstract: This paper discusses a qualitative simulator QRiOM
that uses Qualitative Reasoning (QR) technique, and a process-based
ontology to model, simulate and explain the behaviour of selected
organic reactions. Learning organic reactions requires the application
of domain knowledge at intuitive level, which is difficult to be
programmed using traditional approach. The main objective of
QRiOM is to help learners gain a better understanding of the
fundamental organic reaction concepts, and to improve their
conceptual comprehension on the subject by analyzing the multiple
forms of explanation generated by the software. This paper focuses
on the generation of explanation based on causal theories to explicate
various phenomena in the chemistry subject. QRiOM has been tested
with three classes problems related to organic chemistry, with
encouraging results. This paper also presents the results of
preliminary evaluation of QRiOM that reveal its explanation
capability and usefulness.
Abstract: The objective of the present research manuscript is to
perform parametric, nonparametric, and decision tree analysis to
evaluate two treatments that are being used for breast cancer patients.
Our study is based on utilizing real data which was initially used in
“Tamoxifen with or without breast irradiation in women of 50 years
of age or older with early breast cancer" [1], and the data is supplied
to us by N.A. Ibrahim “Decision tree for competing risks survival
probability in breast cancer study" [2]. We agree upon certain aspects
of our findings with the published results. However, in this
manuscript, we focus on relapse time of breast cancer patients instead
of survival time and parametric analysis instead of semi-parametric
decision tree analysis is applied to provide more precise
recommendations of effectiveness of the two treatments with respect
to reoccurrence of breast cancer.
Abstract: The effects of global warming on India vary from the
submergence of low-lying islands and coastal lands to the melting of
glaciers in the Indian Himalayas, threatening the volumetric flow rate
of many of the most important rivers of India and South Asia. In
India, such effects are projected to impact millions of lives. As a
result of ongoing climate change, the climate of India has become
increasingly volatile over the past several decades; this trend is
expected to continue.
Climate change is one of the most important global environmental
challenges, with implications for food production, water supply,
health, energy, etc. Addressing climate change requires a good
scientific understanding as well as coordinated action at national and
global level. The climate change issue is part of the larger challenge
of sustainable development. As a result, climate policies can be more
effective when consistently embedded within broader strategies
designed to make national and regional development paths more
sustainable. The impact of climate variability and change, climate
policy responses, and associated socio-economic development will
affect the ability of countries to achieve sustainable development
goals.
A very well calibrated Soil and Water Assessment Tool (R2 =
0.9968, NSE = 0.91) was exercised over the Khatra sub basin of the
Kangsabati River watershed in Bankura district of West Bengal,
India, in order to evaluate projected parameters for agricultural
activities. Evapotranspiration, Transmission Losses, Potential
Evapotranspiration and Lateral Flow to reach are evaluated from the
years 2041-2050 in order to generate a picture for sustainable
development of the river basin and its inhabitants.
India has a significant stake in scientific advancement as well as
an international understanding to promote mitigation and adaptation.
This requires improved scientific understanding, capacity building,
networking and broad consultation processes. This paper is a
commitment towards the planning, management and development of
the water resources of the Kangsabati River by presenting detailed
future scenarios of the Kangsabati river basin, Khatra sub basin, over
the mentioned time period.
India-s economy and societal infrastructures are finely tuned to the
remarkable stability of the Indian monsoon, with the consequence
that vulnerability to small changes in monsoon rainfall is very high.
In 2002 the monsoon rains failed during July, causing profound loss
of agricultural production with a drop of over 3% in India-s GDP.
Neither the prolonged break in the monsoon nor the seasonal rainfall
deficit was predicted. While the general features of monsoon
variability and change are fairly well-documented, the causal
mechanisms and the role of regional ecosystems in modulating the
changes are still not clear. Current climate models are very poor at
modelling the Asian monsoon: this is a challenging and critical
region where the ocean, atmosphere, land surface and mountains all
interact. The impact of climate change on regional ecosystems is
likewise unknown. The potential for the monsoon to become more
volatile has major implications for India itself and for economies
worldwide. Knowledge of future variability of the monsoon system,
particularly in the context of global climate change, is of great
concern for regional water and food security.
The major findings of this paper were that of all the chosen
projected parameters, transmission losses, soil water content,
potential evapotranspiration, evapotranspiration and lateral flow to
reach, display an increasing trend over the time period of years 2041-
2050.
Abstract: Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.