Abstract: Fuzzy Load forecasting plays a paramount role in the operation and management of power systems. Accurate estimation of future power demands for various lead times facilitates the task of generating power reliably and economically. The forecasting of future loads for a relatively large lead time (months to few years) is studied here (long term load forecasting). Among the various techniques used in forecasting load, artificial intelligence techniques provide greater accuracy to the forecasts as compared to conventional techniques. Fuzzy Logic, a very robust artificial intelligent technique, is described in this paper to forecast load on long term basis. The paper gives a general algorithm to forecast long term load. The algorithm is an Extension of Short term load forecasting method to Long term load forecasting and concentrates not only on the forecast values of load but also on the errors incorporated into the forecast. Hence, by correcting the errors in the forecast, forecasts with very high accuracy have been achieved. The algorithm, in the paper, is demonstrated with the help of data collected for residential sector (LT2 (a) type load: Domestic consumers). Load, is determined for three consecutive years (from April-06 to March-09) in order to demonstrate the efficiency of the algorithm and to forecast for the next two years (from April-09 to March-11).
Abstract: Measurements of capacitance C and dissipation
factor tand of the stator insulation system provide useful information
about internal defects within the insulation. The index k is defined as
the proportionality constant between the changes at high voltage of
capacitance DC and of the dissipation factor Dtand . DC and
Dtand values were highly correlated when small flat defects were
within the insulation and that correlation was lost in the presence of
large narrow defects like electrical treeing. The discrimination
between small and large defects is made resorting to partial discharge
PD phase angle analysis. For the validation of the results, C and tand
measurements were carried out in a 15MVA 4160V steam turbine
turbogenerator placed in a sugar mill. In addition, laboratory test
results obtained by other authors were analyzed jointly. In such
laboratory tests, model coil bars subjected to thermal cycling resulted
highly degraded and DC and Dtand values were not correlated. Thus,
the index k could not be calculated.
Abstract: The paper investigates the feasibility of constructing a software multi-agent based monitoring and classification system and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. The agents function autonomously to provide continuous and periodic monitoring of excels spreadsheet workbooks. Resulting in, the development of the MultiAgent classification System (MACS) that is in compliance with the specifications of the Foundation for Intelligent Physical Agents (FIPA). However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies that are Windows Communication Foundation (WCF) services, Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). The Microsoft's .NET widows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW that is in order to satisfy the monitoring and classification of the multiple developer aspect. ODM was used to automate the classification phase of MACS.
Abstract: The study of non-equilibrium systems has attracted
increasing interest in recent years, mainly due to the lack of
theoretical frameworks, unlike their equilibrium counterparts.
Studying the steady state and/or simple systems is thus one of the
main interests. Hence in this work we have focused our attention on
the driven lattice gas model (DLG model) consisting of interacting
particles subject to an external field E. The dynamics of the system
are given by hopping of particles to nearby empty sites with rates
biased for jumps in the direction of E. Having used small two
dimensional systems of DLG model, the stochastic properties at nonequilibrium
steady state were analytically studied. To understand the
non-equilibrium phenomena, we have applied the analytic approach
via master equation to calculate probability function and analyze
violation of detailed balance in term of the fluctuation-dissipation
theorem. Monte Carlo simulations have been performed to validate
the analytic results.
Abstract: This paper aims to present knowledge management for solving economic problem and poverty in Thai community. A community in Thailand is studied as a case study for master plan or social and economic plan which derived form the research people conducted by themselves in their community. The result shows that community uses knowledge management in recording income and expense, analyzing their consumption, and then systematic planning of the production, distribution and consumption in the community. Besides, community enterprises, that people create as the by-products of master plan, can facilitate diverse economic activities which are able to reduce economic problem and poverty. The knowledge that people gain from solving their problem through building community enterprises are both tacit and explicit knowledge. Four styles of knowledge conversion: socialization,externalization, combination and internalization, are used. Besides, knowledge sharing inside the organization, between organizations and its environment are found. Keywordsknowledge management, community enterprise, Thailand.
Abstract: The purpose of this study is to research on thoughts transmitted from virtual fitting-room and to deduce discussion in an auxiliary narrative way. The research structure is based on 3D virtual fitting-room as the research subject. Initially, we will discuss the principles of narrate study, User Demand and so on by using a narrative design pattern to transmit their objective indications of “people-situation-reason-object", etc, and then to analyze the virtual fitting-room examples that are able to provide a new thinking for designers who engaged in clothing related industry – which comes in “story telling" and “user-centered design" forms. Clothing designs are not just to cover up the body to keep warm but to draw closer to people-s demand physiologically and psychologically through interactive designs so as to achieve cognition between people and environment. In the “outside" goal of clothing-s functional designs, we use tribal group-s behavior characteristics to “transform" the existing personal cultural stories, and “reform" them to design appropriate interactive products. Synthesizing the above matters, apart from being able to regard “narrate" as a kind of functional thinking process, we are also able to regard it as a kind of choice, arrangement and an activity of story expression, allowing interactive design-s spirit, product characteristics and experience ideas be transmitted to target tribal group in a visual image performance method. It is a far more confident and innovative attempt, and meanwhile, able to achieve entertainment, joyful and so forth fundamental interactive transmissions. Therefore, this study takes “user-centered design" thinking as a basis to establish a set of clothing designs with interactive experience patterns and to assist designers to examine the five sensual feeling of interactive demands in order to initiate a new value in textile industry.
Abstract: In this paper, we propose a hybrid machine learning
system based on Genetic Algorithm (GA) and Support Vector
Machines (SVM) for stock market prediction. A variety of indicators
from the technical analysis field of study are used as input features.
We also make use of the correlation between stock prices of different
companies to forecast the price of a stock, making use of technical
indicators of highly correlated stocks, not only the stock to be
predicted. The genetic algorithm is used to select the set of most
informative input features from among all the technical indicators.
The results show that the hybrid GA-SVM system outperforms the
stand alone SVM system.
Abstract: In this paper, we proposed a new framework to incorporate an intelligent agent software robot into a crisis communication portal (CCNet) in order to send alert news to subscribed users via email and other mobile services such as Short Message Service (SMS), Multimedia Messaging Service (MMS) and General Packet Radio Services (GPRS). The content on the mobile services can be delivered either through mobile phone or Personal Digital Assistance (PDA). This research has shown that with our proposed framework, the embodied conversation agents system can handle questions intelligently with our multilayer architecture. At the same time, the extended framework can take care of delivery content through a more humanoid interface on mobile devices.
Abstract: The quantum mechanics simulation was applied for
calculating the interaction force between 2 molecules based on atomic level. For the simple extractive distillation system, it is ternary
components consisting of 2 closed boiling point components (A,lower boiling point and B, higher boiling point) and solvent (S). The
quantum mechanics simulation was used to calculate the intermolecular force (interaction force) between the closed boiling
point components and solvents consisting of intermolecular between
A-S and B-S.
The requirement of the promising solvent for extractive distillation
is that solvent (S) has to form stronger intermolecular force with only
one component than the other component (A or B). In this study, the
systems of aromatic-aromatic, aromatic-cycloparaffin, and paraffindiolefin
systems were selected as the demonstration for solvent
selection. This study defined new term using for screening the solvents called relative interaction force which is calculated from the
quantum mechanics simulation. The results showed that relative
interaction force gave the good agreement with the literature data
(relative volatilities from the experiment). The reasons are discussed. Finally, this study suggests that quantum mechanics results can improve the relative volatility estimation for screening the solvents leading to reduce time and money consuming
Abstract: In mobile computing environments, there are many
new non existing problems in the distributed system, which is
consisted of stationary hosts because of host mobility, sudden
disconnection by handoff in wireless networks, voluntary
disconnection for efficient power consumption of a mobile host, etc.
To solve the problems, we proposed the architecture of Partial
Connection Manager (PCM) in this paper. PCM creates the limited
number of mobile agents according to priority, sends them in parallel
to servers, and combines the results to process the user request rapidly.
In applying the proposed PCM to the mobile market agent service, we
understand that the mobile agent technique could be suited for the
mobile computing environment and the partial connection problem
management.
Abstract: The aim of this study was to extract sugar from
sugarcane using high electric field pulse (HELP) as a non-thermal cell permeabilization method. The result of this study showed that it
is possible to permeablize sugar cane cells using HELP at very short times (less than 10 sec.) and at room temperature. Increasing the field strength (from 0.5kV/cm to 2kV/cm) and pulse number (1 to 12) led to increasing the permeabilization of sugar cane cells. The energy
consumption during HELP treatment of sugar cane (2.4 kJ/kg) was about 100 times less compared to thermal cell disintegration at 85
Abstract: This study focuses on an evaluation of Hokkaido which
is the northernmost and largest prefecture by surface area in Japan and
particularly on two points: the rivalry between all kinds of land use
such as urban land and agricultural and forestry land in various cities
and their surrounding areas and the possibilities for forestry biomass in
areas other than those mentioned above and grasps which areas require
examination of the nature of land use control and guidance through
conducting land use analysis at the district level using GIS
(Geographic Information Systems). The results of analysis in this
study demonstrated that it is essential to divide the whole of Hokkaido
into two areas: those within delineated city planning areas and those
outside of delineated city planning areas and to conduct an evaluation
of each land use control.
In delineated urban areas, particularly urban areas, it is essential to
re-examine land use from the point of view of compact cities or smart
cities along with conducting an evaluation of land use control that
focuses on issues of rivalry between all kinds of land use such as urban
land and agricultural and forestry land. In areas outside of delineated
urban areas, it is desirable to aim to build a specific community
recycling range based on forest biomass utilization by conducting an
evaluation of land use control concerning the possibilities for forest
biomass focusing particularly on forests within and outside of city
planning areas.
Abstract: In this paper, a model for an information retrieval
system is proposed which takes into account that knowledge about
documents and information need of users are dynamic. Two
methods are combined, one qualitative or symbolic and the other
quantitative or numeric, which are deemed suitable for many
clustering contexts, data analysis, concept exploring and
knowledge discovery. These two methods may be classified as
inductive learning techniques. In this model, they are introduced to
build “long term" knowledge about past queries and concepts in a
collection of documents. The “long term" knowledge can guide
and assist the user to formulate an initial query and can be
exploited in the process of retrieving relevant information. The
different kinds of knowledge are organized in different points of
view. This may be considered an enrichment of the exploration
level which is coherent with the concept of document/query
structure.
Abstract: This paper presents an effective traffic lights detection
method at the night-time. First, candidate blobs of traffic lights are
extracted from RGB color image. Input image is represented on the
dominant color domain by using color transform proposed by Ruta,
then red and green color dominant regions are selected as candidates.
After candidate blob selection, we carry out shape filter for noise
reduction using information of blobs such as length, area, area of
boundary box, etc. A multi-class classifier based on SVM (Support
Vector Machine) applies into the candidates. Three kinds of features
are used. We use basic features such as blob width, height, center
coordinate, area, area of blob. Bright based stochastic features are also
used. In particular, geometric based moment-s values between
candidate region and adjacent region are proposed and used to improve
the detection performance. The proposed system is implemented on
Intel Core CPU with 2.80 GHz and 4 GB RAM and tested with the
urban and rural road videos. Through the test, we show that the
proposed method using PF, BMF, and GMF reaches up to 93 % of
detection rate with computation time of in average 15 ms/frame.
Abstract: A new hybrid coding method for compressing
animated polygonal meshes is presented. This paper assumes
the simplistic representation of the geometric data: a temporal
sequence of polygonal meshes for each discrete frame of the
animated sequence. The method utilizes a delta coding and an
octree-based method. In this hybrid method, both the octree
approach and the delta coding approach are applied to each
single frame in the animation sequence in parallel. The
approach that generates the smaller encoded file size is chosen
to encode the current frame. Given the same quality
requirement, the hybrid coding method can achieve much
higher compression ratio than the octree-only method or the
delta-only method. The hybrid approach can represent 3D
animated sequences with higher compression factors while
maintaining reasonable quality. It is easy to implement and have
a low cost encoding process and a fast decoding process, which
make it a better choice for real time application.
Abstract: Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, particle swarm optimization (PSO) technique is applied to design a robust power system stabilizer (PSS). The design problem of the proposed controller is formulated as an optimization problem and PSO 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 non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations. Further, all the simulations results are compared with a conventionally designed power system stabilizer to show the superiority of the proposed design approach.
Abstract: Aim of this work was to compare the efficacy of two
loading methods of proteins onto polymeric nanocarriers: adsorption
and encapsulation methods. Preliminary studies of protein loading
were done using Bovine Serum Albumin (BSA) as model protein.
Nanocarriers were prepared starting from polylactic co-glycolic acid
(PLGA) polymer; production methods used are two different variants
of emulsion evaporation method. Nanoparticles obtained were
analyzed in terms of dimensions by Dynamic Light Scattering and
Loading Efficiency of BSA by Bradford Assay. Loaded
nanoparticles were then submitted to in-vitro protein dissolution test
in order to study the effect of the delivery system on the release rate
of the protein.
Abstract: The scattering effect of light in fog improves the
difficulty in visibility thus introducing disturbances in transport
facilities in urban or industrial areas causing fatal accidents or public
harassments, therefore, developing an enhanced fog vision system
with radio wave to improvise the way outs of these severe problems
is really a big challenge for researchers. Series of experimental
studies already been done and more are in progress to know the
weather effect on radio frequencies for different ranges. According to
Rayleigh scattering Law, the propagating wavelength should be
greater than the diameter of the particle present in the penetrating
medium. Direct wave RF signal thus have high chance of failure to
work in such weather for detection of any object. Therefore an
extensive study was required to find suitable region in the RF band
that can help us in detecting objects with proper shape. This paper
produces some results on object detection using 912 MHz band with
successful detection of the persistence of any object coming under the
trajectory of a vehicle navigating in indoor and outdoor environment.
The developed images are finally transformed to video signal to
enable continuous monitoring.
Abstract: In recent years Operational Transconductance Amplifier based high frequency integrated circuits, filters and systems have been widely investigated. The usefulness of OTAs over conventional OP-Amps in the design of both first order and second order active filters are well documented. This paper discusses some of the tunability issues using the Matlab/Simulink® software which are previously unreported for any commercial OTA. Using the simulation results two first order voltage controlled all pass filters with phase tuning capability are proposed.
Abstract: FW4 is a newly developed hot die material widely
used in Forging Dies manufacturing. The right selection of the
machining conditions is one of the most important aspects to take
into consideration in the Electrical Discharge Machining (EDM) of
FW4. In this paper an attempt has been made to develop
mathematical models for relating the Material Removal Rate (MRR),
Tool Wear Ratio (TWR) and surface roughness (Ra) to machining
parameters (current, pulse-on time and voltage). Furthermore, a study
was carried out to analyze the effects of machining parameters in
respect of listed technological characteristics. The results of analysis
of variance (ANOVA) indicate that the proposed mathematical
models, can adequately describe the performance within the limits of
the factors being studied.