Abstract: The main objective of this research is to synthesize silk fibroin fiber for indoor air particulate removal. Silk cocoons were de-gummed using 0.5 wt % Na2CO3 alkaline solutions at 90 Ó╣ìC for 60 mins, washed with distilled water, and dried at 80 Ó╣ìC for 3 hrs in a vacuum oven. Two sets of experiment were conducted to investigate the impacts of initial particulate matter (PM) concentration and that of air flow rate on the removal efficiency. Rice bran collected from a local rice mill in Ubonratchathani province was used as indoor air contaminant in this work. The morphology and physical properties of silk fibroin (SF) fiber were measured. The SEM revealed the deposition of PM on the used fiber. The PM removal efficiencies of 72.29 ± 3.03 % and 39.33 ± 1.99 % were obtained of PM10 and PM2.5, respectively, when using the initial PM concentration at 0.040 mg/m3 and 0.020 mg/m3 of PM10 and PM2.5, respectively, with the air flow rate of 5 L/min.
Abstract: This paper proposes to use ETM+ multispectral data
and panchromatic band as well as texture features derived from the
panchromatic band for land cover classification. Four texture features
including one 'internal texture' and three GLCM based textures
namely correlation, entropy, and inverse different moment were used
in combination with ETM+ multispectral data. Two data sets
involving combination of multispectral, panchromatic band and its
texture were used and results were compared with those obtained by
using multispectral data alone. A decision tree classifier with and
without boosting were used to classify different datasets. Results
from this study suggest that the dataset consisting of panchromatic
band, four of its texture features and multispectral data was able to
increase the classification accuracy by about 2%. In comparison, a
boosted decision tree was able to increase the classification accuracy
by about 3% with the same dataset.
Abstract: Our work is part of the heterogeneous data
integration, with the definition of a structural and semantic mediation
model. Our aim is to propose architecture for the heterogeneous
sources metadata mediation, represented by XML, RDF and RuleML
models, providing to the user the metadata transparency. This, by
including data structures, of natures fundamentally different, and
allowing the decomposition of a query involving multiple sources, to
queries specific to these sources, then recompose the result.
Abstract: This study examines the design and construction of AC Electronics load surge protection in order to carry electric surge load arisen from faults in low voltage electricity system (single phase/220V) by using the principle of electronics load clamping voltage during induction period so that electric voltage could go through to safe load and continue to work. The qualification of the designed device could prevent both transient over voltage and voltage swell. Both will work in cooperation, resulting in the ability to improve and modify the quality of electrical power in Thailand electricity distribution system more effective than the past and help increase the lifetime of electric appliances, electric devices, and electricity protection equipments.
Abstract: The use of human hand as a natural interface for humancomputer interaction (HCI) serves as the motivation for research in hand gesture recognition. Vision-based hand gesture recognition involves visual analysis of hand shape, position and/or movement. In this paper, we use the concept of object-based video abstraction for segmenting the frames into video object planes (VOPs), as used in MPEG-4, with each VOP corresponding to one semantically meaningful hand position. Next, the key VOPs are selected on the basis of the amount of change in hand shape – for a given key frame in the sequence the next key frame is the one in which the hand changes its shape significantly. Thus, an entire video clip is transformed into a small number of representative frames that are sufficient to represent a gesture sequence. Subsequently, we model a particular gesture as a sequence of key frames each bearing information about its duration. These constitute a finite state machine. For recognition, the states of the incoming gesture sequence are matched with the states of all different FSMs contained in the database of gesture vocabulary. The core idea of our proposed representation is that redundant frames of the gesture video sequence bear only the temporal information of a gesture and hence discarded for computational efficiency. Experimental results obtained demonstrate the effectiveness of our proposed scheme for key frame extraction, subsequent gesture summarization and finally gesture recognition.
Abstract: Metropolitan areas have suffered from traffic problems, which have steadily increased in many monocentric cities. Urban expansion, population growth, and road network development have resulted in a structural shift toward urban sprawl, increasing commuters’ dependence on private modes of transport. This paper aims to model the influence of socioeconomic and land-use factors on mode choice using a multinomial and nested logit model. Land-use patterns—such as residential, commercial, retail, educational and employment related—affect the choice of mode and destination in the short and medium term. Socioeconomic factors—such as age, gender, income, household size, and house type—also affect choice, while residential location is affected in the long term. Riyadh in Saudi Arabia and Melbourne in Australia were chosen as case studies. Riyadh is a car-dependent city with limited public transport, whereas Melbourne has good public transport but an increase in car dependence. Aggregate level land-use data and disaggregate level individual, household, and journey-to-work data are used to determine the effects of land use and socioeconomic factors on mode choice. The model results determined that urban sprawl is the main factor that affects mode choice, income, and house type.
Abstract: This paper presents an experimental investigation using Acoustic Emission (AE) technology to monitor sand transportation in multiphase flow. The investigations were undertaken on three-phase (air-water-sand) flow in a horizontal pipe where the superficial gas velocity (VSG) had a range of between 0.2msˉ¹ to 2.0msˉ¹ and superficial liquid velocity (VSL) had a range of between 0.2msˉ¹ to 1.0msˉ¹. The experimental findings clearly show a correlation exists between AE energy levels, sand concentration, superficial gas velocity (VSG), and superficial liquid velocity (VSL).
Abstract: The understanding of the system level of biological behavior and phenomenon variously needs some elements such as gene sequence, protein structure, gene functions and metabolic pathways. Challenging problems are representing, learning and reasoning about these biochemical reactions, gene and protein structure, genotype and relation between the phenotype, and expression system on those interactions. The goal of our work is to understand the behaviors of the interactions networks and to model their evolution in time and in space. We propose in this study an ontological meta-model for the knowledge representation of the genetic regulatory networks. Ontology in artificial intelligence means the fundamental categories and relations that provide a framework for knowledge models. Domain ontology's are now commonly used to enable heterogeneous information resources, such as knowledge-based systems, to communicate with each other. The interest of our model is to represent the spatial, temporal and spatio-temporal knowledge. We validated our propositions in the genetic regulatory network of the Aarbidosis thaliana flower
Abstract: This paper presents a new technique for generating sets of synthetic classifiers to evaluate abstract-level combination methods. The sets differ in terms of both recognition rates of the individual classifiers and degree of similarity. For this purpose, each abstract-level classifier is considered as a random variable producing one class label as the output for an input pattern. From the initial set of classifiers, new slightly different sets are generated by applying specific operators, which are defined at the purpose. Finally, the sets of synthetic classifiers have been used to estimate the performance of combination methods for abstract-level classifiers. The experimental results demonstrate the effectiveness of the proposed approach.
Abstract: This paper presents a new method to detect high impedance faults in radial distribution systems. Magnitudes of third and fifth harmonic components of voltages and currents are used as a feature vector for fault discrimination. The proposed methodology uses a learning vector quantization (LVQ) neural network as a classifier for identifying high impedance arc-type faults. The network learns from the data obtained from simulation of a simple radial system under different fault and system conditions. Compared to a feed-forward neural network, a properly tuned LVQ network gives quicker response.
Abstract: An effort to develop a unit commitment approach
capable of handling large power systems consisting of both thermal
and hydro generating units offers a large profitable return. In order to
be feasible, the method to be developed must be flexible, efficient
and reliable. In this paper, various proposed methods have been
described along with their strengths and weaknesses. As all of these
methods have some sort of weaknesses, a comprehensive algorithm
that combines the strengths of different methods and overcomes each
other-s weaknesses would be a suitable approach for solving
industry-grade unit commitment problem.
Abstract: With the explosive growth of data available on the
Internet, personalization of this information space become a
necessity. At present time with the rapid increasing popularity of the
WWW, Websites are playing a crucial role to convey knowledge and
information to the end users. Discovering hidden and meaningful
information about Web users usage patterns is critical to determine
effective marketing strategies to optimize the Web server usage for
accommodating future growth. The task of mining useful information
becomes more challenging when the Web traffic volume is enormous
and keeps on growing. In this paper, we propose a intelligent model
to discover and analyze useful knowledge from the available Web
log data.
Abstract: The evaluation of conversational agents or chatterbots question answering systems is a major research area that needs much attention. Before the rise of domain-oriented conversational agents based on natural language understanding and reasoning, evaluation is never a problem as information retrieval-based metrics are readily available for use. However, when chatterbots began to become more domain specific, evaluation becomes a real issue. This is especially true when understanding and reasoning is required to cater for a wider variety of questions and at the same time to achieve high quality responses. This paper discusses the inappropriateness of the existing measures for response quality evaluation and the call for new standard measures and related considerations are brought forward. As a short-term solution for evaluating response quality of conversational agents, and to demonstrate the challenges in evaluating systems of different nature, this research proposes a blackbox approach using observation, classification scheme and a scoring mechanism to assess and rank three example systems, AnswerBus, START and AINI.
Abstract: Presence of phytosterol compound in Durian seed
(Durio zibethinus) or known as King of fruits has been discovered
from screening work using reagent test. Further analysis work has
been carried out using mass spectrometer in order to support the
priliminary finding. Isolation and purification of the major
phytosterol has been carried out using an open column
chromatography. The separation was monitored using thin layer
chromatography (TLC). Major isolated compounds and purified
phytosterol were identified using mass spectrometer and nuclear
magnetic resonance (NMR). This novel finding could promote
utilization of durian seeds as a functional ingredient in food products
through production of standardized extract based on phytosterol
content.
Abstract: The antioxidant compounds are needed for the food, beverages, and pharmaceuticals industry. For this purpose, an appropriate method is required to measure the antioxidant properties in various types of samples. Spectrophotometric method usually used has some weaknesses, including the high price, long sample preparation time, and less sensitivity. Among the alternative methods developed to overcome these weaknesses is antioxidant biosensor based on superoxide dismutase (SOD) enzyme. Therefore, this study was carried out to measure the SOD activity originating from Deinococcus radiodurans and to determine its kinetics properties. Carbon paste electrode modified with ferrocene and immobilized SOD exhibited anode and cathode current peak at potential of +400 and +300mv respectively, in both pure SOD and SOD of D. radiodurans. This indicated that the current generated was from superoxide catalytic dismutation reaction by SOD. Optimum conditions for SOD activity was at pH 9 and temperature of 27.50C for D. radiodurans SOD, and pH 11 and temperature of 200C for pure SOD. Dismutation reaction kinetics of superoxide catalyzed by SOD followed the Lineweaver-Burk kinetics with D. radiodurans SOD KMapp value was smaller than pure SOD. The result showed that D. radiodurans SOD had higher enzyme-substrate affinity and specificity than pure SOD. It concluded that D. radiodurans SOD had a great potential as biological recognition component for antioxidant biosensor.
Abstract: Global temperature had increased by about 0.5oC over
the past century, increasing temperature leads to a loss or a decrease
of soil organic matter (SOM). Whereas soil organic matter in many
tropical soils is less stable than that of temperate soils, and it will be
easily affected by climate change. Therefore, conservation of soil
organic matter is urgent issue nowadays. This paper presents the
effect of different doses (5%, 15%) of Ca-type zeolite in conjunction
with organic manure, applied to soil samples from Philippines,
Paraguay and Japan, on the decomposition resistance of soil organic
matter under high temperature. Results showed that a remain or
slightly increase the C/N ratio of soil. There are an increase in
percent of humic acid (PQ) that extracted with Na4P2O7. A decrease
of percent of free humus (fH) after incubation was determined. A
larger the relative color intensity (RF) value and a lower the color
coefficient (6logK) value following increasing zeolite rates leading
to a higher degrees of humification. The increase in the aromatic
condensation of humic acid (HA) after incubation, as indicates by the
decrease of H/C and O/C ratios of HA. This finding indicates that the
use of zeolite could be beneficial with respect to SOM conservation
under global warming condition.
Abstract: Beginning from the creator of integro-differential
equations Volterra, many scientists have investigated these
equations. Classic method for solving integro-differential
equations is the quadratures method that is successfully applied up
today. Unlike these methods, Makroglou applied hybrid methods
that are modified and generalized in this paper and applied to the
numerical solution of Volterra integro-differential equations. The
way for defining the coefficients of the suggested method is also
given.
Abstract: This study investigated the effect of oxygen and
micro-cracking on the flotation of low grade nickel sulphide ore. The
ore treated contained serpentine minerals which have a history of
being difficult to process efficiently. The use of oxygen as a bubbling
gas has been noted to be effective because it increases the pulp
potential. The desired effect of micro cracking the ore is that the
nickel sulphide minerals will become activated and this activation
will render these minerals more susceptible to react with potassium
amyl xanthate collectors, resulting in a higher recovery of nickel and
hinder the recovery of other undesired minerals contained in the ore.
Higher nickel recoveries were obtained when pure oxygen was used
as a bubbling gas rather than the conventional air. Microwave
cracking favored the recovery of nickel.
Abstract: In Data mining, Fuzzy clustering algorithms have
demonstrated advantage over crisp clustering algorithms in dealing
with the challenges posed by large collections of vague and uncertain
natural data. This paper reviews concept of fuzzy logic and fuzzy
clustering. The classical fuzzy c-means algorithm is presented and its
limitations are highlighted. Based on the study of the fuzzy c-means
algorithm and its extensions, we propose a modification to the cmeans
algorithm to overcome the limitations of it in calculating the
new cluster centers and in finding the membership values with
natural data. The efficiency of the new modified method is
demonstrated on real data collected for Bhutan-s Gross National
Happiness (GNH) program.
Abstract: Axial Flux Permanent Magnet (AFPM) Machines require effective cooling due to their high power density. The detrimental effects of overheating such as degradation of the insulation materials, magnets demagnetization, and increase of Joule losses are well known. This paper describes the CFD simulations performed on a test rig model of an air cooled Axial Flux Permanent Magnet (AFPM) generator built at Durham University to identify the temperatures and heat transfer coefficient on the stator. The Reynolds Averaged Navier-Stokes and the Energy equations are solved and the flow pattern and heat transfer developing inside the machine are described. The Nusselt number on the stator surfaces has been found. The dependency of the heat transfer on the flow field is described temperature field obtained. Tests on an experimental are undergoing in order to validate the CFD results.