Abstract: The purpose of this study was to investigate the effectiveness of a recreational workout program for adults with disabilities over two semesters. This investigation was an action study conducted in a naturalistic setting. Participants included equal numbers of adults with severe cognitive impairments (n = 35) and adults without disabilities (n = 35). Adults with disabilities severe cognitive impairments were trained 6 self-initiated workout activities over two semesters by adults without disabilities. The numbers of task-analyzed steps of each activity performed correctly by each participant at the first and last weeks of each semester were used for data analysis. Results of the paired t-tests indicate that across two semesters, significant differences between the first and last weeks were found on 4 out of the 6 task-analyzed workout activities at a statistical level of significance p < .05. The recreational workout program developed in this study was effective.
Abstract: SVM ( Support Vector Machine ) is a new method in the artificial neural network ( ANN ). In the steel making, how to use computer to predict the end point of BOF accuracy is a great problem. A lot of method and theory have been claimed, but most of the results is not satisfied. Now the hot topic in the BOF end point predicting is to use optical way the predict the end point in the BOF. And we found that there exist some regular in the characteristic curve of the flame from the mouse of pudding. And we can use SVM to predict end point of the BOF, just single spectrum intensity should be required as the input parameter. Moreover, its compatibility for the input space is better than the BP network.
Abstract: The most suitable Semiconductor detector, Cadmium
Zinc Teloraid , has unique properties because of high Atomic number
and wide Brand Gap . It has been tried in this project with different
processes such as Lead , Diffusion , Produce and Recombination ,
effect of Trapping and injection carrier of CdZnTe , to get hole and
then present a complete answer of it . Then we should investigate the
movement of carrier ( Electron – Hole ) by using above answer.
Abstract: With the advent of emerging personal computing paradigms such as ubiquitous and mobile computing, Web contents are becoming accessible from a wide range of mobile devices. Since these devices do not have the same rendering capabilities, Web contents need to be adapted for transparent access from a variety of client agents. Such content adaptation results in better rendering and faster delivery to the client device. Nevertheless, Web content adaptation sets new challenges for semantic markup. This paper presents an advanced components platform, called MorfeoSMC, enabling the development of mobility applications and services according to a channel model based on Services Oriented Architecture (SOA) principles. It then goes on to describe the potential for integration with the Semantic Web through a novel framework of external semantic annotation of mobile Web contents. The role of semantic annotation in this framework is to describe the contents of individual documents themselves, assuring the preservation of the semantics during the process of adapting content rendering, as well as to exploit these semantic annotations in a novel user profile-aware content adaptation process. Semantic Web content adaptation is a way of adding value to and facilitates repurposing of Web contents (enhanced browsing, Web Services location and access, etc).
Abstract: In this paper, we propose a fuzzy aggregate
production planning (APP) model for blending problem in a brass
factory which is the problem of computing optimal amounts of raw
materials for the total production of several types of brass in a
period. The model has deterministic and imprecise parameters
which follows triangular possibility distributions. The brass casting
APP model can not always be solved by using common approaches
used in the literature. Therefore a mathematical model is presented
for solving this problem. In the proposed model, the Lai and
Hwang-s fuzzy ranking concept is relaxed by using one constraint
instead of three constraints. An application of the brass casting
APP model in a brass factory shows that the proposed model
successfully solves the multi-blend problem in casting process and
determines the optimal raw material purchasing policies.
Abstract: The conjugate gradient optimization algorithm is combined with the modified back propagation algorithm to yield a computationally efficient algorithm for training multilayer perceptron (MLP) networks (CGFR/AG). The computational efficiency is enhanced by adaptively modifying initial search direction as described in the following steps: (1) Modification on standard back propagation algorithm by introducing a gain variation term in the activation function, (2) Calculation of the gradient descent of error with respect to the weights and gains values and (3) the determination of a new search direction by using information calculated in step (2). The performance of the proposed method is demonstrated by comparing accuracy and computation time with the conjugate gradient algorithm used in MATLAB neural network toolbox. The results show that the computational efficiency of the proposed method was better than the standard conjugate gradient algorithm.
Abstract: Computer-mediated communication technologies which provide for virtual communities have typically evolved in a cross-dichotomous manner, such that technical constructs of the technology have evolved independently from the social environment of the community. The present paper analyses some limitations of current implementations of computer-mediated communication technology that are implied by such a dichotomy, and discusses their inhibiting effects on possible developments of virtual communities. A Socio-Technical Indicator Model is introduced that utilizes integrated feedback to describe, simulate and operationalise increasing representativeness within a variety of structurally and parametrically diverse systems. In illustration, applications of the model are briefly described for financial markets and for eco-systems. A detailed application is then provided to resolve the aforementioned technical limitations of moderation on the evolution of virtual communities. The application parameterises virtual communities to function as self-transforming social-technical systems which are sensitive to emergent and shifting community values as products of on-going communications within the collective.
Abstract: Lacking an inherent “natural" dissimilarity measure
between objects in categorical dataset presents special difficulties in
clustering analysis. However, each categorical attributes from a given
dataset provides natural probability and information in the sense of
Shannon. In this paper, we proposed a novel method which
heuristically converts categorical attributes to numerical values by
exploiting such associated information. We conduct an experimental
study with real-life categorical dataset. The experiment demonstrates
the effectiveness of our approach.
Abstract: This research seeks to investigate the frequency and
profitability of index arbitrage opportunities involving the SET50
futures, SET50 component stocks, and the ThaiDEX SET50 ETF
(ticker symbol: TDEX). In particular, the frequency and profit of
arbitrage are measured in the following three arbitrage tests: (1)
SET50 futures vs. ThaiDEX SET50 ETF, (2) SET50 futures vs.
SET50 component stocks, and (3) ThaiDEX SET50 ETF vs. SET50
component stocks are investigated. For tests (2) and (3), the problems
involve conic optimization and quadratic programming as subproblems.
This research is first to apply conic optimization and
quadratic programming techniques in the context of index arbitrage
and is first to investigate such index arbitrage in the Thai equity and
derivatives markets. Thus, the contribution of this study is twofold.
First, its results would help understand the contribution of the
derivatives securities to the efficiency of the Thai markets. Second,
the methodology employed in this study can be applied to other
geographical markets, with minor adjustments.
Abstract: This paper discusses site selection process for
biological soil conservation planning. It was supported by a valuefocused
approach and spatial multi-criteria evaluation techniques. A
first set of spatial criteria was used to design a number of potential
sites. Next, a new set of spatial and non-spatial criteria was
employed, including the natural factors and the financial costs,
together with the degree of suitability for the Bonkuh watershed to
biological soil conservation planning and to recommend the most
acceptable program. The whole process was facilitated by a new
software tool that supports spatial multiple criteria evaluation, or
SMCE in GIS software (ILWIS). The application of this tool,
combined with a continual feedback by the public attentions, has
provided an effective methodology to solve complex decisional
problem in biological soil conservation planning.
Abstract: A Novel fuzzy neural network combining with support vector learning mechanism called support-vector-based fuzzy neural networks (SVBFNN) is proposed. The SVBFNN combine the capability of minimizing the empirical risk (training error) and expected risk (testing error) of support vector learning in high dimensional data spaces and the efficient human-like reasoning of FNN.
Abstract: Reversible logic is becoming more and more prominent
as the technology sets higher demands on heat, power, scaling
and stability. Reversible gates are able at any time to "undo" the
current step or function. Multiple-valued logic has the advantage of
transporting and evaluating higher bits each clock cycle than binary.
Moreover, we demonstrate in this paper, combining these disciplines
we can construct powerful multiple-valued reversible logic structures.
In this paper a reversible block implemented by pseudo floatinggate
can perform AD-function and a DA-function as its reverse
application.
Abstract: An alternative approach to the use of Discrete Fourier
Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction
is the use of parametric modeling technique. This method
is suitable for problems in which the image can be modeled by
explicit known source functions with a few adjustable parameters.
Despite the success reported in the use of modeling technique as an
alternative MRI reconstruction technique, two important problems
constitutes challenges to the applicability of this method, these are
estimation of Model order and model coefficient determination. In
this paper, five of the suggested method of evaluating the model
order have been evaluated, these are: The Final Prediction Error
(FPE), Akaike Information Criterion (AIC), Residual Variance (RV),
Minimum Description Length (MDL) and Hannan and Quinn (HNQ)
criterion. These criteria were evaluated on MRI data sets based on the
method of Transient Error Reconstruction Algorithm (TERA). The
result for each criterion is compared to result obtained by the use of a
fixed order technique and three measures of similarity were evaluated.
Result obtained shows that the use of MDL gives the highest measure
of similarity to that use by a fixed order technique.
Abstract: This paper investigates the influence of various
parameters on the behaviour of water droplets on polymeric surfaces
under high electric fields. An inclined plane test was carried out to
understand the droplet behaviour in strong electric field. Parameters
such as water droplet conductivity, droplet volume, polymeric
surface roughness and droplet positioning with respect to the
electrodes were studied. The flashover voltage is affected by all
aforementioned parameters. The droplet positioning is in some cases
more vital than the droplet volume. Surface damages were analysed
using Scanning Electron Microscopy (SEM) studies and by Energy
dispersive X-ray Analysis (EDAX). It is observes that magnitude of
discharge have direct influence on amount of surface da
Abstract: In the last years numerous applications of Human-
Computer Interaction have exploited the capabilities of Time-of-
Flight cameras for achieving more and more comfortable and precise
interactions. In particular, gesture recognition is one of the most active
fields. This work presents a new method for interacting with a virtual
object in a 3D space. Our approach is based on the fusion of depth
data, supplied by a ToF camera, with color information, supplied
by a HD webcam. The hand detection procedure does not require
any learning phase and is able to concurrently manage gestures of
two hands. The system is robust to the presence in the scene of
other objects or people, thanks to the use of the Kalman filter for
maintaining the tracking of the hands.
Abstract: The paper is included within the framework of a
complex research program, which was initiated from the hypothesis
arguing on the existence of a correlation between pineal indolic and
peptide hormones and the somatic development rhythm, including
thus the epithalamium-epiphysis complex involvement. At birds,
pineal gland contains a circadian oscillator, playing a main role in the
temporal organization of the cerebral functions. The secretion of
pineal indolic hormones is characterized by a high endogenous
rhythmic alternation, modulated by the light/darkness (L/D)
succession and by temperature as well. The research has been carried
out using 100 chicken broilers - “Ross" commercial hybrid,
randomly allocated in two experimental batches: Lc batch, reared
under a 12L/12D lighting schedule and Lexp batch, which was photic
pinealectomised through continuous exposition to light (150 lux, 24
hours, 56 days). Chemical and physical features of the meat issued
from breast fillet and thighs muscles have been studied, determining
the dry matter, proteins, fat, collagen, salt content and pH value, as
well. Besides the variations of meat chemical composition in relation
with lighting schedule, other parameters have been studied: live
weight dynamics, feed intake and somatic development degree. The
achieved results became significant since chickens have 7 days of
age, some variations of the studied parameters being registered,
revealing that the pineal gland physiologic activity, in relation with
the lighting schedule, could be interpreted through the monitoring of
the somatic development technological parameters, usually studied
within the chicken broilers rearing aviculture practice.
Abstract: Electricity market activities and a growing demand for electricity have led to heavily stressed power systems. This requires operation of the networks closer to their stability limits. Power system operation is affected by stability related problems, leading to unpredictable system behavior. Voltage stability refers to the ability of a power system to sustain appropriate voltage levels through large and small disturbances. Steady-state voltage stability is concerned with limits on the existence of steady-state operating points for the network. FACTS devices can be utilized to increase the transmission capacity, the stability margin and dynamic behavior or serve to ensure improved power quality. Their main capabilities are reactive power compensation, voltage control and power flow control. Among the FACTS controllers, Static Var Compensator (SVC) provides fast acting dynamic reactive compensation for voltage support during contingency events. In this paper, voltage stability assessment with appropriate representations of tap-changer transformers and SVC is investigated. Integrating both of these devices is the main topic of this paper. Effect of the presence of tap-changing transformers on static VAR compensator controller parameters and ratings necessary to stabilize load voltages at certain values are highlighted. The interrelation between transformer off nominal tap ratios and the SVC controller gains and droop slopes and the SVC rating are found. P-V curves are constructed to calculate loadability margins.
Abstract: An HPLC-UV analytical method was developed to
determine ethylenediaminetetraacetic acid (EDTA) in dairy
wastewater and surface water. The optimizing separation was achieved
by reversed–phase ion-pair liquid chromatography on a C18 column
using methanol as mobile phase solvent, tetrabutylammonium bromide
as the ion-pair reagent in pH 3.3 formate buffer solution at a flow rate
of 0.9 mL min-1 with a UV detector at 265 nm. No interference of Ca,
Mg or NO3
- was detected. Method performance was evaluated in terms
of linearity, repeatability and reproducibility. The method detection
limit was 5 μg L-1. The contents of EDTA in dairy effluents were 72 ~
261 μg L-1 at a large dairy site. A change of EDTA concentration was
observed downstream of the dairy effluent discharge, but this was well
under the predicted no effect concentration for aquatic ecosystem.
Abstract: Network on a chip (NoC) has been proposed as a viable solution to counter the inefficiency of buses in the current VLSI on-chip interconnects. However, as the silicon chip accommodates more transistors, the probability of transient faults is increasing, making fault tolerance a key concern in scaling chips. In packet based communication on a chip, transient failures can corrupt the data packet and hence, undermine the accuracy of data communication. In this paper, we present a comparative analysis of transient fault tolerant techniques including end-to-end, node-by-node, and stochastic communication based on flooding principle.
Abstract: This paper presents a general trainable framework
for fast and robust upright human face and non-human object
detection and verification in static images. To enhance the
performance of the detection process, the technique we develop is
based on the combination of fast neural network (FNN) and
classical neural network (CNN). In FNN, a useful correlation is
exploited to sustain high level of detection accuracy between input
image and the weight of the hidden neurons. This is to enable the
use of Fourier transform that significantly speed up the time
detection. The combination of CNN is responsible to verify the
face region. A bootstrap algorithm is used to collect non human
object, which adds the false detection to the training process of the
human and non-human object. Experimental results on test images
with both simple and complex background demonstrate that the
proposed method has obtained high detection rate and low false
positive rate in detecting both human face and non-human object.