Abstract: The introduction of haptic elements in a graphic user interfaces are becoming more widespread. Since haptics are being introduced rapidly into computational tools, investigating how these models affect Human-Computer Interaction would help define how to integrate and model new modes of interaction. The interest of this paper is to discuss and investigate the issues surrounding Haptic and Graphic User Interface designs (GUI) as separate systems, as well as understand how these work in tandem. The development of these systems is explored from a psychological perspective, based on how usability is addressed through learning and affordances, defined by J.J. Gibson. Haptic design can be a powerful tool, aiding in intuitive learning. The problems discussed within the text is how can haptic interfaces be integrated within a GUI without the sense of frivolity. Juxtaposing haptics and Graphic user interfaces has issues of motivation; GUI tends to have a performatory process, while Haptic Interfaces use affordances to learn tool use. In a deeper view, it is noted that two modes of perception, foveal and ambient, dictate perception. These two modes were once thought to work in tandem, however it has been discovered that these processes work independently from each other. Foveal modes interpret orientation is space which provide for posture, locomotion, and motor skills with variations of the sensory information, which instructs perceptions of object-task performance. It is contended, here, that object-task performance is a key element in the use of Haptic Interfaces because exploratory learning uses affordances in order to use an object, without meditating an experience cognitively. It is a direct experience that, through iteration, can lead to skill-sets. It is also indicated that object-task performance will not work as efficiently without the use of exploratory or kinesthetic learning practices. Therefore, object-task performance is not as congruently explored in GUI than it is practiced in Haptic interfaces.
Abstract: In the control theory one attempts to find a controller
that provides the best possible performance with respect to some
given measures of performance. There are many sorts of controllers
e.g. a typical PID controller, LQR controller, Fuzzy controller etc. In
the paper will be introduced polynomial controller with novel tuning
method which is based on the special pole placement encoding
scheme and optimization by Genetic Algorithms (GA). The examples
will show the performance of the novel designed polynomial
controller with comparison to common PID controller.
Abstract: This paper describes the performance of TCP Vegas
over the wireless IPv6 network. The performance of TCP Vegas is
evaluated using network simulator (ns-2). The simulation experiment
investigates how packet spacing affects the network delay, network
throughput and network efficiency of TCP Vegas. Moreover, we
investigate how the variable FTP packet sizes affect the network
performance. The result of the simulation experiment shows that as
the packet spacing is implements, the network delay is reduces,
network throughput and network efficiency is optimizes. As the FTP
packet sizes increase, the ratio of delay per throughput decreases.
From the result of experiment, we propose the appropriate packet size
in transmitting file transfer protocol application using TCP Vegas
with packet spacing enhancement over wireless IPv6 environment in
ns-2. Additionally, we suggest the appropriate ratio in determining
the appropriate RTT and buffer size in a network.
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: In this paper, a new Genetic Algorithm (GA) based
methodology is proposed to optimize the Degree of Hybridization
(DOH) in a passenger parallel hybrid car. At first step, target
parameters for the vehicle are decided and then using ADvanced
VehIcle SimulatOR (ADVISOR) software, the variation pattern of
these target parameters, across the different DOHs, is extracted. At
the next step, a suitable cost function is defined and is optimized
using GA. In this paper, also a new technique has been proposed for
deciding the number of battery modules for each DOH, which leads
to a great improvement in the vehicle performance. The proposed
methodology is so simple, fast and at the same time, so efficient.
Abstract: The effects of upflow liquid velocity (ULV) on
performance of expanded granular sludge bed (EGSB) system were
investigated. The EGSB reactor, made from galvanized steel pipe
0.10 m diameter and 5 m height, had been used to treat piggery
wastewater, after passing through acidification tank. It consisted of
39.3 l working volume in reaction zone and 122 l working volume in
sedimentation zone, at the upper part. The reactor was seeded with
anaerobically digested sludge and operated at the ULVs of 4, 8, 12
and 16 m/h, consecutively, corresponding to organic loading rates of
9.6 – 13.0 kg COD/ (m3.d). The average COD concentrations in the
influent were 9,601 – 13,050 mg/l. The COD removal was not
significantly different, i.e. 93.0% - 94.0%, except at ULV 12 m/h where
SS in the influent was exceptionally high so that VSS washout had
occurred, leading to low COD removal. The FCOD and VFA
concentrations in the effluent of all experiments were not much
different, indicating the same range of treatment performance. The
biogas production decreased at higher ULV and ULV of 4 m/h is
suggested as design criterion for EGSB system.
Abstract: The use of technology is increasingly adopted to
support flexible learning in Higher Education institutions. The
adoption of more sophisticated technologies offers a broad range of
facilities for communication and resource sharing, thereby creating a
flexible learning environment that facilitates and even encourages
students not to physically attend classes. However this emerging
trend seems to contradict class attendance requirements within
universities, inevitably leading to a dilemma between amending
traditional regulations and creating new policies for the higher
education institutions. This study presents an investigation into
student engagement in a technology enhanced/driven flexible
environment along with its relationship to attainment. We propose an
approach to modelling engagement from different perspectives in
terms of indicators and then consider what impact these indicators
have on student academic performance. We have carried out a case
study on the relation between attendance and attainment in a flexible
environment. Although our preliminary results show attendance is
quantitatively correlated with successful student development and
learning outcomes, our results also indicate there is a cohort that did
not follow such a pattern. Nevertheless the preliminary results could
provide an insight into pilot studies in the wider deployment of new
technology to support flexible learning.
Abstract: Gurus of the Classical Management School (like
Taylor, Fayol and Ford) had an opinion that work must be delegated
to the individual and the individual has to be instructed, his work
assessed and paid based on individual performance. The theories of
the Human Relations School have changed this mentality regarding
the concept of groups. They came to the conclusion that the influence
of groups greatly affects the behaviour and performance of its
members.
Group theories today are characterized by problem-solving teams
and self-managing groups authorized to make decisions and execute;
professional communities also play an important role during the
operation of knowledge management systems.
In this theoretical research we try to find answers to a question:
what kind of characteristics (professional competencies, personal
features, etc.) a successful team needs to manage a change to operate
a knowledge management system step by step.
Abstract: The estrus female Etawah cross bred goats were
synchronized estrus by controlled internal drug release (CIDR)
implants for 10 days combined with PGF2α injection, and continued
by artificial insemination (AI) within the hours of 24 period. Vaginal
epithelium was taken to determine estrus cycle of the goats without
estrus synchronization. The estrus responds (the puffy of vulva and
vaginal pH) and percentage of pregnancy were investigated. The data
were analyzed descriptively and Independent Sample T-Test. The
results showed that the puffy of vulva and vaginal pH were
significantly different in synchronized estrus goats and control goats
(2.18 ± 0.33 cm vs. 1.20 ± 0.16 cm and 8.55 ± 0.63 vs. 8.22 ± 0.22).
Percentage of pregnancy was higher in synchronized estrus goats
(73.33%) than in control (53.3%). Estrus synchronization by using
CIDR implants and PGF2, continued by AI was effective to improve
reproduction performance of Etawah cross bred goats.
Abstract: This article presents a detailed analysis and comparative
performance evaluation of model reference adaptive control systems.
In contrast to classical control theory, adaptive control methods allow
to deal with time-variant processes. Inspired by the works [1] and
[2], two methods based on the MIT rule and Lyapunov rule are
applied to a linear first order system. The system is simulated and
it is investigated how changes to the adaptation gain affect the
system performance. Furthermore, variations in the reference model
parameters, that is changing the desired closed-loop behaviour are
examinded.
Abstract: Smith Predictor control is theoretically a good solution to the problem of controlling the time delay systems. However, it seldom gets use because it is almost impossible to find out a precise mathematical model of the practical system and very sensitive to uncertain system with variable time-delay. In this paper is concerned with a design method of smith predictor for temperature control system by Coefficient Diagram Method (CDM). The simulation results show that the control system with smith predictor design by CDM is stable and robust whilst giving the desired time domain system performance.
Abstract: The Major Depressive Disorder has been a burden of
medical expense in Taiwan as well as the situation around the world.
Major Depressive Disorder can be defined into different categories by
previous human activities. According to machine learning, we can
classify emotion in correct textual language in advance. It can help
medical diagnosis to recognize the variance in Major Depressive
Disorder automatically. Association language incremental is the
characteristic and relationship that can discovery words in sentence.
There is an overlapping-category problem for classification. In this
paper, we would like to improve the performance in classification in
principle of no overlapping-category problems. We present an
approach that to discovery words in sentence and it can find in high
frequency in the same time and can-t overlap in each category, called
Association Language Features by its Category (ALFC).
Experimental results show that ALFC distinguish well in Major
Depressive Disorder and have better performance. We also compare
the approach with baseline and mutual information that use single
words alone or correlation measure.
Abstract: A multivariable discontinuous feedback linearization approach is proposed to position control of an electrically driven fast robot manipulator. A desired performance is achieved by selecting a useful controller and suitable sampling rate and considering saturation for actuators. There is a high flexibility to apply the proposed control approach on different electrically driven manipulators. The control approach can guarantee the stability and satisfactory tracking performance. A PUMA 560 robot driven by geared permanent magnet dc motors is simulated. The simulation results show a desired performance for control system under technical specifications.
Abstract: Ramadan requires individuals to abstain from food and fluid intake between sunrise and sunset; physiological considerations predict that poorer mood, physical performance and mental performance will result. In addition, any difficulties will be worsened because preparations for fasting and recovery from it often mean that nocturnal sleep is decreased in length, and this independently affects mood and performance.
A difficulty of interpretation in many studies is that the observed changes could be due to fasting but also to the decreased length of sleep and altered food and fluid intakes before and after the daytime fasting. These factors were separated in this study, which took place over three separate days and compared the effects of different durations of fasting (4, 8 or 16h) upon a wide variety of measures (including subjective and objective assessments of performance, body composition, dehydration and responses to a short bout of exercise) - but with an unchanged amount of nocturnal sleep, controlled supper the previous evening, controlled intakes at breakfast and daytime naps not being allowed. Many of the negative effects of fasting observed in previous studies were present in this experiment also. These findings indicate that fasting was responsible for many of the changes previously observed, though some effect of sleep loss, particularly if occurring on successive days (as would occur in Ramadan) cannot be excluded.
Abstract: The approach of subset selection in polynomial
regression model building assumes that the chosen fixed full set of
predefined basis functions contains a subset that is sufficient to
describe the target relation sufficiently well. However, in most cases
the necessary set of basis functions is not known and needs to be
guessed – a potentially non-trivial (and long) trial and error process.
In our research we consider a potentially more efficient approach –
Adaptive Basis Function Construction (ABFC). It lets the model
building method itself construct the basis functions necessary for
creating a model of arbitrary complexity with adequate predictive
performance. However, there are two issues that to some extent
plague the methods of both the subset selection and the ABFC,
especially when working with relatively small data samples: the
selection bias and the selection instability. We try to correct these
issues by model post-evaluation using Cross-Validation and model
ensembling. To evaluate the proposed method, we empirically
compare it to ABFC methods without ensembling, to a widely used
method of subset selection, as well as to some other well-known
regression modeling methods, using publicly available data sets.
Abstract: This paper is prepared to provide a review of how an automotive manufacturer, ISUZU HICOM Malaysia Co. Ltd. sustained the supply chain management after business process reengineering in 2007. One of the authors is currently undergoing industrial attachment and has spent almost 6 months researching in the production and operation management system of the company. This study was carried out as part of the tasks in the attachment program. The result shows that delivery lateness and outsourcing are the main barriers that affected productivity. From the gap analysis, the authors found that new business process operation had improved suppliers delivery performance.
Abstract: The ever increasing use of World Wide Web in the
existing network, results in poor performance. Several techniques
have been developed for reducing web traffic by compressing the size
of the file, saving the web pages at the client side, changing the burst
nature of traffic into constant rate etc. No single method was
adequate enough to access the document instantly through the
Internet. In this paper, adaptive hybrid algorithms are developed for
reducing web traffic. Intelligent agents are used for monitoring the
web traffic. Depending upon the bandwidth usage, user-s preferences,
server and browser capabilities, intelligent agents use the best
techniques to achieve maximum traffic reduction. Web caching,
compression, filtering, optimization of HTML tags, and traffic
dispersion are incorporated into this adaptive selection. Using this
new hybrid technique, latency is reduced to 20 – 60 % and cache hit
ratio is increased 40 – 82 %.
Abstract: Load forecasting has always been the essential part of
an efficient power system operation and planning. A novel approach
based on support vector machines is proposed in this paper for annual
power load forecasting. Different kernel functions are selected to
construct a combinatorial algorithm. The performance of the new
model is evaluated with a real-world dataset, and compared with two
neural networks and some traditional forecasting techniques. The
results show that the proposed method exhibits superior performance.
Abstract: This paper presents a means for reducing the torque
variation during the revolution of a vertical-axis water turbine
(VAWaterT) by increasing the blade number. For this purpose, twodimensional
CFD analyses have been performed on a straight-bladed
Darrieus-type rotor. After describing the computational model and
the relative validation procedure, a complete campaign of
simulations, based on full RANS unsteady calculations, is proposed
for a three, four and five-bladed rotor architectures, characterized by
a NACA 0025 airfoil. For each proposed rotor configuration, flow
field characteristics are investigated at several values of tip speed
ratio, allowing a quantification of the influence of blade number on
flow geometric features and dynamic quantities, such as rotor torque
and power. Finally, torque and power curves are compared for the
three analyzed architectures, achieving a quantification of the effect
of blade number on overall rotor performance.
Abstract: Cancers could normally be marked by a number of
differentially expressed genes which show enormous potential as
biomarkers for a certain disease. Recent years, cancer classification
based on the investigation of gene expression profiles derived by
high-throughput microarrays has widely been used. The selection of
discriminative genes is, therefore, an essential preprocess step in
carcinogenesis studies. In this paper, we have proposed a novel gene
selector using information-theoretic measures for biological
discovery. This multivariate filter is a four-stage framework through
the analyses of feature relevance, feature interdependence, feature
redundancy-dependence and subset rankings, and having been
examined on the colon cancer data set. Our experimental result show
that the proposed method outperformed other information theorem
based filters in all aspect of classification errors and classification
performance.