Abstract: A virtual collaborative classroom was created at East Carolina University, using videoconference technology via regular internet to bring students from 18 different countries, 2 at a time, to the ECU classroom in real time to learn about each other-s culture. Students from two countries are partnered one on one, they meet for 4-5 weeks, and submit a joint paper. Then the same process is repeated for two other countries. Lectures and student discussions are managed with pre-determined topics and questions. Classes are conducted in English and reading assignments are placed on the website. Administratively all partners are independent, students pay fees and get credits at their home institution. Familiarity with technology, knowledge in cultural understanding and attitude change were assessed, only attitude changes are reported in this paper. After taking this course, all students stated their comfort level in working with, and their desire to interact with, culturally different others grew stronger and their xenophobia and isolationist attitudes decreased.
Abstract: The purpose of this paper is to consider the
introduction of online courses to replace the current classroom-based
staff training. The current training is practical, and must be
completed before access to the financial computer system is
authorized. The long term objective is to measure the efficacy,
effectiveness and efficiency of the training, and to establish whether
a transfer of knowledge back to the workplace has occurred. This
paper begins with an overview explaining the importance of staff
training in an evolving, competitive business environment and
defines the problem facing this particular organization. A summary
of the literature review is followed by a brief discussion of the
research methodology and objective. The implementation of the
alpha version of the online course is then described. This paper may
be of interest to those seeking insights into, or new theory regarding,
practical interventions of online learning in the real world.
Abstract: This study adopted previous fault patterns, results of
detection analysis, historical records and data, and experts-
experiences to establish fuzzy principles and estimate the failure
probability index of components of a power transformer. Considering
that actual parameters and limiting conditions of parameters may
differ, this study used the standard data of IEC, IEEE, and CIGRE as
condition parameters. According to the characteristics of each
condition parameter, relative degradation was introduced to reflect the
degree of influence of the factors on the transformer condition. The
method of fuzzy mathematics was adopted to determine the
subordinate function of the transformer condition. The calculation
used the Matlab Fuzzy Tool Box to select the condition parameters of
coil winding, iron core, bushing, OLTC, insulating oil and other
auxiliary components and factors (e.g., load records, performance
history, and maintenance records) of the transformer to establish the
fuzzy principles. Examples were presented to support the rationality
and effectiveness of the evaluation method of power transformer
performance conditions, as based on fuzzy comprehensive evaluation.
Abstract: Knee joint forces are available by in vivo measurement
using an instrumented knee prosthesis for small to moderate knee
flexion but not for high flexion yet. We created a 2D mathematical
model of the lower limb incorporating several new features such as a
patello-femoral mechanism, a thigh-calf contact at high knee flexion
and co-contracting muscles' force ratio, then used it to determine knee
joint forces arising from high knee flexions in four kneeling
conditions: rising with legs in parallel, with one foot forward, with or
without arm use. With arms used, the maximum values of knee joint
force decreased to about 60% of those with arms not used. When rising
with one foot forward, if arms are not used, the forward leg sustains a
force as large as that sustained when rising with legs parallel.
Abstract: Air quality studies were carried out in the towns of
Putrajaya, Petaling Jaya and Nilai in the Malaysian Peninsular. In this
study, the variations of Ozone (O3) concentrations over a four year
period (2008-2011) were investigated using data obtained from the
Malaysian Department of the Environment (DOE). This study aims to
identify and describe the daily and monthly variations of O3
concentrations at the monitoring sites mentioned. The SPPS program
(Statistical Package for the Social Science) was used to analyze this
data in order to obtain the variations of O3 and also to clarify the
relationship between the stations. The findings of the study revealed
that the highest concentration of O3 occurred during the midday and
afternoon (between 13:00-15:00 hrs). The comparison between
stations also showed that highest O3 concentrations were recorded in
Putrajaya. The comparisons of average and maximum concentrations
of O3 for the three stations showed that the strongest significant
correlation was recorded in the Petaling Jaya station with the value
R2= 0.667. Results from this study indicate that in the urban areas of
Peninsular Malaysia, the concentration of O3 depends on the
concentration of NOx. Furthermore, HYSPLIT back trajectories
(-72h) indicated that air-mass transport patterns can also influence the
O3 concentration in the areas studied.
Abstract: In order to investigate water deficit stress on 24 of
soybean (Glycine Max. L) cultivars and lines in temperate climate, an
experiment was conducted in Iran Seed and Plant Improvement
Institute. Stress levels were irrigation after evaporation of 50, 100,
150 mm water from pan, class A. Randomized Completely Block
Design was arranged for each stress levels. Some traits such as, node
number, plant height, pod number per area, grain number per pod,
grain number per area, 1000 grains weight, grain yield and harvest
index were measured. Results showed that water deficit stress had
significant effect on node number, plant height, pod number per area,
grain number per pod, grain number per area, 1000 grains weight and
harvest index. Also all of agronomic traits except harvest index
influenced significantly by cultivars and lines. The least and most
grain yield was belonged to Ronak X Williams and M41 x Clark
respectively.
Abstract: A wireless sensor network with a large number of tiny sensor nodes can be used as an effective tool for gathering data in various situations. One of the major issues in wireless sensor networks is developing an energy-efficient routing protocol which has a significant impact on the overall lifetime of the sensor network. In this paper, we propose a novel hierarchical with static clustering routing protocol called Energy-Efficient Protocol with Static Clustering (EEPSC). EEPSC, partitions the network into static clusters, eliminates the overhead of dynamic clustering and utilizes temporary-cluster-heads to distribute the energy load among high-power sensor nodes; thus extends network lifetime. We have conducted simulation-based evaluations to compare the performance of EEPSC against Low-Energy Adaptive Clustering Hierarchy (LEACH). Our experiment results show that EEPSC outperforms LEACH in terms of network lifetime and power consumption minimization.
Abstract: This study aims to clarify constructions which enable to improve socio-cultural values of environments and also to obtain new knowledge on selecting development plans. CVM is adopted as a method of evaluation. As a case of the research, university campus (CP; the following) is selected on account of its various environments, institutions and many users. Investigations were conducted from 4 points of view, total value and utility value of whole CP environments, values of each environment existing in CP or development plan assumed in CP. Furthermore, respondents- attributes were also investigated. In consequence, the following is obtained. 1) Almost all of total value of CP is composed of utility value of direct use. 2) Each of environment and development plans whose value is the highest is clarified. 3) Moreover, development plan to improve environmental value the most is specified.
Abstract: Weather systems use enormously complex
combinations of numerical tools for study and forecasting.
Unfortunately, due to phenomena in the world climate, such
as the greenhouse effect, classical models may become
insufficient mostly because they lack adaptation. Therefore,
the weather forecast problem is matched for heuristic
approaches, such as Evolutionary Algorithms.
Experimentation with heuristic methods like Particle Swarm
Optimization (PSO) algorithm can lead to the development of
new insights or promising models that can be fine tuned with
more focused techniques. This paper describes a PSO
approach for analysis and prediction of data and provides
experimental results of the aforementioned method on realworld
meteorological time series.
Abstract: In this paper, an artificial intelligent technique for
robust digital image watermarking in multiwavelet domain is
proposed. The embedding technique is based on the quantization
index modulation technique and the watermark extraction process
does not require the original image. We have developed an
optimization technique using the genetic algorithms to search for
optimal quantization steps to improve the quality of watermarked
image and robustness of the watermark. In addition, we construct a
prediction model based on image moments and back propagation
neural network to correct an attacked image geometrically before the
watermark extraction process begins. The experimental results show
that the proposed watermarking algorithm yields watermarked image
with good imperceptibility and very robust watermark against various
image processing attacks.
Abstract: As global industry developed rapidly, the energy
demand also rises simultaneously. In the production process, there’s a
lot of energy consumed in the process. Formally, the energy used in
generating the heat in the production process. In the total energy
consumption, 40% of the heat was used in process heat, mechanical
work, chemical energy and electricity. The remaining 50% were
released into the environment. It will cause energy waste and
environment pollution. There are many ways for recovering the waste
heat in factory. Organic Rankine Cycle (ORC) system can produce
electricity and reduce energy costs by recovering the waste of low
temperature heat in the factory. In addition, ORC is the technology
with the highest power generating efficiency in low-temperature heat
recycling. However, most of factories executives are still hesitated
because of the high implementation cost of the ORC system, even a lot
of heat are wasted. Therefore, this study constructs a nonlinear
mathematical model of waste heat recovery equipment configuration
to maximize profits. A particle swarm optimization algorithm is
developed to generate the optimal facility installation plan for the ORC
system.
Abstract: With the proliferation of multi-channel retailing, developing a better understanding of the factors that affect customers- purchase behaviors within a multi-channel retail context has become an important topic for practitioners and academics. While many studies have investigated the various customer behaviors associated with brick-and-mortar retailing, online retailing, and brick-and-click retailing, little research has explored how customer shopping value perceptions influence online purchase behaviors within the TV-and-online retail environment. The main purpose of this study is to investigate the influence of TV and online shopping values on online patronage intention. Data collected from 116 respondents in Taiwan are tested against the research model using the partial least squares (PLS) approach. The results indicate that utilitarian and hedonic TV shopping values have indirect, positive influences on online patronage intention through their online counterparts in the TV-and-online retail context. The findings of this study provide several important theoretical and practical implications for multi-channel retailing.
Abstract: Testing accounts for the major percentage of technical
contribution in the software development process. Typically, it
consumes more than 50 percent of the total cost of developing a
piece of software. The selection of software tests is a very important
activity within this process to ensure the software reliability
requirements are met. Generally tests are run to achieve maximum
coverage of the software code and very little attention is given to the
achieved reliability of the software. Using an existing methodology,
this paper describes how to use Bayesian Belief Networks (BBNs) to
select unit tests based on their contribution to the reliability of the
module under consideration. In particular the work examines how the
approach can enhance test-first development by assessing the quality
of test suites resulting from this development methodology and
providing insight into additional tests that can significantly reduce
the achieved reliability. In this way the method can produce an
optimal selection of inputs and the order in which the tests are
executed to maximize the software reliability. To illustrate this
approach, a belief network is constructed for a modern software
system incorporating the expert opinion, expressed through
probabilities of the relative quality of the elements of the software,
and the potential effectiveness of the software tests. The steps
involved in constructing the Bayesian Network are explained as is a
method to allow for the test suite resulting from test-driven
development.
Abstract: Software developed for a specific customer under contract
typically undergoes a period of testing by the customer before
acceptance. This is known as user acceptance testing and the process
can reveal both defects in the system and requests for changes to
the product. This paper uses nonhomogeneous Poisson processes to
model a real user acceptance data set from a recently developed
system. In particular a split Poisson process is shown to provide an
excellent fit to the data. The paper explains how this model can be
used to aid the allocation of resources through the accurate prediction
of occurrences both during the acceptance testing phase and before
this activity begins.
Abstract: This paper dissertates about issues which may occur
after next year will be major part of civil aviation in EU included into
system of Emission trading. This system should help to fight against
global warming and to fulfill Kyoto Protocol commitments of
European countries. Main issues mentioned in this paper are
connected with problem of radiative forcing from emissions and lack
of their monitoring and charging in EU legislative. There are
mentioned main differences between industrial emissions and
emissions form aviation with notification about possible negative
impacts of neglecting these differences. Special attention is dedicated
to risk of possible reverse effect of inclusion aviation in EU ETS,
which may theoretically occur.
Abstract: This research explorers the relationship between leadership style and continuous improvement (CI) teams. CI teams have several features that are not always found in other types of teams, including multi-functional members, short time period for performance, positive and actionable results, and exposure to senior leadership. There is no one best style of leadership for these teams. Instead, it is important to select the best leadership style for the situation. The leader must have the flexibility to change styles and the skill to use the chosen style effectively in order to ensure the team’s success.
Abstract: In this paper, we propose a novel time-frequency distribution (TFD) for the analysis of multi-component signals. In particular, we use synthetic as well as real-life speech signals to prove the superiority of the proposed TFD in comparison to some existing ones. In the comparison, we consider the cross-terms suppression and the high energy concentration of the signal around its instantaneous frequency (IF).
Abstract: Information and Communication Technologies (ICT) are increasing in importance everyday, especially since the 90’s (last decade of birth for the Millennials generation). While social interactions involving the Millennials generation have been studied, a lack of investigation remains regarding the use of the ICT by this generation as well as the impact on outcomes in education and professional training. Observing and interviewing students preparing a MSc, we aimed at characterizing the interaction students-ICT during the courses. We found that up to 50% of the students (mainly female) could use ICT during courses at a rate of 0.84 occurrence/minutes for some of them, and they thought this involvement did not disturb learning, even was helpful. As recent researches show that multitasking leads people think they are much better than they actually are, further observations with assessments are needed to conclude whether or not the use ICT by students during the courses is a real strength.
Abstract: Quality of 2D and 3D cross-sectional images produce
by Computed Tomography primarily depend upon the degree of
precision of primary and secondary X-Ray intensity detection.
Traditional method of primary intensity detection is apt to errors.
Recently the X-Ray intensity measurement system along with smart
X-Ray sensors is developed by our group which is able to detect
primary X-Ray intensity unerringly. In this study a new smart X-Ray
sensor is developed using Light-to-Frequency converter TSL230
from Texas Instruments which has numerous advantages in terms of
noiseless data acquisition and transmission. TSL230 construction is
based on a silicon photodiode which converts incoming X-Ray
radiation into the proportional current signal. A current to frequency
converter is attached to this photodiode on a single monolithic CMOS
integrated circuit which provides proportional frequency count to
incoming current signal in the form of the pulse train. The frequency
count is delivered to the center of PICDEM FS USB board with
PIC18F4550 microcontroller mounted on it. With highly compact
electronic hardware, this Demo Board efficiently read the smart
sensor output data. The frequency output approaches overcome
nonlinear behavior of sensors with analog output thus un-attenuated
X-Ray intensities could be measured precisely and better
normalization could be acquired in order to attain high resolution.
Abstract: The state-of-the-art Bag of Words model in Content-
Based Image Retrieval has been used for years but the relevance
feedback strategies for this model are not fully investigated. Inspired
from text retrieval, the Bag of Words model has the ability to use the
wealth of knowledge and practices available in text retrieval. We
study and experiment the relevance feedback model in text retrieval
for adapting it to image retrieval. The experiments show that the
techniques from text retrieval give good results for image retrieval
and that further improvements is possible.