Abstract: This study discovers a novel framework of individual
level technology adoption known as I-P (Individual- Privacy) towards
health information application in Smart National Identity Card. Many
countries introduced smart national identity card (SNIC) with various
applications such as health information application embedded inside
it. However, the degree to which citizens accept and use some of the
embedded applications in smart national identity remains unknown to
many governments and application providers as well. Moreover, the
factors of trust, perceived risk, Privacy concern and perceived
credibility need to be incorporated into more comprehensive models
such as extended Unified Theory of Acceptance and Use of
Technology known as UTAUT2. UTAUT2 is a mainly widespread
and leading theory up to now. This research identifies factors
affecting the citizens’ behavioural intention to use health information
application embedded in SNIC and extends better understanding on
the relevant factors that the government and the application providers
would need to consider in predicting citizens’ new technology
acceptance in the future. We propose a conceptual framework by
combining the UTAUT2 and Privacy Calculus Model constructs and
also adding perceived credibility as a new variable. The proposed
framework may provide assistance to any government planning,
decision, and policy makers involving e-government projects.
Empirical study may be conducted in the future to provide proof and
empirically validate this I-P framework.
Abstract: Kuosheng nuclear power plant (NPP) is a BWR/6 type
NPP and located on the northern coast of Taiwan. First, Kuosheng
NPP TRACE model were developed in this research. In order to assess
the system response of Kuosheng NPP TRACE model, startup tests
data were used to evaluate Kuosheng NPP TRACE model. Second, the
overpressurization transient analysis of Kuosheng NPP TRACE model
was performed. Besides, in order to confirm the mechanical property
and integrity of fuel rods, FRAPTRAN analysis was also performed in
this study.
Abstract: Bone properties and response behavior after static or
dynamic activation (loading) are still interesting topics in many fields
of the science especially in the biomechanical problems such as bone
loss of astronauts in space, osteoporosis, bone remodeling after
fracture or remodeling after surgery (endoprosthesis and implants)
and in osteointegration. This contribution deals with the relation
between physiological, demineralized and deproteinized state of the
turkey long bone – tibia. Three methods for comparison were used: 1)
densitometry, 2) three point bending and 3) frequency analysis. The
main goal of this work was to describe the decrease of the protein
(collagen) or mineral of the bone with relation to the fracture in three
point bending. The comparison is linked to the problem of different
bone mechanical behavior in physiological and osteoporotic state.
Abstract: Recently, an increasing number of researchers have
been focusing on working out realistic solutions to sustainability
problems. As sustainability issues gain higher importance for
organisations, the management of such decisions becomes critical.
Knowledge representation is a fundamental issue of complex
knowledge based systems. Many types of sustainability problems
would benefit from models based on experts’ knowledge. Cognitive
maps have been used for analyzing and aiding decision making. A
cognitive map can be made of almost any system or problem. A
fuzzy cognitive map (FCM) can successfully represent knowledge
and human experience, introducing concepts to represent the essential
elements and the cause and effect relationships among the concepts to
model the behaviour of any system. Integrated waste management
systems (IWMS) are complex systems that can be decomposed to
non-related and related subsystems and elements, where many factors
have to be taken into consideration that may be complementary,
contradictory, and competitive; these factors influence each other and
determine the overall decision process of the system. The goal of the
present paper is to construct an efficient IWMS which considers
various factors. The authors’ intention is to propose an expert based
system design approach for implementing expert decision support in
the area of IWMSs and introduces an appropriate methodology for
the development and analysis of group FCM. A framework for such a
methodology consisting of the development and application phases is
presented.
Abstract: Stochastic User Equilibrium (SUE) model is a widely
used traffic assignment model in transportation planning, which is
regarded more advanced than Deterministic User Equilibrium (DUE)
model. However, a problem exists that the performance of the SUE
model depends on its error term parameter. The objective of this
paper is to propose a systematic method of determining the
appropriate error term parameter value for the SUE model. First, the
significance of the parameter is explored through a numerical
example. Second, the parameter calibration method is developed
based on the Logit-based route choice model. The calibration process
is realized through multiple nonlinear regression, using sequential
quadratic programming combined with least square method. Finally,
case analysis is conducted to demonstrate the application of the
calibration process and validate the better performance of the SUE
model calibrated by the proposed method compared to the SUE
models under other parameter values and the DUE model.
Abstract: In this study, we develop a performance evaluation
model based on a multi-attribute utility approach aiming at reaching
the sustainable banking (SB) status. This model is built accounting
for various banks’ stakeholders in a win-win paradigm. In addition, it
offers the opportunity for adopting a global measure of performance
as an indication of a bank’s sustainability degree. This measure is
referred to as banking sustainability performance index (BSPI). This
index may constitute a basis for ranking banks. Moreover, it may
constitute a bridge between the assessment types of financial and
extra-financial rating agencies. A real application is performed on
three French banks.
Abstract: Urban greenery remains the bastion of urban
landscape and a key to sustainable development due to its integral
connections to the general health and wellbeing of urban residents.
However, in an era of rapid urbanisation, recent studies indicate that
urban greenery, especially ecologically sensitive areas, in many
African cities is becoming increasingly depleted. Given the scale and
rate of natural and anthropogenic change, effective management of
urban greenery as the ultimate goal of restoring depleting urban
landscapes is urgent. This review advocates for an urban resilience
model to managing urban greenery.
Abstract: The systematic evaluation of manufacturing
technologies with regard to the potential for product designing
constitutes a major challenge. Until now, conventional evaluation
methods primarily consider the costs of manufacturing technologies.
Thus, the potential of manufacturing technologies for achieving
additional product design features is not completely captured. To
compensate this deficit, final evaluations of new technologies are
mainly intuitive in practice. Therefore, an additional evaluation
dimension is needed which takes the potential of manufacturing
technologies for specific realizable product designs into account. In
this paper, we present the approach of an evaluation method for
selecting manufacturing technologies with regard to their potential
for product designing. This research is done within the Fraunhofer
innovation cluster »AdaM« (Adaptive Manufacturing) which targets
the development of resource efficient and adaptive manufacturing
technology processes for complex turbomachinery components.
Abstract: The paper is focused on the methods to solutions of
the crisis situation in the Czech Republic associated with the mass
methanol poisoning. The emphasis is put on tasks of individual state
bodies and of Integrated Rescue System during the handling of the
crisis.
The theoretical part describes poisonings, ways of intoxication,
types of intoxicants and cases of mass poisoning by dangerous
substances in the world.
The practical part describes the development, causes and solutions
of extraordinary event, mass methanol poisoning in the Czech
Republic. The main emphasis was put on the crisis management of
the Czech Republic in solving this situation.
Abstract: Characterization of the engineering behavior of
unsaturated soil is dependent on the soil-water characteristic curve
(SWCC), a graphical representation of the relationship between water
content or degree of saturation and soil suction. A reasonable
description of the SWCC is thus important for the accurate prediction
of unsaturated soil parameters. The measurement procedures for
determining the SWCC, however, are difficult, expensive, and timeconsuming.
During the past few decades, researchers have laid a
major focus on developing empirical equations for predicting the
SWCC, with a large number of empirical models suggested. One of
the most crucial questions is how precisely existing equations can
represent the SWCC. As different models have different ranges of
capability, it is essential to evaluate the precision of the SWCC
models used for each particular soil type for better SWCC estimation.
It is expected that better estimation of SWCC would be achieved via
a thorough statistical analysis of its distribution within a particular
soil class. With this in view, a statistical analysis was conducted in
order to evaluate the reliability of the SWCC prediction models
against laboratory measurement. Optimization techniques were used
to obtain the best-fit of the model parameters in four forms of SWCC
equation, using laboratory data for relatively coarse-textured (i.e.,
sandy) soil. The four most prominent SWCCs were evaluated and
computed for each sample. The result shows that the Brooks and
Corey model is the most consistent in describing the SWCC for sand
soil type. The Brooks and Corey model prediction also exhibit
compatibility with samples ranging from low to high soil water
content in which subjected to the samples that evaluated in this study.
Abstract: Web-based Cognitive Writing Instruction (WeCWI) is
a hybrid e-framework for the development of a web-based instruction
(WBI), which contributes towards instructional design and language
development. WeCWI divides its contribution in instructional design
into macro and micro perspectives. In macro perspective, being a 21st
century educator by disseminating knowledge and sharing ideas with
the in-class and global learners is initiated. By leveraging the virtue
of technology, WeCWI aims to transform an educator into an
aggregator, curator, publisher, social networker and ultimately, a
web-based instructor. Since the most notable contribution of
integrating technology is being a tool of teaching as well as a
stimulus for learning, WeCWI focuses on the use of contemporary
web tools based on the multiple roles played by the 21st century
educator. The micro perspective in instructional design draws
attention to the pedagogical approaches focusing on three main
aspects: reading, discussion, and writing. With the effective use of
pedagogical approaches through free reading and enterprises,
technology adds new dimensions and expands the boundaries of
learning capacity. Lastly, WeCWI also imparts the fundamental
theories and models for web-based instructors’ awareness such as
interactionist theory, cognitive information processing (CIP) theory,
computer-mediated communication (CMC), e-learning interactionalbased
model, inquiry models, sensory mind model, and leaning styles
model.
Abstract: This study aimed at investigating whether the
functional brain networks constructed using the initial EEG (obtained
when patients first visited hospital) can be correlated with the
progression of cognitive decline calculated as the changes of
mini-mental state examination (MMSE) scores between the latest and
initial examinations. We integrated the time–frequency cross mutual
information (TFCMI) method to estimate the EEG functional
connectivity between cortical regions, and the network analysis based
on graph theory to investigate the organization of functional networks
in aMCI. Our finding suggested that higher integrated functional
network with sufficient connection strengths, dense connection
between local regions, and high network efficiency in processing
information at the initial stage may result in a better prognosis of the
subsequent cognitive functions for aMCI. In conclusion, the functional
connectivity can be a useful biomarker to assist in prediction of
cognitive declines in aMCI.
Abstract: Brain functional networks based on resting-state EEG
data were compared between patients with mild Alzheimer’s disease
(mAD) and matched patients with amnestic subtype of mild cognitive
impairment (aMCI). We integrated the time–frequency cross mutual
information (TFCMI) method to estimate the EEG functional
connectivity between cortical regions and the network analysis based
on graph theory to further investigate the alterations of functional
networks in mAD compared with aMCI group. We aimed at
investigating the changes of network integrity, local clustering,
information processing efficiency, and fault tolerance in mAD brain
networks for different frequency bands based on several topological
properties, including degree, strength, clustering coefficient, shortest
path length, and efficiency. Results showed that the disruptions of
network integrity and reductions of network efficiency in mAD
characterized by lower degree, decreased clustering coefficient, higher
shortest path length, and reduced global and local efficiencies in the
delta, theta, beta2, and gamma bands were evident. The significant
changes in network organization can be used in assisting
discrimination of mAD from aMCI in clinical.
Abstract: The effect of trucks on the level of service is
determined by considering passenger car equivalents (PCE) of trucks.
The current version of Highway Capacity Manual (HCM) uses a
single PCE value for all tucks combined. However, the composition
of truck traffic varies from location to location; therefore, a single
PCE value for all trucks may not correctly represent the impact of
truck traffic at specific locations. Consequently, present study
developed separate PCE values for single-unit and combination
trucks to replace the single value provided in the HCM on different
freeways. Site specific PCE values, were developed using concept of
spatial lagging headways (that is the distance between rear bumpers
of two vehicles in a traffic stream) measured from field traffic data.
The study used data from four locations on a single urban freeway
and three different rural freeways in Indiana. Three-stage-leastsquares
(3SLS) regression techniques were used to generate models
that predicted lagging headways for passenger cars, single unit trucks
(SUT), and combination trucks (CT). The estimated PCE values for
single-unit and combination truck for basic urban freeways (level
terrain) were: 1.35 and 1.60, respectively. For rural freeways the
estimated PCE values for single-unit and combination truck were:
1.30 and 1.45, respectively. As expected, traffic variables such as
vehicle flow rates and speed have significant impacts on vehicle
headways. Study results revealed that the use of separate PCE values
for different truck classes can have significant influence on the LOS
estimation.
Abstract: The manufacturing technology of band cotton is very
delicate and depends to choice of certain parameters such as torsion
of warp yarn.
The fabric elasticity is achieved without the use of any elastic
material, chemical expansion, artificial or synthetic and it’s capable
of creating pressures useful for therapeutic treatments.
Before use, the band is subjected to treatments of specific
preparation for obtaining certain elasticity, however, during its
treatment, there are some regression parameters. The dependence of
manufacturing parameters on the quality of the chemical treatment
was confirmed.
The aim of this work is to improve the properties of the fabric
through the development of manufacturing technology appropriately.
Finally for the treatment of the strip pancake 100% cotton, a
treatment method is recommended.
Abstract: This paper attempts to evaluate the effect of fire
damage on concrete by using nonlinear resonance vibration method,
one of the nonlinear nondestructive method. Concrete exhibits not
only nonlinear stress-strain relation but also hysteresis and discrete
memory effect which are contained in consolidated materials.
Hysteretic materials typically show the linear resonance frequency
shift. Also, the shift of resonance frequency is changed according to
the degree of micro damage. The degree of the shift can be obtained
through nonlinear resonance vibration method. Five exposure
scenarios were considered in order to make different internal micro
damage. Also, the effect of post-fire-curing on fire-damaged concrete
was taken into account to conform the change in internal damage.
Hysteretic nonlinearity parameter was obtained by amplitudedependent
resonance frequency shift after specific curing periods. In
addition, splitting tensile strength was measured on each sample to
characterize the variation of residual strength. Then, a correlation
between the hysteretic nonlinearity parameter and residual strength
was proposed from each test result.
Abstract: Load Forecasting plays a key role in making today's
and future's Smart Energy Grids sustainable and reliable. Accurate
power consumption prediction allows utilities to organize in advance
their resources or to execute Demand Response strategies more
effectively, which enables several features such as higher
sustainability, better quality of service, and affordable electricity
tariffs. It is easy yet effective to apply Load Forecasting at larger
geographic scale, i.e. Smart Micro Grids, wherein the lower available
grid flexibility makes accurate prediction more critical in Demand
Response applications. This paper analyses the application of
short-term load forecasting in a concrete scenario, proposed within the
EU-funded GreenCom project, which collect load data from single
loads and households belonging to a Smart Micro Grid. Three
short-term load forecasting techniques, i.e. linear regression, artificial
neural networks, and radial basis function network, are considered,
compared, and evaluated through absolute forecast errors and training
time. The influence of weather conditions in Load Forecasting is also
evaluated. A new definition of Gain is introduced in this paper, which
innovatively serves as an indicator of short-term prediction
capabilities of time spam consistency. Two models, 24- and
1-hour-ahead forecasting, are built to comprehensively compare these
three techniques.
Abstract: Class cohesion is a key object-oriented software
quality attribute that is used to evaluate the degree of relatedness of
class attributes and methods. Researchers have proposed several class
cohesion measures. However, the effect of considering the special
methods (i.e., constructors, destructors, and access and delegation
methods) in cohesion calculation is not thoroughly theoretically
studied for most of them. In this paper, we address this issue for three
popular connectivity-based class cohesion measures. For each of the
considered measures we theoretically study the impact of including
or excluding special methods on the values that are obtained by
applying the measure. This study is based on analyzing the
definitions and formulas that are proposed for the measures. The
results show that including/excluding special methods has a
considerable effect on the obtained cohesion values and that this
effect varies from one measure to another. For each of the three
connectivity-based measures, the proposed theoretical study
recommended excluding the special methods in cohesion
measurement.
Abstract: The purpose of this research is to study of consumer
perception and understanding consumer buying behavior that related
between satisfied and factors affecting the purchasing. Methodology
can be classified between qualitative and quantitative approaches for
the qualitative research were interviews from middlemen who bought
organic vegetables, and middlemen related to production and
marketing system. A questionnaire was utilized as a tool to collect
data. Statistics utilized in this research included frequency,
percentage, mean, standard deviation, and multiple regression
analysis. The result show the reason to decision buying motives is
Fresh products of organic vegetables is the most significant factor on
individuals’ income, with a b of –.143, t = –2.470, the price of
organic vegetables is the most significant factor on individuals’
income, with a b of .176, t = 2.561, p value = .011. The results show
that most people with higher income think about the organic products
are expensive and have negative attitudes towards organic vegetable
as individuals with low and medium income level. Therefore,
household income had a significant influence on the purchasing
decision.
Abstract: For a given a simple connected graph, we present
some new bounds via a new approach for a special topological index
given by the sum of the real number power of the non-zero
normalized Laplacian eigenvalues. To use this approach presents an
advantage not only to derive old and new bounds on this topic but
also gives an idea how some previous results in similar area can be
developed.