Abstract: Urbanization, population growth, climate change and the current increase in water demand have made the adoption of innovative demand management strategies crucial to the water industry. Water conservation in urban areas has to be improved by encouraging consumers to adopt more sustainable habits and behaviours. This includes informing and educating them about their households’ water consumption and advising them about ways to achieve significant savings on a daily basis. This paper presents a study conducted in the context of the European FP7 WISDOM Project. By integrating innovative Information and Communication Technologies (ICT) frameworks, this project aims at achieving a change in water savings. More specifically, behavioural change will be attempted by implementing smart meters and in-home displays in a trial group of selected households within Cardiff (UK). Using this device, consumers will be able to receive feedback and information about their consumption but will also have the opportunity to compare their consumption to the consumption of other consumers and similar households. Following an initial survey, it appeared necessary to implement these in-home displays in a way that matches consumer's motivations to save water. The results demonstrated the importance of various factors influencing people’s daily water consumption. Both the relevant literature on the subject and the results of our survey therefore led us to include within the in-home device a variety of elements. It first appeared crucial to make consumers aware of the economic aspect of water conservation and especially of the significant financial savings that can be achieved by reducing their household’s water consumption on the long term. Likewise, reminding participants of the impact of their consumption on the environment by making them more aware of water scarcity issues around the world will help increasing their motivation to save water. Additionally, peer pressure and social comparisons with neighbours and other consumers, accentuated by the use of online social networks such as Facebook or Twitter, will likely encourage consumers to reduce their consumption. Participants will also be able to compare their current consumption to their past consumption and to observe the consequences of their efforts to save water through diverse graphs and charts. Finally, including a virtual water game within the display will help the whole household, children and adults, to achieve significant reductions by providing them with simple tips and advice to save water on a daily basis. Moreover, by setting daily and weekly goals for them to reach, the game will expectantly generate cooperation between family members. Members of each household will indeed be encouraged to work together to reduce their water consumption within different rooms of the house, such as the bathroom, the kitchen, or the toilets. Overall, this study will allow us to understand the elements that attract consumers the most and the features that are most commonly used by the participants. In this way, we intend to determine the main factors influencing water consumption in order to identify the measures that will most encourage water conservation in both the long and short term.
Abstract: MicroRNAs are small non-coding RNA found in
many different species. They play crucial roles in cancer such as
biological processes of apoptosis and proliferation. The identification
of microRNA-target genes can be an essential first step towards to
reveal the role of microRNA in various cancer types. In this paper,
we predict miRNA-target genes for lung cancer by integrating
prediction scores from miRanda and PITA algorithms used as a
feature vector of miRNA-target interaction. Then, machine-learning
algorithms were implemented for making a final prediction. The
approach developed in this study should be of value for future studies
into understanding the role of miRNAs in molecular mechanisms
enabling lung cancer formation.
Abstract: Strategic investment decisions are characterized by
high innovation potential and long-term effects on the
competitiveness of enterprises. Due to the uncertainty and risks
involved in this complex decision making process, the need arises for
well-structured support activities. A method that considers cost and
the long-term added value is the cost-benefit effectiveness estimation.
One of those methods is the “profitability estimation focused on
benefits – PEFB”-method developed at the Institute of Management
Cybernetics at RWTH Aachen University. The method copes with
the challenges associated with strategic investment decisions by
integrating long-term non-monetary aspects whilst also mapping the
chronological sequence of an investment within the organization’s
target system. Thus, this method is characterized as a holistic
approach for the evaluation of costs and benefits of an investment.
This participation-oriented method was applied to business
environments in many workshops. The results of the workshops are a
library of more than 96 cost aspects, as well as 122 benefit aspects.
These aspects are preprocessed and comparatively analyzed with
regards to their alignment to a series of risk levels. For the first time,
an accumulation and a distribution of cost and benefit aspects
regarding their impact and probability of occurrence are given. The
results give evidence that the PEFB-method combines precise
measures of financial accounting with the incorporation of benefits.
Finally, the results constitute the basics for using information
technology and data science for decision support when applying
within the PEFB-method.
Abstract: Cloud computing is a business model which provides
an easier management of computing resources. Cloud users can
request virtual machine and install additional softwares and configure
them if needed. However, user can also request virtual appliance
which provides a better solution to deploy application in much faster
time, as it is ready-built image of operating system with necessary
softwares installed and configured. Large numbers of virtual
appliances are available in different image format. User can
download available appliances from public marketplace and start
using it. However, information published about the virtual appliance
differs from each providers leading to the difficulty in choosing
required virtual appliance as it is composed of specific OS with
standard software version. However, even if user choses the
appliance from respective providers, user doesn’t have any flexibility
to choose their own set of softwares with required OS and
application. In this paper, we propose a referenced architecture for
dynamically customizing virtual appliance and provision them in an
easier manner. We also add our experience in integrating our
proposed architecture with public marketplace and Mi-Cloud, a cloud
management software.
Abstract: Wireless sensors, also known as wireless sensor nodes,
have been making a significant impact on human daily life. The
Radio Frequency Identification (RFID) and Wireless Sensor Network
(WSN) are two complementary technologies; hence, an integrated
implementation of these technologies expands the overall
functionality in obtaining long-range and real-time information on the
location and properties of objects and people. An approach for
integrating ZigBee and RFID networks is proposed in this paper, to
create an energy-efficient network improved by the benefits of
combining ZigBee and RFID architecture. Furthermore, the
compatibility and requirements of the ZigBee device and
communication links in the typical RFID system which is presented
with the real world experiment on the capabilities of the proposed
RFID system.
Abstract: Teaching methods include lectures, workshops and
tutorials for the presentation and discussion of ideas have become out
of date; were developed outside the discipline of architecture from
the college of engineering and do not satisfy the architectural
students’ needs and causes them many difficulties in integrating
structure into their design. In an attempt to improve structure
teaching methods, this paper focused upon proposing a supportive
teaching/learning tool using multi-media applications which seeks to
better meet the architecture student’s needs and capabilities and
improve the understanding and application of basic and intermediate
structural engineering and technology principles. Before introducing
the use of multi-media as a supportive teaching tool, a questionnaire
was distributed to third year students of a structural design course
who were selected as a sample to be surveyed forming a sample of 90
cases. The primary aim of the questionnaire was to identify the
students’ learning style and to investigate whether the selected
method of teaching could make the teaching and learning process
more efficient. Students’ reaction on the use of this method was
measured using three key elements indicating that this method is an
appropriate teaching method for the nature of the students and the
course as well.
Abstract: In order to retrieve images efficiently from a large
database, a unique method integrating color and texture features
using genetic programming has been proposed. Opponent color
histogram which gives shadow, shade, and light intensity invariant
property is employed in the proposed framework for extracting color
features. For texture feature extraction, fast discrete curvelet
transform which captures more orientation information at different
scales is incorporated to represent curved like edges. The recent
scenario in the issues of image retrieval is to reduce the semantic gap
between user’s preference and low level features. To address this
concern, genetic algorithm combined with relevance feedback is
embedded to reduce semantic gap and retrieve user’s preference
images. Extensive and comparative experiments have been conducted
to evaluate proposed framework for content based image retrieval on
two databases, i.e., COIL-100 and Corel-1000. Experimental results
clearly show that the proposed system surpassed other existing
systems in terms of precision and recall. The proposed work achieves
highest performance with average precision of 88.2% on COIL-100
and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3%
on Corel. Thus, the experimental results confirm that the proposed
content based image retrieval system architecture attains better
solution for image retrieval.
Abstract: In the past years electric mobility became part of a
public discussion. The trend to fully electrified vehicles instead of
vehicles fueled with fossil energy has notably gained momentum.
Today nearly every big car manufacturer produces and sells fully
electrified vehicles, but electrified vehicles are still not as competitive
as conventional powered vehicles. As the traction battery states the
largest cost driver, lowering its price is a crucial objective. In
addition to improvements in product and production processes a nonnegligible,
but widely underestimated cost driver of production can
be found in logistics, since the production technology is not
continuous yet and neither are the logistics systems. This paper presents an approach to evaluate cost factors on
different designs of load carrier systems. Due to numerous
interdependencies, the combination of costs factors for a particular
scenario is not transparent. This is effecting actions for cost reduction
negatively, but still cost reduction is one of the major goals for
simultaneous engineering processes. Therefore a concurrent and
phase appropriate cost valuation method is necessary to serve cost
transparency. In this paper the four phases of this cost valuation
method are defined and explained, which based upon a new approach
integrating the logistics development process in to the integrated
product and process development.
Abstract: In this paper, we have reported birefringence
manipulation in regenerated high birefringent fiber Bragg grating
(RPMG) by using CO2 laser annealing method. The results indicate
that the birefringence of RPMG remains unchanged after CO2 laser
annealing followed by slow cooling process, but reduced after fast
cooling process (~5.6×10-5). After a series of annealing procedures
with different cooling rates, the obtained results show that slower the
cooling rate, higher the birefringence of RPMG. The volume, thermal
expansion coefficient (TEC) and glass transition temperature (Tg)
change of stress applying part in RPMG during cooling process are
responsible for the birefringence change. Therefore, these findings
are important to the RPMG sensor in high and dynamic temperature
environment. The measuring accuracy, range and sensitivity of
RPMG sensor is greatly affected by its birefringence value. This
work also opens up a new application of CO2 laser for fiber annealing
and birefringence modification.
Abstract: In this paper, we present an application of Riemannian
geometry for processing non-Euclidean image data. We consider the
image as residing in a Riemannian manifold, for developing a new
method to brain edge detection and brain extraction. Automating this
process is a challenge due to the high diversity in appearance brain
tissue, among different patients and sequences. The main contribution, in this paper, is the use of an edge-based
anisotropic diffusion tensor for the segmentation task by integrating
both image edge geometry and Riemannian manifold (geodesic,
metric tensor) to regularize the convergence contour and extract
complex anatomical structures. We check the accuracy of the
segmentation results on simulated brain MRI scans of single
T1-weighted, T2-weighted and Proton Density sequences. We
validate our approach using two different databases: BrainWeb
database, and MRI Multiple sclerosis Database (MRI MS DB). We
have compared, qualitatively and quantitatively, our approach with
the well-known brain extraction algorithms. We show that using
a Riemannian manifolds to medical image analysis improves the
efficient results to brain extraction, in real time, outperforming the
results of the standard techniques.
Abstract: To decrease the grating scale thermal expansion error,
a novel method which based on multiple temperature detection is
proposed. Several temperature sensors are installed on the grating
scale and the temperatures of these sensors are recorded. The
temperatures of every point on the grating scale are calculated by
interpolating between adjacent sensors. According to the thermal
expansion principle, the grating scale thermal expansion error model
can be established by doing the integral for the variations of position
and temperature. A novel compensation method is proposed in this
paper. By applying the established error model, the grating scale
thermal expansion error is decreased by 90% compared with no
compensation. The residual positioning error of the grating scale is
less than 15μm/10m and the accuracy of the machine tool is
significant improved.
Abstract: There are a number of Distributed Generations (DGs)
installed in microgrid, which may have diverse path and direction of
power flow or fault current. The overcurrent protection scheme for the
traditional radial type distribution system will no longer meet the
needs of microgrid protection. Integrating the Intelligent Electronic
Device (IED) and a Supervisory Control and Data Acquisition
(SCADA) with IEC 61850 communication protocol, the paper
proposes a Microgrid Protection Management System (MPMS) to
protect power system from the fault. In the proposed method, the
MPMS performs logic programming of each IED to coordinate their
tripping sequence. The GOOSE message defined in IEC 61850 is used
as the transmission information medium among IEDs. Moreover, to
cope with the difference in fault current of microgrid between
grid-connected mode and islanded mode, the proposed MPMS applies
the group setting feature of IED to protect system and robust
adaptability. Once the microgrid topology varies, the MPMS will
recalculate the fault current and update the group setting of IED.
Provided there is a fault, IEDs will isolate the fault at once. Finally, the
Matlab/Simulink and Elipse Power Studio software are used to
simulate and demonstrate the feasibility of the proposed method.
Abstract: Traditional mechanical control systems in thrust
vectoring are efficient in rocket thrust guidance but their costs
and their weights are excessive. The fluidic injection in the nozzle
divergent constitutes an alternative procedure to achieve the goal. In
this paper, we present a 3D analytical model for fluidic injection
in a supersonic nozzle integrating an orifice. The fluidic vectoring
uses a sonic secondary injection in the divergent. As a result, the
flow and interaction between the main and secondary jet has built in
order to express the pressure fields from which the forces and thrust
vectoring are deduced. Under various separation criteria, the present
analytical model results are compared with the existing numerical
and experimental data from the literature.
Abstract: Financial innovations can be regarded as the cause
and the effect of the evolution of the financial system. Most of
financial innovations are created by various financial institutions for
their own purposes and needs. However, due to their diversity,
financial innovations can be also applied by various business entities
(other than financial institutions).
This paper focuses on the potential application of financial
innovations by non-financial companies. It is assumed that financial
innovations may be effectively applied in all fields of corporate
financial decisions integrating financial management with the risk
management process. Appropriate application of financial
innovations may enhance the development of the company and
increase its value by improving its financial situation and reducing
the level of risk. On the other hand, misused financial innovations
may become the source of extra risk for the company threatening its
further operation.
The main objective of the paper is to identify the major types of
financial innovations offered to non-financial companies by the
banking system in Poland. It also aims at identifying the main factors
determining the creation of financial innovations in the banking
system in Poland and indicating future directions of their
development.
This paper consists of conceptual and empirical part. Conceptual
part based on theoretical study is focused on the determinants of the
process of financial innovations and their application by the nonfinancial
companies. Theoretical study is followed by the empirical
research based on the analysis of the actual offer of the 20 biggest
banks operating in Poland with regard to financial innovations
offered to SMEs and large corporations. These innovations are
classified according to the main functions of the integrated financial
management, such as financing, investment, working capital
management and risk management.
Empirical study has proved that the biggest banks operating in the
Polish market offer to their business customers many types and
classes of financial innovations. This offer appears vast and adequate
to the needs and purposes of the Polish non-financial companies. It
was observed that financial innovations pertained to financing
decisions dominate in the banks’ offer. However, due to high
diversification of the offered financial innovations, business
customers may effectively apply them in all fields and areas of
integrated financial management. It should be underlined, that the
banks’ offer is highly dispersed, which may limit the implementation
of financial innovations in the corporate finance. It would be also
recommended for the banks operating in the Polish market to
intensify the education campaign aiming at increasing knowledge
about financial innovations among business customers.
Abstract: High Order Thinking Skills (HOTS) are suggested
today as essential for the cognitive development of students and as
preparing them for real life skills. Teachers are encouraged to use
HOTS activities in the classroom to help their students develop
higher order skills and deep thinking. So it is essential to prepare preservice
teachers to write and use HOTS activities for their students.
This paper describes a model for integrating HOTS activities with
GeoGebra in pre-service teachers’ preparation. This model describes
four aspects of HOTS activities and working with them: activity
components, preparation procedure, strategies and processes used in
writing a HOTS activity and types of the HOTS activities. In
addition, the paper describes the pre-service teachers' difficulties in
preparing and working with HOTS activities, as well as their
perceptions regarding the use of these activities and GeoGebra in the
mathematics classroom. The paper also describes the contribution of
a HOTS activity to pupils' learning of mathematics, where this HOTS
activity was prepared and taught by one pre-service teacher.
Abstract: This paper proposes a linear model for optimizing
domestic energy consumption in Romania. The particularity of the
model is that it is putting in competition both tangible technologies
and thermal insulation projects with different financing modes.
The model is optimizing the energy system by minimizing the
global discounted cost in household sector, by integrating residential
lighting, space heating, hot water, combined space heating – hot
water, as well as space cooling, in a monolithic model. Another
demand sector included is the passenger transport.
This paper focuses on space heating part, analyzing technical and
economic issues related to investment decisions to envelope and
insulate buildings, in order to minimize energy consumption.
Abstract: This study addresses a concept of the Sustainable Building Environmental Model (SBEM) developed to optimize energy consumption in air conditioning and ventilation (ACV) systems without any deterioration of indoor environmental quality (IEQ). The SBEM incorporates two main components: an adaptive comfort temperature control module (ACT) and a new carbon dioxide demand control module (nDCV). These two modules take an innovative approach to maintain satisfaction of the Indoor Environmental Quality (IEQ) with optimum energy consumption; they provide a rational basis of effective control. A total of 2133 sets of measurement data of indoor air temperature (Ta), relative humidity (Rh) and carbon dioxide concentration (CO2) were conducted in some Hong Kong offices to investigate the potential of integrating the SBEM. A simulation was used to evaluate the dynamic performance of the energy and air conditioning system with the integration of the SBEM in an air-conditioned building. It allows us make a clear picture of the control strategies and performed any pre-tuned of controllers before utilized in real systems. With the integration of SBEM, it was able to save up to 12.3% in simulation of overall electricity consumption, and maintain the average carbon dioxide concentration within 1000ppm and occupant dissatisfaction in 20%.
Abstract: In this paper, a new concept of closed-loop design for a
product is presented. The closed-loop design model is developed by
integrating forward design and reverse design. Based on this new
concept, a closed-loop design model for sustainable manufacturing by
integrated evaluation of forward design, reverse design, and green
manufacturing using a fuzzy analytic network process is developed. In
the design stage of a product, with a given product requirement and
objective, there can be different ways to design the detailed
components and specifications. Therefore, there can be different
design cases to achieve the same product requirement and objective.
Subsequently, in the design evaluation stage, it is required to analyze
and evaluate the different design cases. The purpose of this research is
to develop a model for evaluating the design cases by integrated
evaluating the criteria in forward design, reverse design, and green
manufacturing. A fuzzy analytic network process method is presented
for integrated evaluation of the criteria in the three models. The
comparison matrices for evaluating the criteria in the three groups are
established. The total relational values among the three groups
represent the total relational effects. In applications, a super matrix
model is created and the total relational values can be used to evaluate
the design cases for decision-making to select the final design case. An
example product is demonstrated in this presentation. It shows that the
model is useful for integrated evaluation of forward design, reverse
design, and green manufacturing to achieve a closed-loop design for
sustainable manufacturing objective.
Abstract: Optical biosensors have become a powerful detection
and analysis tool for wide-ranging applications in biomedical research,
pharmaceuticals and environmental monitoring. This study carried out
the computational fluid dynamics (CFD)-based simulations to explore
the dispersion phenomenon in the micro channel of an optical
biosensor. The predicted time sequences of concentration contours
were utilized to better understand the dispersion development occurred
in different geometric shapes of micro channels. The simulation results
showed the surface concentrations at the sensing probe (with the best
performance of a grating coupler) in respect of time to appraise the
dispersion effect and therefore identify the design configurations
resulting in minimum dispersion.
Abstract: Fabric textures are very common in our daily life.
However, the representation of fabric textures has never been explored
from neuroscience view. Theoretical studies suggest that primary
visual cortex (V1) uses a sparse code to efficiently represent natural
images. However, how the simple cells in V1 encode the artificial
textures is still a mystery. So, here we will take fabric texture as
stimulus to study the response of independent component analysis that
is established to model the receptive field of simple cells in V1. We
choose 140 types of fabrics to get the classical fabric textures as
materials. Experiment results indicate that the receptive fields of
simple cells have obvious selectivity in orientation, frequency and
phase when drifting gratings are used to determine their tuning
properties. Additionally, the distribution of optimal orientation and
frequency shows that the patch size selected from each original fabric
image has a significant effect on the frequency selectivity.