Abstract: In this paper, autonomous performance of a small
manufactured unmanned helicopter is tried to be increased. For this
purpose, a small unmanned helicopter is manufactured in Erciyes
University, Faculty of Aeronautics and Astronautics. It is called as
ZANKA-Heli-I. For performance maximization, autopilot parameters
are determined via minimizing a cost function consisting of flight
performance parameters such as settling time, rise time, overshoot
during trajectory tracking. For this purpose, a stochastic optimization
method named as simultaneous perturbation stochastic approximation
is benefited. Using this approach, considerable autonomous
performance increase (around %23) is obtained.
Abstract: In this paper, it is aimed to improve autonomous flight
performance of a load-carrying (payload: 3 kg and total: 6kg)
unmanned aerial vehicle (UAV) through active wing and horizontal
tail active morphing and also integrated autopilot system parameters
(i.e. P, I, D gains) and UAV parameters (i.e. extension ratios of wing
and horizontal tail during flight) design. For this purpose, a loadcarrying
UAV (i.e. ZANKA-II) is manufactured in Erciyes
University, College of Aviation, Model Aircraft Laboratory is
benefited. Optimum values of UAV parameters and autopilot
parameters are obtained using a stochastic optimization method.
Using this approach autonomous flight performance of UAV is
substantially improved and also in some adverse weather conditions
an opportunity for safe flight is satisfied. Active morphing and
integrated design approach gives confidence, high performance and
easy-utility request of UAV users.
Abstract: The rising demand for format-flexible packaging
machines is caused by current market changes. Increasing the formatflexibility
is a new goal for the packaging machine manufacturers’
product development process. There are no methodical or designorientated
tools for a comprehensive consideration of this target. This
paper defines the term format-flexibility in the context of packaging
machines and shows the state-of-the-art for improving the
changeover of production machines. The requirements for a new
approach and the concept itself will be introduced, and the method
elements will be explained. Finally, the use of the concept and the
result of the development of a format-flexible packaging machine
will be shown.
Abstract: The very well-known stacked sets of numbers referred
to as Pascal’s triangle present the coefficients of the binomial
expansion of the form (x+y)n. This paper presents an approach (the
Staircase Horizontal Vertical, SHV-method) to the generalization of
planar Pascal’s triangle for polynomial expansion of the form
(x+y+z+w+r+⋯)n. The presented generalization of Pascal’s triangle
is different from other generalizations of Pascal’s triangles given in
the literature. The coefficients of the generalized Pascal’s triangles,
presented in this work, are generated by inspection, using embedded
Pascal’s triangles. The coefficients of I-variables expansion are
generated by horizontally laying out the Pascal’s elements of (I-1)
variables expansion, in a staircase manner, and multiplying them with
the relevant columns of vertically laid out classical Pascal’s elements,
hence avoiding factorial calculations for generating the coefficients
of the polynomial expansion. Furthermore, the classical Pascal’s
triangle has some pattern built into it regarding its odd and even
numbers. Such pattern is known as the Sierpinski’s triangle. In this
study, a presentation of Sierpinski-like patterns of the generalized
Pascal’s triangles is given. Applications related to those coefficients
of the binomial expansion (Pascal’s triangle), or polynomial
expansion (generalized Pascal’s triangles) can be in areas of
combinatorics, and probabilities.
Abstract: The recent instability in economy was found to be
influencing the situation in Malaysia whether directly or indirectly.
Taking that into consideration, the government needs to find the best
approach to balance its citizen’s socio-economic strata level urgently.
Through education platform is among the efforts planned and acted
upon for the purpose of balancing the effects of the influence,
through the exposure of social entrepreneurial activity towards youth
especially those in higher institution level. Armed with knowledge
and skills that they gained, with the support by entrepreneurial
culture and environment while in campus; indirectly, the students will
lean more on making social entrepreneurship as a career option when
they graduate. Following the issues of marketability and workability
of current graduates that are becoming dire, research involving how
far the willingness of student to create social innovation that
contribute to the society without focusing solely on personal gain is
relevant enough to be conducted. With that, this research is
conducted with the purpose of identifying the level of entrepreneurial
intention and social entrepreneurship among higher institution
students in Malaysia. Stratified random sampling involves 355
undergraduate students from five public universities had been made
as research respondents and data were collected through surveys. The
data was then analyzed descriptively using min score and standard
deviation. The study found that the entrepreneurial intention of higher
education students are on moderate level, however it is the contrary
for social entrepreneurship activities, where it was shown on a high
level. This means that while the students only have moderate level of
willingness to be a social entrepreneur, they are very committed to
created social innovation through the social entrepreneurship
activities conducted. The implication from this study can be
contributed towards the higher institution authorities in prediction the
tendency of student in becoming social entrepreneurs. Thus, the
opportunities and facilities for realizing the courses related to social
entrepreneurship must be created expansively so that the vision of
creating as many social entrepreneurs as possible can be achieved.
Abstract: We present an approach to triangle mesh simplification
designed to be executed on the GPU. We use a quadric error metric
to calculate an error value for each vertex of the mesh and order all
vertices based on this value. This step is followed by the parallel
removal of a number of vertices with the lowest calculated error
values. To allow for the parallel removal of multiple vertices we use
a set of per-vertex boundaries that prevent mesh foldovers even when
simplification operations are performed on neighbouring vertices. We
execute multiple iterations of the calculation of the vertex errors,
ordering of the error values and removal of vertices until either a
desired number of vertices remains in the mesh or a minimum error
value is reached. This parallel approach is used to speed up the
simplification process while maintaining mesh topology and avoiding
foldovers at every step of the simplification.
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: This research involved the use of word distributions
and morphological knowledge by speakers of Arabic learning English
connected different allomorphs in order to realize how the
morphology and syntax of English gives meaning through using
interactive crossword puzzles (ICP). Fifteen chapters covered with a
class of nine learners over an academic year of an intensive English
program were reviewed using the ICP. Learners were questioned
about how the use of this gaming element enhanced and motivated
their learning of English. The findings were positive indicating a
successful implementation of ICP both at creational and user levels.
This indicated a positive role technology had when learning and
teaching English through adopting an interactive gaming element for
learning English.
Abstract: While the feature sizes of recent Complementary Metal
Oxid Semiconductor (CMOS) devices decrease the influence of static
power prevails their energy consumption. Thus, power savings that
benefit from Dynamic Frequency and Voltage Scaling (DVFS) are
diminishing and temporal shutdown of cores or other microchip
components become more worthwhile. A consequence of powering off unused parts of a chip is that the
relative difference between idle and fully loaded power consumption
is increased. That means, future chips and whole server systems gain
more power saving potential through power-aware load balancing,
whereas in former times this power saving approach had only
limited effect, and thus, was not widely adopted. While powering
off complete servers was used to save energy, it will be superfluous
in many cases when cores can be powered down. An important
advantage that comes with that is a largely reduced time to respond
to increased computational demand. We include the above developments in a server power model
and quantify the advantage. Our conclusion is that strategies from
datacenters when to power off server systems might be used in the
future on core level, while load balancing mechanisms previously
used at core level might be used in the future at server level.
Abstract: The source of the jet noise is generated by rocket exhaust plume during rocket engine testing. A domain decomposition approach is applied to the jet noise prediction in this paper. The aerodynamic noise coupling is based on the splitting into acoustic sources generation and sound propagation in separate physical domains. Large Eddy Simulation (LES) is used to simulate the supersonic jet flow. Based on the simulation results of the flow-fields, the jet noise distribution of the sound pressure level is obtained by applying the Ffowcs Williams-Hawkings (FW-H) acoustics equation and Fourier transform. The calculation results show that the complex structures of expansion waves, compression waves and the turbulent boundary layer could occur due to the strong interaction between the gas jet and the ambient air. In addition, the jet core region, the shock cell and the sound pressure level of the gas jet increase with the nozzle size increasing. Importantly, the numerical simulation results of the far-field sound are in good agreement with the experimental measurements in directivity.
Abstract: Our purpose is to investigate how the relationship
between employees and innovation management processes can drive
organizations to successful innovations. This research is deeply
related to a new way of thinking about human resources management
practices. It’s not simply about improving the employees’
engagement, but rather about a different and more radical
commitment: the employee can take on the role traditionally played
by the customer, namely to become the first tester of an innovative
product or service, the first user/customer and eventually the first
investor in the innovation. This new perception of employees could
create the basis of a novelty in the innovation process where
innovation is taken to a next level when the problems with customer
driven innovation on the one hand, and employees driven innovation
on the other can be balanced. This research identifies an effective
approach to innovation where the employees will participate
throughout the whole innovation process, not only in the idea
creation but also in the idea definition and development by giving
feedback in parallel to that provided by customers and lead-users.
Abstract: Discussing the nexus between global health policy and local practices, this article addresses the recent Ebola outbreak as a role model for narrative co-constructions of epidemic risk. We will demonstrate in how far a theory-driven and methodologically rooted analysis of narrativity can help to improve mechanisms of prevention and intervention whenever epidemic risk needs to be addressed locally in order to contribute to global health. Analyzing the narrative transformation of Ebola, we will also address issues of transcultural problem-solving and of normative questions at stake. In this regard, we seek to contribute to a better understanding of a key question of global health and justice as well as to the underlying ethical questions. By highlighting and analyzing the functions of narratives, this paper provides a translational approach to refine our practices by which we address epidemic risk, be it on the national, the transnational or the global scale.
Abstract: With 40% of total world energy consumption,
building systems are developing into technically complex large
energy consumers suitable for application of sophisticated power
management approaches to largely increase the energy efficiency
and even make them active energy market participants. Centralized
control system of building heating and cooling managed by
economically-optimal model predictive control shows promising
results with estimated 30% of energy efficiency increase. The research
is focused on implementation of such a method on a case study
performed on two floors of our faculty building with corresponding
sensors wireless data acquisition, remote heating/cooling units and
central climate controller. Building walls are mathematically modeled
with corresponding material types, surface shapes and sizes. Models
are then exploited to predict thermal characteristics and changes in
different building zones. Exterior influences such as environmental
conditions and weather forecast, people behavior and comfort
demands are all taken into account for deriving price-optimal climate
control. Finally, a DC microgrid with photovoltaics, wind turbine,
supercapacitor, batteries and fuel cell stacks is added to make the
building a unit capable of active participation in a price-varying
energy market. Computational burden of applying model predictive
control on such a complex system is relaxed through a hierarchical
decomposition of the microgrid and climate control, where the
former is designed as higher hierarchical level with pre-calculated
price-optimal power flows control, and latter is designed as lower
level control responsible to ensure thermal comfort and exploit
the optimal supply conditions enabled by microgrid energy flows
management. Such an approach is expected to enable the inclusion
of more complex building subsystems into consideration in order to
further increase the energy efficiency.
Abstract: Seeking and sharing knowledge on online forums
have made them popular in recent years. Although online forums are
valuable sources of information, due to variety of sources of
messages, retrieving reliable threads with high quality content is an
issue. Majority of the existing information retrieval systems ignore
the quality of retrieved documents, particularly, in the field of thread
retrieval. In this research, we present an approach that employs
various quality features in order to investigate the quality of retrieved
threads. Different aspects of content quality, including completeness,
comprehensiveness, and politeness, are assessed using these features,
which lead to finding not only textual, but also conceptual relevant
threads for a user query within a forum. To analyse the influence of
the features, we used an adopted version of voting model thread
search as a retrieval system. We equipped it with each feature solely
and also various combinations of features in turn during multiple
runs. The results show that incorporating the quality features
enhances the effectiveness of the utilised retrieval system
significantly.
Abstract: Patient-specific models are instance-based learning
algorithms that take advantage of the particular features of the patient
case at hand to predict an outcome. We introduce two patient-specific
algorithms based on decision tree paradigm that use AUC as a
metric to select an attribute. We apply the patient specific algorithms
to predict outcomes in several datasets, including medical datasets.
Compared to the patient-specific decision path (PSDP) entropy-based
and CART methods, the AUC-based patient-specific decision path
models performed equivalently on area under the ROC curve (AUC).
Our results provide support for patient-specific methods being a
promising approach for making clinical predictions.
Abstract: This paper discusses the applicability of the numerical model for a damage prediction method of the accidental hydrogen explosion occurring in a hydrogen facility. The numerical model was based on an unstructured finite volume method (FVM) code “NuFD/FrontFlowRed”. For simulating unsteady turbulent combustion of leaked hydrogen gas, a combination of Large Eddy Simulation (LES) and a combustion model were used. The combustion model was based on a two scalar flamelet approach, where a G-equation model and a conserved scalar model expressed a propagation of premixed flame surface and a diffusion combustion process, respectively. For validation of this numerical model, we have simulated the previous two types of hydrogen explosion tests. One is open-space explosion test, and the source was a prismatic 5.27 m3 volume with 30% of hydrogen-air mixture. A reinforced concrete wall was set 4 m away from the front surface of the source. The source was ignited at the bottom center by a spark. The other is vented enclosure explosion test, and the chamber was 4.6 m × 4.6 m × 3.0 m with a vent opening on one side. Vent area of 5.4 m2 was used. Test was performed with ignition at the center of the wall opposite the vent. Hydrogen-air mixtures with hydrogen concentrations close to 18% vol. were used in the tests. The results from the numerical simulations are compared with the previous experimental data for the accuracy of the numerical model, and we have verified that the simulated overpressures and flame time-of-arrival data were in good agreement with the results of the previous two explosion tests.
Abstract: Recently, traffic monitoring has attracted the attention
of computer vision researchers. Many algorithms have been
developed to detect and track moving vehicles. In fact, vehicle
tracking in daytime and in nighttime cannot be approached with the
same techniques, due to the extreme different illumination conditions.
Consequently, traffic-monitoring systems are in need of having a
component to differentiate between daytime and nighttime scenes. In
this paper, a HSV-based day/night detector is proposed for traffic
monitoring scenes. The detector employs the hue-histogram and the
value-histogram on the top half of the image frame. Experimental
results show that the extraction of the brightness features along with
the color features within the top region of the image is effective for
classifying traffic scenes. In addition, the detector achieves high
precision and recall rates along with it is feasible for real time
applications.
Abstract: Data fusion technology can be the best way to extract
useful information from multiple sources of data. It has been widely
applied in various applications. This paper presents a data fusion
approach in multimedia data for event detection in twitter by using
Dempster-Shafer evidence theory. The methodology applies a mining
algorithm to detect the event. There are two types of data in the
fusion. The first is features extracted from text by using the bag-ofwords
method which is calculated using the term frequency-inverse
document frequency (TF-IDF). The second is the visual features
extracted by applying scale-invariant feature transform (SIFT). The
Dempster - Shafer theory of evidence is applied in order to fuse the
information from these two sources. Our experiments have indicated
that comparing to the approaches using individual data source, the
proposed data fusion approach can increase the prediction accuracy
for event detection. The experimental result showed that the proposed
method achieved a high accuracy of 0.97, comparing with 0.93 with
texts only, and 0.86 with images only.
Abstract: Many cluster based routing protocols have been
proposed in the field of wireless sensor networks, in which a group of
nodes are formed as clusters. A cluster head is selected from one
among those nodes based on residual energy, coverage area, number
of hops and that cluster-head will perform data gathering from
various sensor nodes and forwards aggregated data to the base station
or to a relay node (another cluster-head), which will forward the
packet along with its own data packet to the base station. Here a
Game Theory based Diligent Energy Utilization Algorithm (GTDEA)
for routing is proposed. In GTDEA, the cluster head selection is done
with the help of game theory, a decision making process, that selects
a cluster-head based on three parameters such as residual energy
(RE), Received Signal Strength Index (RSSI) and Packet Reception
Rate (PRR). Finding a feasible path to the destination with minimum
utilization of available energy improves the network lifetime and is
achieved by the proposed approach. In GTDEA, the packets are
forwarded to the base station using inter-cluster routing technique,
which will further forward it to the base station. Simulation results
reveal that GTDEA improves the network performance in terms of
throughput, lifetime, and power consumption.
Abstract: At the Savonia University of Applied Sciences (UAS),
curriculum and studies have been improved by applying an Open
Innovation Space approach (OIS). It is based on multidisciplinary
action learning. The key elements of OIS-ideology are work-life
orientation, and student-centric communal learning. In this approach,
every participant can learn from each other and innovations will be
created. In this social innovation educational approach, all practices
are carried out in close collaboration with enterprises in real-life
settings, not in classrooms. As an example, in this paper, Savonia
UAS’s Future Food RDI hub (FF) shows how OIS practices are
implemented by providing food product development and consumer
research services for enterprises in close collaboration with
academicians, students and consumers. In particular one example of
OIS experimentation in the field is provided by a consumer research
carried out utilizing verbal analysis protocol combined with audiovisual
observation (VAP-WAVO). In this case, all co-learners were
acting together in supermarket settings to collect the relevant data for
a product development and the marketing department of a company.
The company benefitted from the results obtained, students were
more satisfied with their studies, educators and academicians were
able to obtain good evidence for further collaboration as well as
renewing curriculum contents based on the requirements of working
life. In addition, society will benefit over time as young university
adults find careers more easily through their OIS related food science
studies. Also this knowledge interaction model re-news education
practices and brings working-life closer to educational research
institutes.