Abstract: A relationship between face and signature biometrics
is established in this paper. A new approach is developed to predict
faces from signatures by using artificial intelligence. A multilayer
perceptron (MLP) neural network is used to generate face details
from features extracted from signatures, here face is the physical
biometric and signatures is the behavioural biometric. The new
method establishes a relationship between the two biometrics and
regenerates a visible face image from the signature features.
Furthermore, the performance efficiencies of our new technique are
demonstrated in terms of minimum error rates compared to published
work.
Abstract: Innovations not only contribute to competitiveness of
the company but have also positive effects on revenues. On average,
product innovations account to 14 percent of companies’ sales.
Innovation management has substantially changed during the last
decade, because of growing reliance on external partners. As a
consequence, a new task for purchasing arises, as firms need to
understand which suppliers actually do have high potential
contributing to the innovativeness of the firm and which do not.
Proper organization of the purchasing function is important since
for the majority of manufacturing companies deal with substantial
material costs which pass through the purchasing function. In the past
the purchasing function was largely seen as a transaction-oriented,
clerical function but today purchasing is the intermediate with supply
chain partners contributing to innovations, be it product or process
innovations. Therefore, purchasing function has to be organized
differently to enable firm innovation potential.
However, innovations are inherently risky. There are behavioral
risk (that some partner will take advantage of the other party),
technological risk in terms of complexity of products and processes
of manufacturing and incoming materials and finally market risks,
which in fact judge the value of the innovation. These risks are
investigated in this work. Specifically, technological risks which deal
with complexity of the products, and processes will be investigated
more thoroughly. Buying components or such high edge technologies
necessities careful investigation of technical features and therefore is
usually conducted by a team of experts. Therefore it is hypothesized
that higher the technological risk, higher will be the centralization of
the purchasing function as an interface with other supply chain
members.
Main contribution of this research lies is in the fact that analysis
was performed on a large data set of 1493 companies, from 25
countries collected in the GMRG 4 survey. Most analyses of
purchasing function are done by case study analysis of innovative
firms. Therefore this study contributes with empirical evaluations that
can be generalized.
Abstract: In the culture of Thailand, the Yak serve as a mediated
icon representing strength, power, and mystical protection not only
for the Buddha, but for population of worshipers. Originating from
the forests of China, the Yak continues to stand guard at the gates of
Buddhist temples. The Yak represents Thai culture in the hearts of
Thai people. This paper presents a qualitative study regarding the
curious mix of media, culture, and religion that projects the Yak of
Thailand as a larger than life message throughout the political,
cultural, and religious spheres. The gate guardians, or gods as they
are sometimes called, appear throughout the religious temples of
Asian cultures. However, the Asian cultures demonstrate differences
in artistic renditions (or presentations) of such sentinels. Thailand
gate guards (the Yak) stand in front of many Buddhist temples, and
these iconic figures display unique features with varied symbolic
significance. The temple (or wat), plays a vital role in every
community; and, for many people, Thailand’s temples are the
country’s most endearing sights. The authors applied folknography as
a methodology to illustrate the importance of the Thai Yak in serving
as meaningful icons that transcend not only time, but the culture,
religion, and mass media. The Yak represents mythical, religious,
artistic, cultural, and militaristic significance for the Thai people.
Data collection included interviews, focus groups, and natural
observations. This paper summarizes the perceptions of the Thai
people concerning their gate sentries and the relationship,
communication, connection, and the enduring respect that Thai
people hold for their guardians of the gates.
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: Health analytics (HA) is used in healthcare systems
for effective decision making, management and planning of
healthcare and related activities. However, user resistances, unique
position of medical data content and structure (including
heterogeneous and unstructured data) and impromptu HA projects
have held up the progress in HA applications. Notably, the accuracy
of outcomes depends on the skills and the domain knowledge of the
data analyst working on the healthcare data. Success of HA depends
on having a sound process model, effective project management and
availability of supporting tools. Thus, to overcome these challenges
through an effective process model, we propose a HA process model
with features from rational unified process (RUP) model and agile
methodology.
Abstract: Spectrum sensing is the main feature of cognitive
radio technology. Spectrum sensing gives an idea of detecting the
presence of the primary users in a licensed spectrum. In this paper we
compare the theoretical results of detection probability of different
fading environments like Rayleigh, Rician, Nakagami-m fading
channels with the simulation results using energy detection based
spectrum sensing. The numerical results are plotted as Pf Vs Pd for
different SNR values, fading parameters. It is observed that
Nakagami fading channel performance is better than other fading
channels by using energy detection in spectrum sensing. A MATLAB
simulation test bench has been implemented to know the performance
of energy detection in different fading channel environment.
Abstract: Different order modulations combined with different
coding schemes, allow sending more bits per symbol, thus achieving
higher throughputs and better spectral efficiencies. However, it must
also be noted that when using a modulation technique such as 64-
QAM with less overhead bits, better signal-to-noise ratios (SNRs) are
needed to overcome any Inter symbol Interference (ISI) and maintain
a certain bit error ratio (BER). The use of adaptive modulation allows
wireless technologies to yielding higher throughputs while also
covering long distances. The aim of this paper is to implement an
Adaptive Modulation and Coding (AMC) features of the WiMAX
PHY in MATLAB and to analyze the performance of the system in
different channel conditions (AWGN, Rayleigh and Rician fading
channel) with channel estimation and blind equalization. Simulation
results have demonstrated that the increment in modulation order
causes to increment in throughput and BER values. These results
derived a trade-off among modulation order, FFT length, throughput,
BER value and spectral efficiency. The BER changes gradually for
AWGN channel and arbitrarily for Rayleigh and Rician fade
channels.
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: Rice straw pellets are a promising fuel as a renewable
energy source. Financial analysis is needed to make a utilization
system using rise straw pellets financially feasible, considering all
regional conditions including stakeholders related to the collection and
storage, production, transportation and heat utilization. We conducted
the financial analysis of feasibility for a heat utilization system using
rice straw pellets which has been developed for the first time in
Nanporo, Hokkaido, Japan. Especially, we attempted to clarify the
effect of factors required for the system to be financial feasibility, such
as the heating energy demand and collection and storage method of
rice straw. The financial feasibility was found to improve when
increasing the heating energy demand and collecting wheat straw in
August separately from collection of rice straw in November because
the costs of storing rice straw and producing pellets were reduced.
However, the system remained financially unfeasible. This study
proposed a contractor program funded by a subsidy from Nanporo
local government where a contracted company, instead of farmers,
collects and transports rice straw in order to ensure the financial
feasibility of the system, contributing to job creation in the region.
Abstract: In this research work, neural networks were applied to
classify two types of hip joint implants based on the relative hip joint
implant side speed and three components of each ground reaction
force. The condition of walking gait at normal velocity was used and
carried out with each of the two hip joint implants assessed. Ground
reaction forces’ kinetic temporal changes were considered in the first
approach followed but discarded in the second one. Ground reaction
force components were obtained from eighteen patients under such
gait condition, half of which had a hip implant type I-II, whilst the
other half had the hip implant, defined as type III by Orthoload®.
After pre-processing raw gait kinetic data and selecting the time
frames needed for the analysis, the ground reaction force components
were used to train a MLP neural network, which learnt to distinguish
the two hip joint implants in the abovementioned condition. Further
to training, unknown hip implant side and ground reaction force
components were presented to the neural networks, which assigned
those features into the right class with a reasonably high accuracy for
the hip implant type I-II and the type III. The results suggest that
neural networks could be successfully applied in the performance
assessment of hip joint implants.
Abstract: Red River Gum (Eucalyptus camaldulensis) is a tree
of the genus Eucalyptus widely distributed in Algeria and in the
world. The value of its aromatic secondary metabolites offers new
perspectives in the pharmaceutical industry. This strategy can
contribute to the sustainable development of our country. Preliminary
tests performed on the essential oil of Eucalyptus camendulensis
showed that this oil has antibacterial activity vis-à-vis the bacterial
strains (Enterococcus feacalis, Enterobacter cloaceai, Proteus
microsilis, Escherichia coli, Klebsiella pneumonia, and Pseudomonas
aeruginosa) and antifungic (Fusarium sporotrichioide and Fusarium
graminearum). The culture medium used was nutrient broth Muller
Hinton. The interaction between the bacteria and the essential oil is
expressed by a zone of inhibition with diameters of MIC indirectly
expression of. And we used the PDA medium to determine the fungal
activity. The extraction of the aromatic fraction (essentially oilhydrolat)
of the fresh aerian part of the Eucalyptus camendulensis
was performed by hydrodistillation. The average essential oil yield is
0.99%. The antimicrobial and fungal study of the essential oil and
hydrosol showed a high inhibitory effect on the growth of pathogens.
Abstract: Over the past era, there have been a lot of efforts and
studies are carried out in growing proficient tools for performing
various tasks in big data. Recently big data have gotten a lot of
publicity for their good reasons. Due to the large and complex
collection of datasets it is difficult to process on traditional data
processing applications. This concern turns to be further mandatory
for producing various tools in big data. Moreover, the main aim of
big data analytics is to utilize the advanced analytic techniques
besides very huge, different datasets which contain diverse sizes from
terabytes to zettabytes and diverse types such as structured or
unstructured and batch or streaming. Big data is useful for data sets
where their size or type is away from the capability of traditional
relational databases for capturing, managing and processing the data
with low-latency. Thus the out coming challenges tend to the
occurrence of powerful big data tools. In this survey, a various
collection of big data tools are illustrated and also compared with the
salient features.
Abstract: Opportunistic routing is used, where the network has
the features like dynamic topology changes and intermittent network
connectivity. In Delay tolerant network or Disruption tolerant
network opportunistic forwarding technique is widely used. The key
idea of opportunistic routing is selecting forwarding nodes to forward
data packets and coordination among these nodes to avoid duplicate
transmissions. This paper gives the analysis of pros and cons of
various opportunistic routing techniques used in MANET.
Abstract: In development of floating photovoltaic generation
system, finding a suitable place of installation is as important as
development of economically feasible and stable structure. Especially
since floating photovoltaic system has its facility floating on water
surface, it is extremely important to review the effects of weather
conditions such as wind, water flow and floating matters, various
factors (such as fogs) that can reduce generation efficiency, possibility
of connection with power system, and legal restrictions. The method of
investigating suitable area and resource for development of
tracking-type floating photovoltaic generation system was proposed in
this paper, which can be used for development of floating and ocean
photovoltaic system in the future.
Abstract: The system is designed to show images which are
related to the query image. Extracting color, texture, and shape
features from an image plays a vital role in content-based image
retrieval (CBIR). Initially RGB image is converted into HSV color
space due to its perceptual uniformity. From the HSV image, Color
features are extracted using block color histogram, texture features
using Haar transform and shape feature using Fuzzy C-means
Algorithm. Then, the characteristics of the global and local color
histogram, texture features through co-occurrence matrix and Haar
wavelet transform and shape are compared and analyzed for CBIR.
Finally, the best method of each feature is fused during similarity
measure to improve image retrieval effectiveness and accuracy.
Abstract: Anultra-low power capacitor less low-dropout voltage
regulator with improved transient response using gain enhanced feed
forward path compensation is presented in this paper. It is based on a
cascade of a voltage amplifier and a transconductor stage in the feed
forward path with regular error amplifier to form a composite gainenhanced
feed forward stage. It broadens the gain bandwidth and thus
improves the transient response without substantial increase in power
consumption. The proposed LDO, designed for a maximum output
current of 100 mA in UMC 180 nm, requires a quiescent current of
69 )A. An undershot of 153.79mV for a load current changes from
0mA to 100mA and an overshoot of 196.24mV for current change of
100mA to 0mA. The settling time is approximately 1.1 )s for the
output voltage undershooting case. The load regulation is of 2.77
)V/mA at load current of 100mA. Reference voltage is generated by
using an accurate band gap reference circuit of 0.8V.The costly
features of SOC such as total chip area and power consumption is
drastically reduced by the use of only a total compensation
capacitance of 6pF while consuming power consumption of 0.096
mW.
Abstract: The most important part of modern lean low NOx combustors is a premixer where swirlers are often used for intensification of mixing processes and further formation of required flow pattern in combustor liner. Swirling flow leads to formation of complex eddy structures causing flow perturbations. It is able to cause combustion instability. Therefore, at design phase, it is necessary to pay great attention to aerodynamics of premixers. Analysis based on unsteady CFD modeling of swirling flow in production combustor swirler showed presence of large number of different eddy structures that can be conditionally divided into three types relative to its location of origin and a propagation path. Further, features of each eddy type were subsequently defined. Comparison of calculated and experimental pressure fluctuations spectrums verified correctness of computations.
Abstract: The article is devoted to the problem of political
discourse and its reflection on mass cognition. This article is
dedicated to describe the myth as one of the main features of political
discourse. The dominance of an expressional and emotional
component in the myth is shown. Precedent phenomenon plays an
important role in distinguishing the myth from the linguistic point of
view. Precedent phenomena show the linguistic cognition, which is
characterized by their fame and recognition. Four types of myths
such as master myths, a foundation myth, sustaining myth,
eschatological myths are observed. The myths about the national idea
are characterized by national specificity. The main aim of the
political discourse with the help of myths is to influence on the mass
consciousness in order to motivate the addressee to certain actions so
that the target purpose is reached owing to unity of forces.
Abstract: This research proposes a novel reconstruction protocol
for restoring missing surfaces and low-quality edges and shapes in
photos of artifacts at historical sites. The protocol starts with the
extraction of a cloud of points. This extraction process is based on
four subordinate algorithms, which differ in the robustness and
amount of resultant. Moreover, they use different -but
complementary- accuracy to some related features and to the way
they build a quality mesh. The performance of our proposed protocol
is compared with other state-of-the-art algorithms and toolkits. The
statistical analysis shows that our algorithm significantly outperforms
its rivals in the resultant quality of its object files used to reconstruct
the desired model.
Abstract: In this study, a comparative analysis of the approaches
associated with the use of neural network algorithms for effective
solution of a complex inverse problem – the problem of identifying
and determining the individual concentrations of inorganic salts in
multicomponent aqueous solutions by the spectra of Raman
scattering of light – is performed. It is shown that application of
artificial neural networks provides the average accuracy of
determination of concentration of each salt no worse than 0.025 M.
The results of comparative analysis of input data compression
methods are presented. It is demonstrated that use of uniform
aggregation of input features allows decreasing the error of
determination of individual concentrations of components by 16-18%
on the average.