Abstract: Active Power Filters (APFs) are today the most
widely used systems to eliminate harmonics compensate power
factor and correct unbalanced problems in industrial power plants.
We propose to improve the performances of conventional APFs by
using artificial neural networks (ANNs) for harmonics estimation.
This new method combines both the strategies for extracting the
three-phase reference currents for active power filters and DC link
voltage control method. The ANNs learning capabilities to
adaptively choose the power system parameters for both to compute
the reference currents and to recharge the capacitor value requested
by VDC voltage in order to ensure suitable transit of powers to
supply the inverter. To investigate the performance of this
identification method, the study has been accomplished using
simulation with the MATLAB Simulink Power System Toolbox. The
simulation study results of the new (SAPF) identification technique
compared to other similar methods are found quite satisfactory by
assuring good filtering characteristics and high system stability.
Abstract: Off-grid Photovoltaic (PV) systems are empowering
technology in underdeveloped countries like Ethiopia where many
people live far away from the modern world. Where there is
relatively low energy consumption, providing energy from grid
systems is not commercially cost-effective. As a result, significant
people groups worldwide stay without access to electricity. One
remote village in northern Ethiopia was selected by the United
Nations for a pilot project to improve its living conditions. As part of
this comprehensive project, an intelligent charge controller circuit for
Off-grid PV systems was designed for the clinic in that village. In
this paper, design aspects of an intelligent charge controller unit and
its load driver circuits are discussed for an efficient utilization of PVbased
supply systems.
Abstract: While import-substituting industrialization policy
constitute the basis for the industrialization strategies of the 1960s
and 1970s in Turkey, this policy was no longer sustainable by the
1980s. For this reason, export-oriented industrialization policy was
adopted with the decisions taken on January 24, 1980. In other words,
the post-1980 period, Turkey's economy has adopted outwardoriented
industrialization strategy.
In this study, it is aimed to analyze the effect of the change in
economic structure on foreign trade with the transformation of
foreign trade and industrialization policies in the post-1980 period. In
this respect, in order to analyze the relationship between import,
export and economic growth by using variables of the 1960-2011
period, Chow test was applied. In the analysis the reason for using
Chow test is whether there is any difference in economic terms
between import-substituting industrialization policy applied in the
1960-1980 period and the 1981-2011 period during which exportoriented
industrialization policy was applied as a result of the
structural transformation.
Abstract: Some believe that stigma is the worst side effect of the
people who have mental illness. Mental illness researchers have
focused on the influence of mass media on the stigmatization of the
people with mental illness. However, no studies have investigated the
effects of the interactive media, such as blogs, on the stigmatization
of mentally ill people, even though the media have a significant
influence on people in all areas of life. The purpose of this study is to
investigate the use of interactivity in destigmatization of the mentally
ill and the moderating effect of self-construal (independent versus
interdependent self-construal) on the relation between interactivity
and destigmatization. The findings suggested that people in the
human-human interaction condition had less social distance toward
people with mental illness. Additionally, participants with higher
independence showed more favorable affection and less social
distance toward mentally ill people. Finally, direct contact with
mentally ill people increased a person-s positive affect toward people
with mental illness. The current study should provide insights for
mental health practitioners by suggesting how they can use
interactive media to approach the public that stigmatizes the mentally
ill.
Abstract: Characterization and evaluation of the activity of Vespa basalis DPP-IV, which expressed in Spodoptera frugiperda 21 cells. The expression of rDPP-IV was confirmed by SDS–PAGE, Western blot analyses, LC-MS/MS and measurement of its peptidase specificity. One-step purification by Ni-NTA affinity chromatography and the total amount of rDPP-IV recovered was approximately 6.4mg per liter from infected culture medium; an equivalent amount would be produced by 1x109 infected Sf21 insect cells. Through the affinity purification led to highly stable rDPP-IV enzyme was recovered and with significant peptidase activity. The rDPP-IV exhibited classical Michaelis–Menten kinetics, with kcat/Km in the range of 10-500 mM-1×S-1 for the five synthetic substrates and optimum substrate is Ala-Pro-pNA. As expected in inhibition assay, the enzymatic activity of rDPP-IV was significantly reduced by 80 or 60% in the presence of sitagliptin (a DPP-IV inhibitor) or PMSF (a serine protease inhibitor), but was not apparently affected by iodoacetamide (a cysteine protease inhibitor).
Abstract: The emergence of person-centred discourse based
around notions of 'personal development planning- and 'work'life
balance' has taken hold in education and the workplace in recent
years. This paper examines this discourse with regard to recent
developments in higher education as well as the inter-related issue of
work-life balance in occupational careers. In both cases there have
been national and trans-national policy initiatives directed towards
improving both personal opportunities and competitive advantage in
a global knowledge-based economy. However, despite an increasing
concern with looking outward at this globalised educational and
employment marketplace, there is something of a paradox in
encouraging people to look inward at themselves in order to become
more self-determined. This apparent paradox is considered from a
discourse analytic perspective in terms of the ideological effects of an
increasing concern with the personal world. Specifically, it is argued
that there are tensions that emerge from a concern with an innerdirected
process of self-reflection that dissolve any engagement with
wider political issues that impact upon educational and career
development.
Abstract: Image data holds a large amount of different context
information. However, as of today, these resources remain largely
untouched. It is thus the aim of this paper to present a basic technical
framework which allows for a quick and easy exploitation of context
information from image data especially by non-expert users.
Furthermore, the proposed framework is discussed in detail
concerning important social and ethical issues which demand special
requirements in system design. Finally, a first sensor prototype is
presented which meets the identified requirements. Additionally,
necessary implications for the software and hardware design of the
system are discussed, rendering a sensor system which could be
regarded as a good, acceptable and justifiable technical and thereby
enabling the extraction of context information from image data.
Abstract: If price and quantity are the fundamental building
blocks of any theory of market interactions, the importance of trading
volume in understanding the behavior of financial markets is clear.
However, while many economic models of financial markets have
been developed to explain the behavior of prices -predictability,
variability, and information content- far less attention has been
devoted to explaining the behavior of trading volume. In this article,
we hope to expand our understanding of trading volume by
developing a new measure of herding behavior based on a cross
sectional dispersion of volumes betas. We apply our measure to the
Toronto stock exchange using monthly data from January 2000 to
December 2002. Our findings show that the herd phenomenon
consists of three essential components: stationary herding, intentional
herding and the feedback herding.
Abstract: Digital watermarking in medical images can ensure
the authenticity and integrity of the image. This design paper reviews
some existing watermarking schemes and proposes a reversible
tamper detection and recovery watermarking scheme. Watermark
data from ROI (Region Of Interest) are stored in RONI (Region Of
Non Interest). The embedded watermark allows tampering detection
and tampered image recovery. The watermark is also reversible and
data compression technique was used to allow higher embedding
capacity.
Abstract: The purpose of this article is to identify the practical strategies of R&D (research and development) entities for developing converging technology in organizational context. Based on the multi-assignation technological domains of patents derived from entire government-supported R&D projects for 13 years, we find that technology convergence is likely to occur when a university solely develops technology or when university develops technology as one of the collaborators. These results reflect the important role of universities in developing converging technology
Abstract: Thanks to the interdisciplinary nature of crises, the
position of researchers in that field is rather difficult. Very often the
traditional methods of research cannot be applied there. The article is
aimed at the changes in crises research. It describes the substance of
individual changes and emphasizes the shift in research approaches
to the crisis.
Abstract: This paper presents an optimization technique to economic load dispatch (ELD) problems with considering the daily load patterns and generator constraints using a particle swarm optimization (PSO). The objective is to minimize the fuel cost. The optimization problem is subject to system constraints consisting of power balance and generation output of each units. The application of a constriction factor into PSO is a useful strategy to ensure convergence of the particle swarm algorithm. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total constraint cost function is minimized. The performance of the developed methodology is demonstrated by case studies in test system of fifteen-generation units. The results show that the proposed algorithm scan give the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction
Abstract: In two studies we tested the hypothesis that the
appropriate linguistic formulation of a deontic rule – i.e. the
formulation which clarifies the monadic nature of deontic operators
- should produce more correct responses than the conditional
formulation in Wason selection task. We tested this assumption by
presenting a prescription rule and a prohibition rule in conditional
vs. proper deontic formulation. We contrasted this hypothesis with
two other hypotheses derived from social contract theory and
relevance theory. According to the first theory, a deontic rule
expressed in terms of cost-benefit should elicit a cheater detection
module, sensible to mental states attributions and thus able to
discriminate intentional rule violations from accidental rule
violations. We tested this prevision by distinguishing the two types
of violations. According to relevance theory, performance in
selection task should improve by increasing cognitive effect and
decreasing cognitive effort. We tested this prevision by focusing
experimental instructions on the rule vs. the action covered by the
rule. In study 1, in which 480 undergraduates participated, we
tested these predictions through a 2 x 2 x 2 x 2 (type of the rule x
rule formulation x type of violation x experimental instructions)
between-subjects design. In study 2 – carried out by means of a 2 x
2 (rule formulation x type of violation) between-subjects design -
we retested the hypothesis of rule formulation vs. the cheaterdetection
hypothesis through a new version of selection task in
which intentional vs. accidental rule violations were better
discriminated. 240 undergraduates participated in this study.
Results corroborate our hypothesis and challenge the contrasting
assumptions. However, they show that the conditional formulation
of deontic rules produces a lower performance than what is
reported in literature.
Abstract: Data stream analysis is the process of computing
various summaries and derived values from large amounts of data
which are continuously generated at a rapid rate. The nature of a
stream does not allow a revisit on each data element. Furthermore,
data processing must be fast to produce timely analysis results. These
requirements impose constraints on the design of the algorithms to
balance correctness against timely responses. Several techniques
have been proposed over the past few years to address these
challenges. These techniques can be categorized as either dataoriented
or task-oriented. The data-oriented approach analyzes a
subset of data or a smaller transformed representation, whereas taskoriented
scheme solves the problem directly via approximation
techniques. We propose a hybrid approach to tackle the data stream
analysis problem. The data stream has been both statistically
transformed to a smaller size and computationally approximated its
characteristics. We adopt a Monte Carlo method in the approximation
step. The data reduction has been performed horizontally and
vertically through our EMR sampling method. The proposed method
is analyzed by a series of experiments. We apply our algorithm on
clustering and classification tasks to evaluate the utility of our
approach.
Abstract: We are concerned with a class of quadratic matrix
equations arising from the overdamped mass-spring system. By
exploring the structure of coefficient matrices, we propose a fast
cyclic reduction algorithm to calculate the extreme solutions of the
equation. Numerical experiments show that the proposed algorithm
outperforms the original cyclic reduction and the structure-preserving
doubling algorithm.
Abstract: What influences microsystems (MEMS) and nanosystems (NEMS) innovation teams apart from technology complexity? Based on in-depth interviews with innovators, this research explores the key influences on innovation teams in the early phases of MEMS/NEMS. Projects are rare and may last from 5 to 10 years or more from idea to concept. As fundamental technology development in MEMS/NEMS is highly complex and interdisciplinary by involving expertise from different basic and engineering disciplines, R&D is rather a 'testing of ideas' with many uncertainties than a clearly structured process. The purpose of this study is to explore the innovation teams- environment and give specific insights for future management practices. The findings are grouped into three major areas: people, know-how and experience, and market. The results highlight the importance and differences of innovation teams- composition, transdisciplinary knowledge, project evaluation and management compared to the counterparts from new product development teams.
Abstract: Data mining (DM) is the process of finding and extracting frequent patterns that can describe the data, or predict unknown or future values. These goals are achieved by using various learning algorithms. Each algorithm may produce a mining result completely different from the others. Some algorithms may find millions of patterns. It is thus the difficult job for data analysts to select appropriate models and interpret the discovered knowledge. In this paper, we describe a framework of an intelligent and complete data mining system called SUT-Miner. Our system is comprised of a full complement of major DM algorithms, pre-DM and post-DM functionalities. It is the post-DM packages that ease the DM deployment for business intelligence applications.
Abstract: This paper reviews various approaches that have been
used for the modeling and simulation of large-scale engineering
systems and determines their appropriateness in the development of a
RICS modeling and simulation tool. Bond graphs, linear graphs,
block diagrams, differential and difference equations, modeling
languages, cellular automata and agents are reviewed. This tool
should be based on linear graph representation and supports symbolic
programming, functional programming, the development of noncausal
models and the incorporation of decentralized approaches.
Abstract: There are very complex communication systems, as
the multifunction radar, MFAR (Multi-Function Array Radar), where
functions are integrated all together, and simultaneously are
performed the classic functions of tracking and surveillance, as all
the functions related to the communication, countermeasures, and
calibration. All these functions are divided into the tasks to execute.
The task scheduler is a key element of the radar, since it does the
planning and distribution of energy and time resources to be shared
and used by all tasks. This paper presents schedulers based on the use
of multiple queue. Several schedulers have been designed and
studied, and it has been made a comparative analysis of different
performed schedulers. The tests and experiments have been done by
means of system software simulation. Finally a suitable set of radar
characteristics has been selected to evaluate the behavior of the task
scheduler working.
Abstract: Zero inflated strict arcsine model is a newly developed
model which is found to be appropriate in modeling overdispersed
count data. In this study, we extend zero inflated strict arcsine model
to zero inflated strict arcsine regression model by taking into
consideration the extra variability caused by extra zeros and
covariates in count data. Maximum likelihood estimation method is
used in estimating the parameters for this zero inflated strict arcsine
regression model.