Abstract: Tacit knowledge has been one of the most discussed
and contradictory concepts in the field of knowledge management
since the mid 1990s. The concept is used relatively vaguely to refer
to any type of information that is difficult to articulate, which has led
to discussions about the original meaning of the concept (adopted
from Polanyi-s philosophy) and the nature of tacit knowing. It is
proposed that the subject should be approached from the perspective
of cognitive science in order to connect tacit knowledge to
empirically studied cognitive phenomena. Some of the most
important examples of tacit knowing presented by Polanyi are
analyzed in order to trace the cognitive mechanisms of tacit knowing
and to promote better understanding of the nature of tacit knowledge.
The cognitive approach to Polanyi-s theory reveals that the
tacit/explicit typology of knowledge often presented in the
knowledge management literature is not only artificial but totally
opposite approach compared to Polanyi-s thinking.
Abstract: Rapid process of urbanism development has increased
the demand for some infrastructures such as supplying potable water,
electricity network and transportation facilities and etc. Nonefficiency
of the existing system with parallel managements of urban
traffic management has increased the gap between supply and
demand of traffic facilities. A sustainable transport system requires
some activities more important than air pollution control, traffic or
fuel consumption reduction and the studies show that there is no
unique solution for solving complicated transportation problems and
solving such a problem needs a comprehensive, dynamic and reliable
mechanism. Sustainable transport management considers the effects
of transportation development on economic efficiency, environmental
issues, resources consumption, land use and social justice and helps
reduction of environmental effects, increase of transportation system
efficiency as well as improvement of social life and aims to enhance
efficiency, goods transportation, provide services with minimum
access problems that cannot be realized without reorganization of
strategies, policies and plans.
Abstract: The crystalline quality of the AlGaN/GaN high electron mobility transistor (HEMT) structure grown on a 200 mm silicon substrate has been investigated using UV-visible micro- Raman scattering and photoluminescence (PL). The visible Raman scattering probes the whole nitride stack with the Si substrate and shows the presence of a small component of residual in-plane stress in the thick GaN buffer resulting from a wafer bowing, while the UV micro-Raman indicates a tensile interfacial stress induced at the top GaN/AlGaN/AlN layers. PL shows a good crystal quality GaN channel where the yellow band intensity is very low compared to that of the near-band-edge transition. The uniformity of this sample is shown by measurements from several points across the epiwafer.
Abstract: In this empirical research, how marketing managers evaluate their firms- performances and decide to make innovation is examined. They use some standards which are past performance of the firm, target performance of the firm, competitor performance, and average performance of the industry to compare and evaluate the firms- performances. It is hypothesized that marketing managers and owners of the firm compare the firms- current performance with these four standards at the same time to decide when to make innovation relating to any aspects of the firm, either management style or products. Relationship between the comparison of the firm-s performance with these standards and innovation are searched in the same regression model. The results of the regression analysis are discussed and some recommendations are made for future studies and applicants.
Abstract: Falling has been one of the major concerns and threats
to the independence of the elderly in their daily lives. With the
worldwide significant growth of the aging population, it is essential
to have a promising solution of fall detection which is able to operate
at high accuracy in real-time and supports large scale implementation
using multiple cameras. Field Programmable Gate Array (FPGA) is a
highly promising tool to be used as a hardware accelerator in many
emerging embedded vision based system. Thus, it is the main
objective of this paper to present an FPGA-based solution of visual
based fall detection to meet stringent real-time requirements with
high accuracy. The hardware architecture of visual based fall
detection which utilizes the pixel locality to reduce memory accesses
is proposed. By exploiting the parallel and pipeline architecture of
FPGA, our hardware implementation of visual based fall detection
using FGPA is able to achieve a performance of 60fps for a series of
video analytical functions at VGA resolutions (640x480). The results
of this work show that FPGA has great potentials and impacts in
enabling large scale vision system in the future healthcare industry
due to its flexibility and scalability.
Abstract: Research in quantum computation is looking for the consequences of having information encoding, processing and communication exploit the laws of quantum physics, i.e. the laws which govern the ultimate knowledge that we have, today, of the foreign world of elementary particles, as described by quantum mechanics. This paper starts with a short survey of the principles which underlie quantum computing, and of some of the major breakthroughs brought by the first ten to fifteen years of research in this domain; quantum algorithms and quantum teleportation are very biefly presented. The next sections are devoted to one among the many directions of current research in the quantum computation paradigm, namely quantum programming languages and their semantics. A few other hot topics and open problems in quantum information processing and communication are mentionned in few words in the concluding remarks, the most difficult of them being the physical implementation of a quantum computer. The interested reader will find a list of useful references at the end of the paper.
Abstract: Jordan exerts many efforts to nurture their academically gifted students in special schools since 2001. During
the past nine years of launching these schools, their learning and excellence environments were believed to be distinguished compared
to public schools. This study investigated the environments of gifted
students compared with other non-gifted, using a survey instrument
that measures the dimensions of family, peers, teachers, school- support, society, and resources –dimensions rooted deeply in supporting gifted education, learning, and achievement. A total
number of 109 were selected from excellence schools for
academically gifted students, and 119 non-gifted students were selected from public schools. Around 8.3% of the non-gifted students
reported that they “Never" received any support from their surrounding environments, 14.9% reported “Seldom" support, 23.7% reported “ Often" support, 26.0% reported “Frequent" support, and
32.8% reported “Very frequent" support. Where the gifted students reported more “Never" support than the non-gifted did with 11.3%,
“Seldom" support with 15.4%, “Often" support with 26.6%,
“Frequent" support with 29.0%, and reported “Very frequent" support less than the non-gifted students with 23.6%. Unexpectedly,
statistical differences were found between the two groups favoring
non-gifted students in perception of their surrounding environments
in specific dimensions, namely, school- support, teachers, and society. No statistical differences were found in the other dimensions
of the survey, namely, family, peers, and resources. As the
differences were found in teachers, school- support, and society, the
nurturing environments for the excellence schools need to be revised to adopt more creative teaching styles, rich school atmosphere and
infrastructures, interactive guiding for the students and their parents, promoting for the excellence environments, and re-build successful
identification models. Thus, families, schools, and society should
increase their cooperation, communication, and awareness of the
gifted supportive environments. However, more studies to investigate
other aspects of promoting academic giftedness and excellence are recommended.
Abstract: There is a real threat on the VIPs personal pages on
the Social Network Sites (SNS). The real threats to these pages is
violation of privacy and theft of identity through creating fake pages
that exploit their names and pictures to attract the victims and spread
of lies. In this paper, we propose a new secure architecture that
improves the trusting and finds an effective solution to reduce fake
pages and possibility of recognizing VIP pages on SNS. The
proposed architecture works as a third party that is added to
Facebook to provide the trust service to personal pages for VIPs.
Through this mechanism, it works to ensure the real identity of the
applicant through the electronic authentication of personal
information by storing this information within content of their
website. As a result, the significance of the proposed architecture is
that it secures and provides trust to the VIPs personal pages.
Furthermore, it can help to discover fake page, protect the privacy,
reduce crimes of personality-theft, and increase the sense of trust and
satisfaction by friends and admirers in interacting with SNS.
Abstract: This paper presents an application of level sets for the segmentation of abdominal and thoracic aortic aneurysms in CTA
datasets. An important challenge in reliably detecting aortic is the
need to overcome problems associated with intensity
inhomogeneities. Level sets are part of an important class of methods
that utilize partial differential equations (PDEs) and have been extensively applied in image segmentation. A kernel function in the
level set formulation aids the suppression of noise in the extracted
regions of interest and then guides the motion of the evolving contour
for the detection of weak boundaries. The speed of curve evolution
has been significantly improved with a resulting decrease in segmentation time compared with previous implementations of level
sets, and are shown to be more effective than other approaches in
coping with intensity inhomogeneities. We have applied the Courant
Friedrichs Levy (CFL) condition as stability criterion for our algorithm.
Abstract: In this paper, a mathematical model of human immunodeficiency
virus (HIV) is utilized and an optimization problem is
proposed, with the final goal of implementing an optimal 900-day
structured treatment interruption (STI) protocol. Two type of commonly
used drugs in highly active antiretroviral therapy (HAART),
reverse transcriptase inhibitors (RTI) and protease inhibitors (PI), are
considered. In order to solving the proposed optimization problem an
adaptive memetic algorithm with population management (AMAPM)
is proposed. The AMAPM uses a distance measure to control the
diversity of population in genotype space and thus preventing the
stagnation and premature convergence. Moreover, the AMAPM uses
diversity parameter in phenotype space to dynamically set the population
size and the number of crossovers during the search process.
Three crossover operators diversify the population, simultaneously.
The progresses of crossover operators are utilized to set the number
of each crossover per generation. In order to escaping the local optima
and introducing the new search directions toward the global optima,
two local searchers assist the evolutionary process. In contrast to
traditional memetic algorithms, the activation of these local searchers
is not random and depends on both the diversity parameters in
genotype space and phenotype space. The capability of AMAPM in
finding optimal solutions compared with three popular metaheurestics
is introduced.
Abstract: Developing a stable early warning system (EWS)
model that is capable to give an accurate prediction is a challenging
task. This paper introduces k-nearest neighbour (k-NN) method
which never been applied in predicting currency crisis before with the
aim of increasing the prediction accuracy. The proposed k-NN
performance depends on the choice of a distance that is used where in
our analysis; we take the Euclidean distance and the Manhattan as a
consideration. For the comparison, we employ three other methods
which are logistic regression analysis (logit), back-propagation neural
network (NN) and sequential minimal optimization (SMO). The
analysis using datasets from 8 countries and 13 macro-economic
indicators for each country shows that the proposed k-NN method
with k = 4 and Manhattan distance performs better than the other
methods.
Abstract: The paper presents a one-dimensional transient
mathematical model of compressible thermal multi-component gas
mixture flows in pipes. The set of the mass, momentum and enthalpy
conservation equations for gas phase is solved. Thermo-physical
properties of multi-component gas mixture are calculated by solving
the Equation of State (EOS) model. The Soave-Redlich-Kwong
(SRK-EOS) model is chosen. Gas mixture viscosity is calculated on
the basis of the Lee-Gonzales-Eakin (LGE) correlation. Numerical
analysis on rapid decompression in conventional dry gases is
performed by using the proposed mathematical model. The model is
validated on measured values of the decompression wave speed in
dry natural gas mixtures. All predictions show excellent agreement
with the experimental data at high and low pressure. The presented
model predicts the decompression in dry natural gas mixtures much
better than GASDECOM and OLGA codes, which are the most
frequently-used codes in oil and gas pipeline transport service.
Abstract: The ever growing sentiment of environmentalism across the globe has made many people think on the green lines. But most of such ideas halt short of implementation because of the short term economic viability issues with the concept of going green. In this paper we have tried to amalgamate the green concept with social entrepreneurship for solving a variety of issues faced by the society today. In addition the paper also tries to ensure that the short term economic viability does not act as a deterrent. The paper comes up three sustainable models of social entrepreneurship which tackle a wide assortment of issues such as nutrition problem, land problems, pollution problems and employment problems. The models described fall under the following heads: - Spirulina cultivation: The model addresses nutrition, land and employment issues. It deals with cultivation of a blue green alga called Spirulina which can be used as a very nutritious food. Also, the implementation of this model would bring forth employment to the poor people of the area. - Biocomposites: The model comes up with various avenues in which biocomposites can be used in an economically sustainable manner. This model deals with the environmental concerns and addresses the depletion of natural resources. - Packaging material from empty fruit bunches (EFB) of oil palm: This one deals with air and land pollution. It is intended to be a substitute for packaging materials made from Styrofoam and plastics which are non-biodegradable. It takes care of the biodegradability and land pollution issues. It also reduces air pollution as the empty fruit bunches are not incinerated. All the three models are sustainable and do not deplete the natural resources any further. This paper explains each of the models in detail and deals with the operational/manufacturing procedures and cost analysis while also throwing light on the benefits derived and sustainability aspects.
Abstract: In this paper we propose the study of a centrifugal pump control system driven by a three-phase induction motor, which is supplied by a PhotoVoltaic PV generator. The system includes solar panel, a DC / DC converter equipped with its MPPT control, a voltage inverter to three-phase Pulse Width Modulation - PWM and a centrifugal pump driven by a three phase induction motor. In order to control the flow of the centrifugal pump, a Direct Torque Control - DTC of the induction machine is used. To illustrate the performances of the control, simulation results are carried out using Matlab/Simulink.
Abstract: In this paper, the influencing parameters of a novel
purely mechanical wireless in-mould injection moulding sensor
were investigated. The sensor is capable of detecting the melt
front at predefined locations inside the mould. The sensor comprises
a movable pin which acts as the sensor element generating
structure-borne sound triggered by the passing melt front. Due to
the sensor design, melt pressure is the driving force. For pressure
level measurement during pin movement a pressure transducer
located at the same position as the movable pin. By deriving
a mathematical model for the mechanical movement, dominant
process parameters could be investigated towards their impact
on the melt front detection characteristic. It was found that the
sensor is not affected by the investigated parameters enabling it
for reliable melt front detection. In addition, it could be proved
that the novel sensor is in comparable range to conventional melt
front detection sensors.
Abstract: Content-based music retrieval generally involves analyzing, searching and retrieving music based on low or high level features of a song which normally used to represent artists, songs or music genre. Identifying them would normally involve feature extraction and classification tasks. Theoretically the greater features analyzed, the better the classification accuracy can be achieved but with longer execution time. Technique to select significant features is important as it will reduce dimensions of feature used in classification and contributes to the accuracy. Artificial Immune System (AIS) approach will be investigated and applied in the classification task. Bio-inspired audio content-based retrieval framework (B-ACRF) is proposed at the end of this paper where it embraces issues that need further consideration in music retrieval performances.
Abstract: Latvia is the fourth in the world by means of broadband internet speed. The total number of internet users in Latvia exceeds 70% of its population. The number of active mailboxes of the local internet e-mail service Inbox.lv accounts for 68% of the population and 97.6% of the total number of internet users. The Latvian portal Draugiem.lv is a phenomenon of social media, because 58.4 % of the population and 83.5% of internet users use it. A majority of Latvian company profiles are available on social networks, the most popular being Twitter.com. These and other parameters prove the fact consumers and companies are actively using the Internet.
However, after the authors in a number of studies analyzed how enterprises are employing the e-environment, namely, e-environment tools, they arrived to the conclusions that are not as flattering as the aforementioned statistics. There is an obvious contradiction between the statistical data and the actual studies. As a result, the authors have posed a question: Why are entrepreneurs resistant to e-tools? In order to answer this question, the authors have addressed the Technology Acceptance Model (TAM). The authors analyzed each phase and determined several factors affecting the use of e-environment, reaching the main conclusion that entrepreneurs do not have a sufficient level of e-literacy (digital literacy).
The authors employ well-established quantitative and qualitative methods of research: grouping, analysis, statistic method, factor analysis in SPSS 20 environment etc.
The theoretical and methodological background of the research is formed by, scientific researches and publications, that from the mass media and professional literature, statistical information from legal institutions as well as information collected by the author during the survey.
Abstract: Partitioning is a critical area of VLSI CAD. In order to build complex digital logic circuits its often essential to sub-divide multi -million transistor design into manageable Pieces. This paper looks at the various partitioning techniques aspects of VLSI CAD, targeted at various applications. We proposed an evolutionary time-series model and a statistical glitch prediction system using a neural network with selection of global feature by making use of clustering method model, for partitioning a circuit. For evolutionary time-series model, we made use of genetic, memetic & neuro-memetic techniques. Our work focused in use of clustering methods - K-means & EM methodology. A comparative study is provided for all techniques to solve the problem of circuit partitioning pertaining to VLSI design. The performance of all approaches is compared using benchmark data provided by MCNC standard cell placement benchmark net lists. Analysis of the investigational results proved that the Neuro-memetic model achieves greater performance then other model in recognizing sub-circuits with minimum amount of interconnections between them.
Abstract: In this paper, a new method of information fusion – DSmT (Dezert and Smarandache Theory) is introduced to apply to managing and dealing with the uncertain information from robot map building. Here we build grid map form sonar sensors and laser range finder (LRF). The uncertainty mainly comes from sonar sensors and LRF. Aiming to the uncertainty in static environment, we propose Classic DSm (DSmC) model for sonar sensors and laser range finder, and construct the general basic belief assignment function (gbbaf) respectively. Generally speaking, the evidence sources are unreliable in physical system, so we must consider the discounting theory before we apply DSmT. At last, Pioneer II mobile robot serves as a simulation experimental platform. We build 3D grid map of belief layout, then mainly compare the effect of building map using DSmT and DST. Through this simulation experiment, it proves that DSmT is very successful and valid, especially in dealing with highly conflicting information. In short, this study not only finds a new method for building map under static environment, but also supplies with a theory foundation for us to further apply Hybrid DSmT (DSmH) to dynamic unknown environment and multi-robots- building map together.
Abstract: Today's business environment requires that companies have access to highly relevant information in a matter of seconds.
Modern Business Intelligence tools rely on data structured mostly in traditional dimensional database schemas, typically represented by
star schemas. Dimensional modeling is already recognized as a
leading industry standard in the field of data warehousing although
several drawbacks and pitfalls were reported. This paper focuses on
the analysis of another data warehouse modeling technique - the
anchor modeling, and its characteristics in context with the standardized dimensional modeling technique from a query performance perspective. The results of the analysis show
information about performance of queries executed on database
schemas structured according to principles of each database modeling
technique.