Abstract: This paper proposes view-point insensitive human
pose recognition system using neural network. Recognition system
consists of silhouette image capturing module, data driven database,
and neural network. The advantages of our system are first, it is
possible to capture multiple view-point silhouette images of 3D human
model automatically. This automatic capture module is helpful to
reduce time consuming task of database construction. Second, we
develop huge feature database to offer view-point insensitivity at pose
recognition. Third, we use neural network to recognize human pose
from multiple-view because every pose from each model have similar
feature patterns, even though each model has different appearance and
view-point. To construct database, we need to create 3D human model
using 3D manipulate tools. Contour shape is used to convert silhouette
image to feature vector of 12 degree. This extraction task is processed
semi-automatically, which benefits in that capturing images and
converting to silhouette images from the real capturing environment is
needless. We demonstrate the effectiveness of our approach with
experiments on virtual environment.
Abstract: Group work, projects and discussions are important
components of teacher education courses whether they are face-toface,
blended or exclusively online formats. This paper examines the varieties of tasks and challenges with this learning format in a face to
face class teacher education class providing specific examples of both
failure and success from both the student and instructor perspective.
The discussion begins with a brief history of collaborative and cooperative learning, moves to an exploration of the promised
benefits and then takes a look at some of the challenges which can
arise specifically from the use of new technologies. The discussion concludes with guidelines and specific suggestions.
Abstract: With the extensive inclusion of document, especially
text, in the business systems, data mining does not cover the full
scope of Business Intelligence. Data mining cannot deliver its impact
on extracting useful details from the large collection of unstructured
and semi-structured written materials based on natural languages.
The most pressing issue is to draw the potential business intelligence
from text. In order to gain competitive advantages for the business, it
is necessary to develop the new powerful tool, text mining, to expand
the scope of business intelligence.
In this paper, we will work out the strong points of text mining in
extracting business intelligence from huge amount of textual
information sources within business systems. We will apply text
mining to each stage of Business Intelligence systems to prove that
text mining is the powerful tool to expand the scope of BI. After
reviewing basic definitions and some related technologies, we will
discuss the relationship and the benefits of these to text mining. Some
examples and applications of text mining will also be given. The
motivation behind is to develop new approach to effective and
efficient textual information analysis. Thus we can expand the scope
of Business Intelligence using the powerful tool, text mining.
Abstract: In recent years various types of electric vehicles
has gained again increasing attention as an environmentally
benign technology in transport. Especially for urban areas with
high local pollution this Zero-emission technology (at the point
of use) is considered to provide proper solutions. Yet, the bad
economics and the limited driving ranges are still major barriers
for a broader market penetration of battery electric vehicles
(BEV) and of fuel cell vehicles (FCV). The major result of our
analyses is that the most important precondition for a further
dissemination of BEV in urban areas are emission-free zones.
This is an instrument which allows the promotion of BEV
without providing excessive subsidies. In addition, it is
important to note that the full benefits of EV can only be
harvested if the electricity used is produced from renewable
energy sources. That is to say, it has to be ensured that the use of
BEV in urban areas is clearly linked to a green electricity
purchase model. And moreover, the introduction of a CO2-
emission-based tax system would support this requirement.
Abstract: Kernel function, which allows the formulation of nonlinear variants of any algorithm that can be cast in terms of dot products, makes the Support Vector Machines (SVM) have been successfully applied in many fields, e.g. classification and regression. The importance of kernel has motivated many studies on its composition. It-s well-known that reproducing kernel (R.K) is a useful kernel function which possesses many properties, e.g. positive definiteness, reproducing property and composing complex R.K by simple operation. There are two popular ways to compute the R.K with explicit form. One is to construct and solve a specific differential equation with boundary value whose handicap is incapable of obtaining a unified form of R.K. The other is using a piecewise integral of the Green function associated with a differential operator L. The latter benefits the computation of a R.K with a unified explicit form and theoretical analysis, whereas there are relatively later studies and fewer practical computations. In this paper, a new algorithm for computing a R.K is presented. It can obtain the unified explicit form of R.K in general reproducing kernel Hilbert space. It avoids constructing and solving the complex differential equations manually and benefits an automatic, flexible and rigorous computation for more general RKHS. In order to validate that the R.K computed by the algorithm can be used in SVM well, some illustrative examples and a comparison between R.K and Gaussian kernel (RBF) in support vector regression are presented. The result shows that the performance of R.K is close or slightly superior to that of RBF.
Abstract: Recent quasi-experimental evaluation of the Canadian Active Labour Market Policies (ALMP) by Human Resources and Skills Development Canada (HRSDC) has provided an opportunity to examine alternative methods to estimating the incremental effects of Employment Benefits and Support Measures (EBSMs) on program participants. The focus of this paper is to assess the efficiency and robustness of inverse probability weighting (IPW) relative to kernel matching (KM) in the estimation of program effects. To accomplish this objective, the authors compare pairs of 1,080 estimates, along with their associated standard errors, to assess which type of estimate is generally more efficient and robust. In the interest of practicality, the authorsalso document the computationaltime it took to produce the IPW and KM estimates, respectively.
Abstract: Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.
Abstract: CIM is the standard formalism for modeling management
information developed by the Distributed Management Task
Force (DMTF) in the context of its WBEM proposal, designed to
provide a conceptual view of the managed environment. In this
paper, we propose the inclusion of formal knowledge representation
techniques, based on Description Logics (DLs) and the Web Ontology
Language (OWL), in CIM-based conceptual modeling, and then we
examine the benefits of such a decision. The proposal is specified
as a CIM metamodel level mapping to a highly expressive subset
of DLs capable of capturing all the semantics of the models. The
paper shows how the proposed mapping provides CIM diagrams with
precise semantics and can be used for automatic reasoning about the
management information models, as a design aid, by means of newgeneration
CASE tools, thanks to the use of state-of-the-art automatic
reasoning systems that support the proposed logic and use algorithms
that are sound and complete with respect to the semantics. Such a
CASE tool framework has been developed by the authors and its
architecture is also introduced. The proposed formalization is not
only useful at design time, but also at run time through the use of
rational autonomous agents, in response to a need recently recognized
by the DMTF.
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: One part of the total employee’s reward is apart from basic wages or salary, employee’s benefits and intangible remuneration also so called contingent (variable) pay. Contingent pay is connected to performance, contribution, cap competency or skills of individual employees, and to team’s or company-wide performance or to combination of few of the mentioned possibilities. Sometimes among the contingent pay is also incorporated the remuneration based on length of employment, when the financial reward is not connected to performance or skills, but to length of continuous employment either on one working position or in one level of remuneration scale. Main aim of this article is to define, based on available information, contingent pay, describe individual forms, its advantages and disadvantages and possibilities to utilization in practice; but also bring information not only about its extent and level of utilization of contingent pay by companies in one of the Czech Republic’s regions, but also mention their practical experience with this type of remuneration.
Abstract: The objective of this research is to study the technical
and economic performance of wind/diesel/battery (W/D/B) system
supplying a remote small gathering of six families using HOMER
software package. The electrical energy is to cater for the basic needs
for which the daily load pattern is estimated. Net Present Cost (NPC)
and Cost of Energy (COE) are used as economic criteria, while the measure of performance is % of power shortage. Technical and
economic parameters are defined to estimate the feasibility of the
system under study. Optimum system configurations are estimated for two sites. Using HOMER software, the simulation results showed that W/D/B systems are economical for the assumed community sites
as the price of generated electricity is about 0.308 $/kWh, without
taking external benefits into considerations. W/D/B systems are more
economical than W/B or diesel alone systems, as the COE is 0.86 $/kWh for W/B and 0.357 $/kWh for diesel alone.
Abstract: In this research, we propose a weighted class based
queuing (WCBQ) mechanism to provide class differentiation and to
reduce the load for the IMS (IP Multimedia Subsystem) presence
server (PS). The tasks of admission controller for the PS are
demonstrated. Analysis and simulation models are developed to
quantify the performance of WCBQ scheme. An optimized dropping
time frame has been developed based on which some of the preexisting
messages are dropped from the PS-buffer. Cost functions are
developed and simulation comparison has been performed with FCFS
(First Come First Served) scheme. The results show that the PS
benefits significantly from the proposed queuing and dropping
algorithm (WCBQ) during heavy traffic.
Abstract: The increasing industrialization and motorization of the world has led to a steep rise for the demand of petroleum-based fuels. Petroleum-based fuels are obtained from limited reserves. These finite reserves are highly concentrated in certain regions of the world. Therefore, those countries not having these resources are facing energy/foreign exchange crisis, mainly due to the import of crude petroleum. Hence, it is necessary to look for alternative fuels which can be produced from resources available locally within the country such as alcohol, biodiesel, vegetable oils etc. Biodiesel is a renewable, domestically produced fuel that has been shown to reduce particulate, hydrocarbon, and carbon monoxide emissions from combustion. In the present study an experimental investigation on emission characteristic of a liquid burner system operating on several percentage of biodiesel and gas oil is carried out. Samples of exhaust gas are analysed with Testo 350 Xl. The results show that biodiesel can lower some pollutant such as CO, CO2 and particulate matter emissions while NOx emission would increase in comparison with gas oil. The results indicate there may be benefits to using biodiesel in industrial processes.
Abstract: In the paper the study of synthetic transmit aperture
method applying the Golay coded transmission for medical
ultrasound imaging is presented. Longer coded excitation allows to
increase the total energy of the transmitted signal without increasing
the peak pressure. Moreover signal-to-noise ratio and penetration
depth are improved while maintaining high ultrasound image
resolution. In the work the 128-element linear transducer array with
0.3 mm inter-element spacing excited by one cycle and the 8 and 16-
bit Golay coded sequences at nominal frequency 4 MHz was used. To
generate a spherical wave covering the full image region a single
element transmission aperture was used and all the elements received
the echo signals. The comparison of 2D ultrasound images of the
tissue mimicking phantom and in vitro measurements of the beef liver
is presented to illustrate the benefits of the coded transmission. The
results were obtained using the synthetic aperture algorithm with
transmit and receive signals correction based on a single element
directivity function.
Abstract: The study analyzed the risk and returns of commercial-property in Southwestern Nigeria and selected stocksmarket investment between 2000 and 2009; compared the inflation hedging characteristics and diversification potentials of investing in commercial-property and selected stock- market investment. Primary data were collected on characteristics, rental and capital values of commercial- properties from their property managers through the use of questionnaire. Secondary data on stock prices and dividends on banking, insurance and conglomerates sectors were sourced from the Nigerian Stock Exchange (2000-2009). The result showed that average return on all the selected stock- investments was higher than that of commercial-property. As regards risk, commercial-property indicated lower risk, compared to stocks. Also the stock-investment had better inflation hedging capacity than commercial-properties; combination of both had diversification potentials. The study concluded that stock-market investment offered attractive higher return than commercial-property although with higher risk and there could be diversification benefits in combining commercial-property with stock- investment.
Abstract: The paper presents an investigation into the role of virtual reality and web technologies in the field of distance education. Within this frame, special emphasis is given on the building of web-based virtual learning environments so as to successfully fulfill their educational objectives. In particular, basic pedagogical methods are studied, focusing mainly on the efficient preparation, approach and presentation of learning content, and specific designing rules are presented considering the hypermedia, virtual and educational nature of this kind of applications. The paper also aims to highlight the educational benefits arising from the use of virtual reality technology in medicine and study the emerging area of web-based medical simulations. Finally, an innovative virtual reality environment for distance education in medicine is demonstrated. The proposed environment reproduces conditions of the real learning process and enhances learning through a real-time interactive simulator.
Abstract: Emergence of smartphones brings to live the concept
of converged devices with the availability of web amenities. Such
trend also challenges the mobile devices manufactures and service
providers in many aspects, such as security on mobile phones,
complex and long time design flow, as well as higher development
cost. Among these aspects, security on mobile phones is getting more
and more attention. Microkernel based virtualization technology will
play a critical role in addressing these challenges and meeting mobile
market needs and preferences, since virtualization provides essential
isolation for security reasons and it allows multiple operating systems
to run on one processor accelerating development and cutting development
cost. However, virtualization benefits do not come for free.
As an additional software layer, it adds some inevitable virtualization
overhead to the system, which may decrease the system performance.
In this paper we evaluate and analyze the virtualization performance
cost of L4 microkernel based virtualization on a competitive mobile
phone by comparing the L4Linux, a para-virtualized Linux on top of
L4 microkernel, with the native Linux performance using lmbench
and a set of typical mobile phone applications.
Abstract: Ultra-low-power (ULP) circuits have received
widespread attention due to the rapid growth of biomedical
applications and Battery-less Electronics. Subthreshold region of
transistor operation is used in ULP circuits. Major research challenge
in the subthreshold operating region is to extract the ULP benefits
with minimal degradation in speed and robustness. Process, Voltage
and Temperature (PVT) variations significantly affect the
performance of subthreshold circuits. Designed performance
parameters of ULP circuits may vary largely due to temperature
variations. Hence, this paper investigates the effect of temperature
variation on device and circuit performance parameters at different
biasing voltages in the subthreshold region. Simulation results clearly
demonstrate that in deep subthreshold and near threshold voltage
regions, performance parameters are significantly affected whereas in
moderate subthreshold region, subthreshold circuits are more
immune to temperature variations. This establishes that moderate
subthreshold region is ideal for temperature immune circuits.
Abstract: The use of Electronic Commerce (EC)
technologies enables Small Medium Enterprises (SMEs) to improve their efficiency and competitive position. Much of the literature proposes an extensive set of benefits for
organizations that choose to adopt and implement ECommerce
systems. Factors of Business –to-business (B2B)
E-Commerce adoption and implementation have been
extensively investigated. Despite enormous attention given to encourage Small Medium Enterprises (SMEs) to adopt and
implement E-Commerce, little research has been carried out in identifying the factors of Business-to-Consumer ECommerce adoption and implementation for SMEs. To conduct the study, Tornatsky and Fleischer model was adopted
and tested in four SMEs located in Christchurch, New
Zealand. This paper explores the factors that impact the
decision and method of adoption and implementation of ECommerce
systems in automobile industry. Automobile
industry was chosen because the product they deal with i.e.
cars are not a common commodity to be sold online, despite this fact the eCommerce penetration in automobile industry is
high. The factors that promote adoption and implementation of
E-Commerce technologies are discussed, together with the
barriers. This study will help SME owners to effectively
handle the adoption and implementation process and will also
improve the chance of successful E-Commerce
implementation. The implications of the findings for
managers, consultants, and government organizations engaged in promoting E-Commerce adoption and implementation in
small businesses and future research are discussed.
Abstract: Security is an interesting and significance issue for
popular virtual platforms, such as virtualization cluster and cloud
platforms. Virtualization is the powerful technology for cloud
computing services, there are a lot of benefits by using virtual machine
tools which be called hypervisors, such as it can quickly deploy all
kinds of virtual Operating Systems in single platform, able to control
all virtual system resources effectively, cost down for system platform
deployment, ability of customization, high elasticity and high
reliability. However, some important security problems need to take
care and resolved in virtual platforms that include terrible viruses, evil
programs, illegal operations and intrusion behavior. In this paper, we
present useful Intrusion Detection Mechanism (IDM) software that not
only can auto to analyze all system-s operations with the accounting
journal database, but also is able to monitor the system-s state for
virtual platforms.