Abstract: Positron emission particle tracking (PEPT) is a
technique in which a single radioactive tracer particle can be
accurately tracked as it moves. A limitation of PET is that in order to
reconstruct a tomographic image it is necessary to acquire a large
volume of data (millions of events), so it is difficult to study rapidly
changing systems. By considering this fact, PEPT is a very fast
process compared with PET.
In PEPT detecting both photons defines a line and the annihilation
is assumed to have occurred somewhere along this line. The location
of the tracer can be determined to within a few mm from coincident
detection of a small number of pairs of back-to-back gamma rays and
using triangulation. This can be achieved many times per second and
the track of a moving particle can be reliably followed. This
technique was invented at the University of Birmingham [1].
The attempt in PEPT is not to form an image of the tracer particle
but simply to determine its location with time. If this tracer is
followed for a long enough period within a closed, circulating system
it explores all possible types of motion.
The application of PEPT to industrial process systems carried out
at the University of Birmingham is categorized in two subjects: the
behaviour of granular materials and viscous fluids. Granular
materials are processed in industry for example in the manufacture of
pharmaceuticals, ceramics, food, polymers and PEPT has been used
in a number of ways to study the behaviour of these systems [2].
PEPT allows the possibility of tracking a single particle within the
bed [3]. Also PEPT has been used for studying systems such as: fluid
flow, viscous fluids in mixers [4], using a neutrally-buoyant tracer
particle [5].
Abstract: This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.
Abstract: The purpose of this paper is to consider the
introduction of online courses to replace the current classroom-based
staff training. The current training is practical, and must be
completed before access to the financial computer system is
authorized. The long term objective is to measure the efficacy,
effectiveness and efficiency of the training, and to establish whether
a transfer of knowledge back to the workplace has occurred. This
paper begins with an overview explaining the importance of staff
training in an evolving, competitive business environment and
defines the problem facing this particular organization. A summary
of the literature review is followed by a brief discussion of the
research methodology and objective. The implementation of the
alpha version of the online course is then described. This paper may
be of interest to those seeking insights into, or new theory regarding,
practical interventions of online learning in the real world.
Abstract: The increasing competitiveness in manufacturing
industry is forcing manufacturers to seek effective processing
schedules. The paper presents an optimization manufacture
scheduling approach for dependent details processing with given
processing sequences and times on multiple machines. By defining
decision variables as start and end moments of details processing it is
possible to use straightforward variables restrictions to satisfy
different technological requirements and to formulate easy to
understand and solve optimization tasks for multiple numbers of
details and machines. A case study example is solved for seven base
moldings for CNC metalworking machines processed on five
different machines with given processing order among details and
machines and known processing time-s duration. As a result of linear
optimization task solution the optimal manufacturing schedule
minimizing the overall processing time is obtained. The
manufacturing schedule defines the moments of moldings delivery
thus minimizing storage costs and provides mounting due-time
satisfaction. The proposed optimization approach is based on real
manufacturing plant problem. Different processing schedules variants
for different technological restrictions were defined and implemented
in the practice of Bulgarian company RAIS Ltd. The proposed
approach could be generalized for other job shop scheduling
problems for different applications.
Abstract: Property investment in the real estate industry has a
high risk due to the uncertainty factors that will affect the decisions
made and high cost. Analytic hierarchy process has existed for some
time in which referred to an expert-s opinion to measure the
uncertainty of the risk factors for the risk analysis. Therefore,
different level of experts- experiences will create different opinion
and lead to the conflict among the experts in the field. The objective
of this paper is to propose a new technique to measure the uncertainty
of the risk factors based on multidimensional data model and data
mining techniques as deterministic approach. The propose technique
consist of a basic framework which includes four modules: user,
technology, end-user access tools and applications. The property
investment risk analysis defines as a micro level analysis as the
features of the property will be considered in the analysis in this
paper.
Abstract: In India, the quarrel between the budding human
populace and the planet-s unchanging supply of freshwater and
falling water tables has strained attention the reuse of gray water as
an alternative water resource in rural development. This paper
present the finest design of laboratory scale gray water treatment
plant, which is a combination of natural and physical operations such
as primary settling with cascaded water flow, aeration, agitation and
filtration, hence called as hybrid treatment process. The economical
performance of the plant for treatment of bathrooms, basins and
laundries gray water showed in terms of deduction competency of
water pollutants such as COD (83%), TDS (70%), TSS (83%), total
hardness (50%), oil and grease (97%), anions (46%) and cations
(49%). Hence, this technology could be a good alternative to treat
gray water in residential rural area.
Abstract: In this work, the plate bending formulation of the boundary element method - BEM, based on the Reissner?s hypothesis, is extended to the analysis of plates reinforced by beams taking into account the membrane effects. The formulation is derived by assuming a zoned body where each sub-region defines a beam or a slab and all of them are represented by a chosen reference surface. Equilibrium and compatibility conditions are automatically imposed by the integral equations, which treat this composed structure as a single body. In order to reduce the number of degrees of freedom, the problem values defined on the interfaces are written in terms of their values on the beam axis. Initially are derived separated equations for the bending and stretching problems, but in the final system of equations the two problems are coupled and can not be treated separately. Finally are presented some numerical examples whose analytical results are known to show the accuracy of the proposed model.
Abstract: Subdivision is a method to create a smooth surface from a coarse mesh by subdividing the entire mesh. The conventional ways to compute and render surfaces are inconvenient both in terms of memory and computational time as the number of meshes will increase exponentially. An adaptive subdivision is the way to reduce the computational time and memory by subdividing only certain selected areas. In this paper, a new adaptive subdivision method for triangle meshes is introduced. This method defines a new adaptive subdivision rules by considering the properties of each triangle's neighbors and is embedded in a traditional Loop's subdivision. It prevents some undesirable side effects that appear in the conventional adaptive ways. Models that were subdivided by our method are compared with other adaptive subdivision methods
Abstract: In this paper we propose a novel approach for
searching eCommerce products using a mobile phone, illustrated by a
prototype eCoMobile. This approach aims to globalize the mobile
search by integrating the concept of user multilinguism into it. To
show that, we particularly deal with English and Arabic languages.
Indeed the mobile user can formulate his query on a commercial
product in either language (English/Arabic). The description of his
information need on commercial products relies on the ontology that
represents the conceptualization of the product catalogue knowledge
domain defined in both English and Arabic languages. A query
expressed on a mobile device client defines the concept that
corresponds to the name of the product followed by a set of pairs
(property, value) specifying the characteristics of the product. Once a
query is submitted it is then communicated to the server side which
analyses it and in its turn performs an http request to an eCommerce
application server (like Amazon). This latter responds by returning
an XML file representing a set of elements where each element
defines an item of the searched product with its specific
characteristics. The XML file is analyzed on the server side and then
items are displayed on the mobile device client along with its
relevant characteristics in the chosen language.