Abstract: In this study, the effects of biogas fuels on the performance of an annular micro gas turbine (MGT) were assessed experimentally and numerically. In the experiments, the proposed MGT system was operated successfully under each test condition; minimum composition to the fuel with the biogas was roughly 50% CH4 with 50% CO2. The power output was around 170W at 85,000 RPM as 90% CH4 with 10% CO2 was used and 70W at 65,000 RPM as 70% CH4 with 30% CO2 was used. When a critical limit of 60% CH4 was reached, the power output was extremely low. Furthermore, the theoretical Brayton cycle efficiency and electric efficiency of the MGT were calculated as 23% and 10%, respectively. Following the experiments, the measured data helped us identify the parameters of dynamic model in numerical simulation. Additionally, a numerical analysis of re-designed combustion chamber showed that the performance of MGT could be improved by raising the temperature at turbine inlet. This study presents a novel distributed power supply system that can utilize renewable biogas. The completed micro biogas power supply system is small, low cost, easy to maintain and suited to household use.
Abstract: The field of biomedical materials plays an imperative
requisite and a critical role in manufacturing a variety of biological
artificial replacements in a modern world. Recently, titanium (Ti)
materials are being used as biomaterials because of their superior
corrosion resistance and tremendous specific strength, free- allergic
problems and the greatest biocompatibility compared to other
competing biomaterials such as stainless steel, Co-Cr alloys,
ceramics, polymers, and composite materials. However, regardless of
these excellent performance properties, Implantable Ti materials have
poor shear strength and wear resistance which limited their
applications as biomaterials. Even though the wear properties of Ti
alloys has revealed some improvements, the crucial effectiveness of
biomedical Ti alloys as wear components requires a comprehensive
deep understanding of the wear reasons, mechanisms, and techniques
that can be used to improve wear behavior. This review examines
current information on the effect of thermal and thermomechanical
processing of implantable Ti materials on the long-term prosthetic
requirement which related with wear behavior. This paper focuses
mainly on the evolution, evaluation and development of effective
microstructural features that can improve wear properties of bio
grade Ti materials using thermal and thermomechanical treatments.
Abstract: This study systemizes processes and methods in
wooden furniture design that contains uniqueness in function and
aesthetics. The study was done by research and analysis for
designer-s consideration factors that affect function and production.
Therefore, the study result indicates that such factors are design
process (planning for design, product specifications, concept design,
product architecture, industrial design, production), design evaluation
as well as wooden furniture design dependent factors i.e. art (art
style; furniture history, form), functionality (the strength and
durability, area place, using), material (appropriate to function, wood
mechanical properties), joints, cost, safety, and social responsibility.
Specifically, all aforementioned factors affect good design. Resulting
from direct experience gained through user-s usage, the designer
must design the wooden furniture systemically and effectively. As a
result, this study selected dinning armchair as a case study with all
involving factors and all design process stated in this study.
Abstract: Wood as a natural renewable material is vulnerable to
degradation by microorganisms and susceptible to change in
dimension by water. In order to effectively improve the durability of
wood, an active reagent, maleic anhydride (Man) was selected for
wood modification. Man was first dissolved into a solvent, and then
penetrated into wood porous structure under a vacuum/pressure
condition. After a final catalyst-thermal treatment, wood modification
was finished. The test results indicate that acetone is a good solvent for
transporting Man into wood matrix. SEM observation proved that
wood samples treated by Man kept a good cellular structure, indicating
a well penetration of Man into wood cell walls. FTIR analysis
suggested that Man reacted with hydroxyl groups on wood cell walls
by its ring-ether group, resulting in reduction of amount of hydroxyl
groups and resultant good dimensional stability as well as fine decay
resistance. Consequently, Man modifying wood to improve its
durability is an effective method.
Abstract: Recently, nanomaterials are developed in the form of nano-films, nano-crystals and nano-pores. Lanthanide phosphates as a material find extensive application as laser, ceramic, sensor, phosphor, and also in optoelectronics, medical and biological labels, solar cells and light sources. Among the different kinds of rare-earth orthophosphates, yttrium orthophosphate has been shown to be an efficient host lattice for rare earth activator ions, which have become a research focus because of their important role in the field of light display systems, lasers, and optoelectronic devices. It is in this context that the 4fn- « 4fn-1 5d transitions of rare earth in insulating materials, lying in the UV and VUV, are the aim of large number of studies .Though there has been a few reports on Eu3+, Nd3+, Pr3+,Er3+, Ce3+, Tm3+ doped YPO4. The 4fn- « 4fn-1 5d transitions of the rare earth dependent to the host-matrix, several matrices ions were used to study these transitions, in this work we are suggesting to study on a very specific class of inorganic material that are orthophosphate doped with rare earth ions. This study focused on the effect of Ce3+ concentration on the structural and optical properties of Ce3+ doped YPO4 yttrium orthophosphate with powder form prepared by the Sol Gel method.
Abstract: Urbanization and related anthropogenic modifications
cause extent of habitat fragmentation and directly lead to decline of
local biodiversity. Conservation biologists advocate corridor creation
as one approach to rescue biodiversity. Here we examine the utility of
roads as corridors in preserving plant diversity by investigating
roadside vegetation in Yellow River Delta (YRD), China. We
examined the spatio-temporal distribution pattern of plant species
richness, diversity and composition along roadside. The results
suggest that roads, as dispersal conduits, increase occurrence
probability of new settlers to a new area, meanwhile, roads accumulate
the greater propagule pressure and favourable survival condition
during operation phase. As a result, more species, including native and
alien plants, non- halophyte and halophyte species, threatened and
cosmopolitic species, were found prosperous at roadside. Roadside
may be a refuge for more species, and the pattern of vegetation
distribution is affected by road age and the distance from road verge.
Abstract: In this paper we present a new method for over-height
vehicle detection in low headroom streets and highways using digital
video possessing. The accuracy and the lower price comparing to
present detectors like laser radars and the capability of providing
extra information like speed and height measurement make this
method more reliable and efficient. In this algorithm the features are
selected and tracked using KLT algorithm. A blob extraction
algorithm is also applied using background estimation and
subtraction. Then the world coordinates of features that are inside the
blobs are estimated using a noble calibration method. As, the heights
of the features are calculated, we apply a threshold to select overheight
features and eliminate others. The over-height features are
segmented using some association criteria and grouped using an
undirected graph. Then they are tracked through sequential frames.
The obtained groups refer to over-height vehicles in a scene.
Abstract: Dust acoustic solitary waves are studied in warm
dusty plasma containing negatively charged dusts, nonthermal ions
and Boltzmann distributed electrons. Sagdeev pseudopotential
method is used in order to investigate solitary wave solutions in the
plasmas. The existence of compressive and rarefractive solitons is
studied.
Abstract: Cognitive Science appeared about 40 years ago,
subsequent to the challenge of the Artificial Intelligence, as common
territory for several scientific disciplines such as: IT, mathematics,
psychology, neurology, philosophy, sociology, and linguistics. The
new born science was justified by the complexity of the problems
related to the human knowledge on one hand, and on the other by the
fact that none of the above mentioned sciences could explain alone
the mental phenomena. Based on the data supplied by the
experimental sciences such as psychology or neurology, models of
the human mind operation are built in the cognition science. These
models are implemented in computer programs and/or electronic
circuits (specific to the artificial intelligence) – cognitive systems –
whose competences and performances are compared to the human
ones, leading to the psychology and neurology data reinterpretation,
respectively to the construction of new models. During these
processes if psychology provides the experimental basis, philosophy
and mathematics provides the abstraction level utterly necessary for
the intermission of the mentioned sciences.
The ongoing general problematic of the cognitive approach
provides two important types of approach: the computational one,
starting from the idea that the mental phenomenon can be reduced to
1 and 0 type calculus operations, and the connection one that
considers the thinking products as being a result of the interaction
between all the composing (included) systems. In the field of
psychology measurements in the computational register use classical
inquiries and psychometrical tests, generally based on calculus
methods. Deeming things from both sides that are representing the
cognitive science, we can notice a gap in psychological product
measurement possibilities, regarded from the connectionist
perspective, that requires the unitary understanding of the quality –
quantity whole. In such approach measurement by calculus proves to
be inefficient. Our researches, deployed for longer than 20 years,
lead to the conclusion that measuring by forms properly fits to the
connectionism laws and principles.
Abstract: Robots- visual perception is a field that is gaining
increasing attention from researchers. This is partly due to emerging
trends in the commercial availability of 3D scanning systems or
devices that produce a high information accuracy level for a variety of
applications. In the history of mining, the mortality rate of mine workers
has been alarming and robots exhibit a great deal of potentials to
tackle safety issues in mines. However, an effective vision system
is crucial to safe autonomous navigation in underground terrains.
This work investigates robots- perception in underground terrains
(mines and tunnels) using statistical region merging (SRM) model.
SRM reconstructs the main structural components of an imagery
by a simple but effective statistical analysis. An investigation is
conducted on different regions of the mine, such as the shaft, stope
and gallery, using publicly available mine frames, with a stream of
locally captured mine images. An investigation is also conducted on a
stream of underground tunnel image frames, using the XBOX Kinect
3D sensors. The Kinect sensors produce streams of red, green and
blue (RGB) and depth images of 640 x 480 resolution at 30 frames per
second. Integrating the depth information to drivability gives a strong
cue to the analysis, which detects 3D results augmenting drivable and
non-drivable regions in 2D. The results of the 2D and 3D experiment
with different terrains, mines and tunnels, together with the qualitative
and quantitative evaluation, reveal that a good drivable region can be
detected in dynamic underground terrains.
Abstract: The ever-growing usage of aspect-oriented
development methodology in the field of software engineering
requires tool support for both research environments and industry. So
far, tool support for many activities in aspect-oriented software
development has been proposed, to automate and facilitate their
development. For instance, the AJaTS provides a transformation
system to support aspect-oriented development and refactoring. In
particular, it is well established that the abstract interpretation of
programs, in any paradigm, pursued in static analysis is best served
by a high-level programs representation, such as Control Flow Graph
(CFG). This is why such analysis can more easily locate common
programmatic idioms for which helpful transformation are already
known as well as, association between the input program and
intermediate representation can be more closely maintained.
However, although the current researches define the good concepts
and foundations, to some extent, for control flow analysis of aspectoriented
programs but they do not provide a concrete tool that can
solely construct the CFG of these programs. Furthermore, most of
these works focus on addressing the other issues regarding Aspect-
Oriented Software Development (AOSD) such as testing or data flow
analysis rather than CFG itself. Therefore, this study is dedicated to
build an aspect-oriented control flow graph construction tool called
AJcFgraph Builder. The given tool can be applied in many software
engineering tasks in the context of AOSD such as, software testing,
software metrics, and so forth.
Abstract: This work has been carried out in order to provide an understanding of the physical behaviors of the flow variation of pressure and temperature in a vortex tube. A computational fluid dynamics model is used to predict the flow fields and the associated temperature separation within a Ranque–Hilsch vortex tube. The CFD model is a steady axisymmetric model (with swirl) that utilizes the standard k-ε turbulence model. The second–order numerical schemes, was used to carry out all the computations. Vortex tube with a circumferential inlet stream and an axial (cold) outlet stream and a circumferential (hot) outlet stream was considered. Performance curves (temperature separation versus cold outlet mass fraction) were obtained for a specific vortex tube with a given inlet mass flow rate. Simulations have been carried out for varying amounts of cold outlet mass flow rates. The model results have a good agreement with experimental data.
Abstract: Instead of traditional (nominal) classification we investigate
the subject of ordinal classification or ranking. An enhanced
method based on an ensemble of Support Vector Machines (SVM-s)
is proposed. Each binary classifier is trained with specific weights
for each object in the training data set. Experiments on benchmark
datasets and synthetic data indicate that the performance of our
approach is comparable to state of the art kernel methods for
ordinal regression. The ensemble method, which is straightforward
to implement, provides a very good sensitivity-specificity trade-off
for the highest and lowest rank.
Abstract: The rapid pace of technological advancement and its
consequential widening digital divide has resulted in the
marginalization of the disabled especially the communication
challenged. The dearth of suitable technologies for the development
of assistive technologies has served to further marginalize the
communications challenged user population and widen this chasm
even further. Given the varying levels of disability there and its
associated requirement for customized solution based. This paper
explains the use of a Software Development Kits (SDK) for the
bridging of this communications divide through the use of industry
poplar communications SDKs towards identification of requirements
for communications challenged users as well as identification of
appropriate frameworks for future development initiatives.
Abstract: Road industry has challenged the prospect of ecoconstruction. Pavements may fit within the framework of sustainable development. Hence, research implements assessments of conventional pavements impacts on environment in use of life cycle approach. To meet global, and often national, targets on pollution control, newly introduced pavement designs are under study. This is the case of Cyprus demonstration, which occurred within EcoLanes project work. This alternative pavement differs on concrete layer reinforced with tire recycling product. Processing of post-consumer tires produces steel fibers improving strength capacity against cracking. Thus maintenance works are relevantly limited in comparison to flexible pavement. This enables to be more ecofriendly, referenced to current study outputs. More specific, proposed concrete pavement life cycle processes emits 15 % less air pollutants and consumes 28 % less embodied energy than those of the asphalt pavement. In addition there is also a reduction on costs by 0.06 %.
Abstract: The study identified the sources of production
inefficiency of the farming sector in district Faisalabad in the Punjab
province of Pakistan. Data Envelopment Analysis (DEA) technique
was utilized at farm level survey data of 300 farmers for the year
2009. The overall mean efficiency score was 0.78 indicating 22
percent inefficiency of the sample farmers. Computed efficiency
scores were then regressed on farm specific variables using Tobit
regression analysis. Farming experience, education, access to
farming credit, herd size and number of cultivation practices showed
constructive and significant effect on the farmer-s technical
efficiency.
Abstract: Designing, implementing, and debugging concurrency
control algorithms in a real system is a complex, tedious, and errorprone
process. Further, understanding concurrency control
algorithms and distributed computations is itself a difficult task.
Visualization can help with both of these problems. Thus, we have
developed an exploratory environment in which people can prototype
and test various versions of concurrency control algorithms, study
and debug distributed computations, and view performance statistics
of distributed systems. In this paper, we describe the exploratory
environment and show how it can be used to explore concurrency
control algorithms for the interactive steering of distributed
computations.
Abstract: Drinking water is one of the most valuable resources
available to mankind. The presence of pathogens in drinking water is
highly undesirable. Because of the Lateritic soil, the iron
concentrations were high in ground water. High concentration of iron
and other trace elements could restrict bacterial growth and modify
their metabolic pattern as well. The bacterial growth rate reduced in
the presence of iron in water. This paper presents the results of a
controlled laboratory study conducted to assess the inhibition of
micro-organism (pathogen) in well waters in the presence of
dissolved iron concentrations. Synthetic samples were studied in the
laboratory and the results compared with field samples. Predictive
model for microbial inhibition in the presence of iron is presented. It
was seen that the bore wells, open wells and the field results varied,
probably due to the nature of micro-organism utilizing the iron in
well waters.
Abstract: In the semiconductor manufacturing process, large
amounts of data are collected from various sensors of multiple
facilities. The collected data from sensors have several different characteristics
due to variables such as types of products, former processes
and recipes. In general, Statistical Quality Control (SQC) methods
assume the normality of the data to detect out-of-control states of
processes. Although the collected data have different characteristics,
using the data as inputs of SQC will increase variations of data,
require wide control limits, and decrease performance to detect outof-
control. Therefore, it is necessary to separate similar data groups
from mixed data for more accurate process control. In the paper,
we propose a regression tree using split algorithm based on Pearson
distribution to handle non-normal distribution in parametric method.
The regression tree finds similar properties of data from different
variables. The experiments using real semiconductor manufacturing
process data show improved performance in fault detecting ability.
Abstract: A recent neurospiking coding scheme for feature extraction from biosonar echoes of various plants is examined with avariety of stochastic classifiers. Feature vectors derived are employedin well-known stochastic classifiers, including nearest-neighborhood,single Gaussian and a Gaussian mixture with EM optimization.Classifiers' performances are evaluated by using cross-validation and bootstrapping techniques. It is shown that the various classifers perform equivalently and that the modified preprocessing configuration yields considerably improved results.