Abstract: The compatibility of optical resonators with microfluidic systems may be relevant for chemical and biological applications. Here, a fluorescent-core microcavity (FCM) is investigated as a refractometric sensor for heavy oils. A high-index film of silicon quantum dots (QDs) was formed inside the capillary, supporting cylindrical fluorescence whispering gallery modes (WGMs). A set of standard refractive index oils was injected into a capillary, causing a shift of the WGM resonances toward longer wavelengths. A maximum sensitivity of 240 nm/RIU (refractive index unit) was found for a nominal oil index of 1.74. As well, a sensitivity of 22 nm/RIU was obtained for a lower index of 1.48, more typical of fuel hydrocarbons. Furthermore, the observed spectra and sensitivities were compared to theoretical predictions and reproduced via FDTD simulations, showing in general an excellent agreement. This work demonstrates the potential use of FCMs for oil sensing applications and the more generally for detecting liquid solutions with a high refractive index or high viscosity.
Abstract: Heat pipes are two-phase heat transfer devices with
high effective thermal conductivity. Due to the high heat transport
capacity, heat exchanger with heat pipes has become much smaller
than traditional heat exchangers in handling high heat fluxes. With
the working fluid in a heat pipe, heat can be absorbed on the
evaporator region and transported to the condenser region where the
vapour condenses releasing the heat to the cooling media. Heat pipe
technology has found increasing applications in enhancing the
thermal performance of heat exchangers in microelectranics, energy
saving in HVAC systems for operating rooms,surgery centers, hotels,
cleanrooms etc, temperature regulation systems for the human body
and other industrial sectors. Development activity in heat pipe and
thermosyphon technology in asia in recent years is surveyed. Some
new results obtained in Australia and other countries are also
included.
Abstract: The aim of the present study was to investigate the
chemical and biological properties of local cowpea seed protein
cultivated in Gizan region. The results showed that the cowpea and
its products contain high level of protein (22.9-77.6%), high
carbohydrates (9.4-64.3%) and low fats (0.1-0.3%). The trypsin and
chymotrypsin activities were found to be 32.2 and 15.2 units,
respectively. These activities were not affected in both defatted and
protein concentrate whereas they were significantly reduced in
isolated protein and cooked samples. The phytate content of cooked
and concentrated cowpea samples varied from 0.25% -0.32%,
respectively. Tannin content was found to be 0.4% and 0.23% for
cooked and raw samples, respectively. The in vitro protein
digestibility was very high in cowpea seeds (75.04-78.76%). The
biological evaluation using rats showed that the group fed with
animal feed containing casein gain more weight than those fed with
that containing cowpea. However, the group fed with cooked cowpea
gain more weight than those fed with uncooked cowpea. On the
other hand, in vivo digestion showed high value (98.33%) among the
group consumed casein compared to other groups those consumed
cowpea contains feed. This could be attributed to low antinutritional
factors in casein contains feed compared to those of cowpea contains
feed because cooking significantly increased the digestion rate
(80.8% to 83.5%) of cowpea contains feed. Furthermore, the
biological evaluation was high (91.67%) of casein containing feed
compared to that of cowpea containing feed (80.83%-87.5%). The
net protein utilization (NPU) was higher (89.67%) in the group fed
with casein containing feed than that of cowpea containing feed
(56.33%-69.67%).
Abstract: The flow field over a flat roof model building has been numerically investigated in order to determine threedimensional CFD guidelines for the calculation of the turbulent flow over a structure immersed in an atmospheric boundary layer. To this purpose, a complete validation campaign has been performed through a systematic comparison of numerical simulations with wind tunnel experimental data. Wind tunnel measurements and numerical predictions have been compared for five different vertical positions, respectively from the upstream leading edge to the downstream bottom edge of the analyzed model. Flow field characteristics in the neighborhood of the building model have been numerically investigated, allowing a quantification of the capabilities of the CFD code to predict the flow separation and the extension of the recirculation regions. The proposed calculations have allowed the development of a preliminary procedure to be used as guidance in selecting the appropriate grid configuration and corresponding turbulence model for the prediction of the flow field over a three-dimensional roof architecture dominated by flow separation.
Abstract: All climate models agree that the temperature in
Greece will increase in the range of 1° to 2°C by the year 2030 and
mean sea level in Mediterranean is expected to rise at the rate of 5
cm/decade. The aim of the present paper is the estimation of the
coastline displacement driven by the climate change and sea level
rise. In order to achieve that, all known statistical and non-statistical
computational methods are employed on some Greek coastal areas.
Furthermore, Kalman filtering techniques are for the first time
introduced, formulated and tested. Based on all the above, shoreline
change signals and noises are computed and an inter-comparison
between the different methods can be deduced to help evaluating
which method is most promising as far as the retrieve of shoreline
change rate is concerned.
Abstract: Principally, plants grown in soilless culture may be
attacked by the same pests and diseases as cultivated traditionally in
soil. The most destructive phytopathogens are fungi, such as
Phythium, Phytophthora and Fusarium, followed by viruses, bacteria
and nematodes. We investigated effect of carbon nanotube filters on
disease management of soilless culture. Tomato seedlings transplant
in plastic pots filled with a soilless media of vermiculite. The crop
irrigated and fertilized using a hydroponic nutrient solution. We used
carbon nanotube filters for nutrient solution disinfection. Our results
show that carbon nanotube filtration significantly reduces pathogens
on tomato plants. Fungal elimination (Fusarium oxysporum and
Pythium spp.) was usually successful at about 96 to 99.9% all over
the cultural season. It is seem that in tomato soilless culture,
nanofiltration constitutes a reliable method that allows control of the
development of diseases caused by pathogenic fungi
Abstract: Enzymatic hydrolysis of starch from natural sources
finds potential application in commercial production of alcoholic
beverage and bioethanol. In this study the effect of starch
concentration, temperature, time and enzyme concentration were
studied and optimized for hydrolysis of Potato starch powder (of
mesh 80/120) into glucose syrup by immobilized (using Sodium
arginate) α-amylase using central composite design. The
experimental result on enzymatic hydrolysis of Potato starch was
subjected to multiple linear regression analysis using MINITAB 14
software. Positive linear effect of starch concentration, enzyme
concentration and time was observed on hydrolysis of Potato starch
by α-amylase. The statistical significance of the model was validated
by F-test for analysis of variance (p ≤ 0.01). The optimum value of
starch concentration, enzyme concentration, temperature, time and
were found to be 6% (w/v), 2% (w/v), 40°C and 80min respectively.
The maximum glucose yield at optimum condition was 2.34 mg/mL.
Abstract: Two Amphiphilic catalysts, iron (III) dodecylbenzene
sulfonate and nickel (II) dodecylbenzene sulfonate, were synthesized
and used in the catalytic aquathermolysis of heavy crude oil to reduce
its viscosity. The prepared catalysts exhibited good performance in
the aquathermolysis and the viscosity is reduced by ~ 78.9 % for
Egyptian heavy crude oil. The chemical and physical properties of
heavy oil both before and after reaction were investigated by FT-IR,
dynamic viscosity, molecular weight and SARA analysis. The results
indicated that the content of resin, asphaltene, average molecular
weight and sulfur content of heavy oil is reduced after the catalytic
aquathermolysis.
Abstract: The Far From Most Strings Problem (FFMSP) is to obtain a string which is far from as many as possible of a given set of strings. All the input and the output strings are of the same length, and two strings are said to be far if their hamming distance is greater than or equal to a given positive integer. FFMSP belongs to the class of sequences consensus problems which have applications in molecular biology. The problem is NP-hard; it does not admit a constant-ratio approximation either, unless P = NP. Therefore, in addition to exact and approximate algorithms, (meta)heuristic algorithms have been proposed for the problem in recent years. On the other hand, in the recent years, hybrid algorithms have been proposed and successfully used for many hard problems in a variety of domains. In this paper, a new metaheuristic algorithm, called Constructive Beam and Local Search (CBLS), is investigated for the problem, which is a hybridization of constructive beam search and local search algorithms. More specifically, the proposed algorithm consists of two phases, the first phase is to obtain several candidate solutions via the constructive beam search and the second phase is to apply local search to the candidate solutions obtained by the first phase. The best solution found is returned as the final solution to the problem. The proposed algorithm is also similar to memetic algorithms in the sense that both use local search to further improve individual solutions. The CBLS algorithm is compared with the most recent published algorithm for the problem, GRASP, with significantly positive results; the improvement is by order of magnitudes in most cases.
Abstract: Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.
Abstract: This paper describes a novel approach for deriving
modules from protein-protein interaction networks, which combines
functional information with topological properties of the network.
This approach is based on weighted clustering coefficient, which
uses weights representing the functional similarities between the
proteins. These weights are calculated according to the semantic
similarity between the proteins, which is based on their Gene
Ontology terms. We recently proposed an algorithm for identification
of functional modules, called SWEMODE (Semantic WEights for
MODule Elucidation), that identifies dense sub-graphs containing
functionally similar proteins. The rational underlying this approach is
that each module can be reduced to a set of triangles (protein triplets
connected to each other). Here, we propose considering semantic
similarity weights of all triangle-forming edges between proteins. We
also apply varying semantic similarity thresholds between
neighbours of each node that are not neighbours to each other (and
hereby do not form a triangle), to derive new potential triangles to
include in module-defining procedure. The results show an
improvement of pure topological approach, in terms of number of
predicted modules that match known complexes.
Abstract: The significance of emissions from the road transport
sector (such as air pollution, noise, etc) has grown considerably in
recent years. In Australia, 14.3% of national greenhouse gas
emissions in 2000 were the transport sector-s share which 12.9% of
net national emissions were related to a road transport alone.
Considering the growing attention to the green house gas(GHG)
emissions, this paper attempts to provide air pollution modeling
aspects of environmental consequences of the road transport by using
one of the best computer based tools including the Geographic
Information System (GIS). In other word, in this study, GIS and its
applications is explained, models which are used to model air
pollution and GHG emissions from vehicles are described and GIS is
applied in real case study that attempts to forecast GHG emission
from people who travel to work by car in 2031 in Melbourne for
analysing results as thematic maps.
Abstract: Time interleaved sigma-delta (TIΣΔ) architecture is a
potential candidate for high bandwidth analog to digital converters
(ADC) which remains a bottleneck for software and cognitive radio
receivers. However, the performance of the TIΣΔ architecture is
limited by the unavoidable gain and offset mismatches resulting
from the manufacturing process. This paper presents a novel digital
calibration method to compensate the gain and offset mismatch
effect. The proposed method takes advantage of the reconstruction
digital signal processing on each channel and requires only few logic
components for implementation. The run time calibration is estimated
to 10 and 15 clock cycles for offset cancellation and gain mismatch
calibration respectively.
Abstract: In this paper, the innovative intelligent fuzzy weighted
input estimation method (FWIEM) can be applied to the inverse heat
transfer conduction problem (IHCP) to estimate the unknown
time-varying heat flux efficiently as presented. The feasibility of this
method can be verified by adopting the temperature measurement
experiment. We would like to focus attention on the heat flux
estimation to three kinds of samples (Copper, Iron and Steel/AISI 304)
with the same 3mm thickness. The temperature measurements are then
regarded as the inputs into the FWIEM to estimate the heat flux. The
experiment results show that the proposed algorithm can estimate the
unknown time-varying heat flux on-line.
Abstract: This paper discusses the investigation of a wearable
textile monopole antenna on specific absorption rate (SAR) for bodycentric
wireless communication applications at 2.45 GHz. The
antenna is characterized on a realistic 8 x 8 x 8 mm3 resolution
truncated Hugo body model in CST Microwave Studio software. The
result exhibited that the simulated SAR values were reduced
significantly by 83.5% as the position of textile monopole was
varying between 0 mm and 15 mm away from the human upper arm.
A power absorption reduction of 52.2% was also noticed as the
distance of textile monopole increased.
Abstract: Organizational communication is an administrative
function crucial especially for executives in the implementation of
organizational and administrative functions. Executives spend a
significant part of their time on communicative activities. Doing his or her daily routine, arranging meeting schedules, speaking on the telephone, reading or replying to business correspondence, or
fulfilling the control functions within the organization, an executive typically engages in communication processes.
Efficient communication is the principal device for the adequate implementation of administrative and organizational activities. For
this purpose, management needs to specify the kind of
communication system to be set up and the kind of communication
devices to be used. Communication is vital for any organization.
In conventional offices, communication takes place within the hierarchical pyramid called the organizational structure, and is known as formal or informal communication. Formal communication
is the type that works in specified structures within the organizational rules and towards the organizational goals. Informal communication, on the other hand, is the unofficial type taking place among staff as
face-to-face or telephone interaction.
Communication in virtual as well as conventional offices is
essential for obtaining the right information in administrative
activities and decision-making. Virtual communication technologies
increase the efficiency of communication especially in virtual teams.
Group communication is strengthened through an inter-group central
channel. Further, ease of information transmission makes it possible
to reach the information at the source, allowing efficient and correct decisions. Virtual offices can present as a whole the elements of information which conventional offices produce in different
environments.
At present, virtual work has become a reality with its pros and
cons, and will probably spread very rapidly in coming years, in line
with the growth in information technologies.
Abstract: This study aimed to investigate the influence of selected antecedents, which were tourists’ satisfaction towards attractions in Bangkok, perceived value of the attractions, feelings of engagement with the attractions, acquaintance with the attractions, push factors, pull factors and motivation to seek novelty, on foreign tourist’s loyalty towards tourist attractions in Bangkok. By using multi stage sampling technique, 400 international tourists were sampled. After that, Semi Structural Equation Model was utilized in the analysis stage by LISREL. The Semi Structural Equation Model of the selected antecedents of tourist’s loyalty attractions had a correlation with the empirical data through the following statistical descriptions: Chi- square = 3.43, df = 4, P- value = 0.48893; RMSEA = 0.000; CFI = 1.00; CN = 1539.75; RMR = 0.0022; GFI = 1.00 and AGFI = 0.98. The findings indicated that all antecedents were able together to predict the loyalty of the foreign tourists who visited Bangkok at 73 percent.
Abstract: Phytases (myo-inositol hexakisphosphate
phosphohydrolases; EC 3.1.3.8) catalyze the hydrolysis of phytic acid
(myoinositol hexakisphosphate) to the mono-, di-, tri-, tetra-, and
pentaphosphates of myo-inositol and inorganic phosphate.
Therrmophilic bacteria isolated from water sampled from hot spring.
About 120 isolates of bacteria were successfully isolated form hot
spring water sample and tested for extracellular phytase producing.
After 5 passages of the screening on the PSM media, 4 isolates were
found stable in producing phytase enzyme. The 16s RDNA
sequencing for identification of bacteria using molecular technique
revealed that all isolates those positive in phytase producing are
belong to Geobacillus spp. And Anoxybacillus spp. Anoxybacillus
rupiensis UniSZA-7 were identified for their carbon source utilization
using Phenotype Microarray Plate of Biolog and found they utilize
several kind of carbon source provided.
Abstract: Performance of any continuous speech recognition system is highly dependent on performance of the acoustic models. Generally, development of the robust spoken language technology relies on the availability of large amounts of data. Common way to cope with little data for training each state of Markov models is treebased state tying. This tying method applies contextual questions to tie states. Manual procedure for question generation suffers from human errors and is time consuming. Various automatically generated questions are used to construct decision tree. There are three approaches to generate questions to construct HMMs based on decision tree. One approach is based on misrecognized phonemes, another approach basically uses feature table and the other is based on state distributions corresponding to context-independent subword units. In this paper, all these methods of automatic question generation are applied to the decision tree on FARSDAT corpus in Persian language and their results are compared with those of manually generated questions. The results show that automatically generated questions yield much better results and can replace manually generated questions in Persian language.
Abstract: As a popular rank-reduced vector space approach,
Latent Semantic Indexing (LSI) has been used in information
retrieval and other applications. In this paper, an LSI-based content
vector model for text classification is presented, which constructs
multiple augmented category LSI spaces and classifies text by their
content. The model integrates the class discriminative information
from the training data and is equipped with several pertinent feature
selection and text classification algorithms. The proposed classifier
has been applied to email classification and its experiments on a
benchmark spam testing corpus (PU1) have shown that the approach
represents a competitive alternative to other email classifiers based
on the well-known SVM and naïve Bayes algorithms.