Abstract: In this paper, fully developed flow and heat transfer of
viscoelastic materials in curved ducts with square cross section under
constant heat flux have been investigated. Here, staggered mesh is
used as computational grids and flow and heat transfer parameters
have been allocated in this mesh with marker and cell method.
Numerical solution of governing equations has being performed with
FTCS finite difference method. Furthermore, Criminale-Eriksen-
Filbey (CEF) constitutive equation has being used as viscoelastic
model. CEF constitutive equation is a suitable model for studying
steady shear flow of viscoelastic materials which is able to model
both effects of the first and second normal stress differences. Here, it
is shown that the first and second normal stresses differences have
noticeable and inverse effect on secondary flows intensity and mean
Nusselt number which is the main novelty of current research.
Abstract: Potatoes are a good source of carotenoids, which are lipophilic compounds synthesized in plastids from isoprenoids. The aim of this research was to determine the content of carotenoids in relationship with the colour of organically and conventionally cultivated potato genotypes before and after period of storage. In cooperation with the State Priekuli Plant Breeding Institute (Latvia), six potato genotypes were studied: 'Agrie dzeltenie', 'Prelma', 'Imanta', 'S-03135-10', 'S-99108-8' and 'S-01063-5'. All the genotypes were cultivated under three different conditions: organically and conventionally (two conditions). The content of carotenoids was determined by using spectrophotometer and the colour – L*a*b* system. The results of current research show that after the period of storage, carotenoid amount has increased and in conventionally cultivated potatoes it varies from 228.514 to 552.434 μg 100 g-1 while in organically cultivated potato genotypes – from 45.485 to 662.699 μg 100 g-1 FW. Colour of potato flesh was changing during storage.
Abstract: Fuzzy C-means Clustering algorithm (FCM) is a
method that is frequently used in pattern recognition. It has the
advantage of giving good modeling results in many cases, although,
it is not capable of specifying the number of clusters by itself. In
FCM algorithm most researchers fix weighting exponent (m) to a
conventional value of 2 which might not be the appropriate for all
applications. Consequently, the main objective of this paper is to use
the subtractive clustering algorithm to provide the optimal number of
clusters needed by FCM algorithm by optimizing the parameters of
the subtractive clustering algorithm by an iterative search approach
and then to find an optimal weighting exponent (m) for the FCM
algorithm. In order to get an optimal number of clusters, the iterative
search approach is used to find the optimal single-output Sugenotype
Fuzzy Inference System (FIS) model by optimizing the
parameters of the subtractive clustering algorithm that give minimum
least square error between the actual data and the Sugeno fuzzy
model. Once the number of clusters is optimized, then two
approaches are proposed to optimize the weighting exponent (m) in
the FCM algorithm, namely, the iterative search approach and the
genetic algorithms. The above mentioned approach is tested on the
generated data from the original function and optimal fuzzy models
are obtained with minimum error between the real data and the
obtained fuzzy models.
Abstract: Wireless sensor networks have been used in wide
areas of application and become an attractive area for researchers in
recent years. Because of the limited energy storage capability of
sensor nodes, Energy consumption is one of the most challenging
aspects of these networks and different strategies and protocols deals
with this area. This paper presents general methods for designing low
power wireless sensor network. Different sources of energy
consumptions in these networks are discussed here and techniques for
alleviating the consumption of energy are presented.
Abstract: Artificial Immune System is applied as a Heuristic
Algorithm for decades. Nevertheless, many of these applications
took advantage of the benefit of this algorithm but seldom proposed
approaches for enhancing the efficiency. In this paper, a
Self-evolving Artificial Immune System is proposed via developing
the T and B cell in Immune System and built a self-evolving
mechanism for the complexities of different problems. In this
research, it focuses on enhancing the efficiency of Clonal selection
which is responsible for producing Affinities to resist the invading of
Antigens. T and B cell are the main mechanisms for Clonal
Selection to produce different combinations of Antibodies.
Therefore, the development of T and B cell will influence the
efficiency of Clonal Selection for searching better solution.
Furthermore, for better cooperation of the two cells, a co-evolutional
strategy is applied to coordinate for more effective productions of
Antibodies. This work finally adopts Flow-shop scheduling
instances in OR-library to validate the proposed algorithm.
Abstract: In the age of global communications, heterogeneous
networks are seen to be the best choice of strategy to ensure continuous and uninterruptible services. This will allow mobile
terminal to stay in connection even they are migrating into different segment coverage through the handoff process. With the increase of
teletraffic demands in mobile cellular system, hierarchical cellular systems have been adopted extensively for more efficient channel
utilization and better QoS (Quality of Service). This paper presents a
bidirectional call overflow scheme between two layers of microcells and macrocells, where handoffs are decided by the velocity of mobile
making the call. To ensure that handoff calls are given higher priorities, it is assumed that guard channels are assigned in both
macrocells and microcells. A hysteresis value introduced in mobile velocity is used to allow mobile roam in the same cell if its velocity
changes back within the set threshold values. By doing this the number of handoffs is reduced thereby reducing the processing overhead and enhancing the quality of service to the end user.
Abstract: This paper made an attempt to investigate the problem associated with enhancement of emulsions of light crude oil-water recovery in an oil field of Algerian Sahara. Measurements were taken through experiments using RheoStress (RS600). Factors such as shear rate, temperature and light oil concentration on the viscosity behavior were considered. Experimental measurements were performed in terms of shear stress–shear rate, yield stress and flow index on mixture of light crude oil–water. The rheological behavior of emulsion showed Non-Newtonian shear thinning behavior (Herschel-Bulkley). The experiments done in the laboratory showed the stability of some water in light crude oil emulsions form during consolidate oil recovery process. To break the emulsion using additives may involve higher cost and could be very expensive. Therefore, further research should be directed to find solution of these problems that have been encountered.
Abstract: Semisolid metal processing uses solid–liquid slurries
containing fine and globular solid particles uniformly distributed in a
liquid matrix, which can be handled as a solid and flow like a liquid.
In the recent years, many methods have been introduced for the
production of semisolid slurries since it is scientifically sound and
industrially viable with such preferred microstructures called
thixotropic microstructures as feedstock materials. One such process
that needs very low equipment investment and running costs is the
cooling slope. In this research by using a mechanical stirrer slurry
maker constructed by the authors, the effects of mechanical stirring
parameters such as: stirring time, stirring temperature and stirring
Speed on micro-structure and mechanical properties of A360
aluminum alloy in semi-solid forming, are investigated. It is
determined that mold temperature and holding time of part in
temperature of 580ºC have a great effect on micro-structure and
mechanical properties(stirring temperature of 585ºC, stirring time of
20 minutes and stirring speed of 425 RPM). By optimizing the
forming parameters, dendrite microstructure changes to globular and
mechanical properties improves. This is because of breaking and
globularzing dendrites of primary α-AL.
Abstract: Classifying biomedical literature is a difficult and
challenging task, especially when a large number of biomedical
articles should be organized into a hierarchical structure. In this paper,
we present an approach for classifying a collection of biomedical text
abstracts downloaded from Medline database with the help of
ontology alignment. To accomplish our goal, we construct two types
of hierarchies, the OHSUMED disease hierarchy and the Medline
abstract disease hierarchies from the OHSUMED dataset and the
Medline abstracts, respectively. Then, we enrich the OHSUMED
disease hierarchy before adapting it to ontology alignment process for
finding probable concepts or categories. Subsequently, we compute
the cosine similarity between the vector in probable concepts (in the
“enriched" OHSUMED disease hierarchy) and the vector in Medline
abstract disease hierarchies. Finally, we assign category to the new
Medline abstracts based on the similarity score. The results obtained
from the experiments show the performance of our proposed approach
for hierarchical classification is slightly better than the performance of
the multi-class flat classification.
Abstract: In an era of knowledge explosion, the growth of data
increases rapidly day by day. Since data storage is a limited resource,
how to reduce the data space in the process becomes a challenge issue.
Data compression provides a good solution which can lower the
required space. Data mining has many useful applications in recent
years because it can help users discover interesting knowledge in large
databases. However, existing compression algorithms are not
appropriate for data mining. In [1, 2], two different approaches were
proposed to compress databases and then perform the data mining
process. However, they all lack the ability to decompress the data to
their original state and improve the data mining performance. In this
research a new approach called Mining Merged Transactions with the
Quantification Table (M2TQT) was proposed to solve these problems.
M2TQT uses the relationship of transactions to merge related
transactions and builds a quantification table to prune the candidate
itemsets which are impossible to become frequent in order to improve
the performance of mining association rules. The experiments show
that M2TQT performs better than existing approaches.
Abstract: We introduce, a new interactive 3D simulation system of ocular motion and expressions suitable for: (1) character animation applications to game design, film production, HCI (Human Computer Interface), conversational animated agents, and virtual reality; (2) medical applications (ophthalmic neurological and muscular pathologies: research and education); and (3) real time simulation of unconscious cognitive and emotional responses (for use, e.g., in psychological research). The system is comprised of: (1) a physiologically accurate parameterized 3D model of the eyes, eyelids, and eyebrow regions; and (2) a prototype device for realtime control of eye motions and expressions, including unconsciously produced expressions, for application as in (1), (2), and (3) above. The 3D eye simulation system, created using state-of-the-art computer animation technology and 'optimized' for use with an interactive and web deliverable platform, is, to our knowledge, the most advanced/realistic available so far for applications to character animation and medical pedagogy.
Abstract: Today, building automation is advancing from simple
monitoring and control tasks of lightning and heating towards more
and more complex applications that require a dynamic perception
and interpretation of different scenes occurring in a building. Current
approaches cannot handle these newly upcoming demands. In this
article, a bionically inspired approach for multimodal, dynamic scene
perception and interpretation is presented, which is based on neuroscientific
and neuro-psychological research findings about the perceptual
system of the human brain. This approach bases on data from diverse
sensory modalities being processed in a so-called neuro-symbolic
network. With its parallel structure and with its basic elements being
information processing and storing units at the same time, a very
efficient method for scene perception is provided overcoming the
problems and bottlenecks of classical dynamic scene interpretation
systems.
Abstract: In this report, an OTA which is used in fully
differential pipelined ADC was described. Using gain-boost
architecture with difference-ended amplifier, this OTA achieve
high-gain and high-speed. Besides, the CMFB circuit is also used, and
some methods are concerned to improve the performance. Then, by
optimization the layout design, OTA-s mismatch was reduced. This
design was using TSMC 0.18um CMOS process and simulation both
schematic and layout in Cadence. The result of the simulation shows
that the OTA has a gain up to 80dB,a unity gain bandwidth of about
1.437GHz for a 2pF load, a slew rate is about 428V/μs, a output swing
is 0.2V~1.35V, with the power supply of 1.8V, the power
consumption is 88mW. This amplifier was used in a 10bit 150MHz
pipelined ADC.
Abstract: The objective of the research was to evaluate the
quality of milk pomade sweet – sherbet packed in different packaging
materials (Multibarrier 60, met.BOPET/PE, Aluthen), by several
packaging technologies – active and modified atmosphere (MAP)
(consisting of 100% CO2), and control – in air ambiance.
Experiments were carried out at the Faculty of Food Technology of
Latvia University of Agriculture. Samples were stored at the room
temperature +21±1 °C. The physiochemical properties – weight
losses, moisture, hardening, colour and changes in headspace
atmosphere concentration (CO2 and O2) of packs were analysed
before packaging and after 2, 4, 6, 8, 10 and 12 storage weeks.
Abstract: Abrasive waterjet is a novel machining process capable of processing wide range of hard-to-machine materials. This research addresses modeling and optimization of the process parameters for this machining technique. To model the process a set of experimental data has been used to evaluate the effects of various parameter settings in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. Depth of cut, as one of the most important output characteristics, has been evaluated based on different parameter settings. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. The pairwise effects of process parameters settings on process response outputs are also shown graphically. The proposed model is then embedded into a Simulated Annealing algorithm to optimize the process parameters. The optimization is carried out for any desired values of depth of cut. The objective is to determine proper levels of process parameters in order to obtain a certain level of depth of cut. Computational results demonstrate that the proposed solution procedure is quite effective in solving such multi-variable problems.
Abstract: This paper demonstrates a model of an e-Learning
system based on nowadays learning theory and distant education
practice. The relationships in the model are designed to be simple
and functional and do not necessarily represent any particular e-
Learning environments. It is meant to be a generic e-Learning
system model with implications for any distant education course
instructional design. It allows online instructors to move away from
the discrepancy between the courses and body of knowledge. The
interrelationships of four primary sectors that are at the e-Learning
system are presented in this paper. This integrated model includes
[1] pedagogy, [2] technology, [3] teaching, and [4] learning. There
are interactions within each of these sectors depicted by system loop
map.
Abstract: Image retrieval is a topic where scientific interest is currently high. The important steps associated with image retrieval system are the extraction of discriminative features and a feasible similarity metric for retrieving the database images that are similar in content with the search image. Gabor filtering is a widely adopted technique for feature extraction from the texture images. The recently proposed sparsity promoting l1-norm minimization technique finds the sparsest solution of an under-determined system of linear equations. In the present paper, the l1-norm minimization technique as a similarity metric is used in image retrieval. It is demonstrated through simulation results that the l1-norm minimization technique provides a promising alternative to existing similarity metrics. In particular, the cases where the l1-norm minimization technique works better than the Euclidean distance metric are singled out.
Abstract: In recent years, Radio Frequency Identification (RFID)
is followed with interest by many researches, especially for the
purpose of indoor positioning as the innate properties of RFID are
profitable for achieving it. A lot of algorithms or schemes are proposed
to be used in the RFID-based positioning system, but most of them are
lack of environmental consideration and it induces inaccuracy of
application. In this research, a lot of algorithms and schemes of RFID
indoor positioning are discussed to see whether effective or not on
application, and some rules are summarized for achieving accurate
positioning. On the other hand, a new term “Noise Factor" is involved
to describe the signal loss between the target and the obstacle. As a
result, experimental data can be obtained but not only simulation; and
the performance of the positioning system can be expressed
substantially.
Abstract: The research was conducted with three replications as
“Randomized Block Design” in Konya-Turkey ecological conditions.
In the study, 16 of promising safflower lines (A8, E1, F4, F6, G16,
H14, I1), and 1 cultivar (Dinçer) were evaluated in 2008-09 growing
season. Some of the yield components such as plant height (cm), first
branch height (cm), number of branches per plant, 1000 seed weight
(g), seed yield (kg ha-1), oil content (%), oil yield (kg ha-1) were
determined. Winter sowing showed higher values than spring sowing.
The highest values were taken from Dinçer for plant height (86.7
cm), E1 (37.5 cm) for first branch height, F6 for number of branch
(11.6 per plant), I1 for number of head (24.9 per plant), A8 for 1000
seed weight (51.75 g), Dinçer for seed yield (2927.1 kg ha-1), oil
content (28.79 %) and also for oil yield (87.44 kg ha-1) respectively.
Abstract: Road traffic accidents are a major cause of death worldwide. In an attempt to reduce accidents, some research efforts have focused on creating Advanced Driver Assistance Systems (ADAS) able to detect vehicle, driver and environmental conditions and to use this information to identify cues for potential accidents. This paper presents continued work on a novel Non-intrusive Intelligent Driver Assistance and Safety System (Ni-DASS) for assessing driver point of regard within vehicles. It uses an on-board CCD camera to observe the driver-s face. A template matching approach is used to compare the driver-s eye-gaze pattern with a set of eye-gesture templates of the driver looking at different focal points within the vehicle. The windscreen is divided into cells and comparison of the driver-s eye-gaze pattern with templates of a driver-s eyes looking at each cell is used to determine the driver-s point of regard on the windscreen. Results indicate that the proposed technique could be useful in situations where low resolution estimates of driver point of regard are adequate. For instance, To allow ADAS systems to alert the driver if he/she has positively failed to observe a hazard.