Abstract: Mammals are known to use Interaural Intensity Difference (IID) to determine azimuthal position of high frequency sounds. In the Lateral Superior Olive (LSO) neurons have firing behaviours which vary systematicaly with IID. Those neurons receive excitatory inputs from the ipsilateral ear and inhibitory inputs from the contralateral one. The IID sensitivity of a LSO neuron is thought to be due to delay differences between both ears, delays due to different synaptic delays and to intensity-dependent delays. In this paper we model the auditory pathway until the LSO. Inputs to LSO neurons are at first numerous and differ in their relative delays. Spike Timing-Dependent Plasticity is then used to prune those connections. We compare the pruned neuron responses with physiological data and analyse the relationship between IID-s of teacher stimuli and IID sensitivities of trained LSO neurons.
Abstract: A new generation product made from bamboo strips,
known as laminated bamboo, has gained importance. The objective
of this research was to experiment the effect of three factors on the
mechanical property of laminated bamboo. The interested factors for
experimental design were (A) four bamboo species, namely Bambusa
blumeana Schultes (Pai See Suk), Dendrocalamus asper Backer (Pai
Tong), Dendrocalamus hamiltonii Nees (Pai Hok) and
Dendrocalamus sericeus Munro (Pai Sang Mon), (B) two types of
glue adhesive, polyvinyl acetate emulsion (PVAC) fortified with
urea-formaldehyde (UF) and urea-formaldehyde (UF) to make
parallel-oriented bamboo strips laminates and (C) glue weight per
strip area, 150 g/m2 and 190 g/m2. Experimental results showed that
Dendrocalamus asper Backer (Pai Tong) and Dendrocalamus
sericeus Munro (Pai Sang Mon) were best used for manufacturing
due to their highest MOR and MOE. The amount of glue weight 150
g/m2 yielded higher MOR and MOE than the amount of glue weight
190 g/m2. At the conclusion, the laminated bamboo manufacturers
can benefit from this research in order to select right materials
according to strength, cost and accessibility.
Abstract: The excellent suitability of the externally excited synchronous
machine (EESM) in automotive traction drive applications
is justified by its high efficiency over the whole operation range and
the high availability of materials. Usually, maximum efficiency is
obtained by modelling each single loss and minimizing the sum of all
losses. As a result, the quality of the optimization highly depends on
the precision of the model. Moreover, it requires accurate knowledge
of the saturation dependent machine inductances. Therefore, the
present contribution proposes a method to minimize the overall losses
of a salient pole EESM and its inverter in steady state operation based
on measurement data only. Since this method does not require any
manufacturer data, it is well suited for an automated measurement
data evaluation and inverter parametrization. The field oriented control
(FOC) of an EESM provides three current components resp. three
degrees of freedom (DOF). An analytic minimization of the copper
losses in the stator and the rotor (assuming constant inductances) is
performed and serves as a first approximation of how to choose the
optimal current reference values. After a numeric offline minimization
of the overall losses based on measurement data the results are
compared to a control strategy that satisfies cos (ϕ) = 1.
Abstract: Stocking density is considered one of the important
factors affecting fish growth. But, information related to impact of
stocking density on growth performance of monosex tilapia population
under the ecological conditions of Gangetic plains in West Bengal,
India is limited. The aim of our study was to compare the growth
potential of monosex tilapia at various stocking densities and to
determine an ideal stocking density for culture of all-male monosex
fish. The males were isolated by examination of genital papilla region
and were stocked separately in 0.01 ha earthen ponds at different
stocking densities (5000, 10000, 15000, 20000, 25000 and 30000
fingerlings/ha). It was found that the highest weight, length, daily
weight gain, growth rate and protein content were observed for the
20000 fish/ha density class. Thus, culture of monosex tilapia at a
density of 20000 fish/ha can be considered ideal for augmented
production of the fish under Indian context.
Abstract: This paper proposes the stochastic tabu search (STS)
for improving the measurement scheme for power system state
estimation. If the original measured scheme is not observable, the
additional measurements with minimum number of measurements are
added into the system by STS so that there is no critical measurement
pair. The random bit flipping and bit exchanging perturbations are
used for generating the neighborhood solutions in STS. The Pδ
observable concept is used to determine the network observability.
Test results of 10 bus, IEEE 14 and 30 bus systems are shown that
STS can improve the original measured scheme to be observable
without critical measurement pair. Moreover, the results of STS are
superior to deterministic tabu search (DTS) in terms of the best
solution hit.
Abstract: The process of laser absorption in the skin during
laser irradiation was a critical point in medical application
treatments. Delivery the correct amount of laser light is a critical
element in photodynamic therapy (PDT). More amounts of laser
light able to affect tissues in the skin and small amount not able to
enhance PDT procedure in skin. The knowledge of the skin tone
laser dependent distribution of 635 nm radiation and its penetration
depth in skin is a very important precondition for the investigation of
advantage laser induced effect in (PDT) in epidermis diseases
(psoriasis). The aim of this work was to estimate an optimum effect
of diode laser (635 nm) on the treatment of epidermis diseases in
different color skin. Furthermore, it is to improve safety of laser in
PDT in epidermis diseases treatment. Advanced system analytical
program (ASAP) which is a new approach in investigating the PDT,
dependent on optical properties of different skin color was used in
present work. A two layered Realistic Skin Model (RSM); stratum
corneum and epidermal with red laser (635 nm, 10 mW) were used
for irradiative transfer to study fluence and absorbance in different
penetration for various human skin colors. Several skin tones very
fair, fair, light, medium and dark are used to irradiative transfer. This
investigation involved the principles of laser tissue interaction when
the skin optically injected by a red laser diode. The results
demonstrated that the power characteristic of a laser diode (635 nm)
can affect the treatment of epidermal disease in various color skins.
Power absorption of the various human skins were recorded and
analyzed in order to find the influence of the melanin in PDT
treatment in epidermal disease. A two layered RSM show that the
change in penetration depth in epidermal layer of the color skin has a
larger effect on the distribution of absorbed laser in the skin; this is
due to the variation of the melanin concentration for each color.
Abstract: To extract the important physiological factors related to
diabetes from an oral glucose tolerance test (OGTT) by mathematical
modeling, highly informative but convenient protocols are required.
Current models require a large number of samples and extended
period of testing, which is not practical for daily use. The purpose
of this study is to make model assessments possible even from a
reduced number of samples taken over a relatively short period.
For this purpose, test values were extrapolated using a support
vector machine. A good correlation was found between reference and
extrapolated values in evaluated 741 OGTTs. This result indicates
that a reduction in the number of clinical test is possible through a
computational approach.
Abstract: Array signal processing involves signal enumeration and source localization. Array signal processing is centered on the ability to fuse temporal and spatial information captured via sampling signals emitted from a number of sources at the sensors of an array in order to carry out a specific estimation task: source characteristics (mainly localization of the sources) and/or array characteristics (mainly array geometry) estimation. Array signal processing is a part of signal processing that uses sensors organized in patterns or arrays, to detect signals and to determine information about them. Beamforming is a general signal processing technique used to control the directionality of the reception or transmission of a signal. Using Beamforming we can direct the majority of signal energy we receive from a group of array. Multiple signal classification (MUSIC) is a highly popular eigenstructure-based estimation method of direction of arrival (DOA) with high resolution. This Paper enumerates the effect of missing sensors in DOA estimation. The accuracy of the MUSIC-based DOA estimation is degraded significantly both by the effects of the missing sensors among the receiving array elements and the unequal channel gain and phase errors of the receiver.
Abstract: Distance visualization of large datasets often takes the direction of remote viewing and zooming techniques of stored static images. However, the continuous increase in the size of datasets and visualization operation causes insufficient performance with traditional desktop computers. Additionally, the visualization techniques such as Isosurface depend on the available resources of the running machine and the size of datasets. Moreover, the continuous demand for powerful computing powers and continuous increase in the size of datasets results an urgent need for a grid computing infrastructure. However, some issues arise in current grid such as resources availability at the client machines which are not sufficient enough to process large datasets. On top of that, different output devices and different network bandwidth between the visualization pipeline components often result output suitable for one machine and not suitable for another. In this paper we investigate how the grid services could be used to support remote visualization of large datasets and to break the constraint of physical co-location of the resources by applying the grid computing technologies. We show our grid enabled architecture to visualize large medical datasets (circa 5 million polygons) for remote interactive visualization on modest resources clients.
Abstract: This paper introduces a technique of distortion
estimation in image watermarking using Genetic Programming (GP).
The distortion is estimated by considering the problem of obtaining a
distorted watermarked signal from the original watermarked signal as
a function regression problem. This function regression problem is
solved using GP, where the original watermarked signal is
considered as an independent variable. GP-based distortion
estimation scheme is checked for Gaussian attack and Jpeg
compression attack. We have used Gaussian attacks of different
strengths by changing the standard deviation. JPEG compression
attack is also varied by adding various distortions. Experimental
results demonstrate that the proposed technique is able to detect the
watermark even in the case of strong distortions and is more robust
against attacks.
Abstract: Many-core GPUs provide high computing ability and
substantial bandwidth; however, optimizing irregular applications
like SpMV on GPUs becomes a difficult but meaningful task. In this
paper, we propose a novel method to improve the performance of
SpMV on GPUs. A new storage format called HYB-R is proposed to
exploit GPU architecture more efficiently. The COO portion of the
matrix is partitioned recursively into a ELL portion and a COO
portion in the process of creating HYB-R format to ensure that there
are as many non-zeros as possible in ELL format. The method of
partitioning the matrix is an important problem for HYB-R kernel, so
we also try to tune the parameters to partition the matrix for higher
performance. Experimental results show that our method can get
better performance than the fastest kernel (HYB) in NVIDIA-s
SpMV library with as high as 17% speedup.
Abstract: EPA (Ethernet for Plant Automation) resolves the nondeterministic problem of standard Ethernet and accomplishes real-time communication by means of micro-segment topology and deterministic scheduling mechanism. This paper studies the real-time performance of EPA periodic data transmission from theoretical and experimental perspective. By analyzing information transmission characteristics and EPA deterministic scheduling mechanism, 5 indicators including delivery time, time synchronization accuracy, data-sending time offset accuracy, utilization percentage of configured timeslice and non-RTE bandwidth that can be used to specify the real-time performance of EPA periodic data transmission are presented and investigated. On this basis, the test principles and test methods of the indicators are respectively studied and some formulas for real-time performance of EPA system are derived. Furthermore, an experiment platform is developed to test the indicators of EPA periodic data transmission in a micro-segment. According to the analysis and the experiment, the methods to improve the real-time performance of EPA periodic data transmission including optimizing network structure, studying self-adaptive adjustment method of timeslice and providing data-sending time offset accuracy for configuration are proposed.
Abstract: Flood zoning studies have become more efficient in
recent years because of the availability of advanced computational
facilities and use of Geographic Information Systems (GIS). In the
present study, flood inundated areas were mapped using GIS for the
Dikrong river basin of Arunachal Pradesh, India, corresponding to
different return periods (2, 5, 25, 50, and 100 years). Further, the developed inundation maps corresponding to 25, 50, and 100 year return period floods were compared to corresponding maps
developed by conventional methods as reported in the Brahmaputra Board Master Plan for Dikrong basin. It was found that, the average
deviation of modelled flood inundation areas from reported map
inundation areas is below 5% (4.52%). Therefore, it can be said that
the modelled flood inundation areas matched satisfactorily with
reported map inundation areas. Hence, GIS techniques were proved to be successful in extracting the flood inundation extent in a time and cost effective manner for the remotely located hilly basin of Dikrong, where conducting conventional surveys is very difficult.
Abstract: The article presents a new method for detection of
artificial objects and materials from images of the environmental
(non-urban) terrain. Our approach uses the hue and saturation (or Cb
and Cr) components of the image as the input to the segmentation
module that uses the mean shift method. The clusters obtained as the
output of this stage have been processed by the decision-making
module in order to find the regions of the image with the significant
possibility of representing human. Although this method will detect
various non-natural objects, it is primarily intended and optimized for
detection of humans; i.e. for search and rescue purposes in non-urban
terrain where, in normal circumstances, non-natural objects shouldn-t
be present. Real world images are used for the evaluation of the
method.
Abstract: Autism spectrum disorder is characterized by
abnormalities in social communication, language abilities and
repetitive behaviors. The present study focused on some grammatical
deficits in autistic children. We evaluated the impairment of correct
use of different Persian verb tenses in autistic children-s speech. Two
standardized Language Test were administered then gathered data
were analyzed. The main result of this study was significant
difference between the mean scores of correct responses to present
tense in comparison with past tense in Persian language. This study
demonstrated that tense is severely impaired in autistic children-s
speech. Our findings indicated those autistic children-s production of
simple present/ past tense opposition to be better than production of
future and past periphrastic forms (past perfect, present perfect, past
progressive).
Abstract: This study introduces a new method for detecting,
sorting, and localizing spikes from multiunit EEG recordings. The
method combines the wavelet transform, which localizes distinctive
spike features, with Super-Paramagnetic Clustering (SPC) algorithm,
which allows automatic classification of the data without assumptions
such as low variance or Gaussian distributions. Moreover, the method
is capable of setting amplitude thresholds for spike detection. The
method makes use of several real EEG data sets, and accordingly the
spikes are detected, clustered and their times were detected.
Abstract: Performance appraisal of employee is important in
managing the human resource of an organization. With the change
towards knowledge-based capitalism, maintaining talented
knowledge workers is critical. However, management classification
of “outstanding", “poor" and “average" performance may not be an
easy decision. Besides that, superior might also tend to judge the
work performance of their subordinates informally and arbitrarily
especially without the existence of a system of appraisal. In this
paper, we propose a performance appraisal system using
multifactorial evaluation model in dealing with appraisal grades
which are often express vaguely in linguistic terms. The proposed
model is for evaluating staff performance based on specific
performance appraisal criteria. The project was collaboration with
one of the Information and Communication Technology company in
Malaysia with reference to its performance appraisal process.
Abstract: Recently, many web services to provide information for public transport are developed and released. They are optimized for mobile devices such a smartphone. We are also developing better path planning system for route buses and trains called “Bus-Net"[1]. However these systems only provide paths and related information before the user start moving. So we propose a context aware navigation to change the way to support public transport users. If we go to somewhere using many kinds of public transport, we have to know how to use them. In addition, public transport is dynamic system, and these have different characteristic by type. So we need information at real-time. Therefore we suggest the system that can support on user-s state. It has a variety of ways to help public transport users by each state, like turn-by-turn navigation. Context aware navigation will be able to reduce anxiety for using public transport.
Abstract: The right information at the right time influences the
enterprise and technical success. Sharing knowledge among members
of a big organization may be a complex activity. And as long as the
knowledge is not shared, can not be exploited by the organization.
There are some mechanisms which can originate knowledge sharing.
It is intended, in this paper, to trigger these mechanisms by using
semantic nets. Moreover, the intersection and overlapping of terms
and sub-terms, as well as their relationships will be described through
the mereology science for the whole knowledge sharing system. It is
proposed a knowledge system to supply to operators with the right
information about a specific process and possible risks, e.g. at the
assembly process, at the right time in an automated manufacturing
environment, such as at the automotive industry.
Abstract: The goal of data mining algorithms is to discover
useful information embedded in large databases. One of the most
important data mining problems is discovery of frequently occurring
patterns in sequential data. In a multidimensional sequence each
event depends on more than one dimension. The search space is quite
large and the serial algorithms are not scalable for very large
datasets. To address this, it is necessary to study scalable parallel
implementations of sequence mining algorithms.
In this paper, we present a model for multidimensional sequence
and describe a parallel algorithm based on data parallelism.
Simulation experiments show good load balancing and scalable and
acceptable speedup over different processors and problem sizes and
demonstrate that our approach can works efficiently in a real parallel
computing environment.