Abstract: The tree structured approach of non-uniform filterbank
(NUFB) is normally used in perfect reconstruction (PR). The PR is
not always feasible due to certain limitations, i.e, constraints in
selecting design parameters, design complexity and some times
output is severely affected by aliasing error if necessary and
sufficient conditions of PR is not satisfied perfectly. Therefore, there
has been generalized interest of researchers to go for near perfect
reconstruction (NPR). In this proposed work, an optimized tree
structure technique is used for the design of NPR non-uniform
filterbank. Window functions of Blackman family are used to design
the prototype FIR filter. A single variable linear optimization is used
to minimize the amplitude distortion. The main feature of the
proposed design is its simplicity with linear phase property.
Abstract: Ringing effect is one of the most annoying visual
artifacts in digital video. It is a significant factor of subjective quality
deterioration. However, there is a widely-accepted misunderstanding
of its cause. In this paper, we propose a reasonable interpretation of the
cause of ringing effect. Based on the interpretation, we suggest further
two methods to reduce ringing effect in DCT-based video coding. The
methods adaptively adjust quantizers according to video features. Our
experiments proved that the methods could efficiently improve
subjective quality with acceptable additional computing costs.
Abstract: Face Recognition is a field of multidimensional
applications. A lot of work has been done, extensively on the most of
details related to face recognition. This idea of face recognition using
PCA is one of them. In this paper the PCA features for Feature
extraction are used and matching is done for the face under
consideration with the test image using Eigen face coefficients. The
crux of the work lies in optimizing Euclidean distance and paving the
way to test the same algorithm using Matlab which is an efficient tool
having powerful user interface along with simplicity in representing
complex images.
Abstract: This paper demonstrates the feasibility of replacing
the metal coil spring with the composite coil spring. Three different
types of springs were made using glass fiber, carbon fiber and
combination of glass fiber and carbon fiber. The objective of the
study is to reduce the weight of the spring. According to the
experimental results the spring rate of the carbon fiber spring is
34% more than the glass fiber spring and 45% more than the glass
fiber/carbon fiber spring. The weight of the carbon fiber spring is
18% less than the glass fiber spring, 15% less than the Glass
fiber/carbon fiber spring and 80% less than the steel spring.
Abstract: In this paper, the strength of a stabilizer is determined when the static and fatigue multiaxial loading are applied. Stabilizer is a part of suspension system in the heavy truck for stabilizing the cabin against the vibration of the road which composes of a thin-walled tube joined to a forge component by fillet weld. The component is loaded by non proportional random sequence of torsion and bending. Residual stress of welding process is considered here for static loading. This static loading with road irregularities are applied in this study as fatigue case that can affected in the fillet welded area of this part. The stresses in the welded structure are calculated using FEA. In addition, the fatigue with multi axial loading in the fillet weld is also investigated and the critical zone of the stabilizer is specified and presented by graphs. Residual stresses that have been resulted by the thermal forces are considered in FEA. Force increasing is the element of finding the critical point of the component.
Abstract: In this paper, the processing of sonar signals has been
carried out using Minimal Resource Allocation Network (MRAN)
and a Probabilistic Neural Network (PNN) in differentiation of
commonly encountered features in indoor environments. The
stability-plasticity behaviors of both networks have been
investigated. The experimental result shows that MRAN possesses
lower network complexity but experiences higher plasticity than
PNN. An enhanced version called parallel MRAN (pMRAN) is
proposed to solve this problem and is proven to be stable in
prediction and also outperformed the original MRAN.
Abstract: Unlike general-purpose processors, digital signal
processors (DSP processors) are strongly application-dependent. To
meet the needs for diverse applications, a wide variety of DSP
processors based on different architectures ranging from the
traditional to VLIW have been introduced to the market over the
years. The functionality, performance, and cost of these processors
vary over a wide range. In order to select a processor that meets the
design criteria for an application, processor performance is usually
the major concern for digital signal processing (DSP) application
developers. Performance data are also essential for the designers of
DSP processors to improve their design. Consequently, several DSP
performance benchmarks have been proposed over the past decade or
so. However, none of these benchmarks seem to have included recent
new DSP applications.
In this paper, we use a new benchmark that we recently developed
to compare the performance of popular DSP processors from Texas
Instruments and StarCore. The new benchmark is based on the
Selectable Mode Vocoder (SMV), a speech-coding program from the
recent third generation (3G) wireless voice applications. All
benchmark kernels are compiled by the compilers of the respective
DSP processors and run on their simulators. Weighted arithmetic
mean of clock cycles and arithmetic mean of code size are used to
compare the performance of five DSP processors.
In addition, we studied how the performance of a processor is
affected by code structure, features of processor architecture and
optimization of compiler. The extensive experimental data gathered,
analyzed, and presented in this paper should be helpful for DSP
processor and compiler designers to meet their specific design goals.
Abstract: Geographic Profiling has successfully assisted investigations for serial crimes. Considering the multi-cluster feature of serial criminal spots, we propose a Multi-point Centrography model as a natural extension of Single-point Centrography for geographic profiling. K-means clustering is first performed on the data samples and then Single-point Centrography is adopted to derive a probability distribution on each cluster. Finally, a weighted combinations of each distribution is formed to make next-crime spot prediction. Experimental study on real cases demonstrates the effectiveness of our proposed model.
Abstract: Eye localization is necessary for face recognition and
related application areas. Most of eye localization algorithms reported
so far still need to be improved about precision and computational
time for successful applications. In this paper, we propose an eye
location method based on multi-scale Gabor feature vectors, which is
more robust with respect to initial points. The eye localization based
on Gabor feature vectors first needs to constructs an Eye Model Bunch
for each eye (left or right eye) which consists of n Gabor jets and
average eye coordinates of each eyes obtained from n model face
images, and then tries to localize eyes in an incoming face image by
utilizing the fact that the true eye coordinates is most likely to be very
close to the position where the Gabor jet will have the best Gabor jet
similarity matching with a Gabor jet in the Eye Model Bunch. Similar
ideas have been already proposed in such as EBGM (Elastic Bunch
Graph Matching). However, the method used in EBGM is known to be
not robust with respect to initial values and may need extensive search
range for achieving the required performance, but extensive search
ranges will cause much more computational burden. In this paper, we
propose a multi-scale approach with a little increased computational
burden where one first tries to localize eyes based on Gabor feature
vectors in a coarse face image obtained from down sampling of the
original face image, and then localize eyes based on Gabor feature
vectors in the original resolution face image by using the eye
coordinates localized in the coarse scaled image as initial points.
Several experiments and comparisons with other eye localization
methods reported in the other papers show the efficiency of our
proposed method.
Abstract: Identifying and classifying intersections according to
severity is very important for implementation of safety related
counter measures and effective models are needed to compare and
assess the severity. Highway safety organizations have considered
intersection safety among their priorities. In spite of significant
advances in highways safety, the large numbers of crashes with high
severities still occur in the highways. Investigation of influential
factors on crashes enables engineers to carry out calculations in order
to reduce crash severity. Previous studies lacked a model capable of
simultaneous illustration of the influence of human factors, road,
vehicle, weather conditions and traffic features including traffic
volume and flow speed on the crash severity. Thus, this paper is
aimed at developing the models to illustrate the simultaneous
influence of these variables on the crash severity in urban highways.
The models represented in this study have been developed using
binary Logit Models. SPSS software has been used to calibrate the
models. It must be mentioned that backward regression method in
SPSS was used to identify the significant variables in the model.
Consider to obtained results it can be concluded that the main
factor in increasing of crash severity in urban highways are driver
age, movement with reverse gear, technical defect of the vehicle,
vehicle collision with motorcycle and bicycle, bridge, frontal impact
collisions, frontal-lateral collisions and multi-vehicle crashes in
urban highways which always increase the crash severity in urban
highways.
Abstract: This paper presents a new stable robust adaptive controller and observer design for a class of nonlinear systems that contain i. Coupling of unmeasured states and unknown parameters ii. Unknown dead zone at the system actuator. The system is firstly cast into a modified form in which the observer and parameter estimation become feasible. Then a stable robust adaptive controller, state observer, parameter update laws are derived that would provide global adaptive system stability and desirable performance. To validate the approach, simulation was performed to a single-link mechanical system with a dynamic friction model and unknown dead zone exists at the system actuation. Then a comparison is presented with the results when there is no dead zone at the system actuation.
Abstract: Direct and indirect somatic embryogenesis (SE) from
petiole and leaf explants of Scaevola aemula R. Br. cv. 'Purple
Fanfare' was achieved. High frequency of somatic embryos was
obtained directly from petiole and leaf explants using an inductive
plant growth regulator signal thidiazuron (TDZ). Petiole explants
were more responsive to SE than leaves. Plants derived from somatic
embryos of petiole explants germinated more readily into plants. SE
occurred more efficiently in half-strength Murashige and Skoog
(MS) medium than in full-strength MS medium. Non-embryogenic
callus induced by 2, 4-dichlorophenoxyacetic acid was used to
investigate the feasibility of obtaining SE with TDZ as a secondary
inductive plant growth regulator (PGR) signal. Non-embryogenic
callus of S. aemula was able to convert into an “embryogenic
competent mode" with PGR signal. Protocol developed for induction
of direct and indirect somatic embryogenesis in S. aemula can
improve the large scale propagation system of the plant in future.
Abstract: One of the most important problems to solve is eye
location for a driver fatigue monitoring system. This paper presents an
efficient method to achieve fast and accurate eye location in grey level
images obtained in the real-word driving conditions. The structure of
eye region is used as a robust cue to find possible eye pairs. Candidates
of eye pair at different scales are selected by finding regions which
roughly match with the binary eye pair template. To obtain real one,
all the eye pair candidates are then verified by using support vector
machines. Finally, eyes are precisely located by using binary vertical
projection and eye classifier in eye pair images. The proposed method
is robust to deal with illumination changes, moderate rotations, glasses
wearing and different eye states. Experimental results demonstrate its
effectiveness.
Abstract: In this paper, a delayed predator-prey system with Hassell-Varley-Holling type functional response is studied. A sufficient criterion for the permanence of the system is presented, and further some sufficient conditions for the global attractivity and exponential stability of the system are established. And an example is to show the feasibility of the results by simulation.
Abstract: Aluminum alloy sheets have several advantages such
as the lightweight, high-specific strength and recycling efficiency.
Therefore, aluminum alloy sheets in sheet forming have been used in various areas as automotive components and so forth. During the
process of sheet forming, wrinkling which is caused by compression stress might occur and the formability of sheets was affected by
occurrence of wrinkling. A few studies of uniaxial compressive test by
using square tubes, pipes and sheets were carried out to clarify the each wrinkling behavior. However, on uniaxial compressive test,
deformation behavior of the sheets hasn-t be cleared. Then, it is necessary to clarify the relationship between the buckling behavior
and the forming conditions. In this study, the effect of dimension of the sheet in the buckling behavior on compression test of aluminum alloy sheet was cleared by experiment and FEA. As the results, the buckling
deformation was classified by three modes in terms of the distribution of equivalent plastic strain.
Abstract: This study is aimed to investigate feasibility of the
aerobic biological process to treat oily wastewater from palm oil food
industry. Effect of aeration and sludge concentrations are studied.
Raw sludge and raw wastewater was mixed and acclimatized for five
days in a stirred tank reactor. The aeration rate (no aeration, low;
1.5L/min and high rate; 2L/min) and sludge concentration (3675,
7350, and 11025mg/L of VSS) were varied. Responses of process
were pH, COD, oil and grease, VSS, and PHB content. It was found
that the treatment can remove 85.1 to 97.1 % of COD and remove
12.9 to 54.8% of oil & grease. The PHB yield was found to be within
0.15% to 2.4% as PHB/VSS ratio and 0.01% to 0.12% as PHB/COD
removed. The higher aeration results a high COD removal and oil &
grease removal, while experiment without aeration gives better PHB
yield. Higher sludge concentrations (11025mg/L VSS) give higher
removal of oil & grease while moderate sludge concentration
(7350mg/L VSS) give better result in COD removal. Higher PHB
yield is obtained in low sludge concentration (3675mg/L).
Abstract: Voice over Internet Protocol (VoIP) application or commonly known as softphone has been developing an increasingly large market in today-s telecommunication world and the trend is expected to continue with the enhancement of additional features. This includes leveraging on the existing presence services, location and contextual information to enable more ubiquitous and seamless communications. In this paper, we discuss the concept of seamless session transfer for real-time application such as VoIP and IPTV, and our prototype implementation of such concept on a selected open source VoIP application. The first part of this paper is about conducting performance evaluation and assessments across some commonly found open source VoIP applications that are Ekiga, Kphone, Linphone and Twinkle so as to identify one of them for implementing our design of seamless session transfer. Subjective testing has been carried out to evaluate the audio performance on these VoIP applications and rank them according to their Mean Opinion Score (MOS) results. The second part of this paper is to discuss on the performance evaluations of our prototype implementation of session transfer using Linphone.
Abstract: New Growth Theory helps us make sense of the
ongoing shift from a resource-based economy to a knowledge-based
economy. It underscores the point that the economic processes which
create and diffuse new knowledge are critical to shaping the growth
of nations, communities and individual firms. In all too many
contributions to New (Endogenous) Growth Theory – though not in
all – central reference is made to 'a stock of knowledge', a 'stock of
ideas', etc., this variable featuring centre-stage in the analysis. Yet it
is immediately apparent that this is far from being a crystal clear
concept. The difficulty and uncertainty of being able to capture the
value associated with knowledge is a real problem. The intent of this
paper is introducing new thinking and theorizing about the
knowledge and its measurability in new growth theory. Moreover the
study aims to synthesize various strain of the literature with a
practical bearing on knowledge concept. By contribution of
institution framework which is found within NGT, we can indirectly
measure the knowledge concept. Institutions matter because they
shape the environment for production and employment of new
knowledge
Abstract: Amount of dissolve oxygen in a river has a great direct affect on aquatic macroinvertebrates and this would influence on the region ecosystem indirectly. In this paper it is tried to predict dissolved oxygen in rivers by employing an easy Fuzzy Logic Modeling, Wang Mendel method. This model just uses previous records to estimate upcoming values. For this purpose daily and hourly records of eight stations in Au Sable watershed in Michigan, United States are employed for 12 years and 50 days period respectively. Calculations indicate that for long period prediction it is better to increase input intervals. But for filling missed data it is advisable to decrease the interval. Increasing partitioning of input and output features influence a little on accuracy but make the model too time consuming. Increment in number of input data also act like number of partitioning. Large amount of train data does not modify accuracy essentially, so, an optimum training length should be selected.
Abstract: The structure of retinal vessels is a prominent feature,
that reveals information on the state of disease that are reflected in
the form of measurable abnormalities in thickness and colour.
Vascular structures of retina, for implementation of clinical diabetic
retinopathy decision making system is presented in this paper.
Retinal Vascular structure is with thin blood vessel, whose accuracy
is highly dependent upon the vessel segmentation. In this paper the
blood vessel thickness is automatically detected using preprocessing
techniques and vessel segmentation algorithm. First the capture
image is binarized to get the blood vessel structure clearly, then it is
skeletonised to get the overall structure of all the terminal and
branching nodes of the blood vessels. By identifying the terminal
node and the branching points automatically, the main and branching
blood vessel thickness is estimated. Results are presented and
compared with those provided by clinical classification on 50 vessels
collected from Bejan Singh Eye hospital..