Abstract: The original idea for a feature film may come from a
writer, director or a producer. Director is the person responsible for
the creative aspects, both interpretive and technical, of a motion
picture production in a film. Director may be shot discussing his
project with his or her cowriters, members of production staff, and
producer, and director may be shown selecting locales or
constructing sets. All these activities provide, of course, ways of
externalizing director-s ideas about the film. A director sometimes
pushes both the film image and techniques of narration to new artistic
limits, but main responsibility of director is take the spectator to an
original opinion in his philosophical approach. Director tries to find
an artistic angle in every scene and change screenplay into an
effective story and sets his film on a spiritual and philosophical base.
Abstract: This paper presents an effective framework for Chinesesyntactic parsing, which includes two parts. The first one is a parsing framework, which is based on an improved bottom-up chart parsingalgorithm, and integrates the idea of the beam search strategy of N bestalgorithm and heuristic function of A* algorithm for pruning, then get multiple parsing trees. The second is a novel evaluation model, which integrates contextual and partial lexical information into traditional PCFG model and defines a new score function. Using this model, the tree with the highest score is found out as the best parsing tree. Finally,the contrasting experiment results are given. Keywords?syntactic parsing, PCFG, pruning, evaluation model.
Abstract: Octree compression techniques have been used
for several years for compressing large three dimensional data
sets into homogeneous regions. This compression technique
is ideally suited to datasets which have similar values in
clusters. Oil engineers represent reservoirs as a three dimensional
grid where hydrocarbons occur naturally in clusters. This
research looks at the efficiency of storing these grids using
octree compression techniques where grid cells are broken
into active and inactive regions. Initial experiments yielded
high compression ratios as only active leaf nodes and their
ancestor, header nodes are stored as a bitstream to file on
disk. Savings in computational time and memory were possible
at decompression, as only active leaf nodes are sent to the
graphics card eliminating the need of reconstructing the original
matrix. This results in a more compact vertex table, which can
be loaded into the graphics card quicker and generating shorter
refresh delay times.
Abstract: This paper discusses the theory behind the existence of an idealistic model for business network governance and uses a clarifying case-study, containing governance structures and processes within a business network framework. The case study from a German pharmaceutical industry company complements existing literature by providing a comprehensive explanation of the relations between supply chains and business networks, and also between supply chain management and business network governance. Supply chains and supply chain management are only one side of the interorganizational relationships and ensure short-term performance, while real-world governance structures are needed for ensuring the long-term existence of a supply chain. Within this context, a comprehensive model for business governance is presented. An interesting finding from the case study is that multiple business network governance systems co-exist within the evaluated supply chain.
Abstract: In this paper we present a soft timing phase estimation (STPE) method for wireless mobile receivers operating in low signal to noise ratios (SNRs). Discrete Polyphase Matched (DPM) filters, a Log-maximum a posterior probability (MAP) and/or a Soft-output Viterbi algorithm (SOVA) are combined to derive a new timing recovery (TR) scheme. We apply this scheme to wireless cellular communication system model that comprises of a raised cosine filter (RCF), a bit-interleaved turbo-coded multi-level modulation (BITMM) scheme and the channel is assumed to be memory-less. Furthermore, no clock signals are transmitted to the receiver contrary to the classical data aided (DA) models. This new model ensures that both the bandwidth and power of the communication system is conserved. However, the computational complexity of ideal turbo synchronization is increased by 50%. Several simulation tests on bit error rate (BER) and block error rate (BLER) versus low SNR reveal that the proposed iterative soft timing recovery (ISTR) scheme outperforms the conventional schemes.
Abstract: Next generation networks with the idea of convergence of service and control layer in existing networks (fixed, mobile and data) and with the intention of providing services in an integrated network, has opened new horizon for telecom operators. On the other hand, economic problems have caused operators to look for new source of income including consider new services, subscription of more users and their promotion in using morenetwork resources and easy participation of service providers or 3rd party operators in utilizing networks. With this requirement, an architecture based on next generation objectives for service layer is necessary. In this paper, a new architecture based on IMS model explains participation of 3rd party operators in creation and implementation of services on an integrated telecom network.
Abstract: This study created new graphical icons and operating
functions in a CAD/CAM software system by analyzing icons in some
of the popular systems, such as AutoCAD, AlphaCAM, Mastercam
and the 1st edition of LiteCAM. These software systems all focused on
geometric design and editing, thus how to transmit messages
intuitively from icon itself to users is an important function of
graphical icons. The primary purpose of this study is to design
innovative icons and commands for new software.
This study employed the TRIZ method, an innovative design
method, to generate new concepts systematically. Through literature
review, it then investigated and analyzed the relationship between
TRIZ and idea development. Contradiction Matrix and 40 Principles
were used to develop an assisting tool suitable for icon design in
software development. We first gathered icon samples from the
selected CAD/CAM systems. Then grouped these icons by
meaningful functions, and compared useful and harmful properties.
Finally, we developed new icons for new software systems in order to
avoid intellectual property problem.
Abstract: Ultra-low-power (ULP) circuits have received
widespread attention due to the rapid growth of biomedical
applications and Battery-less Electronics. Subthreshold region of
transistor operation is used in ULP circuits. Major research challenge
in the subthreshold operating region is to extract the ULP benefits
with minimal degradation in speed and robustness. Process, Voltage
and Temperature (PVT) variations significantly affect the
performance of subthreshold circuits. Designed performance
parameters of ULP circuits may vary largely due to temperature
variations. Hence, this paper investigates the effect of temperature
variation on device and circuit performance parameters at different
biasing voltages in the subthreshold region. Simulation results clearly
demonstrate that in deep subthreshold and near threshold voltage
regions, performance parameters are significantly affected whereas in
moderate subthreshold region, subthreshold circuits are more
immune to temperature variations. This establishes that moderate
subthreshold region is ideal for temperature immune circuits.
Abstract: Luneberg lens is a new generation of antennas that is
developed in the last few years and inserts itself strongly in
Microwaves, Communications and Telescopes area. The idea of this
research is to improve the radiation pattern by decreasing the side
lobes and increasing the main lobe. The new design is proposed to
work in the X-band. The simulated result and analysis are presented.
Abstract: In this paper, we present the video quality measure
estimation via a neural network. This latter predicts MOS (mean
opinion score) by providing height parameters extracted from
original and coded videos. The eight parameters that are used are: the
average of DFT differences, the standard deviation of DFT
differences, the average of DCT differences, the standard deviation
of DCT differences, the variance of energy of color, the luminance
Y, the chrominance U and the chrominance V. We chose Euclidean
Distance to make comparison between the calculated and estimated
output.
Abstract: In this paper, we present a system for content-based
retrieval of large database of classified satellite images, based on
user's relevance feedback (RF).Through our proposed system, we
divide each satellite image scene into small subimages, which stored
in the database. The modified radial basis functions neural network
has important role in clustering the subimages of database according
to the Euclidean distance between the query feature vector and the
other subimages feature vectors. The advantage of using RF
technique in such queries is demonstrated by analyzing the database
retrieval results.
Abstract: We study a long-range percolation model in the hierarchical
lattice ΩN of order N where probability of connection between
two nodes separated by distance k is of the form min{αβ−k, 1},
α ≥ 0 and β > 0. The parameter α is the percolation parameter,
while β describes the long-range nature of the model. The ΩN is
an example of so called ultrametric space, which has remarkable
qualitative difference between Euclidean-type lattices. In this paper,
we characterize the sizes of large clusters for this model along the
line of some prior work. The proof involves a stationary embedding
of ΩN into Z. The phase diagram of this long-range percolation is
well understood.
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 uses the radial basis function neural
network (RBFNN) for system identification of nonlinear systems.
Five nonlinear systems are used to examine the activity of RBFNN in
system modeling of nonlinear systems; the five nonlinear systems are
dual tank system, single tank system, DC motor system, and two
academic models. The feed forward method is considered in this
work for modelling the non-linear dynamic models, where the KMeans
clustering algorithm used in this paper to select the centers of
radial basis function network, because it is reliable, offers fast
convergence and can handle large data sets. The least mean square
method is used to adjust the weights to the output layer, and
Euclidean distance method used to measure the width of the Gaussian
function.
Abstract: Educating effective architect designers is an important
goal of architectural education. But what contributes to students-
performance, and to critical and creative thinking in architectural
design education? Besides teaching architecture students how to
understand logical arguments, eliminate the inadequate solutions and
focus on the correct ones, it is also crucial to teach students how to
focus on exploring ideas and the alternative solutions and seeking for
other right answers rather than one. This paper focuses on the
enhancing architectural design education and may provide
implications for enhancing teaching design.
Abstract: n-CdO/p-Si heterojunction diode was fabricated using
sol-gel spin coating technique which is a low cost and easily scalable
method for preparing of semiconductor films. The structural and
morphological properties of CdO film were investigated. The X-ray
diffraction (XRD) spectra indicated that the film was of
polycrystalline nature. The scanning electron microscopy (SEM)
images indicate that the surface morphology CdO film consists of the
clusters formed with the coming together of the nanoparticles. The
electrical characterization of Au/n-CdO/p–Si/Al heterojunction diode
was investigated by current-voltage. The ideality factor of the diode
was found to be 3.02 for room temperature. The reverse current of
the diode strongly increased with illumination intensity of 100
mWcm-2 and the diode gave a maximum open circuit voltage Voc of
0.04 V and short-circuits current Isc of 9.92×10-9 A.
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: Here, a new idea to speed up the operation of
complex valued time delay neural networks is presented. The whole
data are collected together in a long vector and then tested as a one
input pattern. The proposed fast complex valued time delay neural
networks uses cross correlation in the frequency domain between the
tested data and the input weights of neural networks. It is proved
mathematically that the number of computation steps required for
the presented fast complex valued time delay neural networks is less
than that needed by classical time delay neural networks. Simulation
results using MATLAB confirm the theoretical computations.
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: Independent component analysis (ICA) in the
frequency domain is used for solving the problem of blind source
separation (BSS). However, this method has some problems. For
example, a general ICA algorithm cannot determine the permutation
of signals which is important in the frequency domain ICA. In this
paper, we propose an approach to the solution for a permutation
problem. The idea is to effectively combine two conventional
approaches. This approach improves the signal separation
performance by exploiting features of the conventional approaches.
We show the simulation results using artificial data.