Abstract: In DMVC, we have more than one options of sources available for construction of side information. The newer techniques make use of both the techniques simultaneously by constructing a bitmask that determines the source of every block or pixel of the side information. A lot of computation is done to determine each bit in the bitmask. In this paper, we have tried to define areas that can only be well predicted by temporal interpolation and not by multiview interpolation or synthesis. We predict that all such areas that are not covered by two cameras cannot be appropriately predicted by multiview synthesis and if we can identify such areas in the first place, we don-t need to go through the script of computations for all the pixels that lie in those areas. Moreover, this paper also defines a technique based on KLT to mark the above mentioned areas before any other processing is done on the side view.
Abstract: Video watermarking is usually considered as watermarking of a set of still images. In frame-by-frame watermarking approach, each video frame is seen as a single watermarked image, so collusion attack is more critical in video watermarking. If the same or redundant watermark is used for embedding in every frame of video, the watermark can be estimated and then removed by watermark estimate remodolulation (WER) attack. Also if uncorrelated watermarks are used for every frame, these watermarks can be washed out with frame temporal filtering (FTF). Switching watermark system or so-called SS-N system has better performance against WER and FTF attacks. In this system, for each frame, the watermark is randomly picked up from a finite pool of watermark patterns. At first SS-N system will be surveyed and then a new collusion attack for SS-N system will be proposed using a new algorithm for separating video frame based on watermark pattern. So N sets will be built in which every set contains frames carrying the same watermark. After that, using WER attack in every set, N different watermark patterns will be estimated and removed later.
Abstract: Many experimental results suggest that more precise spike timing is significant in neural information processing. We construct a self-organization model using the spatiotemporal pat-terns, where Spike-Timing Dependent Plasticity (STDP) tunes the conduction delays between neurons. We show that, for highly syn-chronized inputs, the fluctuation of conduction delays causes globally continuous and locally distributed firing patterns through the self-organization.
Abstract: Global Software Development (GSD) projects are
passing through different boundaries of a company, country and even
in other continents where time zone differs between both sites.
Beside many benefits of such development, research declared plenty
of negative impacts on these GSD projects. It is important to
understand problems which may lie during the execution of GSD
project with different time zones. This research project discussed and
provided different issues related to time delays in GSD projects. In
this paper, authors investigated some of the time delay factors which
usually lie in GSD projects with different time zones. This
investigation is done through systematic review of literature.
Furthermore, the practices to overcome these delay factors which
have already been reported in literature and GSD organizations are
also explored through literature survey and case studies.
Abstract: One of the main concerns in the Information Technology field is adoption with new technologies in organizations which may result in increasing the usage paste of these technologies.This study aims to look at the issue of culture-s role in accepting and using new technologies in organizations. The study examines the effect of culture on accepting and intention to use new technology in organizations. Studies show culture is one of the most important barriers in adoption new technologies. The model used for accepting and using new technology is Technology Acceptance Model (TAM), while for culture and dimensions a well-known theory by Hofsted was used. Results of the study show significant effect of culture on intention to use new technologies. All four dimensions of culture were tested to find the strength of relationship with behavioral intention to use new technologies. Findings indicate the important role of culture in the level of intention to use new technologies and different role of each dimension to improve adaptation process. The study suggests that transferring of new technologies efforts are most likely to be successful if the parties are culturally aligned.
Abstract: School physical education, through its objectives and
contents, efficiently valorizes the pupils- abilities, developing them,
especially the coordinative skill component, which is the basis of
movement learning, of the development of the daily motility and also
of the special, refined motility required by the practice of certain
sports. Medium school age offers the nervous and motor substratum
needed for the acquisition of complex motor habits, a substratum that
is essential for the coordinative skill. Individuals differ as to the level
at which this function is performed, the extent to which this function
turns an individual into a person that is adapted and adaptable to
complex and various situations. Spatio-temporal orientation, together
with movement combination and coupling, and with kinesthetic,
balance, motor reaction, movement transformation and rhythm
differentiation form the coordinative skills. From our viewpoint,
these are characteristic features with high levels of manifestation in a
complex psychomotor act - valorizing the quality of one-s talent - as
well as indices pertaining to one-s psychomotor intelligence and
creativity.
Abstract: This article is investigating Boria which is a kind of common performance in Malaysia. Boria has been known as Boria and Borea and both are correct, but Boria is more common. Boria is a folk performance unique to Penang. This theatre style reached Penang in the mid-19th century and is believed to be derived from the Shia Islamic Passion play performed during the Muslim month of Muharram to commemorate the martyrs of Kerbela. These days in Malaysia (especially Penang) Boria mentions to a choral street performance performed annually by a number of groups composed mostly of Sunni Malaysian. Boria are performed for entertainment and often include an annual singing competition. The size, membership, themes and movements of each Boria troupe may vary from year to year. Similarly, the themes and contents of the Boria performed by the different troupes also changes each year and can have a comical, political or satirical notion. It is common to most groups during the first ten days of Muharram Boria generally is done.
Abstract: This paper presents a forgetting factor scheme for variable step-size affine projection algorithms (APA). The proposed scheme uses a forgetting processed input matrix as the projection matrix of pseudo-inverse to estimate system deviation. This method introduces temporal weights into the projection matrix, which is typically a better model of the real error's behavior than homogeneous temporal weights. The regularization overcomes the ill-conditioning introduced by both the forgetting process and the increasing size of the input matrix. This algorithm is tested by independent trials with coloured input signals and various parameter combinations. Results show that the proposed algorithm is superior in terms of convergence rate and misadjustment compared to existing algorithms. As a special case, a variable step size NLMS with forgetting factor is also presented in this paper.
Abstract: The paper investigates the main issues concerning the activity of mergers and acquisitions in Romania in the period 2000- 2004. As in the first decade after the failure of the socialist economy the market of M&A was living its infancy based exclusively on privatization transactions, after 2000 the market entered in a stage of maturity. We are investigated both the registered evolutions in terms of number and value of transactions, and some sectoral issues, concerning the most important industries affected by the M&A process.
Abstract: Climate change is a cumulative change in weather
patterns over a period of time. Trend analysis using non-parametric
Mann-Kendall test may help to determine the existence and
magnitude of any statistically significant trend in the climatic data.
Another index called Sen slope may be used to quantify the
magnitude of such trends. A toolbar extension to ESRI ArcGIS
named Arc Trends has been developed in this study for performing
the above mentioned tasks. To study the temporal trend of
meteorological parameters, 32 years (1971-2002) monthly
meteorological data were collected for 133 selected stations over
different agro-ecological regions of India. Both the maximum and
minimum temperatures were found to be rising. A significant
increasing trend in the relative humidity and a consistent significant
decreasing trend in the wind speed all over the country were found.
However, a general increase in rainfall was not found in recent years.
Abstract: This study examines regional convergence in per capita personal income in the US and Canada. We find that the disparity in real per capita income levels across US states (Canadian provinces) has declined, but income levels are not identical. Income levels become more aligned once costs of living are accounted for in relative per capita income series. US states (Canadian provinces) converge at an annual rate of between 1.3% and 2.04% (between 2.15% and 2.37%). A pattern of σ and β-convergence in per capita personal income across regions evident over the entire sample period, is reversed over 1979-1989 (1976-1990) period. The reversal may be due to sectoral or region-specific shocks that have highly persistent effects. The latter explanation might be true for half of the US and most of Canada.
Abstract: In this paper, a novel algorithm based on Ridgelet
Transform and support vector machine is proposed for human action
recognition. The Ridgelet transform is a directional multi-resolution
transform and it is more suitable for describing the human action by
performing its directional information to form spatial features
vectors. The dynamic transition between the spatial features is carried
out using both the Principal Component Analysis and clustering
algorithm K-means. First, the Principal Component Analysis is used
to reduce the dimensionality of the obtained vectors. Then, the kmeans
algorithm is then used to perform the obtained vectors to form
the spatio-temporal pattern, called set-of-labels, according to given
periodicity of human action. Finally, a Support Machine classifier is
used to discriminate between the different human actions. Different
tests are conducted on popular Datasets, such as Weizmann and
KTH. The obtained results show that the proposed method provides
more significant accuracy rate and it drives more robustness in very
challenging situations such as lighting changes, scaling and dynamic
environment
Abstract: The vast amount of information hidden in huge
databases has created tremendous interests in the field of data
mining. This paper examines the possibility of using data clustering
techniques in oral medicine to identify functional relationships
between different attributes and classification of similar patient
examinations. Commonly used data clustering algorithms have been
reviewed and as a result several interesting results have been
gathered.
Abstract: In this paper we illuminate a frequency domain based
classification method for video scenes. Videos from certain topical
areas often contain activities with repeating movements. Sports
videos, home improvement videos, or videos showing mechanical
motion are some example areas. Assessing main and side frequencies
of each repeating movement gives rise to the motion type. We
obtain the frequency domain by transforming spatio-temporal motion
trajectories. Further on we explain how to compute frequency features
for video clips and how to use them for classifying. The focus of
the experimental phase is on transforms utilized for our system.
By comparing various transforms, experiments show the optimal
transform for a motion frequency based approach.
Abstract: Most paddy rice fields in East Asia are small parcels,
and the weather conditions during the growing season are usually
cloudy. FORMOSAT-2 multi-spectral images have an 8-meter
resolution and one-day recurrence, ideal for mapping paddy rice fields
in East Asia. To map rice fields, this study first determined the
transplanting and the most active tillering stages of paddy rice and
then used multi-temporal images to distinguish different growing
characteristics between paddy rice and other ground covers. The
unsupervised ISODATA (iterative self-organizing data analysis
techniques) and supervised maximum likelihood were both used to
discriminate paddy rice fields, with training areas automatically
derived from ten-year cultivation parcels in Taiwan. Besides original
bands in multi-spectral images, we also generated normalized
difference vegetation index and experimented with object-based
pre-classification and post-classification. This paper discusses results
of different image classification methods in an attempt to find a
precise and automatic solution to mapping paddy rice in Taiwan.
Abstract: In this paper, we propose a novel adaptive
spatiotemporal filter that utilizes image sequences in order to remove
noise. The consecutive frames include: current, previous and next
noisy frames. The filter proposed in this paper is based upon the
weighted averaging pixels intensity and noise variance in image
sequences. It utilizes the Appropriate Number of Consecutive Frames
(ANCF) based on the noisy pixels intensity among the frames. The
number of consecutive frames is adaptively calculated for each
region in image and its value may change from one region to another
region depending on the pixels intensity within the region. The
weights are determined by a well-defined mathematical criterion,
which is adaptive to the feature of spatiotemporal pixels of the
consecutive frames. It is experimentally shown that the proposed
filter can preserve image structures and edges under motion while
suppressing noise, and thus can be effectively used in image
sequences filtering. In addition, the AWA filter using ANCF is
particularly well suited for filtering sequences that contain segments
with abruptly changing scene content due to, for example, rapid
zooming and changes in the view of the camera.
Abstract: A liquid curved jet has many applications in different
industrial and engineering processes, such as the prilling process
for generating small spherical pellets (fertilizer or magnesium). The
liquids used are usually molten and contain small quantities of
polymers and therefore can be modelled as non-Newtonian liquids. In
this paper, we model the viscoelastic liquid jet by using the Oldroyd-
B model. An asymptotic analysis has been used to simplify the
governing equations. Furthermore, the trajectory and a linear temporal
stability in the presence of gravity and rotation have been determined.
Abstract: In this paper, we propose a novel spatiotemporal fuzzy
based algorithm for noise filtering of image sequences. Our proposed algorithm uses adaptive weights based on a triangular membership
functions. In this algorithm median filter is used to suppress noise.
Experimental results show when the images are corrupted by highdensity
Salt and Pepper noise, our fuzzy based algorithm for noise filtering of image sequences, are much more effective in suppressing
noise and preserving edges than the previously reported algorithms such as [1-7]. Indeed, assigned weights to noisy pixels are very
adaptive so that they well make use of correlation of pixels. On the other hand, the motion estimation methods are erroneous and in highdensity noise they may degrade the filter performance. Therefore, our
proposed fuzzy algorithm doesn-t need any estimation of motion trajectory. The proposed algorithm admissibly removes noise without having any knowledge of Salt and Pepper noise density.
Abstract: A behavioral model of a second order switchedcapacitor Sigma-Delta modulator is presented. The purpose of this work is the presentation of a behavioral model of a second order switched capacitor ΣΔ modulator considering (Error due to Clock Jitter, Thermal noise Amplifier Noise, Amplifier Slew-Rate, Non linearity of amplifiers, Gain error, Charge Injection, Clock Feedthrough, and Nonlinear on-resistance). A comparison between the use of MOS switches and the use transmission gate switches use is analyzed.
Abstract: Due to the legacy of apartheid segregation South Africa remains a divided society where most voters live in politically homogenous social environments. This paper argues that political discussion within one’s social context plays a primary role in shaping political attitudes and vote choice. Using data from the Comparative National Elections Project 2004 and 2009 South African post-election surveys, the paper explores the extent of social context partisan homogeneity in South Africa and finds that voters are not overly embedded in homogenous social contexts. It then demonstrates the consequences of partisan homogeneity on voting behavior. Homogenous social contexts tend to encourage stronger partisan loyalties and fewer defections in vote choice while voters in more heterogeneous contexts show less consistency in their attitudes and behaviour. Finally, the analysis shows how momentous sociopolitical events at the time of a particular election can change the social context, with important consequences for electoral outcomes.