Abstract: One of the major, difficult tasks in automated video
surveillance is the segmentation of relevant objects in the scene.
Current implementations often yield inconsistent results on average
from frame to frame when trying to differentiate partly occluding
objects. This paper presents an efficient block-based segmentation
algorithm which is capable of separating partly occluding objects and
detecting shadows. It has been proven to perform in real time with a
maximum duration of 47.48 ms per frame (for 8x8 blocks on a
720x576 image) with a true positive rate of 89.2%. The flexible
structure of the algorithm enables adaptations and improvements with
little effort. Most of the parameters correspond to relative differences
between quantities extracted from the image and should therefore not
depend on scene and lighting conditions. Thus presenting a
performance oriented segmentation algorithm which is applicable in
all critical real time scenarios.
Abstract: Instead of representing individual cognition only, population cognition is represented using artificial neural networks whilst maintaining individuality. This population network trains continuously, simulating adaptation. An implementation of two coexisting populations is compared to the Lotka-Volterra model of predator-prey interaction. Applications include multi-agent systems such as artificial life or computer games.
Abstract: F-actin fibrils are the cytoskeleton of osteocytes. They react in a dynamic manner to mechanical loading, and strength and
reposition their efforts to reinforce the cells structure. We hypothesize that f-actin is temporarly disrupted after loading and repolymerizes
in a new orientation to oppose the applied load. In vitro studies are conducted to determine f-actin disruption after varying mechanical stimulus parameters that are known to affect bone
formation. Results indicate that the f-actin cytoskeleton is disrupted in vitro as a function of applied mechanical stimulus parameters and
that the f-actin bundles reassemble after loading induced disruption
within 3 minutes after cessation of loading. The disruption of the factin
cytoskeleton depends on the magnitude of stretch, the numbers
of loading cycles, frequency, the insertion of rest between loading
cycles and extracellular calcium. In vivo studies also demonstrate
disruption of the f-actin cytoskeleton in cells embedded in the bone
matrix immediately after mechanical loading. These studies suggest
that adaptation of the f-actin fiber bundles of the cytoskeleton in
response to applied loads occurs by disruption and subsequent repolymerization.
Abstract: Extracting and elaborating software requirements and
transforming them into viable software architecture are still an
intricate task. This paper defines a solution architecture which is
based on the blurred amalgamation of problem space and solution
space. The dependencies between domain constraints, requirements
and architecture and their importance are described that are to be
considered collectively while evolving from problem space to
solution space. This paper proposes a revised version of Twin Peaks
Model named Win Peaks Model that reconciles software
requirements and architecture in more consistent and adaptable
manner. Further the conflict between stakeholders- win-requirements
is resolved by proposed Voting methodology that is simple
adaptation of win-win requirements negotiation model and QARCC.
Abstract: In this paper, we first consider the quality of service
problems in heterogeneous wireless networks for sending the video
data, which their problem of being real-time is pronounced. At last,
we present a method for ensuring the end-to-end quality of service at
application layer level for adaptable sending of the video data at
heterogeneous wireless networks. To do this, mechanism in different
layers has been used. We have used the stop mechanism, the
adaptation mechanism and the graceful degrade at the application
layer, the multi-level congestion feedback mechanism in the network
layer and connection cutting off decision mechanism in the link
layer. At the end, the presented method and the achieved
improvement is simulated and presented in the NS-2 software.
Abstract: We present a simplified equalization technique for a
π/4 differential quadrature phase shift keying ( π/4 -DQPSK) modulated
signal in a multipath fading environment. The proposed equalizer is
realized as a fractionally spaced adaptive decision feedback equalizer
(FS-ADFE), employing exponential step-size least mean square
(LMS) algorithm as the adaptation technique. The main advantage of
the scheme stems from the usage of exponential step-size LMS algorithm
in the equalizer, which achieves similar convergence behavior
as that of a recursive least squares (RLS) algorithm with significantly
reduced computational complexity. To investigate the finite-precision
performance of the proposed equalizer along with the π/4 -DQPSK
modem, the entire system is evaluated on a 16-bit fixed point digital
signal processor (DSP) environment. The proposed scheme is found
to be attractive even for those cases where equalization is to be
performed within a restricted number of training samples.
Abstract: Classification of video sequences based on their contents is a vital process for adaptation techniques. It helps decide which adaptation technique best fits the resource reduction requested by the client. In this paper we used the principal feature analysis algorithm to select a reduced subset of video features. The main idea is to select only one feature from each class based on the similarities between the features within that class. Our results showed that using this feature reduction technique the source video features can be completely omitted from future classification of video sequences.
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: In this study, the use of silicon NAM (Non-Audible
Murmur) microphone in automatic speech recognition is presented.
NAM microphones are special acoustic sensors, which are attached
behind the talker-s ear and can capture not only normal (audible)
speech, but also very quietly uttered speech (non-audible murmur).
As a result, NAM microphones can be applied in automatic speech
recognition systems when privacy is desired in human-machine communication.
Moreover, NAM microphones show robustness against
noise and they might be used in special systems (speech recognition,
speech conversion etc.) for sound-impaired people. Using a small
amount of training data and adaptation approaches, 93.9% word
accuracy was achieved for a 20k Japanese vocabulary dictation
task. Non-audible murmur recognition in noisy environments is also
investigated. In this study, further analysis of the NAM speech has
been made using distance measures between hidden Markov model
(HMM) pairs. It has been shown the reduced spectral space of NAM
speech using a metric distance, however the location of the different
phonemes of NAM are similar to the location of the phonemes
of normal speech, and the NAM sounds are well discriminated.
Promising results in using nonlinear features are also introduced,
especially under noisy conditions.
Abstract: Influence diagrams (IDs) are one of the most commonly used graphical decision models for reasoning under uncertainty. The quantification of IDs which consists in defining conditional probabilities for chance nodes and utility functions for value nodes is not always obvious. In fact, decision makers cannot always provide exact numerical values and in some cases, it is more easier for them to specify qualitative preference orders. This work proposes an adaptation of standard IDs to the qualitative framework based on possibility theory.
Abstract: Evolutionary robotics is concerned with the design of
intelligent systems with life-like properties by means of simulated
evolution. Approaches in evolutionary robotics can be categorized
according to the control structures that represent the behavior and the
parameters of the controller that undergo adaptation. The basic idea
is to automatically synthesize behaviors that enable the robot to
perform useful tasks in complex environments. The evolutionary
algorithm searches through the space of parameterized controllers
that map sensory perceptions to control actions, thus realizing a
specific robotic behavior. Further, the evolutionary algorithm
maintains and improves a population of candidate behaviors by
means of selection, recombination and mutation. A fitness function
evaluates the performance of the resulting behavior according to the
robot-s task or mission. In this paper, the focus is in the use of
genetic algorithms to solve a multi-objective optimization problem
representing robot behaviors; in particular, the A-Compander Law is
employed in selecting the weight of each objective during the
optimization process. Results using an adaptive fitness function show
that this approach can efficiently react to complex tasks under
variable environments.
Abstract: Sexual behavior and semen charactertistics were
evaluated in young male Boer goats in tropical condition during time
period of September to November 2009. The animal was let to have
adaptation for five months after importation from Australian climate.
A total of 20 bucks were observed for sexual behavior and ability of
semen production. Out of this number, 4 faild to libido and 3
produced poor semen. The remaing 13 animals were divided into
three groups according to the ages (11-13, 15-16 and 18-25 months).
Sexual behavior consisting response time to female teaser,
ejaculation time, fixing strenght to female and erection status were
normaly observer in 13 bucks, and there was no significant difference
between age groups. Semen characteristics from 13 bucks were in
normal quality in the volume, sperm mass motility, individual
motility, percentage of live- and abnormal sperm. We concluded that
is possible to collect semen of Boer goats during the period of
September to November under tropical condition. Collection during
other time period should be analyzed.
Abstract: Observations and long-term trends indicate that climate
change impacts would be significant and affects Taiwan directly and
severely. Taiwan engages not only in mitigation, but also in adaptation.
However, there are cognitive gaps on adaptation between government
and populace. Besides, a vision of zero-carbon and renewable energy
100% will be adopted in future. Therefore, the objectives of this
article are to 1) hold a National Forum for knowing differences
between the strategies of zero-carbon and renewable energy 100% and
cognitions of general populace, and 2) plan a clear roadmap for the
vision, strategy, and measures. In this forum, we set 5 group topics, 5
presumed themes, and issues mentioned review for concluding the
critical issues. Finally, there are 4 strategies and 14 critical issues
which correlate with the vision and strategy of government and the
cognition of the general populace.
Abstract: The majority of existing predictors for time series are
model-dependent and therefore require some prior knowledge for the
identification of complex systems, usually involving system
identification, extensive training, or online adaptation in the case of
time-varying systems. Additionally, since a time series is usually
generated by complex processes such as the stock market or other
chaotic systems, identification, modeling or the online updating of
parameters can be problematic. In this paper a model-free predictor
(MFP) for a time series produced by an unknown nonlinear system or
process is derived using tracking theory. An identical derivation of the
MFP using the property of the Newton form of the interpolating
polynomial is also presented. The MFP is able to accurately predict
future values of a time series, is stable, has few tuning parameters and
is desirable for engineering applications due to its simplicity, fast
prediction speed and extremely low computational load. The
performance of the proposed MFP is demonstrated using the
prediction of the Dow Jones Industrial Average stock index.
Abstract: The effects of global warming on India vary from the
submergence of low-lying islands and coastal lands to the melting of
glaciers in the Indian Himalayas, threatening the volumetric flow rate
of many of the most important rivers of India and South Asia. In
India, such effects are projected to impact millions of lives. As a
result of ongoing climate change, the climate of India has become
increasingly volatile over the past several decades; this trend is
expected to continue.
Climate change is one of the most important global environmental
challenges, with implications for food production, water supply,
health, energy, etc. Addressing climate change requires a good
scientific understanding as well as coordinated action at national and
global level. The climate change issue is part of the larger challenge
of sustainable development. As a result, climate policies can be more
effective when consistently embedded within broader strategies
designed to make national and regional development paths more
sustainable. The impact of climate variability and change, climate
policy responses, and associated socio-economic development will
affect the ability of countries to achieve sustainable development
goals.
A very well calibrated Soil and Water Assessment Tool (R2 =
0.9968, NSE = 0.91) was exercised over the Khatra sub basin of the
Kangsabati River watershed in Bankura district of West Bengal,
India, in order to evaluate projected parameters for agricultural
activities. Evapotranspiration, Transmission Losses, Potential
Evapotranspiration and Lateral Flow to reach are evaluated from the
years 2041-2050 in order to generate a picture for sustainable
development of the river basin and its inhabitants.
India has a significant stake in scientific advancement as well as
an international understanding to promote mitigation and adaptation.
This requires improved scientific understanding, capacity building,
networking and broad consultation processes. This paper is a
commitment towards the planning, management and development of
the water resources of the Kangsabati River by presenting detailed
future scenarios of the Kangsabati river basin, Khatra sub basin, over
the mentioned time period.
India-s economy and societal infrastructures are finely tuned to the
remarkable stability of the Indian monsoon, with the consequence
that vulnerability to small changes in monsoon rainfall is very high.
In 2002 the monsoon rains failed during July, causing profound loss
of agricultural production with a drop of over 3% in India-s GDP.
Neither the prolonged break in the monsoon nor the seasonal rainfall
deficit was predicted. While the general features of monsoon
variability and change are fairly well-documented, the causal
mechanisms and the role of regional ecosystems in modulating the
changes are still not clear. Current climate models are very poor at
modelling the Asian monsoon: this is a challenging and critical
region where the ocean, atmosphere, land surface and mountains all
interact. The impact of climate change on regional ecosystems is
likewise unknown. The potential for the monsoon to become more
volatile has major implications for India itself and for economies
worldwide. Knowledge of future variability of the monsoon system,
particularly in the context of global climate change, is of great
concern for regional water and food security.
The major findings of this paper were that of all the chosen
projected parameters, transmission losses, soil water content,
potential evapotranspiration, evapotranspiration and lateral flow to
reach, display an increasing trend over the time period of years 2041-
2050.
Abstract: The current speech interfaces in many military
applications may be adequate for native speakers. However,
the recognition rate drops quite a lot for non-native speakers
(people with foreign accents). This is mainly because the nonnative
speakers have large temporal and intra-phoneme
variations when they pronounce the same words. This
problem is also complicated by the presence of large
environmental noise such as tank noise, helicopter noise, etc.
In this paper, we proposed a novel continuous acoustic feature
adaptation algorithm for on-line accent and environmental
adaptation. Implemented by incremental singular value
decomposition (SVD), the algorithm captures local acoustic
variation and runs in real-time. This feature-based adaptation
method is then integrated with conventional model-based
maximum likelihood linear regression (MLLR) algorithm.
Extensive experiments have been performed on the NATO
non-native speech corpus with baseline acoustic model trained
on native American English. The proposed feature-based
adaptation algorithm improved the average recognition
accuracy by 15%, while the MLLR model based adaptation
achieved 11% improvement. The corresponding word error
rate (WER) reduction was 25.8% and 2.73%, as compared to
that without adaptation. The combined adaptation achieved
overall recognition accuracy improvement of 29.5%, and
WER reduction of 31.8%, as compared to that without
adaptation.
Abstract: This article presents a detailed analysis and comparative
performance evaluation of model reference adaptive control systems.
In contrast to classical control theory, adaptive control methods allow
to deal with time-variant processes. Inspired by the works [1] and
[2], two methods based on the MIT rule and Lyapunov rule are
applied to a linear first order system. The system is simulated and
it is investigated how changes to the adaptation gain affect the
system performance. Furthermore, variations in the reference model
parameters, that is changing the desired closed-loop behaviour are
examinded.
Abstract: Evolutionary Programming (EP) represents a
methodology of Evolutionary Algorithms (EA) in which mutation is
considered as a main reproduction operator. This paper presents a
novel EP approach for Artificial Neural Networks (ANN) learning.
The proposed strategy consists of two components: the self-adaptive,
which contains phenotype information and the dynamic, which is
described by genotype. Self-adaptation is achieved by the addition of
a value, called the network weight, which depends on a total number
of hidden layers and an average number of neurons in hidden layers.
The dynamic component changes its value depending on the fitness
of a chromosome, exposed to mutation. Thus, the mutation step size
is controlled by two components, encapsulated in the algorithm,
which adjust it according to the characteristics of a predefined ANN
architecture and the fitness of a particular chromosome. The
comparative analysis of the proposed approach and the classical EP
(Gaussian mutation) showed, that that the significant acceleration of
the evolution process is achieved by using both phenotype and
genotype information in the mutation strategy.
Abstract: This paper describes the optimization of a complex
dairy farm simulation model using two quite different methods of
optimization, the Genetic algorithm (GA) and the Lipschitz
Branch-and-Bound (LBB) algorithm. These techniques have been
used to improve an agricultural system model developed by Dexcel
Limited, New Zealand, which describes a detailed representation of
pastoral dairying scenarios and contains an 8-dimensional parameter
space. The model incorporates the sub-models of pasture growth and
animal metabolism, which are themselves complex in many cases.
Each evaluation of the objective function, a composite 'Farm
Performance Index (FPI)', requires simulation of at least a one-year
period of farm operation with a daily time-step, and is therefore
computationally expensive. The problem of visualization of the
objective function (response surface) in high-dimensional spaces is
also considered in the context of the farm optimization problem.
Adaptations of the sammon mapping and parallel coordinates
visualization are described which help visualize some important
properties of the model-s output topography. From this study, it is
found that GA requires fewer function evaluations in optimization
than the LBB algorithm.
Abstract: Weather systems use enormously complex
combinations of numerical tools for study and forecasting.
Unfortunately, due to phenomena in the world climate, such
as the greenhouse effect, classical models may become
insufficient mostly because they lack adaptation. Therefore,
the weather forecast problem is matched for heuristic
approaches, such as Evolutionary Algorithms.
Experimentation with heuristic methods like Particle Swarm
Optimization (PSO) algorithm can lead to the development of
new insights or promising models that can be fine tuned with
more focused techniques. This paper describes a PSO
approach for analysis and prediction of data and provides
experimental results of the aforementioned method on realworld
meteorological time series.