Abstract: Digital libraries become more and more necessary in
order to support users with powerful and easy-to-use tools for
searching, browsing and retrieving media information. The starting
point for these tasks is the segmentation of video content into shots.
To segment MPEG video streams into shots, a fully automatic
procedure to detect both abrupt and gradual transitions (dissolve and
fade-groups) with minimal decoding in real time is developed in this
study. Each was explored through two phases: macro-block type's
analysis in B-frames, and on-demand intensity information analysis.
The experimental results show remarkable performance in
detecting gradual transitions of some kinds of input data and
comparable results of the rest of the examined video streams. Almost
all abrupt transitions could be detected with very few false positive
alarms.
Abstract: Thousands of masters athletes participate
quadrennially in the World Masters Games (WMG), yet this cohort
of athletes remains proportionately under-investigated. Due to a
growing global obesity pandemic in context of benefits of physical
activity across the lifespan, the prevalence of obesity in this unique
population was of particular interest. Data gathered on a sub-sample
of 535 football code athletes, aged 31-72 yrs ( =47.4, s =±7.1),
competing at the Sydney World Masters Games (2009) demonstrated
a significantly (p
Abstract: When faced with stochastic networks with an uncertain
duration for their activities, the securing of network completion time
becomes problematical, not only because of the non-identical pdf of
duration for each node, but also because of the interdependence of
network paths. As evidenced by Adlakha & Kulkarni [1], many
methods and algorithms have been put forward in attempt to resolve
this issue, but most have encountered this same large-size network
problem. Therefore, in this research, we focus on network reduction
through a Series/Parallel combined mechanism. Our suggested
algorithm, named the Activity Network Reduction Algorithm
(ANRA), can efficiently transfer a large-size network into an S/P
Irreducible Network (SPIN). SPIN can enhance stochastic network
analysis, as well as serve as the judgment of symmetry for the Graph
Theory.
Abstract: A case study of the generation scheduling optimization
of the multi-hydroplants on the Yuan River Basin in China is reported
in this paper. Concerning the uncertainty of the inflows, the
long/mid-term generation scheduling (LMTGS) problem is solved by
a stochastic model in which the inflows are considered as stochastic
variables. For the short-term generation scheduling (STGS) problem, a
constraint violation priority is defined in case not all constraints are
satisfied. Provided the stage-wise separable condition and low
dimensions, the hydroplant-based operational region schedules
(HBORS) problem is solved by dynamic programming (DP). The
coordination of LMTGS and STGS is presented as well. The
feasibility and the effectiveness of the models and solution methods
are verified by the numerical results.
Abstract: This paper describes fast and efficient method for page segmentation of document containing nonrectangular block. The segmentation is based on edge following algorithm using small window of 16 by 32 pixels. This segmentation is very fast since only border pixels of paragraph are used without scanning the whole page. Still, the segmentation may contain error if the space between them is smaller than the window used in edge following. Consequently, this paper reduce this error by first identify the missed segmentation point using direction information in edge following then, using X-Y cut at the missed segmentation point to separate the connected columns. The advantage of the proposed method is the fast identification of missed segmentation point. This methodology is faster with fewer overheads than other algorithms that need to access much more pixel of a document.
Abstract: In this paper, an extreme learning machine with an automatic segmentation algorithm is applied to heart disorder classification by heart sound signals. From continuous heart sound signals, the starting points of the first (S1) and the second heart pulses (S2) are extracted and corrected by utilizing an inter-pulse histogram. From the corrected pulse positions, a single period of heart sound signals is extracted and converted to a feature vector including the mel-scaled filter bank energy coefficients and the envelope coefficients of uniform-sized sub-segments. An extreme learning machine is used to classify the feature vector. In our cardiac disorder classification and detection experiments with 9 cardiac disorder categories, the proposed method shows significantly better performance than multi-layer perceptron, support vector machine, and hidden Markov model; it achieves the classification accuracy of 81.6% and the detection accuracy of 96.9%.
Abstract: In an emergency, combining Wireless Sensor Network's data with the knowledge gathered from various other information sources and navigation algorithms, could help safely guide people to a building exit while avoiding the risky areas. This paper presents an emergency response and navigation support architecture for data gathering, knowledge manipulation, and navigational support in an emergency situation. At normal state, the system monitors the environment. When an emergency event detects, the system sends messages to first responders and immediately identifies the risky areas from safe areas to establishing escape paths. The main functionalities of the system include, gathering data from a wireless sensor network which is deployed in a multi-story indoor environment, processing it with information available in a knowledge base, and sharing the decisions made, with first responders and people in the building. The proposed architecture will act to reduce risk of losing human lives by evacuating people much faster with least congestion in an emergency environment.
Abstract: Internet is one of the major sources of information for
the person belonging to almost all the fields of life. Major language
that is used to publish information on internet is language. This thing
becomes a problem in a country like Pakistan, where Urdu is the
national language. Only 10% of Pakistan mass can understand
English. The reason is millions of people are deprived of precious
information available on internet. This paper presents a system for
translation from English to Urdu. A module LESSA is used that uses
a rule based algorithm to read the input text in English language,
understand it and translate it into Urdu language. The designed
approach was further incorporated to translate the complete website
from English language o Urdu language. An option appears in the
browser to translate the webpage in a new window. The designed
system will help the millions of users of internet to get benefit of the
internet and approach the latest information and knowledge posted
daily on internet.
Abstract: Signature amortization schemes have been introduced
for authenticating multicast streams, in which, a single signature is
amortized over several packets. The hash value of each packet is
computed, some hash values are appended to other packets, forming
what is known as hash chain. These schemes divide the stream into
blocks, each block is a number of packets, the signature packet in
these schemes is either the first or the last packet of the block.
Amortization schemes are efficient solutions in terms of computation
and communication overhead, specially in real-time environment.
The main effictive factor of amortization schemes is it-s hash chain
construction. Some studies show that signing the first packet of each
block reduces the receiver-s delay and prevents DoS attacks, other
studies show that signing the last packet reduces the sender-s delay.
To our knowledge, there is no studies that show which is better, to
sign the first or the last packet in terms of authentication probability
and resistance to packet loss.
In th is paper we will introduce another scheme for authenticating
multicast streams that is robust against packet loss, reduces the
overhead, and prevents the DoS attacks experienced by the receiver
in the same time. Our scheme-The Multiple Connected Chain signing
the First packet (MCF) is to append the hash values of specific
packets to other packets,then append some hashes to the signature
packet which is sent as the first packet in the block. This scheme
is aspecially efficient in terms of receiver-s delay. We discuss and
evaluate the performance of our proposed scheme against those that
sign the last packet of the block.
Abstract: The mathematical equation for Separation of the
binary aqueous solution is developed by using the Spiegler- Kedem
theory. The characteristics of a B-9 hollow fibre module of Du Pont
are determined by using these equations and their results are
compared with the experimental results of Ohya et al. The agreement
between these results is found to be excellent.
Abstract: The benefits of eco-roofs is quite well known, however there remains very little research conducted for the implementation of eco-roofs in subtropical climates such as Australia. There are many challenges facing Australia as it moves into the future, climate change is proving to be one of the leading challenges. In order to move forward with the mitigation of climate change, the impacts of rapid urbanization need to be offset. Eco-roofs are one way to achieve this; this study presents the energy savings and environmental benefits of the implementation of eco-roofs in subtropical climates. An experimental set-up was installed at Rockhampton campus of Central Queensland University, where two shipping containers were converted into small offices, one with an eco-roof and one without. These were used for temperature, humidity and energy consumption data collection. In addition, a computational model was developed using Design Builder software (state-of-the-art building energy simulation software) for simulating energy consumption of shipping containers and environmental parameters, this was done to allow comparison between simulated and real world data. This study found that eco-roofs are very effective in subtropical climates and provide energy saving of about 13% which agrees well with simulated results.
Abstract: This paper presents a predictive model of sensor readings for mobile robot. The model predicts sensor readings for given time horizon based on current sensor readings and velocities of wheels assumed for this horizon. Similar models for such anticipation have been proposed in the literature. The novelty of the model presented in the paper comes from the fact that its structure takes into account physical phenomena and is not just a black box, for example a neural network. From this point of view it may be regarded as a semi-phenomenological model. The model is developed for the Khepera robot, but after certain modifications, it may be applied for any robot with distance sensors such as infrared or ultrasonic sensors.
Abstract: This paper presents a new compact analytical model of
the gate leakage current in high-k based nano scale MOSFET by
assuming a two-step inelastic trap-assisted tunneling (ITAT) process
as the conduction mechanism. This model is based on an inelastic
trap-assisted tunneling (ITAT) mechanism combined with a semiempirical
gate leakage current formulation in the BSIM 4 model. The
gate tunneling currents have been calculated as a function of gate
voltage for different gate dielectrics structures such as HfO2, Al2O3
and Si3N4 with EOT (equivalent oxide thickness) of 1.0 nm. The
proposed model is compared and contrasted with santaurus
simulation results to verify the accuracy of the model and excellent
agreement is found between the analytical and simulated data. It is
observed that proposed analytical model is suitable for different highk
gate dielectrics simply by adjusting two fitting parameters. It was
also shown that gate leakages reduced with the introduction of high-k
gate dielectric in place of SiO2.
Abstract: Utilizing echoic intension and distribution from different organs and local details of human body, ultrasonic image can catch important medical pathological changes, which unfortunately may be affected by ultrasonic speckle noise. A feature preserving ultrasonic image denoising and edge enhancement scheme is put forth, which includes two terms: anisotropic diffusion and edge enhancement, controlled by the optimum smoothing time. In this scheme, the anisotropic diffusion is governed by the local coordinate transformation and the first and the second order normal derivatives of the image, while the edge enhancement is done by the hyperbolic tangent function. Experiments on real ultrasonic images indicate effective preservation of edges, local details and ultrasonic echoic bright strips on denoising by our scheme.
Abstract: The objective of this project is to study the corrosion
behaviour and hardness based on the presence of martensite in dual
phase steel. This study was conducted on six samples of dual phase
steel which have different percentage of martensite. A total of 9
specimens were prepared by intercritical annealing process to study
the effect of temperature to the formation of martensite. The low
carbon steels specimens were heated for 25 minutes in a specified
temperature ranging from 7250C to 8250C followed by rapid cooling
in water. The measurement of corrosion rate was done by using
extrapolation tafel method, while potentiostat was used to control and
measured the current produced. This measurement is performed
through a system named CMS105. The result shows that a specimen
with higher percentage of martensite is likely to corrode faster.
Hardness test for each specimen was conducted to compare its
hardness with low carbon steel. The results obtained indicate that the
specimen hardness is proportional to the amount of martensite in dual
phase steel.
Abstract: In this paper we propose a new classification method for automatic sleep scoring using an artificial neural network based decision tree. It attempts to treat sleep scoring progress as a series of two-class problems and solves them with a decision tree made up of a group of neural network classifiers, each of which uses a special feature set and is aimed at only one specific sleep stage in order to maximize the classification effect. A single electroencephalogram (EEG) signal is used for our analysis rather than depending on multiple biological signals, which makes greatly simplifies the data acquisition process. Experimental results demonstrate that the average epoch by epoch agreement between the visual and the proposed method in separating 30s wakefulness+S1, REM, S2 and SWS epochs was 88.83%. This study shows that the proposed method performed well in all the four stages, and can effectively limit error propagation at the same time. It could, therefore, be an efficient method for automatic sleep scoring. Additionally, since it requires only a small volume of data it could be suited to pervasive applications.
Abstract: The problems with high complexity had been the challenge in combinatorial problems. Due to the none-determined and polynomial characteristics, these problems usually face to unreasonable searching budget. Hence combinatorial optimizations attracted numerous researchers to develop better algorithms. In recent academic researches, most focus on developing to enhance the conventional evolutional algorithms and facilitate the local heuristics, such as VNS, 2-opt and 3-opt. Despite the performances of the introduction of the local strategies are significant, however, these improvement cannot improve the performance for solving the different problems. Therefore, this research proposes a meta-heuristic evolutional algorithm which can be applied to solve several types of problems. The performance validates BBEA has the ability to solve the problems even without the design of local strategies.
Abstract: The purpose of this study is to analyze the visual
preference of patterns in pedestrian roads. In this study, animation was
applied for the estimation of dynamic streetscape. Six patterns of
pedestrian were selected in order to analyze the visual preference. The
shapes are straight, s-curve, and zigzag. The ratio of building's height
and road's width are 2:1 and 1:1. Twelve adjective pairs used in the
field investigation were selected from adjectives which are used
usually in the estimation of streetscape. They are interesting-boring,
simple-complex, calm-noisy, open-enclosed, active-inactive,
lightly-depressing, regular-irregular, unique-usual, rhythmic-not
rhythmic, united-not united, stable-unstable, tidy-untidy.
Dynamic streetscape must be considered important in pedestrian
shopping mall and park because it will be an attraction. So, s-curve
pedestrian road, which is the most beautiful as a result of this study,
should be designed in this area. Also, the ratio of building's height and
road's width along pedestrian road should be reduced.
Abstract: Chromite is one of the principal ore of chromium in which the metal exists as a complex oxide (FeO.Cr2O3).The prepared chromite can be widely used as refractory in high temperature applications. This study describes the use of local chromite ore as refractory material. To study the feasibility of local chromite, chemical analysis and refractoriness are firstly measured. To produce chromite refractory brick, it is pressed under a press of 400 tons, dried and fired at 1580°C for fifty two hours. Then, the standard properties such as cold crushing strength, apparent porosity, apparent specific gravity, bulk density and water absorption that the chromite brick should possess were measured. According to the results obtained, the brick made by local chromite ore was suitable for use as refractory brick.
Abstract: Jatropha curcas stem was analyzed for chemical
compositions: 19.11% pentosan, 42.99% alphacellulose and 24.11%
lignin based on dry weight of 100-g raw material. The condition to
fractionate cellulose, hemicellulose and lignin in J. curcas stem using
steam explosion was optimized. The procedure started from cutting J.
curcas stem into small pieces and soaked in water for overnight.
After that, they were steam exploded at 214 °C and 21 kg/cm2 for 5
min. The obtained hydrolysate contained 1.55 g/L ferulic acid which
after that was used as substrate for vanillin production by Aspergillus
niger and Pycnoporus cinnabarinus in one-step process. The
maximum 0.65 g/L of vanillin were obtained with the conversion rate
of 45.2% based on the initial ferulic acid.