Abstract: In this paper is investigated a possible
optimization of some linear algebra problems which can be
solved by parallel processing using the special arrays called
systolic arrays. In this paper are used some special types of
transformations for the designing of these arrays. We show
the characteristics of these arrays. The main focus is on
discussing the advantages of these arrays in parallel
computation of matrix product, with special approach to the
designing of systolic array for matrix multiplication.
Multiplication of large matrices requires a lot of
computational time and its complexity is O(n3 ). There are
developed many algorithms (both sequential and parallel) with
the purpose of minimizing the time of calculations. Systolic
arrays are good suited for this purpose. In this paper we show
that using an appropriate transformation implicates in finding
more optimal arrays for doing the calculations of this type.
Abstract: The main goal of the present work is to decrease the
computational burden for optimum design of steel frames with
frequency constraints using a new type of neural networks called
Wavelet Neural Network. It is contested to train a suitable neural
network for frequency approximation work as the analysis program.
The combination of wavelet theory and Neural Networks (NN)
has lead to the development of wavelet neural networks.
Wavelet neural networks are feed-forward networks using
wavelet as activation function. Wavelets are mathematical
functions within suitable inner parameters, which help them to
approximate arbitrary functions. WNN was used to predict the
frequency of the structures. In WNN a RAtional function with
Second order Poles (RASP) wavelet was used as a transfer
function. It is shown that the convergence speed was faster
than other neural networks. Also comparisons of WNN with
the embedded Artificial Neural Network (ANN) and with
approximate techniques and also with analytical solutions are
available in the literature.
Abstract: The present work compares the performance of three
turbulence modeling approach (based on the two-equation k -ε
model) in predicting erosive wear in multi-size dense slurry flow
through rotating channel. All three turbulence models include
rotation modification to the production term in the turbulent kineticenergy
equation. The two-phase flow field obtained numerically
using Galerkin finite element methodology relates the local flow
velocity and concentration to the wear rate via a suitable wear model.
The wear models for both sliding wear and impact wear mechanisms
account for the particle size dependence. Results of predicted wear
rates using the three turbulence models are compared for a large
number of cases spanning such operating parameters as rotation rate,
solids concentration, flow rate, particle size distribution and so forth.
The root-mean-square error between FE-generated data and the
correlation between maximum wear rate and the operating
parameters is found less than 2.5% for all the three models.
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: In the recent years multimedia traffic and in particular
VoIP services are growing dramatically. We present a new algorithm
to control the resource utilization and to optimize the voice codec
selection during SIP call setup on behalf of the traffic condition
estimated on the network path.
The most suitable methodologies and the tools that perform realtime
evaluation of the available bandwidth on a network path have
been integrated with our proposed algorithm: this selects the best
codec for a VoIP call in function of the instantaneous available
bandwidth on the path. The algorithm does not require any explicit
feedback from the network, and this makes it easily deployable over
the Internet. We have also performed intensive tests on real network
scenarios with a software prototype, verifying the algorithm
efficiency with different network topologies and traffic patterns
between two SIP PBXs.
The promising results obtained during the experimental validation
of the algorithm are now the basis for the extension towards a larger
set of multimedia services and the integration of our methodology
with existing PBX appliances.
Abstract: this paper presents a multi-context recurrent network for time series analysis. While simple recurrent network (SRN) are very popular among recurrent neural networks, they still have some shortcomings in terms of learning speed and accuracy that need to be addressed. To solve these problems, we proposed a multi-context recurrent network (MCRN) with three different learning algorithms. The performance of this network is evaluated on some real-world application such as handwriting recognition and energy load forecasting. We study the performance of this network and we compared it to a very well established SRN. The experimental results showed that MCRN is very efficient and very well suited to time series analysis and its applications.
Abstract: Medical negligence disputes in Malaysia are mainly resolved through litigation by using the tort system. The tort system, being adversarial in nature has subjected parties to litigation hazards such as delay, excessive costs and uncertainty of outcome. The dissatisfaction of the tort system in compensating medically injured victims has created various alternatives to litigation. Amongst them is the implementation of a no-fault compensation system which would allow compensation to be given without the need of proving fault on the medical personnel. Instead, the community now bears the burden of compensating and at the end, promotes collective responsibility. For Malaysia, introducing a no-fault system would provide a tempting solution and may ultimately, achieve justice for the medical injured victims. Nevertheless, such drastic change requires a great deal of consideration to determine the suitability of the system and whether or not it will eventually cater for the needs of the Malaysian population
Abstract: Bio-chips are used for experiments on genes and
contain various information such as genes, samples and so on. The
two-dimensional bio-chips, in which one axis represent genes and the
other represent samples, are widely being used these days. Instead of
experimenting with real genes which cost lots of money and much
time to get the results, bio-chips are being used for biological
experiments. And extracting data from the bio-chips with high
accuracy and finding out the patterns or useful information from such
data is very important. Bio-chip analysis systems extract data from
various kinds of bio-chips and mine the data in order to get useful
information. One of the commonly used methods to mine the data is
classification. The algorithm that is used to classify the data can be
various depending on the data types or number characteristics and so
on. Considering that bio-chip data is extremely large, an algorithm that
imitates the ecosystem such as the ant algorithm is suitable to use as an
algorithm for classification. This paper focuses on finding the
classification rules from the bio-chip data using the Ant Colony
algorithm which imitates the ecosystem. The developed system takes
in consideration the accuracy of the discovered rules when it applies it
to the bio-chip data in order to predict the classes.
Abstract: LDPC codes could be used in magnetic storage devices because of their better decoding performance compared to other error correction codes. However, their hardware implementation results in large and complex decoders. This one of the main obstacles the decoders to be incorporated in magnetic storage devices. We construct small high girth and rate 2 columnweight codes from cage graphs. Though these codes have low performance compared to higher column weight codes, they are easier to implement. The ease of implementation makes them more suitable for applications such as magnetic recording. Cages are the smallest known regular distance graphs, which give us the smallest known column-weight 2 codes given the size, girth and rate of the code.
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: Giving birth is a natural process and most women have to go through it. Gynecologist or Midwife usually uses the leg holder to position the cervix in the stitching process. In some part of rural areas in Indonesia, the labor process normally being done at homes by calling in a midwife or gynecologist. The facilities for this kind of labor process is not yet sufficient, as the use of leg holder supposedly on the obstetric bed. The reality is that it is impossible to bring in the obstetric bed to the patient-s house at the time they call for giving birth or the time when the stitching of the cervix need to be done. This research is redesigning the leg holder through Biomechanics and ergonomic approaches to obtain the optimal design which is suitable to the user of a developing country such as Indonesia.
Abstract: The remediation of water resources pollution in
developing countries requires the application of alternative
sustainable cheaper and efficient end-of-pipe wastewater treatment
technologies. The feasibility of use of South African cheap and
abundant pine tree (Pinus patula) sawdust for development of lowcost
AC of comparable quality to expensive commercial ACs in the
abatement of water pollution was investigated. AC was developed at
optimized two-stage N2-superheated steam activation conditions in a
fixed bed reactor, and characterized for proximate and ultimate
properties, N2-BET surface area, pore size distribution, SEM, pHPZC
and FTIR. The sawdust pyrolysis activation energy was evaluated by
TGA. Results indicated that the chars prepared at 800oC and 2hrs
were suitable for development of better quality AC at 800oC and 47%
burn-off having BET surface area (1086m2/g), micropore volume
(0.26cm3/g), and mesopore volume (0.43cm3/g) comparable to
expensive commercial ACs, and suitable for water contaminants
removal. The developed AC showed basic surface functionality at
pHPZC at 10.3, and a phenol adsorption capacity that was higher than
that of commercial Norit (RO 0.8) AC. Thus, it is feasible to develop
better quality low-cost AC from (Pinus patula) sawdust using twostage
N2-steam activation in fixed-bed reactor.
Abstract: Grid computing is growing rapidly in the distributed
heterogeneous systems for utilizing and sharing large-scale resources
to solve complex scientific problems. Scheduling is the most recent
topic used to achieve high performance in grid environments. It aims
to find a suitable allocation of resources for each job. A typical
problem which arises during this task is the decision of scheduling. It
is about an effective utilization of processor to minimize tardiness
time of a job, when it is being scheduled. This paper, therefore,
addresses the problem by developing a general framework of grid
scheduling using dynamic information and an ant colony
optimization algorithm to improve the decision of scheduling. The
performance of various dispatching rules such as First Come First
Served (FCFS), Earliest Due Date (EDD), Earliest Release Date
(ERD), and an Ant Colony Optimization (ACO) are compared.
Moreover, the benefit of using an Ant Colony Optimization for
performance improvement of the grid Scheduling is also discussed. It
is found that the scheduling system using an Ant Colony
Optimization algorithm can efficiently and effectively allocate jobs
to proper resources.
Abstract: With increasing utilization of the wireless devices in
different fields such as medical devices and industrial fields, the
paper presents a method for simplify the Bluetooth packets with
throughput enhancing. The paper studies a vital issue in wireless
communications, which is the throughput of data over wireless
networks. In fact, the Bluetooth and ZigBee are a Wireless Personal
Area Network (WPAN). With taking these two systems competition
consideration, the paper proposes different schemes for improve the
throughput of Bluetooth network over a reliable channel. The
proposition depends on the Channel Quality Driven Data Rate
(CQDDR) rules, which determines the suitable packet in the
transmission process according to the channel conditions. The
proposed packet is studied over additive White Gaussian Noise
(AWGN) and fading channels. The Experimental results reveal the
capability of extension of the PL length by 8, 16, 24 bytes for classic
and EDR packets, respectively. Also, the proposed method is suitable
for the low throughput Bluetooth.
Abstract: The Bayesian Optimization Algorithm (BOA) is an algorithm based on the estimation of distributions. It uses techniques from modeling data by Bayesian networks to estimating the joint distribution of promising solutions. To obtain the structure of Bayesian network, different search algorithms can be used. The key point that BOA addresses is whether the constructed Bayesian network could generate new and useful solutions (strings), which could lead the algorithm in the right direction to solve the problem. Undoubtedly, this ability is a crucial factor of the efficiency of BOA. Varied search algorithms can be used in BOA, but their performances are different. For choosing better ones, certain suitable method to present their ability difference is needed. In this paper, a greedy search algorithm and a stochastic search algorithm are used in BOA to solve certain optimization problem. A method using Kullback-Leibler (KL) Divergence to reflect their difference is described.
Abstract: The objective of this research was to find the
relationship between auspicious meaning in eastern wisdom and the
interpretation as a guideline for the design and development of
community souvenirs. The sample group included 400 customers in
Bangkok who used to buy community souvenir products. The
information was applied to design the souvenirs which were
considered for the appropriateness by 5 design specialists. The data
were analyzed to find frequency, percentage, and SD with the results
as follows. 1) The best factor referring to the auspicious meaning is
color. The application of auspicious meaning can make the value
added to the product and bring the fortune to the receivers. 2) The
effectiveness of the auspicious meaning integration on the design of
community souvenir product was in high level. When considering in
each aspect, it was found that the interpretation aspect was in high
level, the congruency of the auspicious meaning and the utility of the
product was in high level. The attractiveness and the good design
were in very high level while the potential of the value added in the
product design was in high level. The suitable application to the
design of community souvenir product was in high level.
Abstract: This paper discusses the classification process for medical data. In this paper, we use the data from ACM KDDCup 2008 to demonstrate our classification process based on latent topic discovery. In this data set, the target set and outliers are quite different in their nature: target set is only 0.6% size in total, while the outliers consist of 99.4% of the data set. We use this data set as an example to show how we dealt with this extremely biased data set with latent topic discovery and noise reduction techniques. Our experiment faces two major challenge: (1) extremely distributed outliers, and (2) positive samples are far smaller than negative ones. We try to propose a suitable process flow to deal with these issues and get a best AUC result of 0.98.
Abstract: Open urban public spaces comprise an important
element for the development of social, cultural and economic
activities of the population in the modern cities. These spaces are also
considered regulators of the region-s climate conditions, providing
better thermal, visual and auditory conditions which can be optimized
by the application of appropriate strategies of bioclimatic design. The
paper focuses on the analysis and evaluation of the recent unification
of the open spaces in the centre of Xanthi, a medium – size city in
northern Greece, from a bioclimatic perspective, as well as in the
creation of suitable methodology. It is based both on qualitative
observation of the interventions by fieldwork research and
assessment and on quantitative analysis and modeling of the research
area.
Abstract: This paper proposes a novel architecture for At-
Home medical care which enables senior citizens, patients
with chronic ailments and patients requiring post- operative
care to be remotely monitored in the comfort of their homes.
This architecture is implemented using sensors and wireless
networking for transmitting patient data to the hospitals,
health- care centers for monitoring by medical professionals.
Patients are equipped with sensors to measure their
physiological parameters, like blood pressure, pulse rate etc.
and a Wearable Data Acquisition Unit is used to transmit the
patient sensor data. Medical professionals can be alerted to
any abnormal variations in these values for diagnosis and
suitable treatment. Security threats and challenges inherent to
wireless communication and sensor network have been
discussed and a security mechanism to ensure data
confidentiality and source authentication has been proposed.
Symmetric key algorithm AES has been used for encrypting
the data and a patent-free, two-pass block cipher mode CCFB
has been used for implementing semantic security.
Abstract: Shipping comb is mounted on Head Stack Assembly
(HSA) to prevent collision of the heads, maintain the gap between
suspensions and protect HSA tips from unintentional contact
damaged in the manufacturing process. Failure analysis of shipping
comb in hard disk drive production processes is proposed .Field
observations were performed to determine the fatal areas on shipping
comb and their failure fraction. Root cause failure analysis (RCFA) is
applied to specify the failure causes subjected to various loading
conditions. For reliability improvement, failure mode and effects
analysis (FMEA) procedure to evaluate the risk priority is performed.
Consequently, the more suitable information design criterions were
obtained.