Abstract: A computational platform is presented in this
contribution. It has been designed as a virtual laboratory to be used
for exploring optimization algorithms in biological problems. This
platform is built on a blackboard-based agent architecture. As a test
case, the version of the platform presented here is devoted to the
study of protein folding, initially with a bead-like description of the
chain and with the widely used model of hydrophobic and polar
residues (HP model). Some details of the platform design are
presented along with its capabilities and also are revised some
explorations of the protein folding problems with different types of
discrete space. It is also shown the capability of the platform to
incorporate specific tools for the structural analysis of the runs in
order to understand and improve the optimization process.
Accordingly, the results obtained demonstrate that the ensemble of
computational tools into a single platform is worthwhile by itself,
since experiments developed on it can be designed to fulfill different
levels of information in a self-consistent fashion. By now, it is being
explored how an experiment design can be useful to create a
computational agent to be included within the platform. These
inclusions of designed agents –or software pieces– are useful for the
better accomplishment of the tasks to be developed by the platform.
Clearly, while the number of agents increases the new version of the
virtual laboratory thus enhances in robustness and functionality.
Abstract: There are two common types of operational research techniques, optimisation and metaheuristic methods. The latter may be defined as a sequential process that intelligently performs the exploration and exploitation adopted by natural intelligence and strong inspiration to form several iterative searches. An aim is to effectively determine near optimal solutions in a solution space. In this work, a type of metaheuristics called Ant Colonies Optimisation, ACO, inspired by a foraging behaviour of ants was adapted to find optimal solutions of eight non-linear continuous mathematical models. Under a consideration of a solution space in a specified region on each model, sub-solutions may contain global or multiple local optimum. Moreover, the algorithm has several common parameters; number of ants, moves, and iterations, which act as the algorithm-s driver. A series of computational experiments for initialising parameters were conducted through methods of Rigid Simplex, RS, and Modified Simplex, MSM. Experimental results were analysed in terms of the best so far solutions, mean and standard deviation. Finally, they stated a recommendation of proper level settings of ACO parameters for all eight functions. These parameter settings can be applied as a guideline for future uses of ACO. This is to promote an ease of use of ACO in real industrial processes. It was found that the results obtained from MSM were pretty similar to those gained from RS. However, if these results with noise standard deviations of 1 and 3 are compared, MSM will reach optimal solutions more efficiently than RS, in terms of speed of convergence.
Abstract: In this contribution, the use of a new genetic operator is proposed. The main advantage of using this operator is that it is able to assist the evolution procedure to converge faster towards the optimal solution of a problem. This new genetic operator is called ''intuition'' operator. Generally speaking, one can claim that this operator is a way to include any heuristic or any other local knowledge, concerning the problem, that cannot be embedded in the fitness function. Simulation results show that the use of this operator increases significantly the performance of the classic Genetic Algorithm by increasing the convergence speed of its population.
Abstract: This article is devoted to the numerical solution of
large-scale quadratic eigenvalue problems. Such problems arise in
a wide variety of applications, such as the dynamic analysis of
structural mechanical systems, acoustic systems, fluid mechanics,
and signal processing. We first introduce a generalized second-order
Krylov subspace based on a pair of square matrices and two initial
vectors and present a generalized second-order Arnoldi process for
constructing an orthonormal basis of the generalized second-order
Krylov subspace. Then, by using the projection technique and the
refined projection technique, we propose a restarted generalized
second-order Arnoldi method and a restarted refined generalized
second-order Arnoldi method for computing some eigenpairs of largescale
quadratic eigenvalue problems. Some theoretical results are also
presented. Some numerical examples are presented to illustrate the
effectiveness of the proposed methods.
Abstract: Agriculture products are being more demanding in
market today. To increase its productivity, automation to produce
these products will be very helpful. The purpose of this work is to
measure and determine the ripeness and quality of watermelon. The
textures on watermelon skin will be captured using digital camera.
These images will be filtered using image processing technique. All
these information gathered will be trained using ANN to determine
the watermelon ripeness accuracy. Initial results showed that the best
model has produced percentage accuracy of 86.51%, when measured
at 32 hidden units with a balanced percentage rate of training dataset.
Abstract: Architecture as a form of art, whilst actively
developing, finds new methods and conceptions. Currently,
architectural animation is actively developing as a step, successive to
architectural visualization. Interesting vistas of architectural ideas
were discovered by artists of Japanese animation, in which there are
traditional spirits, kami, and imaginary spaces relating to them.
Anime art should be considered abstract painting, another kind of an
architectural workshop, where new architectural ideas are generated.
Abstract: In this paper, a novel approach is presented
for designing multiplier-free state-space digital filters. The
multiplier-free design is obtained by finding power-of-2 coefficients
and also quantizing the state variables to power-of-2
numbers. Expressions for the noise variance are derived for the
quantized state vector and the output of the filter. A “structuretransformation
matrix" is incorporated in these expressions. It
is shown that quantization effects can be minimized by properly
designing the structure-transformation matrix. Simulation
results are very promising and illustrate the design algorithm.
Abstract: Topology Optimization is a defined as the method of
determining optimal distribution of material for the assumed design
space with functionality, loads and boundary conditions [1].
Topology optimization can be used to optimize shape for the
purposes of weight reduction, minimizing material requirements or
selecting cost effective materials [2]. Topology optimization has been
implemented through the use of finite element methods for the
analysis, and optimization techniques based on the method of moving
asymptotes, genetic algorithms, optimality criteria method, level sets
and topological derivatives. Case study of Typical “Fuselage design"
is considered for this paper to explain the benefits of Topology
Optimization in the design cycle. A cylindrical shell is assumed as
the design space and aerospace standard pay loads were applied on
the fuselage with wing attachments as constraints. Then topological
optimization is done using Finite Element (FE) based software. This
optimization results in the structural concept design which satisfies
all the design constraints using minimum material.
Abstract: The objective of this paper is to characterize the spontaneous Electroencephalogram (EEG) signals of four different motor imagery tasks and to show hereby a possible solution for the present binary communication between the brain and a machine ora Brain-Computer Interface (BCI). The processing technique used in this paper was the fractal analysis evaluated by the Critical Exponent Method (CEM). The EEG signal was registered in 5 healthy subjects,sampling 15 measuring channels at 1024 Hz.Each channel was preprocessed by the Laplacian space ltering so as to reduce the space blur and therefore increase the spaceresolution. The EEG of each channel was segmented and its Fractaldimension (FD) calculated. The FD was evaluated in the time interval corresponding to the motor imagery and averaged out for all the subjects (each channel). In order to characterize the FD distribution,the linear regression curves of FD over the electrodes position were applied. The differences FD between the proposed mental tasks are quantied and evaluated for each experimental subject. The obtained results of the proposed method are a substantial fractal dimension in the EEG signal of motor imagery tasks and can be considerably utilized as the multiple-states BCI applications.
Abstract: Sequential pattern mining is a challenging task in data mining area with large applications. One among those applications is mining patterns from weblog. Recent times, weblog is highly dynamic and some of them may become absolute over time. In addition, users may frequently change the threshold value during the data mining process until acquiring required output or mining interesting rules. Some of the recently proposed algorithms for mining weblog, build the tree with two scans and always consume large time and space. In this paper, we build Revised PLWAP with Non-frequent Items (RePLNI-tree) with single scan for all items. While mining sequential patterns, the links related to the nonfrequent items are not considered. Hence, it is not required to delete or maintain the information of nodes while revising the tree for mining updated transactions. The algorithm supports both incremental and interactive mining. It is not required to re-compute the patterns each time, while weblog is updated or minimum support changed. The performance of the proposed tree is better, even the size of incremental database is more than 50% of existing one. For evaluation purpose, we have used the benchmark weblog dataset and found that the performance of proposed tree is encouraging compared to some of the recently proposed approaches.
Abstract: At very high speeds, bubbles form in the underwater vehicles because of sharp trailing edges or of places where the local pressure is lower than the vapor pressure. These bubbles are called cavities and the size of the cavities grows as the velocity increases. A properly designed cavitator can induce the formation of a single big cavity all over the vehicle. Such a vehicle travelling in the vaporous cavity is called a supercavitating vehicle and the present research work mainly focuses on the dynamic modeling of such vehicles. Cavitation of the fins is also accounted and the effect of the same on trajectory is well explained. The entire dynamics has been developed using the state space approach and emphasis is given on the effect of size and angle of attack of the cavitator. Control law has been established for the motion of the vehicle using Non-linear Dynamic Inverse (NDI) with cavitator as the control surface.
Abstract: The 20th century has brought much development to the practice of Architecture worldwide, and technology has bridged inhabitation limits in many regions of the world with high levels of comfort and conveniences, most times at high costs to the environment. Throughout the globe, the tropical countries are being urbanized at an unprecedented rate and housing has become a major issue worldwide, in light of increased demand and lack of appropriate infra-structure and planning. Buildings and urban spaces designed in tropical cities have mainly adopted external concepts that in most cases do not fit the needs of the inhabitants living in such harsh climatic environment, and when they do, do so at high financial, environmental and cultural costs. Traditional architectural practices can provide valuable understanding on how self-reliance and autonomy of construction can be reinforced in rural-urban tropical environments. From traditional housing knowledge, it is possible to derive lessons for the development of new construction materials that are affordable, environmentally friendly, culturally acceptable and accesible to all.Specifically to the urban context, such solutions are of outmost importance, given the needs to a more democratic society, where access to housing is considered high in the agenda for development. Traditional or rural constructions are also ongoing through extensive changes eventhough they have mostly adopted climate-responsive building practices relying on local resources (with minimum embodied energy) and energy (for comfort and quality of life). It is important to note that many of these buildings can actually be called zero-energy, and hold potential answers to enable transition from high energy, high cost, low comfort urban habitations to zero/low energy habitations with high quality urban livelihood. Increasing access to modern urban lifestyels have also an effect on the aspirations from people in terms of performance, comfort and convenience in terms of their housing and the way it is produced and used. These aspirations are resulting in transitions from localresource dependent habitations- to non-local resource based highenergy urban style habitations. And such transitions are resulting in the habitations becoming increasingly unsuited to the local climatic conditions with increasing discomfort, ill-health, and increased CO2 emissions and local environmental disruption. This research studies one specific transition group in the context of 'water communities' in tropical-equatorial regions: Ribeirinhos housing typology (Amazonas, Brazil). The paper presents the results of a qualitative sustainability assessment of the housing typologies under transition, found at the Ribeirinhos communities.
Abstract: The concept of privacy, seen in connection to the consumer's private space and personalization, has recently gained a higher importance as a consequence of the increasing marketing efforts of the organizations based on the capturing, processing and usage of consumer-s personal data.Paper intends to provide a definition of the consumer-s private space based on the types of personal data the consumer is willing to disclose, to assess the attitude toward personalization and to identify the means preferred by consumers to control their personal data and defend their private space. Several implications generated through the definition of the consumer-s private space are identified and weighted from both the consumers- and organizations- perspectives.
Abstract: The fault detection and diagnosis of complicated
production processes is one of essential tasks needed to run the process
safely with good final product quality. Unexpected events occurred in
the process may have a serious impact on the process. In this work,
triangular representation of process measurement data obtained in an
on-line basis is evaluated using simulation process. The effect of using
linear and nonlinear reduced spaces is also tested. Their diagnosis
performance was demonstrated using multivariate fault data. It has
shown that the nonlinear technique based diagnosis method produced
more reliable results and outperforms linear method. The use of
appropriate reduced space yielded better diagnosis performance. The
presented diagnosis framework is different from existing ones in that it
attempts to extract the fault pattern in the reduced space, not in the
original process variable space. The use of reduced model space helps
to mitigate the sensitivity of the fault pattern to noise.
Abstract: In this paper, we use a one-step iteration scheme to approximate common fixed points of two quasi-asymptotically nonexpansive mappings. We prove weak and strong convergence theorems in a uniformly convex Banach space. Our results generalize the corresponding results of Yao and Chen [15] to a wider class of mappings while extend those of Khan, Abbas and Khan [4] to an improved one-step iteration scheme without any condition and improve upon many others in the literature.
Abstract: This paper proposes new hybrid approaches for face
recognition. Gabor wavelets representation of face images is an
effective approach for both facial action recognition and face
identification. Perform dimensionality reduction and linear
discriminate analysis on the down sampled Gabor wavelet faces can
increase the discriminate ability. Nearest feature space is extended to
various similarity measures. In our experiments, proposed Gabor
wavelet faces combined with extended neural net feature space
classifier shows very good performance, which can achieve 93 %
maximum correct recognition rate on ORL data set without any preprocessing
step.
Abstract: Dhaka, the capital city of Bangladesh, is one of the
densely populated cities in the world. Due to rapid urbanization 60%
of its population lives in slum and squatter settlements. The reason
behind this poverty is low economic growth, inequitable distribution
of income, unequal distribution of productive assets, unemployment
and underemployment, high rate of population growth, low level of
human resource development, natural disasters, and limited access to
public services. Along with poverty, creating pressure on urban land,
shelter, plots, open spaces this creates environmental and ecological
degradation. These constraints are mostly resulted from the failures
of the government policies and measures and only Government can
solve this problem. This is now prime time to establish planning and
environmental management policy and sustainable urban
development for the city and for the urban slum dwellers which are
free from eviction, criminals, rent seekers and other miscreants.
Abstract: Most file systems overwrite modified file data and
metadata in their original locations, while the Log-structured File
System (LFS) dynamically relocates them to other locations. We
design and implement the Evergreen file system that can select
between overwriting or relocation for each block of a file or metadata.
Therefore, the Evergreen file system can achieve superior write
performance by sequentializing write requests (similar to LFS-style
relocation) when space utilization is low and overwriting when
utilization is high. Another challenging issue is identifying
performance benefits of LFS-style relocation over overwriting on a
newly introduced SSD (Solid State Drive) which has only
Flash-memory chips and control circuits without mechanical parts.
Our experimental results measured on a SSD show that relocation
outperforms overwriting when space utilization is below 80% and vice
versa.
Abstract: Dynamic models of power converters are normally
time-varying because of their switching actions. Several approaches
are applied to analyze the power converters to achieve the timeinvariant
models suitable for system analysis and design via the
classical control theory. The paper presents how to derive dynamic
models of the power system consisting of a three-phase controlled
rectifier feeding an uncontrolled buck converter by using the
combination between the well known techniques called the DQ and
the generalized state-space averaging methods. The intensive timedomain
simulations of the exact topology model are used to support
the accuracies of the reported model. The results show that the
proposed model can provide good accuracies in both transient and
steady-state responses.
Abstract: In this work, we present for the first time in our
perception an efficient digital watermarking scheme for mpeg audio
layer 3 files that operates directly in the compressed data domain,
while manipulating the time and subband/channel domain. In
addition, it does not need the original signal to detect the watermark.
Our scheme was implemented taking special care for the efficient
usage of the two limited resources of computer systems: time and
space. It offers to the industrial user the capability of watermark
embedding and detection in time immediately comparable to the real
music time of the original audio file that depends on the mpeg
compression, while the end user/audience does not face any artifacts
or delays hearing the watermarked audio file. Furthermore, it
overcomes the disadvantage of algorithms operating in the PCMData
domain to be vulnerable to compression/recompression attacks,
as it places the watermark in the scale factors domain and not in the
digitized sound audio data. The strength of our scheme, that allows it
to be used with success in both authentication and copyright
protection, relies on the fact that it gives to the users the enhanced
capability their ownership of the audio file not to be accomplished
simply by detecting the bit pattern that comprises the watermark
itself, but by showing that the legal owner knows a hard to compute
property of the watermark.