Abstract: Developing a nation geared by the principle of
sustainable development has been one of the piers in moulding a
greater nation for Malaysia since its independence. This is seen by
the act of joining the United Nations in 1957, just a month after
gaining their independence. The United Nations is an international
organization that aims to unite the nations worldwide based on
justice, human dignity and human well-being. Malaysia has
established a local body called the United Nations Malaysia which
collaborates with the government to accomplish the aim of
supporting sustainable development in Malaysia. Agenda 21 is an
international document produced from the Earth Summit providing
guidelines of implementing sustainable development globally,
nationally and locally. Initiatives of applying Agenda 21 in Malaysia
have been taken by the government and non-profit organizations to
expose issues regarding sustainable development and providing
environmental education to the community to increase awareness
towards environmental protection.
Abstract: The lack of security obstructs a large scale de- ployment of the multicast communication model. There- fore, a host of research works have been achieved in order to deal with several issues relating to securing the multicast, such as confidentiality, authentication, non-repudiation, in- tegrity and access control. Many applications require au- thenticating the source of the received traffic, such as broadcasting stock quotes and videoconferencing and hence source authentication is a required component in the whole multicast security architecture. In this paper, we propose a new and efficient source au- thentication protocol which guarantees non-repudiation for multicast flows, and tolerates packet loss. We have simu- lated our protocol using NS-2, and the simulation results show that the protocol allows to achieve improvements over protocols fitting into the same category.
Abstract: Measures of complexity and entropy have not converged to a single quantitative description of levels of organization of complex systems. The need for such a measure is increasingly necessary in all disciplines studying complex systems. To address this problem, starting from the most fundamental principle in Physics, here a new measure for quantity of organization and rate of self-organization in complex systems based on the principle of least (stationary) action is applied to a model system - the central processing unit (CPU) of computers. The quantity of organization for several generations of CPUs shows a double exponential rate of change of organization with time. The exact functional dependence has a fine, S-shaped structure, revealing some of the mechanisms of self-organization. The principle of least action helps to explain the mechanism of increase of organization through quantity accumulation and constraint and curvature minimization with an attractor, the least average sum of actions of all elements and for all motions. This approach can help describe, quantify, measure, manage, design and predict future behavior of complex systems to achieve the highest rates of self organization to improve their quality. It can be applied to other complex systems from Physics, Chemistry, Biology, Ecology, Economics, Cities, network theory and others where complex systems are present.
Abstract: B2E portals represent a new class of web-based
information technologies which many organisations are introducing
in recent years to stay in touch with their distributed workforces and
enable them to perform value added activities for organisations.
However, actual usage of these emerging systems (measured using
suitable instruments) has not been reported in the contemporary
scholarly literature. We argue that many of the instruments to
measure usage of various types of IT-enabled information systems
are not directly applicable for B2E portals because they were
developed for the context of traditional mainframe and PC-based
information systems. It is therefore important to develop a new
instrument for web-based portal technologies aimed at employees. In
this article, we report on the development and initial qualitative
evaluation of an instrument that seeks to operationaise a set of
independent factors affecting the usage of portals by employees. The
proposed instrument is useful to IT/e-commerce researchers and
practitioners alike as it enhances their confidence in predicting
employee usage of portals in organisations.
Abstract: In this study, we consider a special situation that only a pair of hydrophone on a moving underwater vehicle is available to localize a fixed acoustic source of far distance. The trigonometry can be used in this situation by using two different DOA of different locations. Notice that the distance between the two locations should be measured. Therefore, we assume that the vehicle is sailing straightly and the moving distance for each unit time is measured continuously. However, the accuracy of the localization using the trigonometry is highly dependent to the accuracy of DOAs and measured moving distances. Therefore, we proposed another method based on the extended Kalman filter that gives more robust and accurate localization result.
Abstract: This paper presents an ESN-based Arabic phoneme
recognition system trained with supervised, forced and combined
supervised/forced supervised learning algorithms. Mel-Frequency
Cepstrum Coefficients (MFCCs) and Linear Predictive Code (LPC)
techniques are used and compared as the input feature extraction
technique. The system is evaluated using 6 speakers from the King
Abdulaziz Arabic Phonetics Database (KAPD) for Saudi Arabia
dialectic and 34 speakers from the Center for Spoken Language
Understanding (CSLU2002) database of speakers with different
dialectics from 12 Arabic countries. Results for the KAPD and
CSLU2002 Arabic databases show phoneme recognition
performances of 72.31% and 38.20% respectively.
Abstract: In wavelet regression, choosing threshold value is a crucial issue. A too large value cuts too many coefficients resulting in over smoothing. Conversely, a too small threshold value allows many coefficients to be included in reconstruction, giving a wiggly estimate which result in under smoothing. However, the proper choice of threshold can be considered as a careful balance of these principles. This paper gives a very brief introduction to some thresholding selection methods. These methods include: Universal, Sure, Ebays, Two fold cross validation and level dependent cross validation. A simulation study on a variety of sample sizes, test functions, signal-to-noise ratios is conducted to compare their numerical performances using three different noise structures. For Gaussian noise, EBayes outperforms in all cases for all used functions while Two fold cross validation provides the best results in the case of long tail noise. For large values of signal-to-noise ratios, level dependent cross validation works well under correlated noises case. As expected, increasing both sample size and level of signal to noise ratio, increases estimation efficiency.
Abstract: The 15-a-side Fiji rugby team trains well in preparations for any rugby competition but rarely performs to expectations. In order to help the Fiji local based rugby players to identify some key basic areas in improving their performance, a series of workshops were conducted to assess their nutritional status and dietary habits in relation to energy demand during rugby matches. The nutrition workshop included the administration of questionnaires to 19 local based rugby players, requesting the following information: usual food intakes, training camp food intakes, carbohydrate loading, pre-game meals and post-game meals. The study revealed that poor eating habits of the players resulted in the low carbohydrate intake, which may have contributed to increase levels of fatigue leading to loss of stamina even before the second half of the game. It appears that the diet of most 15-a-side players does not provide enough energy to enable them to last the full eightyminutes of the game.
Abstract: Both the minimum energy consumption and
smoothness, which is quantified as a function of jerk, are generally
needed in many dynamic systems such as the automobile and the
pick-and-place robot manipulator that handles fragile equipments.
Nevertheless, many researchers come up with either solely
concerning on the minimum energy consumption or minimum jerk
trajectory. This research paper considers the indirect minimum Jerk
method for higher order differential equation in dynamics
optimization proposes a simple yet very interesting indirect jerks
approaches in designing the time-dependent system yielding an
alternative optimal solution. Extremal solutions for the cost functions
of indirect jerks are found using the dynamic optimization methods
together with the numerical approximation. This case considers the
linear equation of a simple system, for instance, mass, spring and
damping. The simple system uses two mass connected together by
springs. The boundary initial is defined the fix end time and end
point. The higher differential order is solved by Galerkin-s methods
weight residual. As the result, the 6th higher differential order shows
the faster solving time.
Abstract: As a primitive assumption, if a new information
system is able to remind users their old work habits, it should have a
better opportunity to be accepted, adopted and finally, utilized. In
this paper some theoretical concepts borrowed from psychodynamic
theory e.g. ego defenses are discussed to show how such resemblance
can be made without necessarily affecting the performance of the
new system. The main assertion is a new system should somehow
imitate old work habits, not literally, but through following their
paces in terms of the order of habitual tensional states including
stimulation, defensive actions and satisfactions.
Abstract: This paper presents a method for the detection of OD in the retina which takes advantage of the powerful preprocessing techniques such as the contrast enhancement, Gabor wavelet transform for vessel segmentation, mathematical morphology and Earth Mover-s distance (EMD) as the matching process. The OD detection algorithm is based on matching the expected directional pattern of the retinal blood vessels. Vessel segmentation method produces segmentations by classifying each image pixel as vessel or nonvessel, based on the pixel-s feature vector. Feature vectors are composed of the pixel-s intensity and 2D Gabor wavelet transform responses taken at multiple scales. A simple matched filter is proposed to roughly match the direction of the vessels at the OD vicinity using the EMD. The minimum distance provides an estimate of the OD center coordinates. The method-s performance is evaluated on publicly available DRIVE and STARE databases. On the DRIVE database the OD center was detected correctly in all of the 40 images (100%) and on the STARE database the OD was detected correctly in 76 out of the 81 images, even in rather difficult pathological situations.
Abstract: Brassinosteroids (BRs) regulate cell elongation,
vascular differentiation, senescence, and stress responses. BRs signal
through the BES1/BZR1 family of transcription factors, which
regulate hundreds of target genes involved in this pathway. In this
research a comprehensive genome-wide analysis was carried out in
BES1/BZR1 gene family in Arabidopsis thaliana, Cucumis sativus,
Vitis vinifera, Glycin max and Brachypodium distachyon.
Specifications of the desired sequences, dot plot and hydropathy plot
were analyzed in the protein and genome sequences of five plant
species. The maximum amino acid length was attributed to protein
sequence Brdic3g with 374aa and the minimum amino acid length
was attributed to protein sequence Gm7g with 163aa. The maximum
Instability index was attributed to protein sequence AT1G19350
equal with 79.99 and the minimum Instability index was attributed to
protein sequence Gm5g equal with 33.22. Aliphatic index of these
protein sequences ranged from 47.82 to 78.79 in Arabidopsis
thaliana, 49.91 to 57.50 in Vitis vinifera, 55.09 to 82.43 in Glycin
max, 54.09 to 54.28 in Brachypodium distachyon 55.36 to 56.83 in
Cucumis sativus. Overall, data obtained from our investigation
contributes a better understanding of the complexity of the
BES1/BZR1 gene family and provides the first step towards directing
future experimental designs to perform systematic analysis of the
functions of the BES1/BZR1 gene family.
Abstract: In this paper we present the deep study about the Bio-
Medical Images and tag it with some basic extracting features (e.g.
color, pixel value etc). The classification is done by using a nearest
neighbor classifier with various distance measures as well as the
automatic combination of classifier results. This process selects a
subset of relevant features from a group of features of the image. It
also helps to acquire better understanding about the image by
describing which the important features are. The accuracy can be
improved by increasing the number of features selected. Various
types of classifications were evolved for the medical images like
Support Vector Machine (SVM) which is used for classifying the
Bacterial types. Ant Colony Optimization method is used for optimal
results. It has high approximation capability and much faster
convergence, Texture feature extraction method based on Gabor
wavelets etc..
Abstract: Biological sequences from different species are called or-thologs if they evolved from a sequence of a common ancestor species and they have the same biological function. Approximations of Kolmogorov complexity or entropy of biological sequences are already well known to be useful in extracting similarity information between such sequences -in the interest, for example, of ortholog detection. As is well known, the exact Kolmogorov complexity is not algorithmically computable. In prac-tice one can approximate it by computable compression methods. How-ever, such compression methods do not provide a good approximation to Kolmogorov complexity for short sequences. Herein is suggested a new ap-proach to overcome the problem that compression approximations may notwork well on short sequences. This approach is inspired by new, conditional computations of Kolmogorov entropy. A main contribution of the empir-ical work described shows the new set of entropy-based machine learning attributes provides good separation between positive (ortholog) and nega-tive (non-ortholog) data - better than with good, previously known alter-natives (which do not employ some means to handle short sequences well).Also empirically compared are the new entropy based attribute set and a number of other, more standard similarity attributes sets commonly used in genomic analysis. The various similarity attributes are evaluated by cross validation, through boosted decision tree induction C5.0, and by Receiver Operating Characteristic (ROC) analysis. The results point to the conclu-sion: the new, entropy based attribute set by itself is not the one giving the best prediction; however, it is the best attribute set for use in improving the other, standard attribute sets when conjoined with them.
Abstract: In this paper, a mathematical model for data object replication in ad hoc networks is formulated. The derived model is general, flexible and adaptable to cater for various applications in ad hoc networks. We propose a game theoretical technique in which players (mobile hosts) continuously compete in a non-cooperative environment to improve data accessibility by replicating data objects. The technique incorporates the access frequency from mobile hosts to each data object, the status of the network connectivity, and communication costs. The proposed technique is extensively evaluated against four well-known ad hoc network replica allocation methods. The experimental results reveal that the proposed approach outperforms the four techniques in both the execution time and solution quality
Abstract: Selected Mapping (SLM) is a PAPR reduction technique, which converts the OFDM signal into several independent signals by multiplication with the phase sequence set and transmits one of the signals with lowest PAPR. But it requires the index of the selected signal i.e. side information (SI) to be transmitted with each OFDM symbol. The PAPR reduction capability of the SLM scheme depends on the selection of phase sequence set. In this paper, we have proposed a new phase sequence set generation scheme based on M-ary chaotic sequence and a mapping scheme to map quaternary data to concentric circle constellation (CCC) is used. It is shown that this method does not require SI and provides better SER performance with good PAPR reduction capability as compared to existing SLMOFDM methods.
Abstract: A novel physico-chemical route to produce few layer graphene nanoribbons with atomically smooth edges is reported, via acid treatment (H2SO4:HNO3) followed by characteristic thermal shock processes involving extremely cold substances. Samples were studied by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman spectroscopy and X-ray photoelectron spectroscopy. This method demonstrates the importance of having the nanotubes open ended for an efficient uniform unzipping along the nanotube axis. The average dimensions of these nanoribbons are approximately ca. 210 nm wide and consist of few layers, as observed by transmission electron microscopy. The produced nanoribbons exhibit different chiralities, as observed by high resolution transmission electron microscopy. This method is able to provide graphene nanoribbons with atomically smooth edges which could be used in various applications including sensors, gas adsorption materials, composite fillers, among others.
Abstract: We considered repeated-root cyclic codes whose
block length is divisible by the characteristic of the underlying field.
Cyclic self dual codes are also the repeated root cyclic codes. It is
known about the one-level squaring construction for binary repeated
root cyclic codes. In this correspondence, we introduced of two
level squaring construction for binary repeated root cyclic codes of
length 2a b , a > 0, b is odd.
Abstract: Biologically human brain processes information in both unimodal and multimodal approaches. In fact, information is progressively abstracted and seamlessly fused. Subsequently, the fusion of multimodal inputs allows a holistic understanding of a problem. The proliferation of technology has exponentially produced various sources of data, which could be likened to being the state of multimodality in human brain. Therefore, this is an inspiration to develop a methodology for exploring multimodal data and further identifying multi-view patterns. Specifically, we propose a brain inspired conceptual model that allows exploration and identification of patterns at different levels of granularity, different types of hierarchies and different types of modalities. A structurally adaptive neural network is deployed to implement the proposed model. Furthermore, the acquisition of multi-view patterns with the proposed model is demonstrated and discussed with some experimental results.
Abstract: Neural processors have shown good results for
detecting a certain character in a given input matrix. In this paper, a
new idead to speed up the operation of neural processors for character
detection is presented. Such processors are designed based on cross
correlation in the frequency domain between the input matrix and the
weights of neural networks. This approach is developed to reduce the
computation steps required by these faster neural networks for the
searching process. The principle of divide and conquer strategy is
applied through image decomposition. Each image is divided into
small in size sub-images and then each one is tested separately by
using a single faster neural processor. Furthermore, faster character
detection is obtained by using parallel processing techniques to test the
resulting sub-images at the same time using the same number of faster
neural networks. In contrast to using only faster neural processors, the
speed up ratio is increased with the size of the input image when using
faster neural processors and image decomposition. Moreover, the
problem of local subimage normalization in the frequency domain is
solved. The effect of image normalization on the speed up ratio of
character detection is discussed. Simulation results show that local
subimage normalization through weight normalization is faster than
subimage normalization in the spatial domain. The overall speed up
ratio of the detection process is increased as the normalization of
weights is done off line.