Abstract: The present study has been carried out with a view to calculate the coastal vulnerability index (CVI) to know the high and low sensitive areas and area of inundation due to future SLR. Both conventional and remotely sensed data were used and analyzed through the modelling technique. Out of the total study area, 8.26% is very high risk, 14.21% high, 9.36% medium, 22.46% low and 7.35% in the very low vulnerable category, due to costal components. Results of the inundation analysis indicate that 225.2 km² and 397 km² of the land area will be submerged by flooding at 1m and 10m inundation levels. The most severely affected sectors are expected to be the residential, industrial and recreational areas. As this coast is planned for future coastal developmental activities, measures such as industrializations, building regulation, urban growth planning and agriculture, development of an integrated coastal zone management, strict enforcement of the Coastal Regulation Zone (CRZ) Act, monitoring of impacts and further research in this regard are recommended for the study area.
Abstract: The oil and gas industry has moved towards Load and
Resistance Factor Design through API RP2A - LRFD and the
recently published international standard, ISO-19902, for design of
fixed steel offshore structures. The ISO 19902 is intended to provide
a harmonized design practice that offers a balanced structural fitness
for the purpose, economy and safety. As part of an ongoing work, the
reliability analysis of tubular joints of the jacket structure has been
carried out to calibrate the load and resistance factors for the design
of offshore platforms in Malaysia, as proposed in the ISO.
Probabilistic models have been established for the load effects (wave,
wind and current) and the tubular joints strengths. In this study the
First Order Reliability Method (FORM), coded in MATLAB
Software has been employed to evaluate the reliability index of the
typical joints, designed using API RP2A - WSD and ISO 19902.
Abstract: In this paper, we propose a novel improvement for the generalized Lloyd Algorithm (GLA). Our algorithm makes use of an M-tree index built on the codebook which makes it possible to reduce the number of distance computations when the nearest code words are searched. Our method does not impose the use of any specific distance function, but works with any metric distance, making it more general than many other fast GLA variants. Finally, we present the positive results of our performance experiments.
Abstract: In the last few years, three multivariate spectral
analysis techniques namely, Principal Component Analysis (PCA),
Independent Component Analysis (ICA) and Non-negative Matrix
Factorization (NMF) have emerged as effective tools for oscillation
detection and isolation. While the first method is used in determining
the number of oscillatory sources, the latter two methods
are used to identify source signatures by formulating the detection
problem as a source identification problem in the spectral domain.
In this paper, we present a critical drawback of the underlying linear
(mixing) model which strongly limits the ability of the associated
source separation methods to determine the number of sources
and/or identify the physical source signatures. It is shown that the
assumed mixing model is only valid if each unit of the process gives
equal weighting (all-pass filter) to all oscillatory components in its
inputs. This is in contrast to the fact that each unit, in general, acts
as a filter with non-uniform frequency response. Thus, the model
can only facilitate correct identification of a source with a single
frequency component, which is again unrealistic. To overcome
this deficiency, an iterative post-processing algorithm that correctly
identifies the physical source(s) is developed. An additional issue
with the existing methods is that they lack a procedure to pre-screen
non-oscillatory/noisy measurements which obscure the identification
of oscillatory sources. In this regard, a pre-screening procedure
is prescribed based on the notion of sparseness index to eliminate
the noisy and non-oscillatory measurements from the data set used
for analysis.
Abstract: Knowing the geometrical object pose of products in manufacturing line before robot manipulation is required and less time consuming for overall shape measurement. In order to perform it, the information of shape representation and matching of objects is become required. Objects are compared with its descriptor that conceptually subtracted from each other to form scalar metric. When the metric value is smaller, the object is considered closed to each other. Rotating the object from static pose in some direction introduce the change of value in scalar metric value of boundary information after feature extraction of related object. In this paper, a proposal method for indexing technique for retrieval of 3D geometrical models based on similarity between boundaries shapes in order to measure 3D CAD object pose using object shape feature matching for Computer Aided Testing (CAT) system in production line is proposed. In experimental results shows the effectiveness of proposed method.
Abstract: In this study a clustering technique has been implemented which is K-Means like with hierarchical initial set (HKM). The goal of this study is to prove that clustering document sets do enhancement precision on information retrieval systems, since it was proved by Bellot & El-Beze on French language. A comparison is made between the traditional information retrieval system and the clustered one. Also the effect of increasing number of clusters on precision is studied. The indexing technique is Term Frequency * Inverse Document Frequency (TF * IDF). It has been found that the effect of Hierarchical K-Means Like clustering (HKM) with 3 clusters over 242 Arabic abstract documents from the Saudi Arabian National Computer Conference has significant results compared with traditional information retrieval system without clustering. Additionally it has been found that it is not necessary to increase the number of clusters to improve precision more.
Abstract: This paper proposes an innovative approach for the Connection Admission Control (CAC) problem. Starting from an abstract network modelling, the CAC problem is formulated in a technology independent fashion allowing the proposed concepts to be applied to any wireless and wired domain. The proposed CAC is decoupled from the other Resource Management procedures, but cooperates with them in order to guarantee the desired QoS requirements. Moreover, it is based on suitable performance measurements which, by using proper predictors, allow to forecast the domain dynamics in the next future. Finally, the proposed CAC control scheme is based on a feedback loop aiming at maximizing a suitable performance index accounting for the domain throughput, whilst respecting a set of constraints accounting for the QoS requirements.