Abstract: The hydrologic time series data display periodic
structure and periodic autoregressive process receives considerable
attention in modeling of such series. In this communication long
term record of monthly waste flow of Lyari river is utilized to
quantify by using PAR modeling technique. The parameters of
model are estimated by using Frances & Paap methodology. This
study shows that periodic autoregressive model of order 2 is the most
parsimonious model for assessing periodicity in waste flow of the
river. A careful statistical analysis of residuals of PAR (2) model is
used for establishing goodness of fit. The forecast by using proposed
model confirms significance and effectiveness of the model.
Abstract: A model based fault detection and diagnosis
technique for DC motor is proposed in this paper. Fault detection
using Kalman filter and its different variants are compared. Only
incipient faults are considered for the study. The Kalman Filter
iterations and all the related computations required for fault detection
and fault confirmation are presented. A second order linear state
space model of DC motor is used for this work. A comparative
assessment of the estimates computed from four different observers
and their relative performance is evaluated.
Abstract: Where renewable energy sources, solar, hydro, wind are available the remote communities and businesses can be provided with the most reliable and affordable source of electrical energy. This paper presents a model of safari rest contains all the necessary services for the interested tourists who visit the safari Sinai desert. The PV energy system provides the rural energy needs of remote communities. A photovoltaic renewable energy system is designed to feed the global Ac and Dc electrical required load of this safari rest . The benefits of photovoltaic renewable energy at rural applications are its versatility and convenience. This model of safari rest must be taken in consideration by Egyptian Government as it will provide the tourism plane by new interested tourism field which put a big spot on Red sea area: El Ghordaka.
Abstract: In this paper we propose a new approach to constructing the Delaunay Triangulation and the optimum algorithm for the case of multidimensional spaces (d ≥ 2). Analysing the modern state, it is possible to draw a conclusion, that the ideas for the existing effective algorithms developed for the case of d ≥ 2 are not simple to generalize on a multidimensional case, without the loss of efficiency. We offer for the solving this problem an effective algorithm that satisfies all the given requirements. But theoretical complexity of the problem it is impossible to improve as the Worst - Case Optimality for algorithms of solving such a problem is proved.
Abstract: Modern spatial database management systems require a unique Spatial Access Method (SAM) in order solve complex spatial quires efficiently. In this case the spatial data structure takes a prominent place in the SAM. Inadequate data structure leads forming poor algorithmic choices and forging deficient understandings of algorithm behavior on the spatial database. A key step in developing a better semantic spatial object data structure is to quantify the performance effects of semantic and outlier detections that are not reflected in the previous tree structures (R-Tree and its variants). This paper explores a novel SSRO-Tree on SAM to the Topo-Semantic approach. The paper shows how to identify and handle the semantic spatial objects with outlier objects during page overflow/underflow, using gain/loss metrics. We introduce a new SSRO-Tree algorithm which facilitates the achievement of better performance in practice over algorithms that are superior in the R*-Tree and RO-Tree by considering selection queries.
Abstract: With the increasing spread of computers and the internet among culturally, linguistically and geographically diverse communities, issues of internationalization and localization and becoming increasingly important. For some of the issues such as different scales for length and temperature, there is a well-developed measurement theory. For others such as date formats no such theory will be possible. This paper fills a gap by developing a measurement theory for a class of scales previously overlooked, based on discrete and interval-valued scales such as spanner and shoe sizes. The paper gives a theoretical foundation for a class of data representation problems.
Abstract: Matrix metalloproteinases (MMP) are a class of
structural and functional related enzymes involved in altering the
natural elements of the extracellular matrix. Most of the MMP
structures are cristalographycally determined and published in
WorldWide ProteinDataBank, isolated, in full structure or bound to
natural or synthetic inhibitors. This study proposes an algorithm to
replace missing crystallographic structures in PDB database. We
have compared the results of a chosen docking algorithm with a
known crystallographic structure in order to validate enzyme sites
reconstruction there where crystallographic data are missing.
Abstract: In this paper we present a novel approach for density estimation. The proposed approach is based on using the logistic regression model to get initial density estimation for the given empirical density. The empirical data does not exactly follow the logistic regression model, so, there will be a deviation between the empirical density and the density estimated using logistic regression model. This deviation may be positive and/or negative. In this paper we use a linear combination of Gaussian (LCG) with positive and negative components as a model for this deviation. Also, we will use the expectation maximization (EM) algorithm to estimate the parameters of LCG. Experiments on real images demonstrate the accuracy of our approach.
Abstract: The degradation of selected pharmaceuticals in some
water matrices was studied by using several chemical treatments. The
pharmaceuticals selected were the beta-blocker metoprolol, the
nonsteroidal anti-inflammatory naproxen, the antibiotic amoxicillin,
and the analgesic phenacetin; and their degradations were conducted
by using UV radiation alone, ozone, Fenton-s reagent, Fenton-like
system, photo-Fenton system, and combinations of UV radiation and
ozone with H2O2, TiO2, Fe(II), and Fe(III). The water matrices, in
addition to ultra-pure water, were a reservoir water, a groundwater,
and two secondary effluents from two municipal WWTP. The results
reveal that the presence of any second oxidant enhanced the
oxidation rates, with the systems UV/TiO2 and O3/TiO2 providing the
highest degradation rates. It is also observed in most of the
investigated oxidation systems that the degradation rate followed the
sequence: amoxicillin > naproxen > metoprolol > phenacetin. Lower
rates were obtained with the pharmaceuticals dissolved in natural
waters and secondary effluents due to the organic matter present
which consume some amounts of the oxidant agents.
Abstract: Kojic acid is an organic acid that is widely used as an ingredient for dermatological products, precursor for flavor enhancer and also as anti-inflammatory drug. The present study was undertaken to test the feasibility of pineapple residues as substrate for kojic acid production by Aspergillus flavus Link 44-1 via solid-state fermentation. The effect of initial moisture content, pH and incubation time on kojic acid fermentation was investigated. The best initial moisture content for kojic acid production from pineapple residues was observed at 70% (v/w) whereas initial culture pH 2.5 was identified to give high production of kojic acid. The optimal range of incubation time was identified between 8 and 14 days of incubation which corresponded to highest range of kojic acid produced. The results from this study pronounce the promising usability of pineapple residues as alternative substrate for kojic acid production by A. flavus Link 44-1.
Abstract: Laser engraving is a manufacturing method for those applications where previously Electrical Discharge Machining (EDM) was the only choice. Laser engraving technology removes material layer-by-layer and the thickness of layers is usually in the range of few microns. The aim of the present work is to investigate the influence of the process parameters on the surface quality when machined by laser engraving. The examined parameters were: the pulse frequency, the beam speed and the layer thickness. The surface quality was determined by the surface roughness for every set of parameters. Experimental results on Al7075 material showed that the surface roughness strictly depends on the process parameters used.
Abstract: As the network based technologies become
omnipresent, demands to secure networks/systems against threat
increase. One of the effective ways to achieve higher security is
through the use of intrusion detection systems (IDS), which are a
software tool to detect anomalous in the computer or network. In this
paper, an IDS has been developed using an improved machine
learning based algorithm, Locally Linear Neuro Fuzzy Model
(LLNF) for classification whereas this model is originally used for
system identification. A key technical challenge in IDS and LLNF
learning is the curse of high dimensionality. Therefore a feature
selection phase is proposed which is applicable to any IDS. While
investigating the use of three feature selection algorithms, in this
model, it is shown that adding feature selection phase reduces
computational complexity of our model. Feature selection algorithms
require the use of a feature goodness measure. The use of both a
linear and a non-linear measure - linear correlation coefficient and
mutual information- is investigated respectively
Abstract: This paper presents a software quality support tool, a
Java source code evaluator and a code profiler based on
computational intelligence techniques. It is Java prototype software
developed by AI Group [1] from the Research Laboratories at
Universidad de Palermo: an Intelligent Java Analyzer (in Spanish:
Analizador Java Inteligente, AJI). It represents a new approach to
evaluate and identify inaccurate source code usage and transitively,
the software product itself.
The aim of this project is to provide the software development
industry with a new tool to increase software quality by extending
the value of source code metrics through computational intelligence.
Abstract: Buildings with floating column are highly undesirable built in seismically active areas. Many urban multi-storey buildings today have floating column buildings which are adopted to accommodate parking at ground floor or reception lobbies in the first storey. The earthquake forces developed at different floor levels in a building need to be brought down along the height to the ground by the shortest path; any deviation or discontinuity in this load transfer path results in poor performance of the building. Floating column buildings are severely damaged during earthquake. Damage on this structure can be reduce by taking the effect of infill wall. This paper presents the effect of stiffness of infill wall to the damage occurred in floating column building when ground shakes. Modelling and analysis are carried out by non linear analysis programme IDARC-2D. Damage occurred in beams, columns, storey are studied by formulating modified Park & Ang model to evaluate damage indices. Overall structural damage indices in buildings due to shaking of ground are also obtained. Dynamic response parameters i.e. lateral floor displacement, storey drift, time period, base shear of buildings are obtained and results are compared with the ordinary moment resisting frame buildings. Formation of cracks, yield, plastic hinge, are also observed during analysis.
Abstract: In this paper, we propose an efficient hierarchical DNA
sequence search method to improve the search speed while the
accuracy is being kept constant. For a given query DNA sequence,
firstly, a fast local search method using histogram features is used as a
filtering mechanism before scanning the sequences in the database.
An overlapping processing is newly added to improve the robustness
of the algorithm. A large number of DNA sequences with low
similarity will be excluded for latter searching. The Smith-Waterman
algorithm is then applied to each remainder sequences. Experimental
results using GenBank sequence data show the proposed method
combining histogram information and Smith-Waterman algorithm is
more efficient for DNA sequence search.
Abstract: The aim of this study was to develop a dynamic cardiac phantom for quality control in myocardial scintigraphy. The dynamic heart phantom constructed only contained the left ventricle, made of elastic material (latex), comprising two cavities: one internal and one external. The data showed a non-significant variation in the values of left ventricular ejection fraction (LVEF) obtained by varying the heart rate. It was also possible to evaluate the ejection fraction (LVEF) through different arrays of image acquisition and to perform an intercomparison of LVEF by two different scintillation cameras. The results of the quality control tests were satisfactory, showing that they can be used as parameters in future assessments. The new dynamic heart phantom was demonstrated to be effective for use in LVEF measurements. Therefore, the new heart simulator is useful for the quality control of scintigraphic cameras.
Abstract: Access Management is the proactive management of
vehicular access points to land parcels adjacent to all manner of
roadways. Good access management promotes safe and efficient use
of the transportation network. This study attempts to utilize archived
data from the University Technology of Malaysia on-campus area to
assess the accuracy with which access management display some
benefits. Results show that usage of access management reduces
delay and fewer crashes. Clustered development can improve
walking, cycling and transit travel, reduce parking requirements and
improve emergency responses. Effective Access Management
planning can also reduce total roadway facility costs by reducing the
number of driveways and intersections. At the end after presenting
recommendations some of the travel impact, and benefits that
can be derived if these suggestions are implemented have
been summarized with the related comments.
Abstract: This study examines knowledge management in the public organizations in Iran. The purpose of this article is to provide a conceptual framework for application of knowledge management in public organizations. The study indicates that an increasing tendency for implementation of knowledge management in organizations is emerging. Nonetheless knowledge management in public organizations is toddler and little has been done to bring the subject to use in the public sector. The globalization of change and popularization of some values like participation, citizen-orientation and knowledge-orientation in the new theories of public administration requires that the knowledge management is considered and attend to in the public sector. This study holds that a knowledge management framework for public organizations is different from this in the public sector, because public sector is stakeholder-dependent while the private is shareholder-dependent. Based on the research, we provide a conceptual model. The model proposed involves three factors: Organizational, knowledge citizens and contextual factors. The study results indicate these factors affect on knowledge management in public organizations in Iran.
Abstract: This paper addresses the problem of recognizing and
interpreting the behavior of human workers in industrial
environments for the purpose of integrating humans in software
controlled manufacturing environments. In this work we propose a
generic concept in order to derive solutions for task-related manual
production applications. Thus, we are able to use a versatile concept
providing flexible components and being less restricted to a specific
problem or application. We instantiate our concept in a spot welding
scenario in which the behavior of a human worker is interpreted
when performing a welding task with a hand welding gun. We
acquire signals from inertial sensors, video cameras and triggers and
recognize atomic actions by using pose data from a marker based
video tracking system and movement data from inertial sensors.
Recognized atomic actions are analyzed on a higher evaluation level
by a finite state machine.
Abstract: In this paper we describe the recognition process of Greek compound words using the PC-KIMMO software. We try to show certain limitations of the system with respect to the principles of compound formation in Greek. Moreover, we discuss the computational processing of phenomena such as stress and syllabification which are indispensable for the analysis of such constructions and we try to propose linguistically-acceptable solutions within the particular system.