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This paper presents the application of the Parallel Small Baseline Subset (P-SBAS) algorithm, provided by the Geohazards Exploitation Platform for the precise monitoring of an earth dam's ground deformation using C-band Sentinel-1 data. The test site object of this study was the Kramis dam, located in the Mostaganem State, Western Algeria. Among the multiple advanced DInSAR techniques, SBAS is very adequate for long-term displacement monitoring in areas with changing terrain and vegetation. Ten corner reflectors were installed as a backscattered radar signal amplification tool to reduce the effect of temporal decorrelation and delineate the dam area. Four Sentinel-1 A and B satellite tracks were available (T30, T37, T103, and T110) to measure displacements, in the Line of Site (LoS) direction, for two years since the installation of the CRs in July 2019. The results showed a subsiding area on the left bank of the dam dike, with a velocity of 4mm/yr, and an uplifting rate of 3-4mm/yr in the upper part of the dike. The entire 3- dimensional vector of displacement of the dam vicinity was estimated using the least-squares method, proving a better understanding of the dam's temporal deformation, particularly for dams with a high exposure factor and associated risk. [ABSTRACT FROM AUTHOR]

This paper, studies the class of diffusion processes generated by a first-order continuous-time bilinear processes (COBL(1, 1)) with time-varying coefficients. So, we used the It o ̂ formula approach for examining the L 2 − structure of the process and its powers. In time-invariant case, an expression of the moments of any order are given and the continuous autoregressive (C A R) representation of such version is given, in particular the moments properties of some specifications are however derived. Based on these results we are able to examine the statistical properties as well as we develop an estimation method of the process via the so-called Yule-Walker (YW) type algorithm which relates with unknown parameters of CAR representation. The method is illustrated by a Monte Carlo study and applied to modeling the electricity consumption sampled at each 15 mn in Algeria. [ABSTRACT FROM AUTHOR]

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With the increasing amount of medical data available on the Web, looking for health information has become one of the most widely searched topics on the Internet. Patients and people of several backgrounds are now using Web search engines to acquire medical information, including information about a specific disease, medical treatment or professional advice. Nonetheless, due to a lack of medical knowledge, many laypeople have difficulties in forming appropriate queries to articulate their inquiries, which deem their search queries to be imprecise due the use of unclear keywords. The use of these ambiguous and vague queries to describe the patients' needs has resulted in a failure of Web search engines to retrieve accurate and relevant information. One of the most natural and promising method to overcome this drawback is Query Expansion. In this paper, an original approach based on Bat Algorithm is proposed to improve the retrieval effectiveness of query expansion in medical field. In contrast to the existing literature, the proposed approach uses Bat Algorithm to find the best expanded query among a set of expanded query candidates, while maintaining low computational complexity. Moreover, this new approach allows the determination of the length of the expanded query empirically. Numerical results on MEDLINE, the on-line medical information database, show that the proposed approach is more effective and efficient compared to the baseline. [ABSTRACT FROM AUTHOR]

In this paper, we suggest a novel method for ECG baseline correction, exclusively based on pattern recognition tools, namely, dominant points (DPs). The DPs are computed by the Douglas-Peucker curve simplification algorithm. The so-computed DPs include peak and baseline points, the discrimination of which yields gradual piecewise linear estimation of the baseline wander (BaselineW) in two iterations. At each iteration, the current BaselineW is subtracted from the input signal according to the decomposition scheme: ECG approximately ECG(ZBLW) + BaselineW, where ECG(ZBLW) is the underlying baseline wander free ECG. The method targets many types of baseline deviations in a unified approach: baseline drift due to respiration, amplitude modulation due to perspiration and abrupt potential change due to electrode loose contact. We tested the developed method on a variety of ECG records including half synthesized records contaminated with different types of baseline deviations (simulated) noise, and on records from the MITBIH database presenting important baseline deviations, including normal and abnormal heart beats cases. The method showed good performance in computing a piecewise linear estimation of the baseline deviation and in extracting the ECG(ZBLW), which represents the clinically significant electrocardiogram information.

Copyright of Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ) is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper we use the backstepping approach to control climate parameters of greenhouse simulated trough effect of real weather data collected in the south region of Algeria (Biskra) for the period of June 2008. The greenhouse model is a sixth order nonlinear multivariable system. We consider the control of both temperature, relative humidity, CO2 concentration by acting on four control variables such as heating, ventilation, CO2 injection and water injection. To get an optimal controller, we try to solve a multi-objective problem. The multi- objective genetic algorithms based on Non dominated Sorting Genetic Algorithms (NSGA) techniques are used to get a set of optimal controllers. To choose one controller from the above set, we take into account the application of the Multi-Criteria Decision Analysis (MCDA) approach. [ABSTRACT FROM AUTHOR]

Abstract: The main objective of this study is the characterization of meteorological conditions in the region of Annaba (Algeria) using clustering tools. The proposed two stages clustering approach is based on using the Self-Organizing Maps (SOMs) and the well known K-means clustering algorithm. Quantitative (using two categories of validity indices) and qualitative criteria were introduced to compare and verify the correctness of the results. The different experiments developed, extracted five classes, which were related to typical meteorological conditions in the area. The obtained meteorological clusters are then used to better elucidate the dependency of meteorology on air quality in the presence of seven measured pollutants. In the current paper, Artificial Neural Networks (ANNs), and more precisely, Multi-Layered Perceptron (MLP) is used for modeling air pollutants, as well as, simulating their behaviour in relation to the meteorological parameters of interest. This behaviour is also investigated with the aid of correlation coefficient, where only results are shown for comparison, several relations and conclusions have been drawn. [Copyright &y& Elsevier]

Summary: In this article, an optimal design model using metaheuristic techniques to overcome such difficult optimization problems has been proposed. For this purpose, various well‐known metaheuristic algorithms have been used, namely: ant lion optimizer (ALO), bat algorithm (BA), cuckoo search algorithm (CSA), and gray wolf optimization algorithm (GWO). To provide optimal system configurations, an objective function based on the total net present cost (TNPC) has been specified while taking into account a number of constraints, including the loss of power supply probability (LPSP). The effectiveness of the used algorithms in solving such problem is assessed and their performances compared with each other. To assess the suggested model's effectiveness, a case study has been conducted to investigate a stand‐alone photovoltaic water pumping system (PVWPS), designed to supply water to a one‐hectare field of date palm trees. This field of an oasis located in the Ghardaïa region of Algeria consists of 130 date palm trees spaced 9 m apart. The simulation results show the effectiveness of the GWO algorithm over the other algorithms. GWO converges toward the optimal solutions for different heads and all reliability levels required by the customer. Another aspect, supported by the developed methodology, is the accounting of the excess water volume. It has been found that the relative surplus is inversely proportional to the PVWPS reliability level. For a head of 30 m, the relative excess is estimated at 120% for LPS0%, while it is 27% for LPSP of 10%. The same observations are made for the other heads. [ABSTRACT FROM AUTHOR]