Techno-economic Analysis of a Wind-Diesel Hybrid Power System in the South Algeria

The electrical energy is often produced with the help of diesel generators in isolated areas in the Saharan region. While the latter requiring relatively little investment because is generally expensive to exploit due to the transportation to remote areas adds extra cost, significant fuel consumption and relatively high maintenance cost, etc. Moreover, the electricity production by the diesel is ineffective, presents significant environmental risks. But these isolated areas have significant wind energy potential; which is good position for the exploitation of clean and sustainable wind energy. The use of wind-diesel power system is widely recommended especially to reduce fuel consumption and in this way to reduce system operating costs and environmental impact. The subject of this paper is to present the techno-economic analysis of a wind-diesel hybrid power system. In this context, the contribution envisaged with this research is to collaborate on the optimal design of a hybrid power system including a wind turbine generator, a diesel generator and an energy storage system for powering a continuous way an isolated site in the South Algerian installed power of 120 kW.This system has a high control strategy for the management of different power sources (wind, diesel, battery) that depending to weather conditions, especially wind speed values and the power demanded by the consumer load

Seroprevalence of and associated risk factors for Leptospira interrogans serovar Hardjo infection of cattle in Setif, Algeria

Background: Leptospirosis is a cosmopolitan zoonosis caused by Leptospira interrogans responsible for heavy loss both economically and in health, in humans and animals. This study was conducted to determine the seroprevalence and risk factors associated with Leptospira interrogans serovar Hardjo infection in cattle in the state of Setif, northeastern Algeria.Methodology: Between the period 2015 and 2019, a total of 48 randomly selected herds of cattle were investigated, and 406 sera from apparently healthy cattle were analyzed using an indirect enzyme-linked immuno-sorbent assay (ELISA). In order to determine possible risk factors related to leptospirosis, a pre-validated questionnaire was administered to herd owners.Results: The herd prevalence of Leptospira interrogans serovar Hardjo was 31.25% (15/48, 95% CI 19.95–45.33) while the cattle prevalence was 5.42% (22/406, 95% CI 3.61–8.07). Multivariable logistic regression analysis showed that the age of cattle between 3 and 6 years (OR = 9.25; p< 0.03), breeding herd size > 20 cows (OR = 13.65; p< 0.01), and semi-intensive management system (OR = 0.21; p< 0,02) were significantly associated with seropositivity to Leptospira interrogans serovar Hardjo.Conclusion: We concluded from this study that Leptospira interrogans serovar Hardjo is circulating among cattle farms in the state of Setif, Algeria. Furthermore, we recommend more studies to be carried out to prove the infectivity and implementation good hygienic practices among cattle farms and people at risk. Keywords: ELISA, herds, questionnaire, leptospirosis, prevalence, Algeri

On Building Maps of Web Pages with a Cellular Automaton

Abstract. We present in this paper a clustering algorithm which is based on a cellular automaton and which aims at displaying a map of web pages. We describe the main principles of methods that build such maps, and the main principles of cellular automata. We show how these principles can be applied to the problem of web pages clustering: the cells, which are organized in a 2D grid, can be either empty or may contain a page. The local transition function of cells favors the creation of groups of similar states (web pages) in neighbouring cells. We then present the visual results obtained with our method on standard data as well as on sets of documents. These documents are thus organized into a visual map which eases the browsing of these pages

AntTree: a New Model for Clustering with Artificial Ants

In this paper we will present a new clustering algorithm for unsupervised learning. It is inspired from the self-assembling behavior observed in real ants where ants progressively become attached to an existing support and then successively to other attached ants. The artificial ants that we have defined will similarly build a tree. Each ant represents one data. The way ants move and build this tree depends on the similarity between the data. We have compared our results to those obtained by the k-means algorithm and by AntClass on numerical databases (either artificial, real, or from the CE.R.I.E.S.). We show that AntTree significantly improves the clustering process

How to Use Ants for Hierarchical Clustering

Abstract. We present in this paper, a new model for document hierarchical clustering, which is inspired from the self-assembly behavior of real ants. We have simulated the way ants build complex structures with different functions by connecting themselves to each other. Ants may thus build ”chains of ants ” or form ”drops of ants”. The artificial ants that we have defined will similarly build a tree. Each ant represents one document. The way ants move, disconnect or connect themselves depends on the similarity between these documents. The result obtained is presented as a hierarchical structure with a series of HTML files with hyperlinks.

Growing Hierarchical Trees for Data Stream Clustering and Visualization

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