Flea beetles (Coleoptera: Chrysomelidae: Alticinae) collected by malaise trap method in Gölcük Natural Park (Isparta, Turkey), with a new record for Turkish fauna

This study is based on Alticinae (Coleoptera: Chrysomelidae) material collected by Malaise trapping which is different from other standardized collecting methods. A total of 19 flea beetle species belonging to 6 genera were collected from Gölcük Natural Park, Isparta (Turkey) during 2009. The species are listed in a table together with distributional data in Turkey. Among them, Longitarsus curtus (Allard, 1860) is recorded for the first time in Turkey. L. monticola Kutschera, 1863 and L. curtus are recently separated synonyms and thus all data referring to the distribution of both species are currently important. Hence, the zoogeographical distribution of the new record is reviewed with some remarks; habitus and genitalia are illustrated

Non-parametric comparison of histogrammed two-dimensional data distributions using the Energy Test

When monitoring complex experiments, comparison is often made between regularly acquired histograms of data and reference histograms which represent the ideal state of the equipment. With the larger HEP experiments now ramping up, there is a need for automation of this task since the volume of comparisons could overwhelm human operators. However, the two-dimensional histogram comparison tools available in ROOT have been noted in the past to exhibit shortcomings. We discuss a newer comparison test for two-dimensional histograms, based on the Energy Test of Aslan and Zech, which provides more conclusive discrimination between histograms of data coming from different distributions than methods provided in a recent ROOT release.The Science and Technology Facilities Council, U

A framework for use of wireless sensor networks in forest fire detection and monitoring

Cataloged from PDF version of article.Forest fires are one of the main causes of environmental degradation nowadays. Current surveillance systems for forest fires lack in supporting real-time monitoring of every point of a region at all times and early detection of fire threats. Solutions using wireless sensor networks, on the other hand, can gather sensory data values, such as temperature and humidity, from all points of a field continuously, day and night, and, provide fresh and accurate data to the fire-fighting center quickly. However, sensor networks face serious obstacles like limited energy resources and high vulnerability to harsh environmental conditions, that have to be considered carefully. In this paper, we propose a comprehensive framework for the use of wireless sensor networks for forest fire detection and monitoring. Our framework includes proposals for the wireless sensor network architecture, sensor deployment scheme, and clustering and communication protocols. The aim of the framework is to detect a fire threat as early as possible and yet consider the energy consumption of the sensor nodes and the environmental conditions that may affect the required activity level of the network. We implemented a simulator to validate and evaluate our proposed framework. Through extensive simulation experiments, we show that our framework can provide fast reaction to forest fires while also consuming energy efficiently. (C) 2012 Elsevier Ltd. All rights reserved