This paper deals with image compression over Wireless Camera Sensor Networks (WCSNs) in order to decrease the energy consumption of sensors and thus to maintain a long network lifetime. As the radio tranceiver is the most power greedy components of sensor nodes, it seems natural to consider lossy compression before transmission as the appropriate answer to the problem of energy consumption. However, the limitation of sensor nodes in terms of memory as well as processor speed makes most of the compression algorithms inapplicable. Indeed, the most popular methods such as JPEG or JPEG2000 can yield a higher energy consumption than when transmitting uncompressed images. Here we propose to solve this problem by the design of a fast zonal DCT-based image compression algorithm which allows an efficient tuning of the trade-off between energy consumption and image distortion, as shown by experimental results provided in the paper.

Background: To report survival, spontaneous prognostic factors, and treatment efficacy in a French monocentric cohort of diffuse low-grade glioma (DLGG) patients over 35 years of follow-up.Methods: A monocentric retrospective study of 339 patients diagnosed with a new DLGG between 01/01/1982 and 01/01/2017 was created. Inclusion criteria were patient age ≥18 years at diagnosis and histological diagnosis of WHO grade II glioma (according to 1993(according to , 2007(according to , and 2016. The survival parameters were estimated using the Kaplan-Meier method with a 95% confidence interval. Differences in survival were tested for statistical significance by the log-rank test. Factors were considered significant when p ≤ 0.1 and p ≤ 0.05 in the univariate and multivariate analyses, respectively.Results: A total of 339 patients were included with a median follow-up of 8.7 years. The Kaplan-Meier median overall survival was 15.7 years. At the time of radiological diagnosis, Karnofsky Performance Status score and initial tumor volume were significant independent prognostic factors. Oncological prognostic factors were the extent of resection for patients who underwent surgery and the timing of radiotherapy for those concerned. In this study, patients who had delayed radiotherapy (provided remaining low grade) did not have worse survival compared with patients who had early radiotherapy.

The problem of energy conservation in wireless image sensor networks is addressed, and a fast zonal discrete consine transform (DCT) design which aims to decrease the complexity of JPEG baseline compression is presented. Energy consumption measurements have been made on a real wireless camera node in order to evaluate the amount of energy which can be saved during the image compression process without loss of visual quality. Although the gain depends on the compression rate, such a DCT design is a simple and effective way to prolong the lifetime of the camera nodes, and thereby the network lifetime.Introduction: Wireless sensor networks refer to the large-scale deployment of small, inexpensive, and battery-powered sensing devices with on-board processing and wireless communication capabilities which achieve a self-organised, infrastructure-less, and fault-tolerant sensor network in a cooperative way. Such networks make possible dense monitoring and analysis of complex physical or biological phenomena over large regions of space and over long periods of time (e.g. for months or even years) [1]. Of course, energy conservation is a fundamental concern for achieving the required network lifetime since battery replacement of sensor nodes is often undesirable or impossible. Recently, there is a growing interest in the applications which require image sensing in order to achieve object detection, localisation, tracking, and counting [2]. In this case, all or some of the sensor nodes are equipped with a small CMOS camera, referred to as Wireless Image Sensor Network (WISN). However, WISNs make the energy consumption problem worse owing to the large volumes of data to be transmitted compared to applications dealing with scalar data such as temperature and soil moisture. As the radio transceiver is one of the most power hungry of all electronic components of sensor nodes, lossy compression of image data before transmission seems an appropriate answer to this problem, for the source camera node as well as the nodes forwarding data towards the sink. Unfortunately, most of the compression algorithms, for example JPEG, may perform poorly owing to the resource limitations of sensor nodes in terms of memory size or processor speed, and even sometimes lead to greater energy consumption than in the uncompressed case [3]! For JPEG baseline compression, the energy conservation problem can be dealt with by a zonal DCT approach (also referred to as pruned DCT [4]). In a previous work presented in [5], we showed that the zonal DCT using a square shape provides a better energy-distortion trade-off than the one using a triangle shape.In this Letter, we present an energy-efficient design for JPEG baseline compression. The novelty of our contribution is threefold. First, we propose a low-complexity DCT scheme combining the best lifting DCT algorithm of the literature and the zonal DCT using a square shape. The former aims to reduce the number of operations per coefficient while the latter aims to reduce the number of coefficients to be pro...