The Poisson-Lomax Distribution

In this paper we propose a new three-parameter lifetime distribution with upside-down bathtub shaped failure rate. The distribution is a compound distribution of the zero-truncated Poisson and the Lomax distributions (PLD). The density function, shape of the hazard rate function, a general expansion for moments, the density of the rth order statistic, and the mean and median deviations of the PLD are derived and studied in detail. The maximum likelihood estimators of the unknown parameters are obtained. The asymptotic confidence intervals for the parameters are also obtained based on asymptotic variance-covariance matrix. Finally, a real data set is analyzed to show the potential of the new proposed distribution

Interpretation of Well Test Data from Two Hydraulically Communicating Reservoirs

Naturally fractured reservoirs (NFR) have been receiving more attention than ever since the beginning of the last decade due to various reasons. The current understanding is not sufficient to achieve a favorable recovery factor due to the complexity associated with the fracture characterization and the dynamic behavior of the fractured system. The majority of the fractured reservoirs are developed. Therefore, before proceeding into secondary or possibly tertiary recovery processes a thorough understanding must be reached to avoid undesirable results. The huge reserve volume present in fractured oil and gas reservoirs motivate engineers, researchers, and geoscientists to exert additional efforts to economically exploit these reserves. The fact that they are widely distributed and found in many countries around the globe in almost every lithology is another justification for more interest.;Fracture characterization is the first building block in any NFR study. Therefore, the primary focus of this study is to show the effectiveness of data integration of various dynamic and static data. The study considers a NFR field which consists of two reservoirs that are hydraulically communicating. The reservoirs have prolific porosity and permeability separated by a non reservoir formation. The field well test data was analyzed to identify fractures, and a simulation model was constructed to predict the type of response that would be observed in communicating reservoirs. A unique shape on the derivative was seen due to the communication through fractures. In addition, this study demonstrates the impact of a well, several reservoirs, and fracture attributes on the derivative

Traffic accidents in Saudi Arabia: a study of their causes and association with driver behaviour, with specific reference to the eastern region

A high incidence of road accidents has been recorded in Saudi Arabia in recent years (Traffic Department Statistics 1991). Various factors might have accounted for this high rate of road accidents; the aim of this research, therefore, was to examine what factors contribute to road accidents in the country.In pursuit of this aim, a review of relevant literature on factors related with road accidents in many countries of the world was undertaken. Through this review, a list of road, vehicle and driver-related variables was selected for investigation in this study.The target population for the study was 4,100 drivers in Eastern Saudi Arabia who had been involved in road accidents in the period. Out of this population, a sample of 600 drivers was selected. The instrument used to collect data for the study was a questionnaire which requested demographic information on factors which had caused them to have an accident, and questions analysing habitual driving behaviour. Drivers were also tested on their knowledge of road signs. Returns were received from 484 drivers, 81% of the study sample.Two statistical techniques, chi square and correlation coefficient Spearman Brown formula, were utilised to test the relationship between the independent variables and the dependent variable - the number of road accidents.The findings of the study show that certain variables were significantly associated with road accidents in Saudi Arabia. Among the significant variables were the age of the driver, education level, profession, violation record, vehicle ownership, joy-riding, poor eye sight, sun haze, sand storm, long hours driving, non-observance of speed limit, emerging and exiting from roads without signals, presence of stray animals, non-marking of the road, non-familiarity with the road, lack of regular checking of vehicles, lack of regular servicing of vehicles and driving under medication.The variables that were not significant include marital status, non-possession of a licence, mechanical fault, reversing, non-alertness to others' errors, use of high beam lights while driving, non-lighting of the roads, passengers' behaviour, ear disorder.Conclusions were drawn as to deficiencies in driver training in Saudi Arabia and inadequacies of supervision by the law enforcement agents. It is recommended that policy makers should make intensive efforts in organising training programmes and seminars for drivers and curriculum of driving schools should be expanded. Measures for improving enforcement of traffic regulations are made, and it is suggested that an Islamic insurance policy for vehicles should be introduced in the country. Finally, suggestions are made for further research

UOLO - automatic object detection and segmentation in biomedical images

We propose UOLO, a novel framework for the simultaneous detection and segmentation of structures of interest in medical images. UOLO consists of an object segmentation module which intermediate abstract representations are processed and used as input for object detection. The resulting system is optimized simultaneously for detecting a class of objects and segmenting an optionally different class of structures. UOLO is trained on a set of bounding boxes enclosing the objects to detect, as well as pixel-wise segmentation information, when available. A new loss function is devised, taking into account whether a reference segmentation is accessible for each training image, in order to suitably backpropagate the error. We validate UOLO on the task of simultaneous optic disc (OD) detection, fovea detection, and OD segmentation from retinal images, achieving state-of-the-art performance on public datasets.Comment: Publised on DLMIA 2018. Licensed under the Creative Commons CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0