Using Epanet To Optimize Operation Of The Rural Water Distribution System At Braggs, Oklahoma

This study was carried out in order to assess the performance of the drinking water distribution system at Braggs, Oklahoma using hydraulic simulation software and to address any improvements required in order to improve quality of service to their customers. The study also aimed to establish how common problems experienced by rural water systems can be detected and addressed using hydraulic simulation software. The main focus of the study was water quality, pressure at different points within the distribution system, fire flow requirements, pipe materials and age of the distribution system. The study was conducted as part of a larger project funded by the Oklahoma Water Resources Research Institute (OWRRI) that aimed to provide an easily accessible and cost effective way for rural water systems in Oklahoma to evaluate the performance of their distribution networks and plan for improvements. The city of Braggs which is located in eastern Oklahoma, 56 miles south east of Tulsa, was selected because it fits the description of a Rural Water System (RWS). The water distribution system serves 1030 people in the city and surrounding areas. Water utilities seek to provide customers with a reliable and continuous supply of high quality water while minimizing costs. Due to their nature, distribution networks contain points of vulnerability where contamination can occur. Rural water systems are often small and struggle to meet even the basic requirements of the safe drinking water act (SDWA) since they often collect insufficient revenues to keep their networks operating properly. Distribution system modeling helps to identify points where contamination is likely to occur, identifies required upgrades in advance, and forms a basis for decision support by evaluating possible alternatives.School of Civil & Environmental Engineerin

Evaluation of the diagnostic accuracy and cost of different methods for the assessment of severe anaemia in hospitalised children in Eastern Uganda [version 2; referees: 3 approved]

Background: Severe anaemia in children requiring hospital admission is a major public health problem in malaria-endemic Africa. Affordable methods for the assessment of haemoglobin have not been validated against gold standard measures for identifying those with severe anaemia requiring a blood transfusion, despite this resource being in short supply. Methods: We conducted a prospective descriptive study of hospitalized children aged 2 months – 12 years at Mbale and Soroti Regional Referral Hospitals, assessed to have pallor at triage by a nurse and two clinicians. Haemoglobin levels were measured using the HemoCue ® Hb 301 system (gold standard); the Haemoglobin Colour Scale; calorimetric and Sahli’s methods. We report clinical assessments of the degree of pallor, clinicians’ intention to transfuse, inter-observer agreement, limits of agreement using the Bland-Altman method, and the sensitivity and specificity of each method in comparison to HemoCue ® Results: We recruited 322 children assessed by the admitting nurse as having severe (164; 51.0%), moderate (99; 30.7%) or mild (57; 17.7%) pallor. Agreement between the clinicians and the nurse were good: Clinician A Kappa=0.68 (0.60–0.76) and Clinician B Kappa=0.62 (0.53–0.71) respectively ( P <0.0001 for both). The nurse, clinicians A and B indicated that of 94/116 (81.0%), 83/121 (68.6%) and 93/120 (77.5%) respectively required transfusion. HemoCue ® readings indicated anaemia as mild (Hb10.0–11.9g/dl) in 8/292 (2.7%), moderate (Hb5.0–9.9g/dl) in 132/292 (45.2%) and severe (Hb<5.0g/dl) in 152/292 (52.1%). Comparing to HemoCue® the Sahli’s method performed best in estimation of severe anaemia, with sensitivity 84.0% and specificity 87.9% and a Kappa score of  0.70 (0.64–0.80). Conclusions : Clinical assessment of severe pallor results has a low specificity for the diagnosis of severe anaemia. To target blood transfusion Hb measurement by either Hemocue® or Sahli’s method for the cost of USD 4 or and USD 0.25 per test, respectively would be more cost-effective

Evaluation of the diagnostic accuracy and cost of different methods for the assessment of severe anaemia in hospitalised children in Eastern Uganda [version 2; peer review: 3 approved]

Background: Severe anaemia in children requiring hospital admission is a major public health problem in malaria-endemic Africa. Affordable methods for the assessment of haemoglobin have not been validated against gold standard measures for identifying those with severe anaemia requiring a blood transfusion, despite this resource being in short supply. Methods: We conducted a prospective descriptive study of hospitalized children aged 2 months – 12 years at Mbale and Soroti Regional Referral Hospitals, assessed to have pallor at triage by a nurse and two clinicians. Haemoglobin levels were measured using the HemoCue ® Hb 301 system (gold standard); the Haemoglobin Colour Scale; Colorimetric and Sahli’s methods. We report clinical assessments of the degree of pallor, clinicians’ intention to transfuse, inter-observer agreement, limits of agreement using the Bland-Altman method, and the sensitivity and specificity of each method in comparison to HemoCue ® Results: We recruited 322 children, clinically-assessed by the admitting nurse (n=314) as having severe (166; 51.6%), moderate (97; 30.1%) or mild (51; 15.8%) pallor. Agreement between the clinicians and the nurse were good: Clinician A Kappa=0.68 (0.60–0.76) and Clinician B Kappa=0.62 (0.53–0.71) respectively ( P<0.0001 for both). The nurse, clinicians A and B indicated that of 94/116 (81.0%), 83/121 (68.6%) and 93/120 (77.5%) respectively required transfusion. HemoCue ® readings indicated anaemia as mild (Hb10.0–11.9g/dl) in 8/292 (2.7%), moderate (Hb5.0–9.9g/dl) in 132/292 (45.2%) and severe (Hb<5.0g/dl) in 152/292 (52.1%). Comparing to HemoCue® the Sahli’s method performed best in estimation of severe anaemia, with sensitivity 84.0% and specificity 87.9% and a Kappa score of  0.70 (0.64–0.80). Conclusions: Clinical assessment of severe pallor results has a low specificity for the diagnosis of severe anaemia. To target blood transfusion Hb measurement by either Hemocue® or Sahli’s method for the cost of USD 4 or and USD 0.25 per test, respectively would be more cost-effective

Evaluation of the diagnostic accuracy and cost of different methods for the assessment of severe anaemia in hospitalised children in Eastern Uganda [version 1; referees: 2 approved, 1 approved with reservations]

Background: Severe anaemia in children requiring hospital admission is a major public health problem in malaria-endemic Africa. Affordable methods for the assessment of haemoglobin have not been validated against gold standard measures for identifying those with severe anaemia requiring a blood transfusion, despite this resource being in short supply. Methods: We conducted a prospective descriptive study of hospitalized children aged 2 months – 12 years at Mbale and Soroti Regional Referral Hospitals, assessed to have pallor at triage by a nurse and two clinicians. Haemoglobin levels were measured using the HemoCue® Hb 301 system (gold standard); the Haemoglobin Colour Scale; calorimetric and Sahli’s methods. We report clinical assessments of the degree of pallor, clinicians’ intention to transfuse, inter-observer agreement, limits of agreement using the Bland-Altman method, and the sensitivity and specificity of each method in comparison to HemoCue® Results: We recruited 322 children assessed by the admitting nurse as having severe (164; 51.0%), moderate (99; 30.7%) or mild (57; 17.7%) pallor. Agreement between the clinicians and the nurse were good: Clinician A Kappa=0.68 (0.60–0.76) and Clinician B Kappa=0.62 (0.53–0.71) respectively (P<0.0001 for both). The nurse, clinicians A and B indicated that of 94/116 (81.0%), 83/121 (68.6%) and 93/120 (77.5%) respectively required transfusion. HemoCue® readings indicated anaemia as mild (Hb10.0–11.9g/dl) in 8/292 (2.7%), moderate (Hb5.0–9.9g/dl) in 132/292 (45.2%) and severe (Hb<5.0g/dl) in 152/292 (52.1%). Comparing to HemoCue® the Sahli’s method performed best in estimation of severe anaemia, with sensitivity 84.0% and specificity 87.9% and a Kappa score of  0.70 (0.64–0.80). Conclusions: Clinical assessment of severe pallor results has a low specificity for the diagnosis of severe anaemia. To target blood transfusion Hb measurement by either Hemocue® or Sahli’s method for the cost of USD 4 or and USD 0.25 per test, respectively would be more cost-effective

Formal Analysis and Verification of Cyber-Physical Systems for the Smart Grid

The current development in cyber-physical systems technology, from a static to a more dynamically distributed environment, has contributed towards the need for the development of the future cyber-physical security support systems. These power systems have evolved from a unidirectional to a bidirectional infrastructure with millions of nodes from the source to the destined power user. The existing security tools cannot provide the required level of trusted platform for these system. The monitoring of this dynamic network involves ensuring that the network is in a stable state under all circumstances. The circumstances could include natural disasters, attacks from terrorist activities, undetected malfunctions and poor configurations. The existing security schemes in power control systems only consider securing the the power grid at single point of the infrastructure level especially using firewalls. In this thesis, we present a series of threat models that could be used against the evolving cyber-physical system and we model tools that prevent these attacks. We utilize the SMT verification solver engine to perform the formal analysis of the system components.</p

nicholasjclark/mvgam: v1.07

&lt;p&gt;This release coincides with new additions for moving average terms in autoregressive process models, as well as the possibility to estimate correlated process errors for RW and AR(1-3) models when working with multivariate time series&lt;/p&gt

USING EPANET TO OPTIMIZE OPERATION OF THE RURAL WATER DISTRIBUTION SYSTEM AT BRAGGS, OKLAHOMA By

Everything I have accomplished is simply a sign of God’s grace to me. I have taken a journey that seemed very discouraging as I tried to settle in at the beginning of the Spring Semester of 2008. Now, looking back at what I have been able to achieve since then, I am glad I kept the faith and the resolve to see the end. I would like to thank the Oklahoma Water Resources Research Institute (OWRRI) for providing the funding that made this study possible and my advisor, Dr. DeeAnn Sanders for her unwavering support and tremendous encouragement throughout the course of my graduate studies at Oklahoma State University and especially over the last couple of months as I worked to complete my thesis. I would also like to thank the other members of my thesis committee, Dr. Arthur Stoecker and Dr. Gregory Wilber. Dr. Stoecker has been of immense help since we started working on this project and helped me immensely as I tried to get my model running last summer. Dr. Wilber has provided me with a wealth of knowledge throughout the course of my graduate studies. My thesis committee members have been available throughout to answer the questions that came up as I worked to complete the study and I am very thankful to them. I would like t

DeepForest: A Python package for RGB deep learning tree crown delineation

Abstract Remote sensing of forested landscapes can transform the speed, scale and cost of forest research. The delineation of individual trees in remote sensing images is an essential task in forest analysis. Here we introduce a new Python package, DeepForest that detects individual trees in high resolution RGB imagery using deep learning. While deep learning has proven highly effective in a range of computer vision tasks, it requires large amounts of training data that are typically difficult to obtain in ecological studies. DeepForest overcomes this limitation by including a model pretrained on over 30 million algorithmically generated crowns from 22 forests and fine-tuned using 10,000 hand-labelled crowns from six forests. The package supports the application of this general model to new data, fine tuning the model to new datasets with user labelled crowns, training new models and evaluating model predictions. This simplifies the process of using and retraining deep learning models for a range of forests, sensors and spatial resolutions. We illustrate the workflow of DeepForest using data from the National Ecological Observatory Network, a tropical forest in French Guiana, and street trees from Portland, Oregon