Bangladesh University

About: Bangladesh University is a education organization based out in Dhaka, Bangladesh. It is known for research contribution in the topics: Population & Diabetes mellitus. The organization has 871 authors who have published 840 publications receiving 7426 citations. The organization is also known as: BU.

Simple field method for determining unsaturated hydraulic conductivity

Abstract: A new method is proposed for determining in situ unsaturated hydraulic conductivities from unsaturated infiltration measurements made at several tensions on the same infiltration surface. Wooding's equation for steady-state unconfined infiltration rates is used in calculating hydraulic conductivities. Hydraulic conductivities calculated with the new method are consistent with unit gradient laboratory measurements of saturated and unsaturated hydraulic conductivity. This simple field method is potentially valuable because it is faster than unit gradient laboratory methods, and it is less disruptive of pore continuity than other field infiltration techniques. R OF SOIL WATER INFILTRATION and SUbSUrface water movement are important to researchers developing soil management practices to minimize potential groundwater contamination from land applied chemicals. A simple and rapid field technique of determining field unsaturated hydraulic conductivity would be useful in achieving this objective. Field and laboratory techniques for measurement of unsaturated hydraulic properties of soil were described by Green et al. (1986) and by Klute and Dirksen (1986), respectively. Solution of unsaturated flow problems generally requires experimental determination of the relationship between hydraulic conductivity and water potential or water content. Field methods used to obtain these relationships include the instantaneous profile method, steady-flux methods (with sprinkler irrigation or artificial crusts), sorptivity measurements, and use of tension infiltrometers (Clothier and White, 1981; Ankeny et al., 1988, 1989; Elrick et al., 1988a; White and Perroux, 1987, 1989; Smettem and Clothier, 1989). Because instantaneous profile and steady-flux techniques require laborious installation of tensiometers or neutron probe access tubes, sample numbers and the extensiveness of a site characterization can be limited. Sorptivity is an unsaturated soil parameter sometimes measured in the field (Green et al., 1986). Although sorptivity measurements are fast and simple, these measurements usually require that initial water content be known. White and Perroux (1989) have proposed a laboratory method for calculating unsaturated hydraulic conductivity from sorptivity measurements. Their method, however, requires air drying the sample between measurements at different tensions, which increases experimental time and may cause wetting/drying effects on soil structure. The Guelph infiltrometer (Soilmoisture Equipment Corp., Santa Barbara, CA) compares infiltration rates for difM.D. Ankeny, Daniel B. Stephens & Assoc., 4415 Hawkins NE, Albuquerque, NM 87109; M. Ahmed, Bangladesh Univ. of Engineering and Technology, Dhaka-1000, Bangladesh; T.C. Kaspar, National Soil Tilth Lab., Ames, IA 50011; and R. Horton, Dep. of Agronomy, Iowa State Univ., Ames, IA 50011. Joint contribution from USDA-ARS and Iowa State Univ. Journal Paper no. J-13716 of the Iowa Agric. and Home Economics Exp. Stn. Projects no. 2659 and 2715. Received 6 Nov. 1989. *Corresponding author. Published in Soil Sci. Soc. Am. J. 55:467-470 (1991). ferent radii surface disks and does not require driving a ring. Different soil surface areas, however, are being compared, which may introduce spatial variability associated with the different soil surfaces. A field method to measure in situ hydraulic conductivity at low water tensions is needed for studies of macroporosity and water flow in agricultural soils. The desired criteria for such a method are: 1. Only steady-state infiltration rate measurements are needed. Knowledge of the initial water potential or content should not be required. 2. Soil pore structure should not be disturbed by driving a ring into soil to obtain one-dimensional flow. This way, larger pores are not truncated or collapsed and infiltration through larger pores is less likely to be underestimated. 3. Measurements should be taken on the same soil surface. Measurements taken by using different radii (e.g., Elrick et al. 1988a) are more dependent on the assumption of soil homogeneity. 4. Calculation of hydraulic conductivities should be straightforward. We present a simple scheme for determination of in situ hydraulic conductivity that meets these criteria.

CoroDet: A deep learning based classification for COVID-19 detection using chest X-ray images.

Abstract: Background and Objective The Coronavirus 2019, or shortly COVID-19, is a viral disease that causes serious pneumonia and impacts our different body parts from mild to severe depending on patient’s immune system. This infection was first reported in Wuhan city of China in December 2019, and afterward, it became a global pandemic spreading rapidly around the world. As the virus spreads through human to human contact, it has affected our lives in a devastating way, including the vigorous pressure on the public health system, the world economy, education sector, workplaces, and shopping malls. Preventing viral spreading requires early detection of positive cases and to treat infected patients as quickly as possible. The need for COVID-19 testing kits has increased, and many of the developing countries in the world are facing a shortage of testing kits as new cases are increasing day by day. In this situation, the recent research using radiology imaging (such as X-ray and CT scan) techniques can be proven helpful to detect COVID-19 as X-ray and CT scan images provide important information about the disease caused by COVID-19 virus. The latest data mining and machine learning techniques such as Convolutional Neural Network (CNN) can be applied along with X-ray and CT scan images of the lungs for the accurate and rapid detection of the disease, assisting in mitigating the problem of scarcity of testing kits. Methods Hence a novel CNN model called CoroDet for automatic detection of COVID-19 by using raw chest X-ray and CT scan images have been proposed in this study. CoroDet is developed to serve as an accurate diagnostics for 2 class classification (COVID and Normal), 3 class classification (COVID, Normal, and non-COVID pneumonia), and 4 class classification (COVID, Normal, non-COVID viral pneumonia, and non-COVID bacterial pneumonia). Results The performance of our proposed model was compared with ten existing techniques for COVID detection in terms of accuracy. A classification accuracy of 99.1% for 2 class classification, 94.2% for 3 class classification, and 91.2% for 4 class classification was produced by our proposed model, which is obviously better than the state-of-the-art-methods used for COVID-19 detection to the best of our knowledge. Moreover, the dataset with x-ray images that we prepared for the evaluation of our method is the largest datasets for COVID detection as far as our knowledge goes. Conclusion The experimental results of our proposed method CoroDet indicate the superiority of CoroDet over the existing state-of-the-art-methods. CoroDet may assist clinicians in making appropriate decisions for COVID-19 detection and may also mitigate the problem of scarcity of testing kits.