scholarly journals Soil Fertility Levels in Bangladesh for Rice Cultivation

2019 ◽  
pp. 1-11 ◽  
Author(s):  
Jatish C. Biswas ◽  
N. Kalra ◽  
M. Maniruzzaman ◽  
M. M. Haque ◽  
U. A. Naher ◽  
...  
Keyword(s):  
Soil Fertility ◽  
Evaluation Method ◽  
Dry Season ◽  
Rice Soil ◽  
Data Set ◽  
Irrigated Rice ◽  
Rice Yields ◽  
Zn Status ◽  
Crop Zoning

Determination of soil fertility with minimum data set for crop zoning and devising fertilizer recommendations as well as soil fertility evaluation method based on soil properties. The data were collected from existing literatures and scoring was done on 0–100 scale. The lowest score was assigned for the minimum value of tested attributes and then gradually higher scoring values. Arithmetic, weighted, geometric and most minimum of mean scores were calculated and their performances were compared with grain yield of dry season irrigated (Boro) rice. Soil fertility in 10-12 and 39-52% areas in Bangladesh are very low and low, respectively. Medium fertile and fertile soils are distributed in 17-41% and in about 8% areas of the country. About 55% soils scored 70–95 (medium to high SOC) and the rest belongs to inferior quality. In some areas P build up has taken place (25% areas), but widespread K mining. Sulphur and Zn status in about 40% areas are low to very low (scored <35 and <40). Soils of the major areas of the country are with low pH (5.0-6.0) and CEC in the range of 15-25 cmolc kg-1. Weighted mean score and most minimum of eight attributes score showed good relationships with dry season irrigated rice yields than other tested methods indicating that this technique can be used for soil fertility rating in tropical countries.

The result of equilibrium-constant calculations strongly depends on the evaluation method used and on the type of experimental errors

2001 ◽  
Vol 359 (2) ◽  
pp. 411-418 ◽  
Author(s):  
Hendrik FUCHS ◽  
Reinhard GESSNER
Keyword(s):  
Protein Interactions ◽  
Evaluation Method ◽  
Equilibrium Constants ◽  
Scatchard Analysis ◽  
Protein Protein Interactions ◽  
Data Set ◽  
Slow Kinetics ◽  
Experimental Errors ◽  
Saturation Effects

The determination of equilibrium constants is a widespread tool both to understand and to characterize protein–protein interactions. A variety of different methods, among them Scatchard analysis, is used to calculate these constants. Although more than 1000 articles dealing with equilibrium constants are published every year, the effects of experimental errors on the results are often disregarded when interpreting the data. In the present study we theoretically analysed the effect of various types of experimental errors on equilibrium constants derived by three different methods. A computer simulation clearly showed that certain experimental errors, namely inaccurate background correction, inexact calibration, saturation effects, slow kinetics and simple scattering, can adversely affect the result. The analysis further revealed that, for a given type of error, the same data set can produce different results depending on the method used.

Detection for Approximately Duplicate Records Based on Fuzzy Comprehensive Evaluation

2013 ◽  
Vol 397-400 ◽  
pp. 2464-2468
Author(s):  
Li Juan Zhou ◽  
Zhe Xiao
Keyword(s):  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Massive Data ◽  
Data Set ◽  
Comprehensive Evaluation Method ◽  
Attribute Weight ◽  
Massive Data Set ◽  
Composition Factors

To solve the problem of attribute weight determination in the approximately duplicate records, we put forward a method based on fuzzy comprehensive evaluation to get attribute weight in data set. We first perform an analysis of the composition factors of attribute. Then we carry out an evaluation of their rank. Finally, we make a determination of the attribute weight using the fuzzy comprehensive evaluation method, on the basis of which the approximately duplicate records are detected. Theoretical analysis and experimental results show that the method can objectively determine all attributes weight, and effectively detect the approximately duplicate records in massive data set.

Methods of risk assessment in forecasting the consequences of accidents at pipeline transport facilities

2020 ◽  
Vol 10 (6) ◽  
pp. 663-673
Author(s):  
Vladislav N. Slepnev ◽  
◽  
Alexander F. Maksimenko ◽  
Elena V. Glebova ◽  
Alla Т. Volokhina ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Evaluation Method ◽  
Assessment Procedure ◽  
Expert Evaluation ◽  
Main Pipeline ◽  
Pipeline Transport ◽  
Forecasting Accuracy ◽  
Distribution Of Resources ◽  
Expert Evaluation Method

The choice of risk assessment procedure is one of the essential stages of efficient structuring of processes on prevention, localization and elimination of the consequences of accidents at main pipeline transport facilities. The authors analyzed themed publications and regulatory documents, governing procedures of risk assessment and forecasting of the consequences of possible accidents, and defined main problems in this area. Procedure for the risk assessment of accidents at main pipeline facilities was developed, the basis of which is the expert evaluation method. The procedure includes the determination of the main criteria for the assessment the probability of accident initiation and development and the evaluation of the severity of its consequences, an expert evaluation of criteria significance, their classification, and creation of a rating for hazardous pipeline sections. The application of the procedure application allows to specify the list of facilities that require high priority forecasting of accidents consequences, thus to optimize the distribution of resources and the overall increase of efficiency in planning while defining forces and special technical devices, necessary for containment and rectification of emergencies. Expert evaluation method application allows considering the specifics of certain enterprises, their technical and technological peculiarities, thereby increasing forecasting accuracy.

scholarly journals Determination of Body Parts in Holstein Friesian Cows Comparing Neural Networks and k Nearest Neighbour Classification

Animals ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 50
Author(s):  
Jennifer Salau ◽  
Jan Henning Haas ◽  
Wolfgang Junge ◽  
Georg Thaller
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Body Parts ◽  
Nearest Neighbour ◽  
Data Set ◽  
3D Data ◽  
Holstein Friesian ◽  
Knn Classification ◽  
Friesian Cows

Machine learning methods have become increasingly important in animal science, and the success of an automated application using machine learning often depends on the right choice of method for the respective problem and data set. The recognition of objects in 3D data is still a widely studied topic and especially challenging when it comes to the partition of objects into predefined segments. In this study, two machine learning approaches were utilized for the recognition of body parts of dairy cows from 3D point clouds, i.e., sets of data points in space. The low cost off-the-shelf depth sensor Microsoft Kinect V1 has been used in various studies related to dairy cows. The 3D data were gathered from a multi-Kinect recording unit which was designed to record Holstein Friesian cows from both sides in free walking from three different camera positions. For the determination of the body parts head, rump, back, legs and udder, five properties of the pixels in the depth maps (row index, column index, depth value, variance, mean curvature) were used as features in the training data set. For each camera positions, a k nearest neighbour classifier and a neural network were trained and compared afterwards. Both methods showed small Hamming losses (between 0.007 and 0.027 for k nearest neighbour (kNN) classification and between 0.045 and 0.079 for neural networks) and could be considered successful regarding the classification of pixel to body parts. However, the kNN classifier was superior, reaching overall accuracies 0.888 to 0.976 varying with the camera position. Precision and recall values associated with individual body parts ranged from 0.84 to 1 and from 0.83 to 1, respectively. Once trained, kNN classification is at runtime prone to higher costs in terms of computational time and memory compared to the neural networks. The cost vs. accuracy ratio for each methodology needs to be taken into account in the decision of which method should be implemented in the application.

scholarly journals Seasonal Variation of Rainy and Dry Season Per Capita Water Consumption in Freetown City Sierra Leone

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 499
Author(s):  
Salmatta Ibrahim A ◽  
Fayyaz Ali Memon ◽  
David Butler
Keyword(s):  
Seasonal Variation ◽  
Water Use ◽  
Water Consumption ◽  
Low Income ◽  
Rainy Season ◽  
Predictor Variable ◽  
Dry Season ◽  
Data Set ◽  
Per Capita ◽  
End Use

Ensuring a sustainable urban water supply for developing/low-income countries requires an understanding of the factors affecting water consumption and technical evidence of individual consumption which can be used to design an improved water demand projection. This paper compared dry and rainy season water sources available for consumption and the end-use volume by each person in the different income groups. The study used a questionnaire survey to gather household data for a total of 398 households, which was analysed to develop the relationship between per capita water consumption characteristics: Socio-economic status, demographics, water use behaviour around indoor and outdoor water use activities. In the per capita water consumption patterns of Freetown, a seasonal variation was found: In the rainy season, per capita water consumption was found to be about 7% higher than the consumption for the full sample, whilst in the dry season, per capita water consumption was almost 14% lower than the full survey. The statistical analysis of the data shows that the average per capita water consumption for both households increases with income for informal slum-, low-, middle- and high-income households without piped connection (73, 78, 94 and 112 L/capita/day) and with connection (91, 97, 113 and 133 L/capita/day), respectively. The collected data have been used to develop 20 statistical models using the multiple linear stepwise regression method for selecting the best predictor variable from the data set. It can be seen from the values that the strongest significant relationships of per capita consumption are with the number of occupants (R = −0.728) in the household and time spent to fetch water for use (R = −0.711). Furthermore, the results reveal that the highest fraction of end use is showering (18%), then bathing (16%), followed by toilet use (14%). This is not in agreement with many developing countries where toilet use represents the largest component of indoor end use.

Importance of basic cultivation techniques to increase irrigated rice yields in Tanzania

2017 ◽  
Vol 15 (4) ◽  
pp. 847-859 ◽  
Author(s):  
Nobuhito Sekiya ◽  
Motonori Tomitaka ◽  
Nobuaki Oizumi ◽  
Adam Gabriel Pyuza ◽  
Richard James Shayo ◽  
...  
Keyword(s):  
Irrigated Rice ◽  
Rice Yields ◽  
Cultivation Techniques

scholarly journals Evaluating irrigated rice yields in Japan within the Climate Zonation Scheme of the Global Yield Gap Atlas

2021 ◽  
pp. 1-12
Author(s):  
S. Ishikawa ◽  
T. Nakashima ◽  
T. Iizumi ◽  
M. C. Hare
Keyword(s):  
Production Capacity ◽  
Aridity Index ◽  
Data Sets ◽  
Yield Gap ◽  
Yield Data ◽  
Irrigated Rice ◽  
Rice Yields ◽  
The Stability ◽  
Temperature Seasonality ◽  
Government Statistics

Abstract The Global Yield Gap Atlas (GYGA) is an international project that addresses global food production capacity in the form of yield gaps (Yg). The GYGA project is unique in employing its original Climate Zonation Scheme (CZS) composed of three indexed factors, i.e. Growing Degree Days (GDD) related to temperature, Aridity Index (AI) related to available water and Temperature Seasonality (TS) related to annual temperature range, creating 300 Climate Zones (CZs) theoretically across the globe. In the present study, the GYGA CZs were identified for Japan on a municipality basis and analysis of variance (ANOVA) was performed on irrigated rice yield data sets, equating to actual yields (Ya) in the GYGA context, from long-term government statistics. The ANOVA was conducted for the data sets over two decades between 1994 and 2016 by assigning the GDD score of 6 levels and the TS score of 2 levels as fixed factors. Significant interactions with respect to Ya were observed between GDD score and TS score for 13 years out of 21 years implying the existence of favourable combinations of the GDD score and the TS score for rice cultivation. The implication was also supported by the observation with Yg. The lower values of coefficient of variance obtained from the CZs characterized by medium GDD scores indicated the stability over time of rice yields in these areas. These findings suggest a possibility that the GYGA-CZS can be recognized as a tool suitable to identify favourable CZs for growing crops.

A NEW TECHNIQUE ESTIMATING LOCATION OF MEAN JOINT CENTERS OF ROTATION WITH ASSOCIATED DISPERSIONS AND ASSESSING TO FUNCTIONAL COORDINATE SYSTEM OF MOVING LIMB SEGMENTS

2006 ◽  
Vol 06 (04) ◽  
pp. 373-384
Author(s):  
ERIC BERTHONNAUD ◽  
JOANNÈS DIMNET
Keyword(s):  
Numerical Technique ◽  
New Technique ◽  
Helical Axis ◽  
Joint Movement ◽  
Time Step ◽  
Data Set ◽  
Minimization Procedure ◽  
A New Technique ◽  
Joint Center

Joint centers are obtained from data treatment of a set of markers placed on the skin of moving limb segments. Finite helical axis (FHA) parameters are calculated between time step increments. Artifacts associated with nonrigid body movements of markers entail ill-determination of FHA parameters. Mean centers of rotation may be calculated over the whole movement, when human articulations are likened to spherical joints. They are obtained using numerical technique, defining point with minimal amplitude, during joint movement. A new technique is presented. Hip, knee, and ankle mean centers of rotation are calculated. Their locations depend on the application of two constraints. The joint center must be located next to the estimated geometric joint center. The geometric joint center may migrate inside a cube of possible location. This cube of error is located with respect to the marker coordinate systems of the two limb segments adjacent to the joint. Its position depends on the joint and the patient height, and is obtained from a stereoradiographic study with specimen. The mean position of joint center and corresponding dispersion are obtained through a minimization procedure. The location of mean joint center is compared with the position of FHA calculated between different sequential steps: time sequential step, and rotation sequential step where a minimal rotation amplitude is imposed between two joint positions. Sticks are drawn connecting adjacent mean centers. The animation of stick diagrams allows clinical users to estimate the displacements of long bones (femur and tibia) from the whole data set.

Improved soil fertility and weed management is profitable for irrigated rice farmers in Sahelian West Africa

2000 ◽  
Vol 66 (2) ◽  
pp. 101-113 ◽  
Author(s):  
S.M Haefele ◽  
D.E Johnson ◽  
S Diallo ◽  
M.C.S Wopereis ◽  
I Janin
Keyword(s):  
West Africa ◽  
Soil Fertility ◽  
Weed Management ◽  
Irrigated Rice ◽  
Rice Farmers
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