Mathematical modelling of ammonia volatilization from slurry stores and its effect on Cryptosporidium oocyst viability

1995 ◽  
Vol 124 (1) ◽  
pp. 55-60 ◽  
Author(s):  
G. D. Ruxton
Keyword(s):  
Mathematical Model ◽  
Time Series ◽  
Mathematical Modelling ◽  
Ammonia Volatilization ◽  
Time Series Data ◽  
Cryptosporidium Oocyst ◽  
Critical Value ◽  
Series Data ◽  
Simple Mathematical Model ◽  
Ammonia Loss

SUMMARYA simple mathematical model is shown to provide reasonably good predictions of time series data on ammonia loss from three experiments on slurry stores. The model produces predictions of changes in the distribution of ammonia with depth. Experimental evidence suggests that ammonia concentrations above a critical value appear to destroy the viability of Cryptosporidium oocysts. Using this criterion, the model predicts that, even under the most favourable circumstances, oocysts are unlikely to remain viable in slurry stores except in the top few centimetres. The effect of stirring the slurry is considered.

scholarly journals PENDISC: A Simple Method for Constructing a Mathematical Model from Time-Series Data of Metabolite Concentrations

2014 ◽  
Vol 76 (6) ◽  
pp. 1333-1351 ◽  
Author(s):  
Kansuporn Sriyudthsak ◽  
Michio Iwata ◽  
Masami Yokota Hirai ◽  
Fumihide Shiraishi
Keyword(s):  
Mathematical Model ◽  
Time Series ◽  
Time Series Data ◽  
Series Data ◽  
Simple Method ◽  
Metabolite Concentrations

scholarly journals ANALISIS HUBUNGAN CURAH HUJAN DENGAN KEJADIAN BANJIR DAN KEKERINGAN PADA WILAYAH DENGAN SISTIM USAHATANI BERBASIS PADI DI PROPINSI JAWA BARAT (ANALYSIS OF RELATIONSHIP BETWEEN RAINFALL AND FLOOD AS WELL AS DROUGHT EVENTS ON AREA WITH RICE ...

Agromet ◽  
2009 ◽  
Vol 23 (1) ◽  
pp. 11 ◽  
Author(s):  
Woro Estiningtyas ◽  
Rizaldi Boer ◽  
Agus Buono
Keyword(s):  
Time Series ◽  
Paddy Field ◽  
Time Series Data ◽  
Critical Value ◽  
Climate Risk ◽  
Series Data ◽  
Food Crops ◽  
Drought Event ◽  
West Java ◽  
Central Food

There are significantly decreasing of rainfall in wet season and dry season, and changed in onset of early season, that all of them can make crouded in plan of planting date, field actifity especially for food crops africulture. In the other side, climate is one of condition that has been ready and can not change, where probability of climate change will be reality that should be happened every time. Increasing frequency of climate extrem will give high impact in agriculture, especialy in rice-based farming system. This paper describes the climate risk based on statistical approaches. The climate risk is focused on flood and drought event. The analysis used was a chance occurrence based on time series data of rainfall and flood/droughts (affected and puso) based on median value from time series data. The goal of this research are : (1) to know rainfall critical value that can be influence flood and drought event in some of central food crops i West Java, (2) to know probability of flood and drought event in some of central food crops in West Java. The result of this research show that critical value of the rainfall that can be influence flood and drought event is very variety. Average of for flood event for paddy field near coastal based on median approach is 140 mm/month with probability 0,6. For another location, 166 mm/month with probability 0,68. Average of critical value of the rainfall for drought event is 64 mm/month for paddy field near coastal with probability 0,73. For another location, critical rainfall value is 119 mm/month with probability 0,76. For spesific research or detail scale (district or sub distric) we can use rainfall critical value and probablity based on data in that specific location because the data is more representative local riil condition.

scholarly journals Metode ARIMA untuk Memodelkan Volume Produksi Kelapa Sawit pada PT. SOCFINDO di Kabupaten Aceh Tamiang

2021 ◽  
Vol 3 (2) ◽  
pp. 309-319
Author(s):  
Wiwin Apriani ◽  
◽  
Rahmi Hayati
Keyword(s):  
Mathematical Model ◽  
Time Series ◽  
Stationary State ◽  
Oil Palm ◽  
Time Series Data ◽  
Series Data ◽  
Test Results ◽  
Selection Of

This study aims to create a mathematical model that can be used to predict the amount of oil palm that will be produced at PT. Socfindo in Aceh Tamiang Regency in the coming period. The data used is data on the amount of oil palm that is ready to be produced every month in 2012-2015. The method used is the ARIMA method. The selection of this method is based on the data used, namely time series data. Before carrying out further testing, first, ensure that the data used meets the stationary state. From the test results, it is found that the data used fulfills the stationary state, then it is found that the MA (1) model can be used to predict the time series data. Furthermore, we obtain a model that can be used to predict the volume of oil palm production at PT. Socfindo is: Z_t = a_t-0.4096a_ (t-1) +521.57 With a_t ~ N (0; 29192.72)

Coexistence of Periodic Roll Motion and Chaotic One in a Forced Flooded Ship

1998 ◽  
Vol 08 (03) ◽  
pp. 619-626 ◽  
Author(s):  
Sunao Murashige ◽  
Kazuyuki Aihara
Keyword(s):  
Mathematical Model ◽  
Time Series ◽  
Periodic Solution ◽  
Time Series Data ◽  
Series Data ◽  
Roll Motion ◽  
Positive Maximum ◽  
Liapunov Exponent ◽  
Wave Condition ◽  
Low Dimensional

This letter describes the coexistence of periodic and chaotic roll motion of a flooded ship in waves. We found experimentally, both with a flooded ferry model and with a simplified box-shaped model, that the two types of roll motion can coexist under the same wave condition. A trajectory reconstructed in a delay-coordinate state space from the time series data of the measured roll angle looks like a low-dimensional strange attractor. Moreover, a mathematical model for the simplified box-shaped ship shows the coexistence of a periodic solution and a chaotic one with a positive maximum Liapunov exponent.

Graphical Exploratory Data Analysis for Categorical Longitudinal and Time Series Data

2013 ◽  
Author(s):  
Stephen J. Tueller ◽  
Richard A. Van Dorn ◽  
Georgiy Bobashev ◽  
Barry Eggleston
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Exploratory Data

Faktor-Faktor Yang Mempengaruhi Nilai Tukar Dollar Amerika Serikat Terhadap Rupiah Tahun 2000–2013

2017 ◽  
Vol 1 (2) ◽  
pp. 177-191
Author(s):  
Rizki Rahma Kusumadewi ◽  
Wahyu Widayat
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Money Supply ◽  
Time Series Data ◽  
The United States ◽  
Economic Conditions ◽  
Series Data ◽  
Arch Model ◽  
United States Dollar ◽  
The Exchange Rate

Exchange rate is one tool to measure a country’s economic conditions. The growth of a stable currency value indicates that the country has a relatively good economic conditions or stable. This study has the purpose to analyze the factors that affect the exchange rate of the Indonesian Rupiah against the United States Dollar in the period of 2000-2013. The data used in this study is a secondary data which are time series data, made up of exports, imports, inflation, the BI rate, Gross Domestic Product (GDP), and the money supply (M1) in the quarter base, from first quarter on 2000 to fourth quarter on 2013. Regression model time series data used the ARCH-GARCH with ARCH model selection indicates that the variables that significantly influence the exchange rate are exports, inflation, the central bank rate and the money supply (M1). Whereas import and GDP did not give any influence.

An Anomaly Detection Method with Exemplar Subsequence for Time Series Data

2016 ◽  
Vol 136 (3) ◽  
pp. 363-372
Author(s):  
Takaaki Nakamura ◽  
Makoto Imamura ◽  
Masashi Tatedoko ◽  
Norio Hirai
Keyword(s):  
Time Series ◽  
Anomaly Detection ◽  
Time Series Data ◽  
Detection Method ◽  
Series Data

The Comparison of Land Subsidence between East and West Side of Bangkok, Thailand

2020 ◽  
Vol 17 (3) ◽  
pp. 1
Author(s):  
Angkana Pumpuang ◽  
Anuphao Aobpaet
Keyword(s):  
Time Series ◽  
Land Subsidence ◽  
Time Series Data ◽  
Series Data ◽  
Industrial Estates ◽  
Vertical Displacements ◽  
Land Deformation ◽  
Extensive Farming ◽  
Chao Phraya River ◽  
Set Up

The land deformation in line of sight (LOS) direction can be measured using time series InSAR. InSAR can successfully measure land subsidence based on LOS in many big cities, including the eastern and western regions of Bangkok which is separated by Chao Phraya River. There are differences in prosperity between both sides due to human activities, land use, and land cover. This study focuses on the land subsidence difference between the western and eastern regions of Bangkok and the most possible cause affecting the land subsidence rates. The Radarsat-2 single look complex (SLC) was used to set up the time series data for long term monitoring. To generate interferograms, StaMPS for Time Series InSAR processing was applied by using the PSI algorithm in DORIS software. It was found that the subsidence was more to the eastern regions of Bangkok where the vertical displacements were +0.461 millimetres and -0.919 millimetres on the western and the eastern side respectively. The districts of Nong Chok, Lat Krabang, and Khlong Samwa have the most extensive farming area in eastern Bangkok. Besides, there were also three major industrial estates located in eastern Bangkok like Lat Krabang, Anya Thani and Bang Chan Industrial Estate. By the assumption of water demand, there were forty-eight wells and three wells found in the eastern and western part respectively. The number of groundwater wells shows that eastern Bangkok has the demand for water over the west, and the pumping of groundwater is a significant factor that causes land subsidence in the area.Keywords: Subsidence, InSAR, Radarsat-2, Bangkok

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