scholarly journals An association between change in types of roads and cultivated farm area at Agriculture Sector

2021 ◽  
Vol 258 ◽  
pp. 02008
Author(s):  
Elena Kozlova ◽  
Muhammad Imtiaz Subhani ◽  
Fatima Ulbasheva ◽  
Denis Ushakov
Keyword(s):  
Time Series ◽  
Significant Relationship ◽  
Data Stream ◽  
Time Series Data ◽  
Series Data ◽  
Annual Data ◽  
High Type ◽  
Agriculture Sector

This study investigates the association between change in types of roads and cultivated farm area at Agriculture Sector. Time series data was used to interrogate the proposition of this paper. The time series annual data from 2000 to 2020 was collected from the Eikon data stream on variables which include change in high type roads & change in low type roads around the farm area and cultivated farm area from of the 12 rural zones of provinces of Sind, Punjab and KPK of Pakistan. Findings confirmed that there is a significant association between increases in low type of roads and cultivates farm area of all selected rural zones of outlined provinces. While there is no significant relationship between the high type roads and the farm area and the cultivated area of stated 12 zones of outlined provinces findings further revealed.

scholarly journals HUBUNGAN TINGKAT PENDAPATAN DENGAN TINGKAT KONSUMSI MASYARAKAT DI KECAMATAN BONTONOMPO KABUPATEN GOWA

2013 ◽  
Vol 9 (1) ◽  
Author(s):  
Sanusi Am Sanusi Am ◽  
Ansar Ansar
Keyword(s):  
Time Series ◽  
Significant Relationship ◽  
Time Series Data ◽  
Pearson Correlation ◽  
Income Level ◽  
Analytical Tool ◽  
Central Bureau ◽  
Series Data ◽  
Public Consumption ◽  
The Relationship

The purpose of this study is to explain the relationship between the level of income with the level of public consumption in District Bontonompo Gowa District. This research uses time series data obtained from Central Bureau of Statistics (BPS). The analytical tool used is Pearson correlation formula with the help of SPSS For Windows Release 16. The results concluded that the income level has a significant relationship to the level of public income in District Bontonompo Gowa Regency. It is expected that the Gowa Regency government can pursue programs that can encourage the creation of more and more diverse employment so that the communities of each bias can earn a decent income and meet their consumption needs

scholarly journals Are male to female employment ratio and salary compensations in agricultural sector co-integrated?

2021 ◽  
Vol 258 ◽  
pp. 06041
Author(s):  
Evgenia Ezhak ◽  
Tatiana Podolskaya ◽  
Elizaveta Karagozova ◽  
Muhammad Imtiaz Subhani ◽  
Denis Ushakov
Keyword(s):  
Time Series ◽  
World Bank ◽  
Agricultural Sector ◽  
Time Series Data ◽  
Female Employment ◽  
Series Data ◽  
Agriculture Sector ◽  
Yearly Period ◽  
Male To Female

This study has been conducted in order to identify whether there is the co-movements between Male to Female employment ratio and Salary compensations in agricultural sector of Pakistan. To analyze the possible co-movement between the Male to Female employment ratio and Salary compensations in agricultural sector of Pakistan, the time series data for the yearly period of 1990 to 2020 for agriculture sector are taken from the publically available source i.e. website of World Bank. The result indicated that there is a long term relationship exists in between Male to Female employment ratio and Salary compensations in agricultural sector of Pakistan.

Customization of the OSSEM model for application to annual data from the Talar aquifer, Northern Iran

2015 ◽  
Vol 15 (3) ◽  
pp. 656-666
Author(s):  
Nazila Sedaei ◽  
Abolghasem Akbari ◽  
Leila Sedaei ◽  
Jonathan Peter Cox
Keyword(s):  
Time Series ◽  
Water Resources ◽  
Water Deficit ◽  
Time Series Data ◽  
Driving Forces ◽  
Anthropogenic Activities ◽  
Government Support ◽  
Series Data ◽  
Annual Data ◽  
Water Resource System

There are several principal driving forces behind the damaging coastal water resources depletion in many countries, including: high population growth, degrading water resources due to overexploitation and contamination, lack of awareness among local beneficiaries regarding sustainable management, and deficient government support and enforcement of conservation programs. To ensure a water resource system is productive in coastal areas, holistic and comprehensive management approaches are required. To address the aforementioned issues, a combined methodology which considers anthropogenic activities, together with environmental problems defined as the Overall Susceptibility Socio-Ecological System Environmental Management (OSSEM) has been investigated. The OSSEM model has been applied successfully in Spain based upon daily time series data. This research is ground breaking in that it integrates the OSSEM model in a geographic information system (GIS) environment to assess the groundwater contamination based on annual time series data and the assessment of system management by means of an overall susceptibility index (OSI). Centered on OSI indicators, the renewal, salinization and water deficit potentials in the Talar aquifer were estimated to be 4.89%, 4.61%, and 3.99%, respectively. This data demonstrates a high susceptibility in terms of environmental pollution, salinization, and water deficit.

scholarly journals FAKTOR – FAKTOR YANG MEMPENGARUHI INVESTASI PEMERINTAH PADA SEKTOR PERTANIAN DI PROVINSI JAMBI

2017 ◽  
Vol 2 (2) ◽  
pp. 85
Author(s):  
Mulyani Mulyani
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Interest Rate ◽  
Linear Regression ◽  
Real Interest Rate ◽  
Agricultural Sector ◽  
Time Series Data ◽  
Series Data ◽  
Government Investment ◽  
Agriculture Sector

This research was conducted to analyse government investment in agriculture sector at Jambi Province. This research was held  on June - September 2017 by collecting data from several agencies. It used a time series data for 10 years (2006-2015).  This research  applied   multiple linear regression to  analyse the data. The results show that 95.9% of government investment in agriculture sector could  be  explained by  domestic  income variable, export-import growth of agriculture sector, real interest rate, rupiah exchange rate, previous government investment, and growth of agriculture sector. In fact the factors that had a significant effect were domestic  income variable, , export-import growth of agricultural sector, previous government investment and the growth of agriculture sector.Keywords: government investment, agricultural sector, growthPenelitian ini dilakukan untuk menganalisis investasi pemerintah pada sektor pertanian di Provinsi Jambi. Penelitian dilaksanakan di Provinsi Jambi dengan mengumpulkan data dari beberapa instansi terkait, yang dilaksanakan pada bulan Juni 2017 sampai September 2017. Dimana penelitian ini menggunakan data time series, dengan rentang waktu 10 tahun (2006-2015). Analisis data pada penelitian ini menggunakan regresi linear berganda. Hasil penelitian menunjukkan 95,9% penyerapan investasi pemerintah pada sektor pertanian dapat dijelaskan oleh variabel pendapatan asli daerah,pertumbuhan ekspor-impor sektor pertanian, tingkat suku bunga riil, nilai tukar rupiah, investasi pemerintah pada tahun sebelumnya, dan pertumbuhan sektor pertanian. Dari faktor-faktor tersebut yang berpengaruh signifikan adalah Pendapatan asli daerah, pertumbuhan ekspor impor sektor pertanian, investasi pemrintah pada tahun sebelumnya dan pertumbuhan sektor pertanian.Kata Kunci : investasi pemerintah, sektor Pertanian, pertumbuhan

scholarly journals Fault Detection for Turbine Engine Disk Based on Adaptive Weighted One-Class Support Vector Machine

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Jiusheng Chen ◽  
Xingkai Xu ◽  
Xiaoyu Zhang
Keyword(s):  
Time Series ◽  
Support Vector Machine ◽  
Fault Detection ◽  
Data Stream ◽  
Time Series Data ◽  
Series Data ◽  
Support Vector ◽  
Turbine Engine ◽  
Detection Model ◽  
Redundant Data

Fault detection for turbine engine components is becoming increasingly important for the efficient running of commercial aircraft. Recently, the support vector machine (SVM) with kernel function is the most popular technique for monitoring nonlinear processes, which can better handle the nonlinear representation of fault detection of turbine engine disk. In this paper, an adaptive weighted one-class SVM-based fault detection method coupled with incremental and decremental strategy is proposed, which can efficiently solve the time series data stream drifting problem. To update the efficient training of the fault detection model, the incremental strategy based on the new incoming data and support vectors is proposed. The weight of the training sample is updated by the variations of the decision boundaries. Meanwhile, to increase the calculating speed of the fault detection model and reduce the redundant data, the decremental strategy based on the k-nearest neighbor (KNN) is adopted. Based on time series data stream, numerical simulations are conducted and the results validated the superiority of the proposed approach in terms of both the detection performance and robustness.

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