Data Analysis
The dataset utilized in this research originates from two primary sources: the Central Bureau of Statistics of Indonesia, which provides data on Harvested Area and Production, and the Meteorology, Climatology, and Geophysics Agency of Indonesia, responsible for data on Rainfall, Humidity, and Temperature. This dataset encompasses six years of observations, collected annually from 2018 to 2023. It is important to note that the data for December 2023 are predictive estimates from these agencies.
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Please cite the following paper when using this dataset:
N. Thakur, K. Khanna, S. Cui, N. Azizi, and Z. Liu, “Mining and Analysis of Search Interests related to Online Learning Platforms from Different Countries since the Beginning of COVID-19” [Unpublished Paper - Paper submitted to HCI International 2023, Copenhagen, Denmark, 23-28 July 2023]
Brief Description of Dataset file - Interest_Dataset.csv:
Attribute Name: Week
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222 Views
Please cite the following paper when using this dataset:
N. Thakur, K. Khanna, S. Cui, N. Azizi, and Z. Liu, “Mining and Analysis of Search Interests related to Online Learning Platforms from Different Countries since the Beginning of COVID-19” [Unpublished Paper - Paper submitted to HCI International 2023, Copenhagen, Denmark, 23-28 July 2023]
Brief Description of Dataset file - Interest_Dataset.csv:
Attribute Name: Week
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Views
Please cite the following paper when using this dataset:
N. Thakur, K. Khanna, S. Cui, N. Azizi, and Z. Liu, “Mining and Analysis of Search Interests related to Online Learning Platforms from Different Countries since the Beginning of COVID-19”, Proceedings of the 25th International Conference on Human-Computer Interaction (HCII 2023), Copenhagen, Denmark, July 23-28, 2023 (Accepted for Publication)
Brief Description of Dataset file - Interest_Dataset.csv:
Attribute Name: Week
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1173 Views
It is a large-scale data set of wireless network coverage for over 22,000 4G base stations in France. This data set is generated by applying VoronoiBoost and official sources of base station deployment. The data covers ten main metropolitan areas in the country, encompassing a variety of dense urban, suburban and rural areas.
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210 Views
This dataset includes gathering 18-month raw PV data at time intervals of about 200 µs (5 kHz sampling). A post-processing 365-day day-by-day downsampled version, converted to 10 ms intervals (100 Hz sampling), is also included. The end results are two databases: 1. The original, raw, data, including both fast (short circuit, 200 µs) and slow (sweep, 2.5-3.9 s) information for 18 months. These show intervals of missing points, but are provided to allow potential users to reproduce any new work. 2.
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1016 Views
Normal
0
false
false
false
EN-US
X-NONE
X-NONE
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195 Views
Archival bundle of District Information System for Education (DISE) Delhi primary to upper-primary level schools in academic session 2012-2013. DISE is a school-level dataset consisting of government-recognized schools. It is a joint initiative of the Government of India, UNICEF and the National University of Education and Planning (NUPEA).
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206 Views
Archival bundle of District Information System for Education (DISE) Delhi primary to upper-primary level schools in academic session 2012-2013. DISE is a school-level dataset consisting of government-recognized schools. It is a joint initiative of the Government of India, UNICEF and the National University of Education and Planning (NUPEA).
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202 Views
Here we intend to review the current state of the art of interactive data exploration techniques,
and to discover the maturity of the existing solutions. We look for solutions that satisfy three requirements:
access to raw data files, stored in a distributed environment, and with a reasonably low latency.
Method This work follows the well-defined guidelines for Systematic Mapping Studies, which is well-
suited for gathering and classifying available studies.
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191 Views