scholarly journals Prediction of Short-Time Rainfall Based on Deep Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Dechao Sun ◽  
Jiali Wu ◽  
Hong Huang ◽  
Renfang Wang ◽  
Feng Liang ◽  
...  
Keyword(s):  
Heavy Precipitation ◽  
Rainfall Prediction ◽  
Spatial Features ◽  
Short Period ◽  
Radar Echo ◽  
Real Value ◽  
Temporal And Spatial ◽  
The Government ◽  
Short Time ◽  
Regional Rainfall

Short-time heavy rainfall is a kind of sudden strong and heavy precipitation weather, which seriously threatens people’s life and property safety. Accurate precipitation nowcasting is of great significance for the government to make disaster prevention and mitigation decisions in time. In order to make high-resolution forecasts of regional rainfall, this paper proposes a convolutional 3D GRU (Conv3D-GRU) model to predict the future rainfall intensity over a relatively short period of time from the machine learning perspective. Firstly, the spatial features of radar echo maps with different heights are extracted by 3D convolution, and then, the radar echo maps on time series are coded and decoded by using GRU. Finally, the trained model is used to predict the radar echo maps in the next 1-2 hours. The experimental results show that the algorithm can effectively extract the temporal and spatial features of radar echo maps, reduce the error between the predicted value and the real value of rainfall, and improve the accuracy of short-term rainfall prediction.

scholarly journals Two-Stage Spatiotemporal Context Refinement Network for Precipitation Nowcasting

2021 ◽  
Vol 13 (21) ◽  
pp. 4285
Author(s):  
Dan Niu ◽  
Junhao Huang ◽  
Zengliang Zang ◽  
Liujia Xu ◽  
Hongshu Che ◽  
...  
Keyword(s):  
Heavy Precipitation ◽  
Machine Learning Algorithms ◽  
Two Stage ◽  
Rainfall Prediction ◽  
Multi Scale ◽  
Second Stage ◽  
Proposed Model ◽  
Radar Echo ◽  
Echo Threshold ◽  
Residual Block

Precipitation nowcasting by radar echo extrapolation using machine learning algorithms is a field worthy of further study, since rainfall prediction is essential in work and life. Current methods of predicting the radar echo images need further improvement in prediction accuracy as well as in presenting the predicted details of the radar echo images. In this paper, we propose a two-stage spatiotemporal context refinement network (2S-STRef) to predict future pixel-level radar echo maps (deterministic output) more accurately and with more distinct details. The first stage is an efficient and concise spatiotemporal prediction network, which uses the spatiotemporal RNN module embedded in an encoder and decoder structure to give a first-stage prediction. The second stage is a proposed detail refinement net, which can preserve the high-frequency detailed feature of the radar echo images by using the multi-scale feature extraction and fusion residual block. We used a real-world radar echo map dataset of South China to evaluate the proposed 2S-STRef model. The experiments showed that compared with the PredRNN++ and ConvLSTM method, our 2S-STRef model performs better on the precipitation nowcasting, as well as at the image quality evaluating index and the forecasting indices. At a given 45dBZ echo threshold (heavy precipitation) and with a 2 h lead time, the widely used CSI, HSS, and SSIM indices of the proposed 2S-STRef model are found equal to 0.195, 0.312, and 0.665, respectively. In this case, the proposed model outperforms the OpticalFlow method and PredRNN++ model.

scholarly journals Early Detection of Baby-Rain-Cell Aloft in a Severe Storm and Risk Projection for Urban Flash Flood

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Eiichi Nakakita ◽  
Hiroto Sato ◽  
Ryuta Nishiwaki ◽  
Hiroyuki Yamabe ◽  
Kosei Yamaguchi
Keyword(s):  
Heavy Rainfall ◽  
Flash Flood ◽  
Early Stage ◽  
Rainfall Prediction ◽  
Radar Echo ◽  
Risk Projection ◽  
Important Sign ◽  
Short Time ◽  
The Relationship ◽  
Vortex Tubes

In July 2008, five people were killed by a tragic flash flood caused by a local torrential heavy rainfall in a short time in Toga River. From this tragic accident, we realized that a system which can detect hazardous rain-cells in the earlier stage is strongly needed and would provide an additional 5 to 10 min for evacuation. By analyzing this event, we verified that a first radar echo aloft, by volume scan observation, is a practical and important sign for early warning of flash flood, and we named a first echo as a “baby-rain-cell” of Guerrilla-heavy rainfall. Also, we found a vertical vorticity criterion for identifying hazardous rain-cells and developed a heavy rainfall prediction system that has the important feature of not missing any hazardous rain-cell. Being able to detect heavy rainfall by 23.6 min on average before it reaches the ground, this system is implemented in XRAIN in the Kinki area. Additionally, to resolve the relationship between baby-rain-cell growth and vorticity behavior, we carried out an analysis of vorticity inside baby-rain-cells and verified that a pair of positive and negative vertical vortex tubes as well as an updraft between them existed in a rain-cell in the early stage.

An Indian Official’s Trials and Tribulations

2018 ◽  
Author(s):  
Ruchi Ram Sahni
Keyword(s):  
Psychological Trauma ◽  
Government College ◽  
Chemistry Department ◽  
Senior Professor ◽  
Short Period ◽  
The Government ◽  
The University

In this chapter Ruchi Ram Sahni recounts what he calls the most depressing and unpleasant incident of his life. It involved his supersession for the position of Professor-in-Charge of the Chemistry Department at the Government College, Lahore, by a much younger Englishman, fresh from university. The post in question was vacated by an English colleague, a Senior Professor, with whom the author had a difficult relationship involving a dispute about who was to be selected for the post of Examiner in the university examinations. This colleague went on to write a secret report against Sahni, resulting in his supersession despite his vast seniority. Sahni relates the psychological trauma resulting from this experience, and its contribution to strengthen his resolve to leave Lahore for a short period to do research in Europe.

scholarly journals The role of action effects in motor sequence planning and execution: exploring the influence of temporal and spatial effect anticipation

2021 ◽  
Author(s):  
Rachel M. Brown ◽  
Erik Friedgen ◽  
Iring Koch
Keyword(s):  
Action Planning ◽  
Spatial Effects ◽  
Motor Sequence ◽  
Action Sequence ◽  
Sequential Action ◽  
Spatial Features ◽  
Temporal Features ◽  
Action Sequences ◽  
Temporal And Spatial ◽  
Anticipation Effect

AbstractActions we perform every day generate perceivable outcomes with both spatial and temporal features. According to the ideomotor principle, we plan our actions by anticipating the outcomes, but this principle does not directly address how sequential movements are influenced by different outcomes. We examined how sequential action planning is influenced by the anticipation of temporal and spatial features of action outcomes. We further explored the influence of action sequence switching. Participants performed cued sequences of button presses that generated visual effects which were either spatially compatible or incompatible with the sequences, and the spatial effects appeared after a short or long delay. The sequence cues switched or repeated across trials, and the predictability of action sequence switches was varied across groups. The results showed a delay-anticipation effect for sequential action, whereby a shorter anticipated delay between action sequences and their outcomes speeded initiation and execution of the cued action sequences. Delay anticipation was increased by predictable action switching, but it was not strongly modified by the spatial compatibility of the action outcomes. The results extend previous demonstrations of delay anticipation to the context of sequential action. The temporal delay between actions and their outcomes appears to be retrieved for sequential planning and influences both the initiation and the execution of actions.

scholarly journals Inferring Long-Term Demand of Newly Established Stations for Expansion Areas in Bike Sharing System

2021 ◽  
Vol 11 (15) ◽  
pp. 6748
Author(s):  
Hsun-Ping Hsieh ◽  
Fandel Lin ◽  
Jiawei Jiang ◽  
Tzu-Ying Kuo ◽  
Yu-En Chang
Keyword(s):  
New York ◽  
Feature Extraction ◽  
Real World ◽  
Extraction Methods ◽  
Real World Data ◽  
Urban Dynamics ◽  
Bike Sharing ◽  
The Government ◽  
Short Time

Research on flourishing public bike-sharing systems has been widely discussed in recent years. In these studies, many existing works focus on accurately predicting individual stations in a short time. This work, therefore, aims to predict long-term bike rental/drop-off demands at given bike station locations in the expansion areas. The real-world bike stations are mainly built-in batches for expansion areas. To address the problem, we propose LDA (Long-Term Demand Advisor), a framework to estimate the long-term characteristics of newly established stations. In LDA, several engineering strategies are proposed to extract discriminative and representative features for long-term demands. Moreover, for original and newly established stations, we propose several feature extraction methods and an algorithm to model the correlations between urban dynamics and long-term demands. Our work is the first to address the long-term demand of new stations, providing the government with a tool to pre-evaluate the bike flow of new stations before deployment; this can avoid wasting resources such as personnel expense or budget. We evaluate real-world data from New York City’s bike-sharing system, and show that our LDA framework outperforms baseline approaches.

The African Press in Kenya, 1945–1952

1980 ◽  
Vol 21 (4) ◽  
pp. 515-535 ◽  
Author(s):  
Fay Gadsden
Keyword(s):  
The Political ◽  
Constitutional Change ◽  
African Union ◽  
Direct Role ◽  
State Of Emergency ◽  
Social Reforms ◽  
The Press ◽  
Grassroots Level ◽  
The Government ◽  
Short Time

This paper discusses the African press in Kenya in the years between 1945 and 1952. The growth of an extensive vernacular press was caused by the political frustrations suffered by Kenya's Africans and the political, social and ethnic divisions which separated them. The press can be divided into three major categories: moderate nationalist, regional vernacular and populist newspapers. The moderate nationalist newspapers were edited by members of the educated elite who campaigned for constitutional change and social reforms. The regional vernacular papers were concerned more with local than national issues. The populist press was edited by semi-educated men active in politics at the grassroots level who came to reject the moderate leadership. All these papers publicized the activities of the Kenya African Union and demanded an improvement in the political and social position of Africans in Kenya. But they also expressed the ethnic, political and social hostilities which divided their editors. The decline of moderate leadership was reflected in the closure of their newspapers. The radicals who seized power in K.A.U. in 1951 were supported by the populist press and began new newspapers in 1951 and 1952.Some of the African newspapers achieved quite large circulations, were distributed by agents throughout the towns of Kenya and attracted some advertising revenue. But they all suffered from lack of money and found it difficult to find and pay a printer, and they suffered also from the lack of experience of their editors. Many newspapers lasted only a short time. But throughout these years there were always a number of newspapers published. These were widely read and were politically influential. The populist press played a direct role in stimulating militant resistance. Government attempts to curb the African press and to replace it with government newspapers were not successful. Only in 1952 when a State of Emergency had been imposed and the government had assumed powers to refuse printing licences and to suppress newspapers could the African press be silenced.

Finding beneficiaries: trade adjustment assistance system in South Korea

2017 ◽  
Vol 16 (2) ◽  
pp. 92-105 ◽  
Author(s):  
Joon-heon Song
Keyword(s):  
South Korea ◽  
Analytical Framework ◽  
Policy Preferences ◽  
Trade Adjustment Assistance ◽  
Content Type ◽  
South Korean ◽  
Policy Failure ◽  
Short Period ◽  
Trade Adjustment ◽  
The Government

Purpose The purpose of this study is to explore the essential cause for the policy failure of Trade Adjustment Assistance (TAA) in South Korea. Design/methodology/approach To substantiate the claims made for the failure of the policy, this paper focuses on the differences in policy preferences among the government ministries and agencies involved in TAA. Findings The failure in the TAA policy, according to this study, was attributed to the conflicts and miscoordination arising from the differences in policy preferences among government ministries and agencies. To rectify this failure, the South Korean government had to revise its laws and regulations several times over a short period. Originality/value Drawing on the analytical framework of the literature on policy failure, this paper examines the causal relationships between outcomes of TAA policy and the conflicts or miscoordination among government bodies at each stage: initiatives and planning, implementation and operation of the policy.

The Success of Cognitive Activity of Students of the Northern (Arctic) Federal University with Different Levels of Anxietyin Different Time Conditions

2021 ◽  
Vol 18 (1) ◽  
pp. 52-59
Author(s):  
A.I. Taleeva ◽  
◽  
I.T. Madumarova ◽  
N.V. Zvyagina ◽  
◽  
...  
Keyword(s):  
Emotional State ◽  
Cognitive Task ◽  
Cognitive Activity ◽  
Whole Body ◽  
Modern World ◽  
Short Period ◽  
Personal Anxiety ◽  
Psychophysiological Testing ◽  
Short Time ◽  
Different Levels

The dynamic development of the modern world requires the processing and development of a large enough amount of information in a short period of time, which leads to a violation of the psychophysiological and psycho-emotional balance of the person. Violation of the psycho-emotional state leads to the development of increased anxiety. Students need to learn a lot of information in a very short time. The time limit affects students as a stress factor, leads to increased stress and therefore negatively affects the quality of work and in general on the whole body. The aim of the study is to determine the success of cognitive tasks by students of the Northern (Arctic) Federal University with different levels of anxiety in different time conditions. The study used a psychophysiological testing device to determine the level of situational and personal anxiety, to assess the psycho-emotional state used the technique of simple visual-motor reaction, to determine the success of the cognitive task were presented words with one missing letter.

Anomaly Detection of Budgetary Allocations Using Machine-Learning-Based Techniques

2021 ◽  
Vol 107 ◽  
pp. 174-181
Author(s):  
Garba Aliyu ◽  
Ibrahim Enesi Umar ◽  
Irunokhai Eric Aghiomesi ◽  
Hassan Jimoh Onawola ◽  
Sandip Rakshit
Keyword(s):  
Machine Learning ◽  
Anomaly Detection ◽  
Unintended Consequences ◽  
Critical Examination ◽  
Machine Learning Technique ◽  
National Assembly ◽  
Substantial Modification ◽  
Short Period ◽  
Learning Technique ◽  
The Government

In Nigeria, a crucial responsibility of the executive arms of the government is to submit annual budgetary allocations to the national assembly for approval. Due to the diversity and complexity of the budget, the national assembly is mandated to carry out its constitutional duty of scrutinizing the budget to discover irregularity or anomaly, make recommendations, or substantial modification upon what it received. This is very challenging, particularly in Nigeria where there are many different ethnicities and regional, to ensure inclusiveness, the national assembly must carry out its constitutional duty diligently and carefully without fear or favor that often has unintended consequences. This might not be very easy to accomplish within a short period. Thus, this research aims at detecting an anomaly in the budget that will ease the legislative duty thereby facilitating the process of appropriation. The concept of Clustering for Machine learning technique was used for the detection of an anomaly, where the detected ones are noted and indicated for critical examination.

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