scholarly journals Performance of the Car Carrier Shipping Sector in the Iberian Peninsula under the COVID-19 Scenario

2021 ◽  
Vol 9 (11) ◽  
pp. 1295
Author(s):  
Jerónimo Esteve-Pérez ◽  
José Enrique Gutiérrez-Romero ◽  
Carlos Mascaraque-Ramírez
Keyword(s):  
Time Series ◽  
Seasonal Variation ◽  
Iberian Peninsula ◽  
Maritime Transportation ◽  
Ship Traffic ◽  
Worldwide Population ◽  
Port Logistics ◽  
Dynamic Portfolio ◽  
Variation Index ◽  
Eighth World

The Iberian Peninsula represents the second European producer and the eighth world producer of vehicles in 2020. The pandemic of SARS-Cov2 introduced severe challenges for the worldwide population and for the industrial production and supply chains. The car carrier shipping sector has not been studied in depth in the Maritime Transportation and Port Logistics literature. This research pays special attention to the performance of this traffic in the Iberian Peninsula in the pre-pandemic era and under COVID-19 pandemic conditions, in which seven ports with car-carrier ship traffic in the Iberian Peninsula are analyzed. First, a dynamic portfolio analysis about how the COVID-19 pandemic affected the evolution of competitive positions of Iberian Peninsula ports is performed. Second, studies of the seasonality patterns of vehicle movements in ports of the Iberian Peninsula were carried out using time series of the periods from 2012 to 2019 and from 2012 to 2020. The Seasonal Variation Index (SVI) was employed to determine the seasonality of vehicle traffic in the periods considered and analyses were performed independently for both embarking and disembarking traffic. Important conclusions are revealed, e.g., during a year of COVID-19, the seven ports had decreased vehicle movements for disembarking traffic and only one port increased the traffic for embarking traffic. Furthermore, COVID-19 introduced important changes in the seasonality patterns of vehicle movements during the first months of the pandemic.

scholarly journals Time-series modelling and forecasting of hand, foot and mouth disease cases in China from 2008 to 2018

2019 ◽  
Vol 147 ◽  
Author(s):  
C. W. Tian ◽  
H. Wang ◽  
X. M. Luo
Keyword(s):  
Time Series ◽  
Seasonal Variation ◽  
Moving Average ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Sarima Model ◽  
Autoregressive Integrated Moving Average ◽  
Annual Peak ◽  
Time Series Modelling ◽  
Foot And Mouth

AbstractSeasonal autoregressive-integrated moving average (SARIMA) has been widely used to model and forecast incidence of infectious diseases in time-series analysis. This study aimed to model and forecast monthly cases of hand, foot and mouth disease (HFMD) in China. Monthly incidence HFMD cases in China from May 2008 to August 2018 were analysed with the SARIMA model. A seasonal variation of HFMD incidence was found from May 2008 to August 2018 in China, with a predominant peak from April to July and a trough from January to March. In addition, the annual peak occurred periodically with a large annual peak followed by a relatively small annual peak. A SARIMA model of SARIMA (1, 1, 2) (0, 1, 1)12 was identified, and the mean error rate and determination coefficient were 16.86% and 94.27%, respectively. There was an annual periodicity and seasonal variation of HFMD incidence in China, which could be predicted well by a SARIMA (1, 1, 2) (0, 1, 1)12 model.

scholarly journals Remote sensing-based soil water balance for irrigation water accounting at the Spanish Iberian Peninsula

2018 ◽  
Vol 380 ◽  
pp. 29-35 ◽  
Author(s):  
Jesús Garrido-Rubio ◽  
Alfonso Calera Belmonte ◽  
Lorena Fraile Enguita ◽  
Irene Arellano Alcázar ◽  
Mario Belmonte Mancebo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Water Balance ◽  
Iberian Peninsula ◽  
Soil Water ◽  
Irrigation Water ◽  
Water Governance ◽  
Soil Water Balance ◽  
Water Requirements ◽  
Water Accounting

Abstract. Temporal series maps of irrigated areas, and the corresponding irrigation water requirements based on remote sensing, is a recognized tool contributing to water governance at different scales, from water user associations to whole river basin districts. These thematic cartographies offer a first estimation of the crop irrigation requirements, and a biophysical based approach of the temporal and spatial distribution of the crop water use in the cultivated areas. This work describes the operational application of these methodologies, providing valuable information for water governance and management purposes. The basic products obtained in the whole Spanish part of the Iberian Peninsula during the period 2014–2017 were: (i) annual maps of irrigated crops based on time series of multispectral satellite imagery; and (ii) the direct remote sensing-based water accounting, by quantifying agricultural water flows (e.g. rainfall, irrigation, evapotranspiration, drainage and recharge), through a remote sensing-based soil water balance. Hence this paper provides a remote sensing based water accounting approach, which relies on dense time series of multispectral imagery acquired by the multisensor constellation arranged by Landsat 8 and Sentinel-2 satellites, jointly with meteorological data and agronomic knowledge. Then, based on these purpose and approach, annual and monthly maps of net irrigation water requirements have been elaborated at the most practical spatial and temporal scales for water governance purposes over big areas such river basin districts. This work summarizes the methodologies used and discuss the technical and non-technical feasibility of the proposed approach.

scholarly journals Seasonal variation and change trends for quit smoking: evidence from Internet search engine query data

2019 ◽  
Author(s):  
Fang Wang ◽  
Dingtao Hu ◽  
Xiaoqi Lou ◽  
Nana Meng ◽  
Qiaomei Xie ◽  
...  
Keyword(s):  
Time Series ◽  
Smoking Cessation ◽  
Seasonal Variation ◽  
New Zealand ◽  
Google Trends ◽  
Internet Search ◽  
Quit Smoking ◽  
Significant Seasonal Variation ◽  
The Usa ◽  
The Uk

Abstract Background: The outcomes of smoking have generated considerable clinical interest in recent years. Although people from different countries are more interested to the topic of quit smoking during the winter, few studies have tested this hypothesis. The current study aimed to quantify public interest in quit smoking via Google.Methods: We use Google Trends to obtain the Internet search query volume for terms relating to quit smoking for major northern and southern hemisphere countries in this research. Normally search volumes for the term “quit smoking + stop smoking + smoking cessation” were retrieved within the USA, the UK, Canada, Ireland, New Zealand and Australia from January 2004 to December 2018. Seasonal effects were investigated using cosinor analysis and seasonal decomposition of time series models.Results: Significant seasonal variation patterns in those search terms were revealed by cosinor analysis and demonstrated by the evidence from Google Trends analysis in the representative countries including the USA (pcos = 2.36×10-7), the UK (pcos < 2.00×10-16), Canada (pcos < 2.00×10-16), Ireland (pcos <2.00×10-16) ,Australia (pcos = 5.13×10-6) and New Zealand (pcos = 4.87×10-7). Time series plots emphasized the consistency of seasonal trends with peaks in winter / late autumn by repeating in nearly all years. The overall trend of search volumes, observed by dynamic series analysis, declined from 2004 to 2018.Conclusions: The preliminary evidence from Google Trends search tool showed a significant seasonal variation and decreasing trend for the RSV of quit smoking. Our novel findings in smoking cessation epidemiology need to be verified with further studies, and the mechanisms underlying these findings must be clarified.

Time-series analysis—Seasonal variation.

2011 ◽  
pp. 617-636
Author(s):  
James G. Smith ◽  
Acheson J. Duncan
Keyword(s):  
Time Series ◽  
Seasonal Variation ◽  
Time Series Analysis ◽  
Series Analysis

Crop Decision Tree Classification Extraction Based on MODIS NDVI in Beijing

2014 ◽  
Vol 955-959 ◽  
pp. 787-790 ◽  
Author(s):  
Shi Wei Dong ◽  
Dan Feng Sun ◽  
Hong Li
Keyword(s):  
Time Series ◽  
Spatial Distribution ◽  
Seasonal Variation ◽  
Decision Tree ◽  
Land Surface ◽  
Satellite Images ◽  
Overwhelming Majority ◽  
Modis Ndvi ◽  
Decision Tree Classification ◽  
Double Cropping

Time-series satellite images can reflect the seasonal variation from vegetation on land surface. Single cropping and double cropping were extracted by decision tree classification based on MODIS NDVI of Beijing in 2007, and spatial distribution of dominant crops in Beijing was obtained. The dominant crops of single cropping were maize, wheat and vegetable, and the overwhelming majority of crops with double cropping were wheat-maize. The results showed that this method could effectively determine the dominated crops in Beijing.

Operation Management of Port Logistics in the Global Supply Chain

2013 ◽  
Vol 706-708 ◽  
pp. 2087-2090
Author(s):  
Chien Chang Chou ◽  
Ji Feng Ding ◽  
Tzu Min Chang ◽  
Chun Pong Wong ◽  
Wen Cheng Lin ◽  
...  
Keyword(s):  
Supply Chain ◽  
Global Supply Chain ◽  
Maritime Transportation ◽  
Operation Management ◽  
Analysis Method ◽  
Supply Chain System ◽  
Chain System ◽  
Threat Analysis ◽  
Port Logistics ◽  
Container Ports

The global supply chain system includes sea, air, and inland transportations. The port logistics plays an important role in the maritime transportation. The aim of this study is to analyze the operation management of the world’s top 20 container ports by using SWOT (Strength, Weakness, Opportunity, and Threat) analysis method. Finally, some conclusions and suggestions are given to the international manufacturers, port managers, and departments of governmental maritime.

The effect of season and the introduction of rams on oestrous activity in Somali, Nandi, Merino, Karakul and New Zealand Romney Marsh ewes in Kenya

1986 ◽  
Vol 43 (3) ◽  
pp. 447-457 ◽  
Author(s):  
A. B. Carles ◽  
W. A. K. Kipngeno
Keyword(s):  
Time Series ◽  
Seasonal Variation ◽  
New Zealand ◽  
Time Series Analysis ◽  
Oestrous Cycle ◽  
Significant Source ◽  
Short Term ◽  
Series Analysis ◽  
The Mean

ABSTRACTA study was made of the levels of oestrous activity of two indigenous breeds of sheep (Somali and Nandi) and three exotic breeds of sheep (Merino, Karakul and New Zealand Romney Marsh) over a period of 3 years, in an equatorial environment. Breed was the only significant source of variation for the length of the oestrous cycle (P < 0·01). The mean lengths of the oestrous cycle were 17·2 (s.d. 3·21), 17·5 (s.d. 2·24), 17·9 (s.d. 2·99), 17·5 (s.d. 2·57) and 16·5 (s.d. 3·41) days for the Somali, Nandi, Merino, Karakul and Romney Marsh breeds, respectively.The mean percentage of ewes of the different breeds showing oestrus in 20-day periods were 69·8 (s.d. 22·57), 49·9 (s.d. 18·67), 63·4 (s.d. 25·70), 79·2 (s.d. 20·30) and 33·2 (s.d. 23·50) % for the Somali, Nandi, Merino, Karakul and Romney Marsh breeds, respectively. Time-series analysis did not detect any evidence of seasonal variation in oestrous activity, although there was an indication that the Merino and Romney Marsh breeds showed a marked increase in oestrous activity following, the introduction of rams. It was concluded that the variation in level of oestrous activity was short term and random.

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