Who's onboard? A predictive analysis of cooperative formation in commercial fisheries

2021 ◽  
Vol 279 ◽  
pp. 111715
Author(s):  
Michael De Alessi ◽  
Michael C. Melnychuk ◽  
Edward Wort ◽  
Ray Hilborn
2019 ◽  
Vol 13 (1) ◽  
pp. 27-36
Author(s):  
Andreas Neubert

Due to the different characteristics of the piece goods (e.g. size and weight), they are transported in general cargo warehouses by manually-operated industrial trucks such as forklifts and pallet trucks. Since manual activities are susceptible to possible human error, errors occur in logistical processes in general cargo warehouses. This leads to incorrect loading, stacking and damage to storage equipment and general cargo. It would be possible to reduce costs arising from errors in logistical processes if these errors could be remedied in advance. This paper presents a monitoring procedure for logistical processes in manually-operated general cargo warehouses. This is where predictive analysis is applied. Seven steps are introduced with a view to integrating predictive analysis into the IT infrastructure of general cargo warehouses. These steps are described in detail. The CRISP4BigData model, the SVM data mining algorithm, the data mining tool R, the programming language C++ for the scoring in general cargo warehouses represent the results of this paper. After having created the system and installed it in general cargo warehouses, initial results obtained with this method over a certain time span will be compared with results obtained without this method through manual recording over the same period.


2020 ◽  
Vol 642 ◽  
pp. 163-177 ◽  
Author(s):  
Y Niella ◽  
AF Smoothey ◽  
V Peddemors ◽  
R Harcourt

In the face of accelerating climate change, conservation strategies will need to consider how marine animals deal with forecast environmental change as well as ongoing threats. We used 10 yr (2009-2018) of data from commercial fisheries and a bather protection program along the coast of New South Wales (NSW), southeastern Australia, to investigate (1) spatial and temporal patterns of occurrence in bull sharks and (2) environmental factors affecting bull shark occurrence along the coast of NSW. Predicted future distribution for this species was modelled for the forecast strengthening East Australian Current. Bull sharks were mostly harvested in small to larger estuaries, with average depth and rainfall responsible for contrasting patterns for each of the fisheries. There was an increase in the occurrence of bull sharks over the last decade, particularly among coastal setline fisheries, associated with seasonal availability of thermal gradients >22°C and both westward and southward coastal currents stronger than 0.15 and 0.60 m s-1, respectively, during the austral summer. Our model predicts a 3 mo increase in the availability of favourable water temperatures along the entire coast of NSW for bull sharks by 2030. This coastline provides a uniquely favourable topography for range expansion in the face of a southerly shift of warmer waters, and habitat is unlikely to be a limiting factor for bull sharks in the future. Such a southerly shift in distribution has implications for the management of bull sharks both in commercial fisheries and for mitigation of shark-human interactions.


2013 ◽  
Vol 26 (1 (special Issue)) ◽  
pp. 220-238 ◽  
Author(s):  
Thamer S. Ali ◽  
Asma A. Abahussain
Keyword(s):  

2010 ◽  
Vol 4 (4) ◽  
pp. 33-39 ◽  
Author(s):  
Thomas Page ◽  
Gisli Thorsteinsson

Author(s):  
Yogesh Awasthi

Agriculture is the backbone of the developing country. In old era agriculture was based on the experience which was shared by people to people but in this digital era technology play a very important and significant role in agriculture. Now agriculture become a business hub therefore farmers are focusing on precision farming. They introduced the technology in agriculture to define the accurate information about seed, soil, weather, disease and all factors which affecting the farming. Artificial Intelligence uses predictive analysis, image analysis, learning techniques and Pattern analysis to declare the best cost effective and maximum gain for the agriculturist. The aim of this paper is to provide the crucial information with the help of technology which a farmers can use to harvest the variety of crops as per the demand in world so that they can get maximum benefits.


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