Predicting Potential Conflict Areas of the Malayan Sun Bear (Helarctos malayanus) in Peninsular Malaysia Using Maximum Entropy Model

Mammal Study ◽  
2019 ◽  
Vol 44 (3) ◽  
pp. 193
Author(s):  
Kamaruddin Z. Abidin ◽  
Tukimat Lihan ◽  
Taherah M. Taher ◽  
Nabilah Nazri ◽  
Izzat-Husna Ahmad Zaini ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Peninsular Malaysia ◽  
Maximum Entropy Model ◽  
Entropy Model ◽  
Potential Conflict ◽  
Helarctos Malayanus ◽  
Sun Bear

scholarly journals Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Arian Ashourvan ◽  
Preya Shah ◽  
Adam Pines ◽  
Shi Gu ◽  
Christopher W. Lynn ◽  
...  
Keyword(s):  
White Matter ◽  
Maximum Entropy ◽  
Large Scale ◽  
Structural Connectivity ◽  
Quantitative Relationship ◽  
Brain Regions ◽  
Maximum Entropy Model ◽  
Entropy Model ◽  
Activation Patterns ◽  
Co Activation

AbstractA major challenge in neuroscience is determining a quantitative relationship between the brain’s white matter structural connectivity and emergent activity. We seek to uncover the intrinsic relationship among brain regions fundamental to their functional activity by constructing a pairwise maximum entropy model (MEM) of the inter-ictal activation patterns of five patients with medically refractory epilepsy over an average of ~14 hours of band-passed intracranial EEG (iEEG) recordings per patient. We find that the pairwise MEM accurately predicts iEEG electrodes’ activation patterns’ probability and their pairwise correlations. We demonstrate that the estimated pairwise MEM’s interaction weights predict structural connectivity and its strength over several frequencies significantly beyond what is expected based solely on sampled regions’ distance in most patients. Together, the pairwise MEM offers a framework for explaining iEEG functional connectivity and provides insight into how the brain’s structural connectome gives rise to large-scale activation patterns by promoting co-activation between connected structures.

Video segmentation using Maximum Entropy Model

2005 ◽  
Vol 6 (S1) ◽  
pp. 47-52
Author(s):  
Li-juan Qin ◽  
Yue-ting Zhuang ◽  
Yun-he Pan ◽  
Fei Wu
Keyword(s):  
Maximum Entropy ◽  
Video Segmentation ◽  
Maximum Entropy Model ◽  
Entropy Model

scholarly journals Spatial Assessment of Potential Conflict of Sun Bear- Human Based on Landscape Ecology in Pasaman

2020 ◽  
Author(s):  
Muhammad Hanif ◽  
Henzulkifli Rahman ◽  
Rizki Atthoriq Hidayat ◽  
Hariyo Tabah Wibisono
Keyword(s):  
Forest Edge ◽  
Geographical Information ◽  
Potential Conflict ◽  
Geospatial Modeling ◽  
Helarctos Malayanus ◽  
Average Value ◽  
Ecological Problems ◽  
Variable Contribution ◽  
Sun Bear ◽  
The One

The sun bear is conservation mammal in Indonesia. The ecological problems as conflict among mammals and human often happen around wildlife, the one of the case is the conflict between sun bear (helarctos malayanus) with human. In Pasaman where around the anthropogenic landscape is bounded by natural forest as sun bear habitat. In this decade, the story has recorded about ±16 incidents. The aim of this research is to geospatial modeling the area of potential conflict between sun bear- human. The method in this research is to use natural logarithmic and regression logistic. The tool is geographical information system and maximum entropy. The result of this research, there has found the distribute energy each variable landscape ecosystem. The statistical model of the potential conflict it has spread on landscape ecosystem. The average value of AUC prediction in this model is at number of 0.91. The variable contribution which affect are forest edge at number of 39.2%, the alternative food (plantation) at number of 31.4%, and forest fragmentation at number of 16.9%.

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