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Chapman University

Mathematics, Physics, and Computer Science Faculty Articles and Research

2019

Articles 1 - 7 of 7

Full-Text Articles in Life Sciences

Estimating Live Fuel Moisture Using Smap L-Band Radiometer Soil Moisture For Southern California, Usa, Shenyue Jia, Seung Hee Kim, Son V. Nghiem, Menas Kafatos Jul 2019

Estimating Live Fuel Moisture Using Smap L-Band Radiometer Soil Moisture For Southern California, Usa, Shenyue Jia, Seung Hee Kim, Son V. Nghiem, Menas Kafatos

Mathematics, Physics, and Computer Science Faculty Articles and Research

Live fuel moisture (LFM) is a field-measured indicator of vegetation water content and a crucial observation of vegetation flammability. This study presents a new multi-variant regression model to estimate LFM in the Mediterranean ecosystem of Southern California, USA, using the Soil Moisture Active Passive (SMAP) L-band radiometer soil moisture (SMAP SM) from April 2015 to December 2018 over 12 chamise (Adenostoma fasciculatum) LFM sites. The two-month lag between SMAP SM and LFM was utilized either as steps to synchronize the SMAP SM to the LFM series or as the leading time window to calculate the accumulative SMAP SM. …


Coral Reef Change Detection In Remote Pacific Islands Using Support Vector Machine Classifiers, Justin J. Gapper, Hesham El-Askary, Erik Linstead, Thomas Piechota Jun 2019

Coral Reef Change Detection In Remote Pacific Islands Using Support Vector Machine Classifiers, Justin J. Gapper, Hesham El-Askary, Erik Linstead, Thomas Piechota

Mathematics, Physics, and Computer Science Faculty Articles and Research

Despite the abundance of research on coral reef change detection, few studies have been conducted to assess the spatial generalization principles of a live coral cover classifier trained using remote sensing data from multiple locations. The aim of this study is to develop a machine learning classifier for coral dominated benthic cover-type class (CDBCTC) based on ground truth observations and Landsat images, evaluate the performance of this classifier when tested against new data, then deploy the classifier to perform CDBCTC change analysis of multiple locations. The proposed framework includes image calibration, support vector machine (SVM) training and tuning, statistical assessment …


Integration Of Random Forest Classifiers And Deep Convolutional Neural Networks For Classification And Biomolecular Modeling Of Cancer Driver Mutations, Steve Agajanian, Odeyemi Oluyemi, Gennady M. Verkhivker Jun 2019

Integration Of Random Forest Classifiers And Deep Convolutional Neural Networks For Classification And Biomolecular Modeling Of Cancer Driver Mutations, Steve Agajanian, Odeyemi Oluyemi, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Development of machine learning solutions for prediction of functional and clinical significance of cancer driver genes and mutations are paramount in modern biomedical research and have gained a significant momentum in a recent decade. In this work, we integrate different machine learning approaches, including tree based methods, random forest and gradient boosted tree (GBT) classifiers along with deep convolutional neural networks (CNN) for prediction of cancer driver mutations in the genomic datasets. The feasibility of CNN in using raw nucleotide sequences for classification of cancer driver mutations was initially explored by employing label encoding, one hot encoding, and embedding to …


Assessment Of Agricultural Drought Considering The Hydrological Cycle And Crop Phenology In The Korean Peninsula, Chul-Hee Lim, Seung Hee Kim, Jong Ahn Chun, Menas Kafatos, Woo-Kyun Lee May 2019

Assessment Of Agricultural Drought Considering The Hydrological Cycle And Crop Phenology In The Korean Peninsula, Chul-Hee Lim, Seung Hee Kim, Jong Ahn Chun, Menas Kafatos, Woo-Kyun Lee

Mathematics, Physics, and Computer Science Faculty Articles and Research

Hydrological changes attributable to global warming increase the severity and frequency of droughts, which in turn affect agriculture. Hence, we proposed the Standardized Agricultural Drought Index (SADI), which is a new drought index specialized for agriculture and crops, and evaluated current and expected droughts in the Korean Peninsula. The SADI applies crop phenology to the hydrological cycle, which is a basic element that assesses drought. The SADI of rice and maize was calculated using representative hydrological variables (precipitation, evapotranspiration, and runoff) of the crop growing season. In order to evaluate the effectiveness of SADI, the three-month Standardized Precipitation Index, which …


Using Multi-Indices Approach To Quantify Mangrove Changes Over The Western Arabian Gulf Along Saudi Arabia Coast, Wenzhao Li, Hesham El-Askary, Mohamed A. Qurban, Jingjing Li, K. P. Manikandan, Thomas Piechota Mar 2019

Using Multi-Indices Approach To Quantify Mangrove Changes Over The Western Arabian Gulf Along Saudi Arabia Coast, Wenzhao Li, Hesham El-Askary, Mohamed A. Qurban, Jingjing Li, K. P. Manikandan, Thomas Piechota

Mathematics, Physics, and Computer Science Faculty Articles and Research

Mangroves habitat present an important resource for large coastal communities benefiting from activities such as fisheries, forest products and clean water as well as protection against coastal erosion and climate related extreme events. Yet they are increasingly threatened by natural pressure and anthropogenic activities. We observed an inaccurate distribution of mangroves over the Western Arabian Gulf (WAG) which is a vital habitat and resource for the local ecosystem, according to the United Stated Geological Survey (USGS) mangrove database through spectral analysis. Change detection analysis is conducted on mangrove forests along the Saudi Arabian coast of the WAG for the years …


Allosteric Mechanism Of The Circadian Protein Vivid Resolved Through Markov State Model And Machine Learning Analysis, Hongyu Zhou, Zheng Dong, Gennady M. Verkhivker, Brian D. Zoltowski, Peng Tao Feb 2019

Allosteric Mechanism Of The Circadian Protein Vivid Resolved Through Markov State Model And Machine Learning Analysis, Hongyu Zhou, Zheng Dong, Gennady M. Verkhivker, Brian D. Zoltowski, Peng Tao

Mathematics, Physics, and Computer Science Faculty Articles and Research

The fungal circadian clock photoreceptor Vivid (VVD) contains a photosensitive allosteric light, oxygen, voltage (LOV) domain that undergoes a large N-terminal conformational change. The mechanism by which a blue-light driven covalent bond formation leads to a global conformational change remains unclear, which hinders the further development of VVD as an optogenetic tool. We answered this question through a novel computational platform integrating Markov state models, machine learning methods, and newly developed community analysis algorithms. Applying this new integrative approach, we provided a quantitative evaluation of the contribution from the covalent bond to the protein global conformational change, and proposed an …


Ecological Response Of Phytoplankton To The Oil Spills In The Oceans, Danling Tang, Jing Sun, Li Zhou, Sufen Wang, Ramesh P. Singh, Gang Pan Feb 2019

Ecological Response Of Phytoplankton To The Oil Spills In The Oceans, Danling Tang, Jing Sun, Li Zhou, Sufen Wang, Ramesh P. Singh, Gang Pan

Mathematics, Physics, and Computer Science Faculty Articles and Research

Oil spills in oceans have substantial influence on marine ecosystems. This study investigates 21 oil spills in the world. Analyzing Chlorophyll-a (Chl-a) from Moderate Resolution Imaging Spectroradiomerer (MODIS) data after Penglai oil spills on 4 June 2011, found a bloom with peak value of Chl-a (13.66 mg m−3) spread over an area of 800 km2 during 18–25 June 2011, and a pronounced increase in the monthly Chl-a concentration (6.40 mg m−3) on June 2012 in the Bohai Sea. Out of the 21 oil spills, 14 blooms were observed, while 11 …