6,342 research outputs found
Global Rice Market and Export Restriction
No full textAbdullah Mamun and Joseph Glauber IFPRI-AMIS SEMINAR SERIES A Look at Global Rice Markets: Export Restrictions, El Niño, and Price Controls Co-organized by IFPRI and Agricultural Market Information System (AMIS) OCT 18, 2023 - 9:00 TO 10:30AM ED
Surge_Susceptibility
No full textCurrently, this dataset should be used by the journal reviewers to verify the results
NJN881745 Supplemental Material - Supplemental material for Multidisciplinary perceptions of working with children and their parents in small rural and remote Australian hospitals
No full textSupplemental material, NJN881745 Supplemental Material for Multidisciplinary perceptions of working with children and their parents in small rural and remote Australian hospitals by Wendy Smyth, Abdullah Al Mamun and Linda Shields in Nordic Journal of Nursing Research</p
Arsenic Speciation and Bioavailability to Macroalgae in Seawater
Get PDF金沢大学博士（学術）博士論文本文Full 以下に掲載：Chemosphere 222 pp.705-713 2019. Elsevier. 共著者：M. Abdullah Al Mamun, Ismail M. M. Rahman, Rakhi Rani Datta, Chika Kosugi, Asami S. Mashio, Teruya Maki, Hiroshi Hasegawadoctoral thesi
Convergence Analysis of MCMC Methods for Subsurface Flow Problems
No full textFull text access from Treasures at UT Dallas is restricted to current UTD affiliates (use the provided link to the article). Non UTD affiliates will find the web address for this item by clicking the Show full item record link and copying the "relation.uri" metadata.In subsurface characterization using a history matching algorithm subsurface properties are reconstructed with a set of limited data. Here we focus on the characterization of the permeability field in an aquifer using Markov Chain Monte Carlo (MCMC) algorithms, which are reliable procedures for such reconstruction. The MCMC method is serial in nature due to its Markovian property. Moreover, the calculation of the likelihood information in the MCMC is computationally expensive for subsurface flow problems. Running a long MCMC chain for a very long period makes the method less attractive for the characterization of subsurface. In contrast, several shorter MCMC chains can substantially reduce computation time and can make the framework more suitable to subsurface flows. However, the convergence of such MCMC chains should be carefully studied. In this paper, we consider multi-MCMC chains for a single–phase flow problem and analyze the chains aiming at a reliable characterization.National Science Foundation under Grant Nos DMS 1514808, HRD 1600818.School of Natural Sciences and Mathematic
Pattern identification of movement related states in biosignals
No full textThe advancement in biosignal processing and modelling has led to exploring the human brain and developing assistive Human Machine Interface (HMI) as well as Brain Machine Interface (BMI). HMI and BMI require specialised techniques for signal processing and pattern recognition to reliably translate information from complex non-stationary dynamics of biosignals into controlling commands. The information translation process consists of signal pre-processing, feature identification and classification. Even though there is continuous progress in biosignal processing research, the critical requirement for HMI and BMI has raised significant challenges for current state-of-art translation methods, such as high accuracy, reliability, and robustness in noise, provided that only small amount of data is available in practice. Therefore, analysing biosignals with novel feature enhancement, feature selection and classification methods are important for decoding of movement intention towards development of reliable assistive HMI as well as BMI. It is particularly valuable for neural signal analysis to understand the neural circuit mechanisms. This research project aims to design decoding algorithm with improved classification performance in robustness and accuracy to recognise movement related states from tongue movement ear pressure (TMEP) signals and deep brain local field potentials (LFPs) by integrating features extracted through multiple domains, and applying pattern classification methods. To achieve the above aim, this project addresses a number of research issues by utilising conventional and efficient signal information extraction, selection and pattern classification techniques.The first part of this research project successfully developed a robust decoding technique for identifying tongue movement commands from TMEP signals in adverse environment for designing an assistive HMI. This decoding strategy utilised wavelet method for optimal feature enhancement and achieved high accuracy in real time with pattern classification methods of Bayesian and support vector machine (SVM). In the second part, the movement commands are decoded from deep brain local field potentials (LFPs) from basal ganglia (Subthalamic Nucleus (STN) or Globus Pallidus interna (GPi)). An efficient translation algorithm is developed to decode deep brain LFPs for identification of movement activities. Neural synchronisation measures including event related desynchronisation and synchronisation, and functional coupling are utilised to extract discriminatory information as features. We further developed a new feature selection strategy named as weighted sequential feature selection (WSFS) to select an optimal feature subset, which is proved robust for high dimensional, small size dataset. Together with WSFS and pattern classification methods (Bayesian or SVM) high decoding performance for identifying movements was achieved. This research work not only assists decoding movement activities for the application of BMI, but also may help to advance understanding of the neural circuit mechanisms related to motor control as well as development of more efficient therapeutic techniques for neuromotor diseases, such as Parkinson disease
Supplementary_Material - Inflammatory Responses are Sex Specific in Chronic Hypoxic–Ischemic Encephalopathy
No full textSupplementary_Material for Inflammatory Responses are Sex Specific in Chronic Hypoxic–Ischemic Encephalopathy by Abdullah Al Mamun, Haifu Yu, Sharmeen Romana, and Fudong Liu in Cell Transplantation</p
sj-docx-1-sgo-10.1177_21582440211061373 – Supplemental material for Predicting the Intention and Purchase of Health Insurance Among Malaysian Working Adults
No full textSupplemental material, sj-docx-1-sgo-10.1177_21582440211061373 for Predicting the Intention and Purchase of Health Insurance Among Malaysian Working Adults by Abdullah Al Mamun, Muhammad Khalilur Rahman, Uma Thevi Munikrishnan and P. Yukthamarani Permarupan in SAGE Open</p
sj-docx-2-sgo-10.1177_21582440231187583 – Supplemental material for Green Gardening Practices Among Urban Botanists: Using the Value-Belief-Norm Model
No full textSupplemental material, sj-docx-2-sgo-10.1177_21582440231187583 for Green Gardening Practices Among Urban Botanists: Using the Value-Belief-Norm Model by Abdullah Al Mamun, Naeem Hayat, Muhammad Mohiuddin, Anas A. Salameh and Syed Shah Alam in SAGE Open</p
sj-docx-1-dhj-10.1177_20552076231180728 - Supplemental material for Exploring the mass adoption potential of wearable fitness devices in Malaysia
No full textSupplemental material, sj-docx-1-dhj-10.1177_20552076231180728 for Exploring the mass adoption potential of wearable fitness devices in Malaysia by Naeem Hayat, Anas A Salameh, Abdullah Al Mamun, Syed Shah Alam and Noor Raihani Zainol in DIGITAL HEALTH</p
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