A5091887664- Remote-Sensing Image Classification
- Remote Sensing and Land Use
- Remote Sensing in Agriculture
- Geochemistry and Geologic Mapping
- Geology and Paleoclimatology Research
- Physical Unclonable Functions (PUFs) and Hardware Security
- Cryptographic Implementations and Security
- Coastal wetland ecosystem dynamics
- Biomedical and Engineering Education
- Chaos-based Image/Signal Encryption
- Seismic Performance and Analysis
- Climate change and permafrost
- Methane Hydrates and Related Phenomena
- Spectroscopy and Chemometric Analyses
- Soil erosion and sediment transport
- Entrepreneurship Studies and Influences
- Advanced Statistical Methods and Models
- Advanced Image Fusion Techniques
- Structural Engineering and Vibration Analysis
- Hydrology and Sediment Transport Processes
- Wireless Communication Security Techniques
- Grey System Theory Applications
- Structural Health Monitoring Techniques
- Advanced Chemical Sensor Technologies
- Conferences and Exhibitions Management
Université de Montréal
2020-2023
Université Laval
2020-2023
Center for Northern Studies
2023
Université du Québec à Montréal
2023
Imam Hossein University
2022
Bridge University
2022
Michigan Medicine
2021-2022
Shahid Bahonar University of Kerman
2019-2022
University of Tehran
2017-2018
Several machine-learning algorithms have been proposed for remote sensing image classification during the past two decades. Among these machine learning algorithms, Random Forest (RF) and Support Vector Machines (SVM) drawn attention to in several applications. This article reviews RF SVM concepts relevant applies a meta-analysis of 251 peer-reviewed journal papers. A database with more than 40 quantitative qualitative fields was constructed from reviewed The mainly focuses on 1) analysis...
Since the rise of deep learning in past few years, convolutional neural networks (CNNs) have quickly found their place within remote sensing (RS) community. As a result, they transitioned away from other machine techniques, achieving unprecedented improvements many specific RS applications. This article presents meta-analysis 416 peer-reviewed journal articles, summarizes CNN advancements, and its current status under The review process includes statistical descriptive analysis database...
Covering 55% of Canada’s total surface area and stretching from coast to coast, the Canadian boreal zone is crucial nation’s economic ecological integrity. Although often viewed as relatively underdeveloped, it vulnerable numerous stressors such mining, forestry, anthropogenic climate change. Natural archives preserved in lake sediments can provide key insights by quantifying pre-disturbance conditions (pre-1850 CE) nature, magnitude, direction, speed environmental change induced over past...
Abstract Lake sedimentation rate represents a synthetic metric of ecosystem functioning. Many localized studies have reported significant association between land use/land cover changes and lake sediment mass accumulation rates, with few global syntheses echoing these findings at larger scales. In the literature, evaluating lead‐210 ( 210 Pb) for establishing chronologies will report least one three dating models, but constant supply (CRS) model is most widely used. However, it often unclear...
The particle size of lake sediments integrates important environmental information, and the detection changes in this variable over time provides information for understanding ecosystem sedimentary processes. Although standard machine learning regression algorithms especially random forest (RF) have shown great potential mapping sediment cores using hyperspectral imaging, no research has yet applied deep approaches. One-dimensional convolutional neural networks (CNN) recently been developed...
Hyperspectral imaging has recently emerged in the geosciences as a technology that provides rapid, accurate, and high-resolution information from lake sediment cores. Here we introduce new methodology to infer particle size distribution, an insightful proxy tracks past changes aquatic ecosystems their catchments, laboratory hyperspectral images of The proposed includes data preparation, spectral preprocessing transformation, variable selection, model fitting. We evaluated random forest...
Relative radiometric normalization is often required in time series analysis of satellite Earth observations such as land cover change detection. Normalization process reduces the differences caused by changes environmental conditions during acquisition multitemporal images. In this paper, we proposed an efficient and automatic method based on Gaussian mixture model (GMM) to find a set subjectively chosen invariant pixels. A linear model, Error Ellipse, was then adjusted normalize subject...
The High Arctic plays a vital role in Earth's climate system, and its ecosystems are highly sensitive to global change. lakes valuable sentinels of change, as their sediments integrate long-term natural climatic fluctuations anthropogenic influences. Here, we present high-resolution ∼5000 year-reconstruction NE Greenland variability from Aucella Lake (74°N, 20°E) based on physical, chemical, biological properties lake sediments. We use CT-scans, hyperspectral imaging, organic matter, XRD,...
This paper presents a novel method for reliable and efficient spatial-spectral classification of hyperspectral data. algorithm is based on the Bayesian labelling by combining results Gaussian mixture model (GMM) with spatial-contextual information extracted Markov random fields (MRF). Moreover, new fuzzy segmentation-based function was defined incorporated into spatial energy involved to improve performance MRF. To evaluate proposed in real analysis scenarios, three benchmark datasets, i.e....
In-scene atmospheric correction (ISAC) is a procedure that accounts for effects by direct use of the hyperspectral radiance data without recourse to ancillary meteorological data. This letter aims improve accuracy ISAC algorithm. In method after calculating brightness temperature, computed and measured at sensor are plotted on graph in each band. Then, estimate parameters, straight line fit upper boundary plot. One issues find an optimal The main innovation this Gaussian mixture model (GMM)...
Seismic fragility curves measure induced levels of structural damage against strong ground motions earthquakes, probabilistically. These play an important role in seismic performance assessment, risk analysis and making rational decisions regarding management structures. It has been demonstrated that the calculated structures are changed while excited by near-field comparison with far-field ones. The objective this paper is to evaluate extents modification for various variety heights. To...
Traditional training and funding mechanisms in academic health centers often do not support its faculty, staff, trainees evaluating implementing innovative ideas, necessitating supplemental innovation programming. The University of Michigan (U-M) Frankel Cardiovascular Center partnered with U-M Fast Forward Medical Innovation (FMMI), a biomedical commercialization unit funded part by the Clinical Translational Science Award awarded to Institute for & Health Research, provide resources...
Characteristics of earthquake strong ground motions play an important role in the calculation seismic-induced risk imposed on structures. Distinguished features exist movements recorded near seismic sources, as a result substantial amount energy short period record arrival time. In this article, analysis concrete moment-resisting frames due to near-fault motion is calculated and compared with that caused by far-field motions. To achieve goal, three 4, 6, 10 stories were designed based...
Abstract Time series analyses of pigment concentrations are key to understanding past aquatic ecosystem dynamics. As lake sediments provide a window into longer‐term changes, innovative paleolimnological chlorophyll quantification could impactful insights environmental processes. Lab‐based hyperspectral imaging sediment cores is an emerging technique develop rapid, non‐destructive, high‐resolution inferences but it requires more extensive vetting. Despite recent advances in model...
Earth and Space Science Open Archive This preprint has been submitted to is under consideration at Surface Processes Landforms . ESSOAr a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing the latest version by default [v1]A framework 210Pb model selection its application 37 cores from Eastern Canada identify dynamics drivers of lake sedimentation...
Today, Internet communication security has become more complex as technology becomes faster and efficient, especially for resource-limited devices such embedded devices, wireless sensors, radio frequency identification (RFID) tags, of Things (IoT). Lightweight encryption algorithms provide these to protect data against intruders. But the limitation using energy in lightweight block ciphers (LBCs) is one major challenges ever-expanding IoT technologies. Also, LBC are subject Side-channel...
OBJECTIVES/GOALS: The University of Michigan Frankel Cardiovascular Center (FCVC) Innovation Challenge is an annual competition offering funding for innovative ideas to improve cardiovascular care. Due the COVID-19 pandemic, administrators converted recruitment process and pitch event fully virtual. METHODS/STUDY POPULATION: We detail converting from a hybrid (virtual in-person recruiting event) virtual one. Changes included implementing utilizing short video recordings as submission format;...
Recently, with the rapid advancement of technology, Internet Things (IoT‏‏‏‏) security has become more efficient and complex, especially for resource-limited devices such as embedded devices, wireless sensors radio frequency identification tags (RFID). Lightweight block ciphers (LBCs) provide these technologies to protect them against adversaries, but need low power consumption in LBCs is one most important challenges IoT‏ technologies. Furthermore,...
The main goal of this research is the performance evaluation sampled moment-resisting steel structure against 3D simulated blast loading. In first stage present research, numerically wave verified by comparing with relevant renowned numerical and experimental previous researches. second stage, sensitivity blast-induced pressure to finite element mesh size surrounding air cube dimensions are investigated considering one-story building block real based on Computational Fluid Dynamics (CFD)...