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Full-Text Articles in Physical Sciences and Mathematics

A Survey On Subsurface Signal Propagation, Usman Raza, Abdul Salam Dec 2020

A Survey On Subsurface Signal Propagation, Usman Raza, Abdul Salam

Faculty Publications

Wireless Underground Communication (WUC) is an emerging field that is being developed continuously. It provides secure mechanism of deploying nodes underground which shields them from any outside temperament or harsh weather conditions. This paper works towards introducing WUC and give a detail overview of WUC. It discusses system architecture of WUC along with the anatomy of the underground sensor motes deployed in WUC systems. It also compares Over-the-Air and Underground and highlights the major differences between the both type of channels. Since, UG communication is an evolving field, this paper also presents the evolution of the field along with the …


Conditional Generative Adversarial Network Demosaicing Strategy For Division Of Focal Plane Polarimeters, Garrett Sargent, Bradley M. Ratliff, Vijayan K. Asari Dec 2020

Conditional Generative Adversarial Network Demosaicing Strategy For Division Of Focal Plane Polarimeters, Garrett Sargent, Bradley M. Ratliff, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Division of focal plane (DoFP), or integrated microgrid polarimeters, typically consist of a 2 × 2 mosaic of linear polarization filters overlaid upon a focal plane array sensor and obtain temporally synchronized polarized intensity measurements across a scene, similar in concept to a Bayer color filter array camera. However, the resulting estimated polarimetric images suffer a loss in resolution and can be plagued by aliasing due to the spatially-modulated microgrid measurement strategy. Demosaicing strategies have been proposed that attempt to minimize these effects, but result in some level of residual artifacts. In this work we propose a conditional generative adversarial …


3-D Fabry–Pérot Cavities Sculpted On Fiber Tips Using A Multiphoton Polymerization Process, Jonathan W. Smith, Jeremiah C. Williams, Joseph S. Suelzer, Nicholas G. Usechak, Hengky Chandrahalim Dec 2020

3-D Fabry–Pérot Cavities Sculpted On Fiber Tips Using A Multiphoton Polymerization Process, Jonathan W. Smith, Jeremiah C. Williams, Joseph S. Suelzer, Nicholas G. Usechak, Hengky Chandrahalim

Faculty Publications

This paper presents 3-D Fabry–Pérot (FP) cavities fabricated directly onto cleaved ends of low-loss optical fibers by a two-photon polymerization (2PP) process. This fabrication technique is quick, simple, and inexpensive compared to planar microfabrication processes, which enables rapid prototyping and the ability to adapt to new requirements. These devices also utilize true 3-D design freedom, facilitating the realization of microscale optical elements with challenging geometries. Three different device types were fabricated and evaluated: an unreleased single-cavity device, a released dual-cavity device, and a released hemispherical mirror dual-cavity device. Each iteration improved the quality of the FP cavity's reflection spectrum. The …


Transfer-To-Transfer Learning Approach For Computer Aided Detection Of Covid-19 In Chest Radiographs, Barath Narayanan Narayanan, Russell C. Hardie, Vignesh Krishnaraja, Christina Karam, Venkata Salini Priyamvada Davuluru Dec 2020

Transfer-To-Transfer Learning Approach For Computer Aided Detection Of Covid-19 In Chest Radiographs, Barath Narayanan Narayanan, Russell C. Hardie, Vignesh Krishnaraja, Christina Karam, Venkata Salini Priyamvada Davuluru

Electrical and Computer Engineering Faculty Publications

The coronavirus disease 2019 (COVID-19) global pandemic has severely impacted lives across the globe. Respiratory disorders in COVID-19 patients are caused by lung opacities similar to viral pneumonia. A Computer-Aided Detection (CAD) system for the detection of COVID-19 using chest radiographs would provide a second opinion for radiologists. For this research, we utilize publicly available datasets that have been marked by radiologists into two-classes (COVID-19 and non-COVID-19). We address the class imbalance problem associated with the training dataset by proposing a novel transfer-to-transfer learning approach, where we break a highly imbalanced training dataset into a group of balanced mini-sets and …


Polarization-Selective Modulation Of Supercavity Resonances Originating From Bound States In The Continuum, Chan Kyaw, Riad Yahiaoui, Joshua A. Burrow, Viet Tran, Kyron Keelen, Wesley Sims, Eddie C. Red, Willie S. Rockward, Mikkel A. Thomas, Andrew M. Sarangan, Imad Agha, Thomas A. Searles Dec 2020

Polarization-Selective Modulation Of Supercavity Resonances Originating From Bound States In The Continuum, Chan Kyaw, Riad Yahiaoui, Joshua A. Burrow, Viet Tran, Kyron Keelen, Wesley Sims, Eddie C. Red, Willie S. Rockward, Mikkel A. Thomas, Andrew M. Sarangan, Imad Agha, Thomas A. Searles

Electro-Optics and Photonics Faculty Publications

Bound states in the continuum (BICs) are widely studied for their ability to confine light, produce sharp resonances for sensing applications and serve as avenues for lasing action with topological characteristics. Primarily, the formation of BICs in periodic photonic band gap structures are driven by symmetry incompatibility; structural manipulation or variation of incidence angle from incoming light. In this work, we report two modalities for driving the formation of BICs in terahertz metasurfaces. At normal incidence, we experimentally confirm polarization driven symmetry-protected BICs by the variation of the linear polarization state of light. In addition, we demonstrate through strong coupling …


Atmospheric Turbulence Study With Deep Machine Learning Of Intensity Scintillation Patterns, Artem V. Vorontsov, Mikhail A. Vorontsov, Grigorii A. Fillimonov, Ernst Polnau Nov 2020

Atmospheric Turbulence Study With Deep Machine Learning Of Intensity Scintillation Patterns, Artem V. Vorontsov, Mikhail A. Vorontsov, Grigorii A. Fillimonov, Ernst Polnau

Electro-Optics and Photonics Faculty Publications

A new paradigm for machine learning-inspired atmospheric turbulence sensing is developed and applied to predict the atmospheric turbulence refractive index structure parameter using deep neural network (DNN)-based processing of short-exposure laser beam intensity scintillation patterns obtained with both: experimental measurement trials conducted over a 7 km propagation path, and imitation of these trials using wave-optics numerical simulations. The developed DNN model was optimized and evaluated in a set of machine learning experiments. The results obtained demonstrate both good accuracy and high temporal resolution in sensing. The machine learning approach was also employed to challenge the validity of several eminent atmospheric …


Digital And Mixed Domain Hardware Reduction Algorithms And Implementations For Massive Mimo, Najath A. Mohomed Nov 2020

Digital And Mixed Domain Hardware Reduction Algorithms And Implementations For Massive Mimo, Najath A. Mohomed

FIU Electronic Theses and Dissertations

Emerging 5G and 6G based wireless communications systems largely rely on multiple-input-multiple-output (MIMO) systems to reduce inherently extensive path losses, facilitate high data rates, and high spatial diversity. Massive MIMO systems used in mmWave and sub-THz applications consists of hundreds perhaps thousands of antenna elements at base stations. Digital beamforming techniques provide the highest flexibility and better degrees of freedom for phased antenna arrays as compared to its analog and hybrid alternatives but has the highest hardware complexity.

Conventional digital beamformers at the receiver require a dedicated analog to digital converter (ADC) for every antenna element, leading to ADCs for …


Defense By Deception Against Stealthy Attacks In Power Grids, Md Hasan Shahriar Nov 2020

Defense By Deception Against Stealthy Attacks In Power Grids, Md Hasan Shahriar

FIU Electronic Theses and Dissertations

Cyber-physical Systems (CPSs) and the Internet of Things (IoT) are converging towards a hybrid platform that is becoming ubiquitous in all modern infrastructures. The integration of the complex and heterogeneous systems creates enormous space for the adversaries to get into the network and inject cleverly crafted false data into measurements, misleading the control center to make erroneous decisions. Besides, the attacker can make a critical part of the system unavailable by compromising the sensor data availability. To obfuscate and mislead the attackers, we propose DDAF, a deceptive data acquisition framework for CPSs' hierarchical communication network. Each switch in the hierarchical …


Enhancing The Visibility Of Vernier Effect In A Tri-Microfiber Coupler Fiber Loop Interferometer For Ultrasensitive Refractive Index And Temperature Sensing, Fangfang Wei, Dejun Liu, Zhe Wang, Zhuochen Wang, Gerald Farrell, Qiang Wu, Gang-Ding Peng, Yuliya Semenova Nov 2020

Enhancing The Visibility Of Vernier Effect In A Tri-Microfiber Coupler Fiber Loop Interferometer For Ultrasensitive Refractive Index And Temperature Sensing, Fangfang Wei, Dejun Liu, Zhe Wang, Zhuochen Wang, Gerald Farrell, Qiang Wu, Gang-Ding Peng, Yuliya Semenova

Articles

In this paper a Vernier effect based sensor is analyzed and demonstrated experimentally in a tri-microfiber coupler (Tri-MFC) and polarization-maintaining fiber (PMF) loop interferometer (Tri-MFC-PMF) to provide ultrasensitive refractive index and temperature sensing. The main novelty of this work is an analysis of parameters of the proposed Tri-MFC-PMF with the objective of determining the conditions leading to a strong Vernier effect. It has been identified by simulation that the Vernier effect is a primary factor in the design of Tri-MFC-PMF loop sensing structure for sensitivity enhancement. It is furthermore demonstrated experimentally that enhancing the visibility of the Vernier spectrum in …


Strain And Stress Relationships For Optical Phonon Modes In Monoclinic Crystals With Β-Ga2O3 As An Example, Rafal Korlacki, Megan Stokey, Alyssa Lynn Mock, Sean Knight, Alexis Papamichail, Vanya Darakchieva, Mathias Schubert Nov 2020

Strain And Stress Relationships For Optical Phonon Modes In Monoclinic Crystals With Β-Ga2O3 As An Example, Rafal Korlacki, Megan Stokey, Alyssa Lynn Mock, Sean Knight, Alexis Papamichail, Vanya Darakchieva, Mathias Schubert

Department of Electrical and Computer Engineering: Faculty Publications

Strain-stress relationships for physical properties are of interest for heteroepitaxial material systems, where strain and stress are inherent due to thermal expansion and lattice mismatch. We report linear perturbation theory strain and stress relationships for optical phonon modes in monoclinic crystals for strain and stress situations which maintain the monoclinic symmetry of the crystal. By using symmetry group analysis and phonon frequencies obtained under various deformation scenarios from density-functional perturbation theory calculations on β-Ga2O3, we obtain four strain and four stress potential parameters for each phonon mode. We demonstrate that these parameters are sufficient to …


Electromagnetic-Triboelectric-Hybrid Energy Tile For Biomechanical Green Energy Harvesting, Elaijah Islam, Abu Musa Abdullah, Aminur Rashid Chowdhury, Farzana Tasnim, Madelyne Martinez, Carolina Olivares, Karen Lozano, Mohammed Uddin Nov 2020

Electromagnetic-Triboelectric-Hybrid Energy Tile For Biomechanical Green Energy Harvesting, Elaijah Islam, Abu Musa Abdullah, Aminur Rashid Chowdhury, Farzana Tasnim, Madelyne Martinez, Carolina Olivares, Karen Lozano, Mohammed Uddin

Chemistry Faculty Publications and Presentations

Highlights

  • Hybrid nanogenerator based floor-tile was developed to convert the Bio-Mechanical energy of human footsteps to Electrical Energy.

  • Hybridization of Triboelectric Nanogenerator and Electro-Magnetic Generator consisting of Aluminum and Kapton.

  • MoS2 is working as an electron acceptor.

  • The maximum output is 1200V as open-circuit voltage, 5mA as short-circuit current, and 6W as power.

  • Produces 20% more power than a commercially sold energy-harvester floor tile.

Abstract

Since the invention of Piezoelectric Nanogenerator in 2006, nanogenerators has become an attractive technology to the researchers for scavenging mechanical energy from the ambient environment for real life applications. Hybridization of these nanogenerators has been …


Hu Aquaponics Monitoring And Control System : European Annual Edunet Conference 2020, Rachel L. Fogle, Glenn P. Williams, Josh R. Krug Oct 2020

Hu Aquaponics Monitoring And Control System : European Annual Edunet Conference 2020, Rachel L. Fogle, Glenn P. Williams, Josh R. Krug

Presidential Research Grants

The functional purpose of the HU Aquaponics Monitoring and Control System Project is to develop an environmental and plant monitoring and control system for the HU Aquaponics Lab, located in the Student Union. The project involves the design and implementation of technology that will regularly take measurements from the environment (e.g., air temperature, water temperature, pH, dissolved oxygen, etc). PLCnext Technology will systematically collect, store, and web-publish the measurement data for HU researchers and the public to use for scientific research.


Integrated Cyberattack Detection And Resilient Control Strategies Using Lyapunov-Based Economic Model Predictive Control, Henrique Oyama, Helen Durand Oct 2020

Integrated Cyberattack Detection And Resilient Control Strategies Using Lyapunov-Based Economic Model Predictive Control, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

The use of an integrated system framework, characterized by numerous cyber/physical components (sensor measurements, signals to actuators) connected through wired/wireless networks, has not only increased the ability to control industrial systems, but also the vulnerabilities to cyberattacks. State measurement cyberattacks could pose threats to process control systems since feedback control may be lost if the attack policy is not thwarted. Motivated by this, we propose three detection concepts based on Lyapunov‐based economic model predictive control (LEMPC) for nonlinear systems. The first approach utilizes randomized modifications to an LEMPC formulation online to potentially detect cyberattacks. The second method detects attacks when …


Gaining Insight Into Solar Photovoltaic Power Generation Forecasting Utilizing Explainable Artificial Intelligence Tools, Murat Kuzlu, Umit Cali, Vinayak Sharma, Özgür Güler Oct 2020

Gaining Insight Into Solar Photovoltaic Power Generation Forecasting Utilizing Explainable Artificial Intelligence Tools, Murat Kuzlu, Umit Cali, Vinayak Sharma, Özgür Güler

Engineering Technology Faculty Publications

Over the last two decades, Artificial Intelligence (AI) approaches have been applied to various applications of the smart grid, such as demand response, predictive maintenance, and load forecasting. However, AI is still considered to be a ‘‘black-box’’ due to its lack of explainability and transparency, especially for something like solar photovoltaic (PV) forecasts that involves many parameters. Explainable Artificial Intelligence (XAI) has become an emerging research field in the smart grid domain since it addresses this gap and helps understand why the AI system made a forecast decision. This article presents several use cases of solar PV energy forecasting using …


Cleanpage: Fast And Clean Document And Whiteboard Capture, Jane Courtney Oct 2020

Cleanpage: Fast And Clean Document And Whiteboard Capture, Jane Courtney

Articles

The move from paper to online is not only necessary for remote working, it is also significantly more sustainable. This trend has seen a rising need for the high-quality digitization of content from pages and whiteboards to sharable online material. However, capturing this information is not always easy nor are the results always satisfactory. Available scanning apps vary in their usability and do not always produce clean results, retaining surface imperfections from the page or whiteboard in their output images. CleanPage, a novel smartphone-based document and whiteboard scanning system, is presented. CleanPage requires one button-tap to capture, identify, crop, and …


Non-Conventional Vehicles As A Way Towards Carbon Neutrality In Iceland, Julia Sokolowska Oct 2020

Non-Conventional Vehicles As A Way Towards Carbon Neutrality In Iceland, Julia Sokolowska

Independent Study Project (ISP) Collection

Paris Agreement’s chief objective is to protect the Earth and its inhabitants from a point of no return, when the effects of climate change will be so intense that they will shift the equilibrium of ecosystems. The distinctiveness of this international environmental treaty is that it does not impose climate change mitigation measures, but rather allows nation states to create their own set of measures, the NDCs, to reach the global warming of ‘well below 2oC’ by the end of the century. Thus, Iceland has submitted its own NDC, the Climate Action Plan 2018-2030, which has an ambitious goal of …


Memory Foreshadow: Memory Forensics Of Hardware Cryptocurrency Wallets – A Tool And Visualization Framework, Tyler Thomas, Mathew Piscitelli, Ilya Shavrov, Ibrahim Baggili Sep 2020

Memory Foreshadow: Memory Forensics Of Hardware Cryptocurrency Wallets – A Tool And Visualization Framework, Tyler Thomas, Mathew Piscitelli, Ilya Shavrov, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

We present Memory FORESHADOW: Memory FOREnSics of HArDware cryptOcurrency Wallets. To the best of our knowledge, this is the primary account of cryptocurrency hardware wallet client memory forensics. Our exploratory analysis revealed forensically relevant data in memory including transaction history, extended public keys, passphrases, and unique device identifiers. Data extracted with FORESHADOW can be used to associate a hardware wallet with a computer and allow an observer to deanonymize all past and future transactions due to hierarchical deterministic wallet address derivation. Additionally, our novel visualization framework enabled us to measure both the persistence and integrity of artifacts produced by the …


Exploring The Learning Efficacy Of Digital Forensics Concepts And Bagging & Tagging Of Digital Devices In Immersive Virtual Reality, Courtney Hassenfeldt, Jillian Jacques, Ibrahim Baggili Sep 2020

Exploring The Learning Efficacy Of Digital Forensics Concepts And Bagging & Tagging Of Digital Devices In Immersive Virtual Reality, Courtney Hassenfeldt, Jillian Jacques, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

This work presents the first account of evaluating learning inside a VR experience created to teach Digital Forensics (DF) concepts, and a hands-on laboratory exercise in Bagging & Tagging a crime scene with digital devices. First, we designed and developed an immersive VR experience which included a lecture and a lab. Next, we tested it with (n = 57) participants in a controlled experiment where they were randomly assigned to a VR group or a physical group. Both groups were subjected to the same lecture and lab, but one was in VR and the other was in the real world. …


Forecasting Vegetation Health In The Mena Region By Predicting Vegetation Indicators With Machine Learning Models, Sachi Perera, Wenzhao Li, Erik Linstead, Hesham El-Askary Sep 2020

Forecasting Vegetation Health In The Mena Region By Predicting Vegetation Indicators With Machine Learning Models, Sachi Perera, Wenzhao Li, Erik Linstead, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Machine learning (ML) techniques can be applied to predict and monitor drought conditions due to climate change. Predicting future vegetation health indicators (such as EVI, NDVI, and LAI) is one approach to forecast drought events for hotspots (e.g. Middle East and North Africa (MENA) regions). Recently, ML models were implemented to predict EVI values using parameters such as land types, time series, historical vegetation indices, land surface temperature, soil moisture, evapotranspiration etc. In this work, we collected the MODIS atmospherically corrected surface spectral reflectance imagery with multiple vegetation related indices for modeling and evaluation of drought conditions in the MENA …


Single‐Molecule 3d Orientation Imaging Reveals Nanoscale Compositional Heterogeneity In Lipid Membranes, Jin Lu, Hesam Mazidi, Tianben Ding, Oumeng Zhang, Matthew D. Lew Sep 2020

Single‐Molecule 3d Orientation Imaging Reveals Nanoscale Compositional Heterogeneity In Lipid Membranes, Jin Lu, Hesam Mazidi, Tianben Ding, Oumeng Zhang, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

In soft matter, thermal energy causes molecules to continuously translate and rotate, even in crowded environments, thereby impacting the spatial organization and function of most molecular assemblies, such as lipid membranes. Directly measuring the orientation and spatial organization of large collections (>3000 molecules μm−2) of single molecules with nanoscale resolution remains elusive. In this paper, we utilize SMOLM, single‐molecule orientation localization microscopy, to directly measure the orientation spectra (3D orientation plus “wobble”) of lipophilic probes transiently bound to lipid membranes, revealing that Nile red's (NR) orientation spectra are extremely sensitive to membrane chemical composition. SMOLM images resolve …


An Explainable And Statistically Validated Ensemble Clustering Model Applied To The Identification Of Traumatic Brain Injury Subgroups, Dacosta Yeboah, Louis Steinmeister, Daniel B. Hier, Bassam Hadi, Donald C. Wunsch, Gayla R. Olbricht, Tayo Obafemi-Ajayi Sep 2020

An Explainable And Statistically Validated Ensemble Clustering Model Applied To The Identification Of Traumatic Brain Injury Subgroups, Dacosta Yeboah, Louis Steinmeister, Daniel B. Hier, Bassam Hadi, Donald C. Wunsch, Gayla R. Olbricht, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

We present a framework for an explainable and statistically validated ensemble clustering model applied to Traumatic Brain Injury (TBI). The objective of our analysis is to identify patient injury severity subgroups and key phenotypes that delineate these subgroups using varied clinical and computed tomography data. Explainable and statistically-validated models are essential because a data-driven identification of subgroups is an inherently multidisciplinary undertaking. In our case, this procedure yielded six distinct patient subgroups with respect to mechanism of injury, severity of presentation, anatomy, psychometric, and functional outcome. This framework for ensemble cluster analysis fully integrates statistical methods at several stages of …


A Statistical Impulse Response Model Based On Empirical Characterization Of Wireless Underground Channel, Abdul Salam, Mehmet C. Vuran, Suat Irmak Sep 2020

A Statistical Impulse Response Model Based On Empirical Characterization Of Wireless Underground Channel, Abdul Salam, Mehmet C. Vuran, Suat Irmak

Faculty Publications

Wireless underground sensor networks (WUSNs) are becoming ubiquitous in many areas. The design of robust systems requires extensive understanding of the underground (UG) channel characteristics. In this paper, an UG channel impulse response is modeled and validated via extensive experiments in indoor and field testbed settings. The three distinct types of soils are selected with sand and clay contents ranging from $13\%$ to $86\%$ and $3\%$ to $32\%$, respectively. The impacts of changes in soil texture and soil moisture are investigated with more than $1,200$ measurements in a novel UG testbed that allows flexibility in soil moisture control. Moreover, the …


Evaluation Of Standard And Semantically-Augmented Distance Metrics For Neurology Patients, Daniel B. Hier, Jonathan Kopel, Steven U. Brint, Donald C. Wunsch, Gayla R. Olbricht, Sima Azizi, Blaine Allen Aug 2020

Evaluation Of Standard And Semantically-Augmented Distance Metrics For Neurology Patients, Daniel B. Hier, Jonathan Kopel, Steven U. Brint, Donald C. Wunsch, Gayla R. Olbricht, Sima Azizi, Blaine Allen

Electrical and Computer Engineering Faculty Research & Creative Works

Background: Patient distances can be calculated based on signs and symptoms derived from an ontological hierarchy. There is controversy as to whether patient distance metrics that consider the semantic similarity between concepts can outperform standard patient distance metrics that are agnostic to concept similarity. The choice of distance metric can dominate the performance of classification or clustering algorithms. Our objective was to determine if semantically augmented distance metrics would outperform standard metrics on machine learning tasks.

Methods: We converted the neurological findings from 382 published neurology cases into sets of concepts with corresponding machine-readable codes. We calculated patient distances by …


Electromagnetic Characteristics Of The Soil, Abdul Salam, Usman Raza Aug 2020

Electromagnetic Characteristics Of The Soil, Abdul Salam, Usman Raza

Faculty Publications

The electromagnetic characteristics of the soil are discussed in this chapter. The characteristics of porous bedrock, soil medium, and impacts of rain attenuations are also presented. The models of dielectric soil properties are studied with a rigorous focus on the constitutive parameters of subsurface soil medium. Moreover, the permittivity and wavenumber in soil are explained. In addition, the frequency-dependent dielectric properties such as dispersion in soil, absorption characteristic, and penetration depth versus frequency are reviewed. Furthermore, the effective permittivity of soil–water mixture for through-the soil-propagation mechanism is analyzed thoroughly.


Underground Phased Arrays And Beamforming Applications, Abdul Salam, Usman Raza Aug 2020

Underground Phased Arrays And Beamforming Applications, Abdul Salam, Usman Raza

Faculty Publications

This chapter presents a framework for adaptive beamforming in underground communication. The wireless propagation is thoroughly analyzed to develop a model using the soil moisture as an input parameter to provide feedback mechanism while enhancing the system performance. The working of array element in the soil is analyzed. Moreover, the effect of soil texture and soil moisture on the resonant frequency and return loss is studied in detail. The wave refraction from the soil–air interface highly degrades the performance of the system. Furthermore, to beam steering is done to achieve high gain for lateral component improving the UG communication. The …


Signals In The Soil: An Introduction To Wireless Underground Communications, Abdul Salam, Usman Raza Aug 2020

Signals In The Soil: An Introduction To Wireless Underground Communications, Abdul Salam, Usman Raza

Faculty Publications

In this chapter, wireless underground (UG) communications are introduced. A detailed overview of WUC is given. A comprehensive review of research challenges in WUC is presented. The evolution of underground wireless is also discussed. Moreover, different component of UG communications is wireless. The WUC system architecture is explained with a detailed discussion of the anatomy of an underground mote. The examples of UG wireless communication systems are explored. Furthermore, the differences of UG wireless and over-the-air wireless are debated. Different types of wireless underground channel (e.g., In-Soil, Soil-to-Air, and Air-to-Soil) are reported as well.


Modulation Schemes And Connectivity In Wireless Underground Channel, Abdul Salam, Usman Raza Aug 2020

Modulation Schemes And Connectivity In Wireless Underground Channel, Abdul Salam, Usman Raza

Faculty Publications

In this chapter, a thorough treatment of the modulation schemes for UG Wireless is presented. The effects of soil texture and water content on the capacity of multi-carrier modulation in WUC are discussed. The multi-carrier capacity model results are analyzed. Moreover, the underground MIMO design for underground communications is explained thoroughly. An analysis of medium access in wireless underground is done as well. Furthermore, the soil properties are considered for cross-layer communications of UG wireless. The performance analysis of traditional modulation schemes is also considered. The soil moisture-based modulation approach is also explored in this chapter. The connectivity and diversity …


Underground Wireless Channel Bandwidth And Capacity, Abdul Salam, Usman Raza Aug 2020

Underground Wireless Channel Bandwidth And Capacity, Abdul Salam, Usman Raza

Faculty Publications

The UG channel bandwidth and capacity are vital parameters in wireless underground communication system design. In this chapter, a comprehensive analysis of the wireless underground channel capacity is presented. The impact of soil on return loss, bandwidth, and path loss is discussed. The results of underground multi-carrier modulation capacity are also outlined. Moreover, the single user capacity and multi-carrier capacity are also introduced with an in-depth treatment of soil texture, soil moisture, and distance effects on channel capacity. Finally, the chapter is concluded with a discussion of challenges and open research issues.


Signals In The Soil: Underground Antennas, Abdul Salam, Usman Raza Aug 2020

Signals In The Soil: Underground Antennas, Abdul Salam, Usman Raza

Faculty Publications

Antenna is a major design component of Internet of Underground Things (IOUT) communication system. The use of antenna, in IOUT, differs from traditional communication in that it is buried in the soil. Therefore, one of the main challenges, in IOUT applications, is to establish a reliable communication. To that end, there is a need of designing an underground-specific antenna. Three major factors that can impact the performance of a buried antenna are: (1) effect of high soil permittivity changes the wavelength of EM waves, (2) variations in soil moisture with time affecting the permittivity of the soil, and (3) difference …


Soil Moisture And Permittivity Estimation, Abdul Salam, Usman Raza Aug 2020

Soil Moisture And Permittivity Estimation, Abdul Salam, Usman Raza

Faculty Publications

The soil moisture and permittivity estimation is vital for the success of the variable rate approaches in the field of the decision agriculture. In this chapter, the development of a novel permittivity estimation and soil moisture sensing approach is presented. The empirical setup and experimental methodology for the power delay measurements used in model are introduced. Moreover, the performance analysis is explained that includes the model validation and error analysis. The transfer functions are reported as well for soil moisture and permittivity estimation. Furthermore, the potential applications of the developed approach in different disciplines are also examined.