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Articles 1 - 30 of 548
Full-Text Articles in Engineering
Emergence Of Coherent Backscattering From Sparse And Finite Disordered Media, Nooshin M. Estakhri, Nasim Mohammadi Estrakhri, Theodore B. Norris
Emergence Of Coherent Backscattering From Sparse And Finite Disordered Media, Nooshin M. Estakhri, Nasim Mohammadi Estrakhri, Theodore B. Norris
Engineering Faculty Articles and Research
Coherent backscattering (CBS) arises from complex interactions of a coherent beam with randomly positioned particles, which has been typically studied in media with large numbers of scatterers and high opacity. We develop a first-principles scattering model for scalar waves to study the CBS cone formation in finite-sized and sparse random media with specific geometries. The current study provides insights into the effects of density, volume size, and other relevant parameters on the angular characteristics of the CBS cone emerging from sparse and bounded random media for various types of illumination, with results consistent with well-known CBS studies which are typically …
Weakly-Supervised Learning Method For The Recognition Of Potato Leaf Diseases, Junde Chen, Xiaofang Deng, Yuxin Wen, Weirong Chen, Adnan Zeb, Defu Zhang
Weakly-Supervised Learning Method For The Recognition Of Potato Leaf Diseases, Junde Chen, Xiaofang Deng, Yuxin Wen, Weirong Chen, Adnan Zeb, Defu Zhang
Engineering Faculty Articles and Research
As a crucial food crop, potatoes are highly consumed worldwide, while they are also susceptible to being infected by diverse diseases. Early detection and diagnosis can prevent the epidemic of plant diseases and raise crop yields. To this end, this study proposed a weakly-supervised learning approach for the identification of potato plant diseases. The foundation network was applied with the lightweight MobileNet V2, and to enhance the learning ability for minute lesion features, we modified the existing MobileNet-V2 architecture using the fine-tuning approach conducted by transfer learning. Then, the atrous convolution along with the SPP module was embedded into the …
Digital Platform To Aid Youth Substance Abuse Prevention, Bingxuan Li
Digital Platform To Aid Youth Substance Abuse Prevention, Bingxuan Li
Discovery Undergraduate Interdisciplinary Research Internship
Through research and interviews, I discovered that a significant portion of students in Africa become drug addicts and drop out of school. The solution is to prevent youth substance abuse before it happens, so that more students in Africa may continue their education. With the strong motivation of expanding African student involvement in higher education, I participated DURI program to increase higher education rates in the Democratic Republic of the Congo, Africa. The local government is establishing rehabilitation centers to monitor at-risk students and prevent youth substance abuse, but due to extremely limited resources, it is critical to evaluate the …
Leveraging Fpga Primitives To Improve Word Reconstruction During Netlist Reverse Engineering, Reilly Mckendrick, Corey Simpson, Brent Nelson, Jeffrey Goeders
Leveraging Fpga Primitives To Improve Word Reconstruction During Netlist Reverse Engineering, Reilly Mckendrick, Corey Simpson, Brent Nelson, Jeffrey Goeders
Faculty Publications
While attempting to perform hardware trojan detection, or other low-level design analyses, it is often necessary to inspect and understand the gate-level netlist of an implemented hardware design. Unfortunately this process is challenging, as at the physical level, the design does not contain any hierarchy, net names, or word groupings. Previous work has shown how gate-level netlists can be analyzed to restore high-level circuit structures, including reconstructing multi-bit signals, which aids a user in understanding the behavior of the design. In this work we explore improvements to the word reconstruction process, specific to FPGA platforms. We demonstrate how hard-block primitives …
Development Of Directed Randomization For Discussing A Minimal Security Architecture, Henrique Oyama, Dominic Messina, Keshav Kasturi Rangan, Akkarakaran Francis Leonard, Kip Nieman, Helen Durand, Katie Tyrrell, Katrina Hinzman, Michael Williamson
Development Of Directed Randomization For Discussing A Minimal Security Architecture, Henrique Oyama, Dominic Messina, Keshav Kasturi Rangan, Akkarakaran Francis Leonard, Kip Nieman, Helen Durand, Katie Tyrrell, Katrina Hinzman, Michael Williamson
Chemical Engineering and Materials Science Faculty Research Publications
Strategies for mitigating the impacts of cyberattacks on control systems using a control-oriented perspective have become of greater interest in recent years. Our group has contributed to this trend by developing several methods for detecting cyberattacks on process sensors, actuators, or both sensors and actuators simultaneously using an advanced optimization-based control strategy known as Lyapunov-based economic model predictive control (LEMPC). However, each technique comes with benefits and limitations, both with respect to one another and with respect to traditional information technology and computer science-type approaches to cybersecurity. An important question to ask, therefore, is what the goal should be of …
Establishment And Mapping Of Heterogeneous Anomalies In Network Intrusion Datasets, Liam Riddell, Mohiuddin Ahmed, Paul Haskell-Dowland
Establishment And Mapping Of Heterogeneous Anomalies In Network Intrusion Datasets, Liam Riddell, Mohiuddin Ahmed, Paul Haskell-Dowland
Research outputs 2022 to 2026
Anomaly detection in the scope of network security aims to identify network instances for the unexpected and unique, with various security operations employing such techniques to facilitate effective threat detection. However, many systems have been designed based on the absolute mapping of attacks to one of three anomaly types (i.e. point, collective, or contextual), a strategy not supported by the recent findings of hybrid anomaly classifications. Given the growing usage of network anomaly detection and the implications of hybrid anomalies, we propose several heterogeneous anomaly types and provide an unsupervised approach for the automated mapping of network threats. Initial findings …
Autonomous Gyroscopic 2-Wheel Differential Robot, Haruka Kido, James Vrtis, Luke Anderson, Tarek Elderini
Autonomous Gyroscopic 2-Wheel Differential Robot, Haruka Kido, James Vrtis, Luke Anderson, Tarek Elderini
Electrical Engineering Student Publications
This paper demonstrates the implementation of an autonomous gyroscopic 2-wheel differential robot, including a forward and inverse kinematics simulation in MatLAB, a test hardware robot and programmed demonstration of a simple move forward and spin left motion, and a final configuration of a complete square path based on programming kinematics, gyroscopic speed responses, and remote-control functionality.
Six-Dimensional Single-Molecule Imaging With Isotropic Resolution Using A Multi-View Reflector Microscope, Oumeng Zhang, Zijian Guo, Yuanyuan He, Tingting Wu, Michael D. Vahey, Matthew D. Lew
Six-Dimensional Single-Molecule Imaging With Isotropic Resolution Using A Multi-View Reflector Microscope, Oumeng Zhang, Zijian Guo, Yuanyuan He, Tingting Wu, Michael D. Vahey, Matthew D. Lew
Electrical & Systems Engineering Publications and Presentations
Imaging of both the positions and orientations of single fluorophores, termed single-molecule orientation-localization microscopy, is a powerful tool for the study of biochemical processes. However, the limited photon budget associated with single-molecule fluorescence makes high-dimensional imaging with isotropic, nanoscale spatial resolution a formidable challenge. Here we realize a radially and azimuthally polarized multi-view reflector (raMVR) microscope for the imaging of the three-dimensional (3D) positions and 3D orientations of single molecules, with precisions of 10.9 nm and 2.0° over a 1.5-μm depth range. The raMVR microscope achieves 6D super-resolution imaging of Nile red molecules transiently bound to lipid-coated spheres, accurately resolving …
A Robust Platform For Mobile Robotics Teaching And Developing Using Arduino’S Integrated Development Environment (Ide) For Programming The Arduino Mega 2560, Sajjad Alhassan
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
In light of the rapid pace at which development happens with modern technology, mobile robots play an important role in our daily lives. This is due to their great importance in facilitating the affairs of life in various economic, commercial, industrial, scientific, and many other fields. In this research and project, we have restructured the microcontroller and system for one of the mobile robots (CEENBOT) that was designed by the University of Nebraska and replaced it with an Arduino Mega 2560.
The purpose of using the Arduino Mega 2560 robot is to provide alternative programming for the CEENBOT platform to …
Character Spotting And Autonomous Tagging: Offline Handwriting Recognition For Bangla, Korean And Other Alphabetic Scripts, Nishatul Majid, Elisa H. Barney Smith
Character Spotting And Autonomous Tagging: Offline Handwriting Recognition For Bangla, Korean And Other Alphabetic Scripts, Nishatul Majid, Elisa H. Barney Smith
Electrical and Computer Engineering Faculty Publications and Presentations
This paper demonstrates a framework for offline handwriting recognition using character spotting and autonomous tagging which works for any alphabetic script. Character spotting builds on the idea of object detection to find character elements in unsegmented word images. An autonomous tagging approach is introduced which automates the production of a character image training set by estimating character locations in a word based on typical character size. Although scripts can vary vividly from each other, our proposed approach provides a simple and powerful workflow for unconstrained offline recognition that should work for any alphabetic script with few adjustments. Here we demonstrate …
Effective Short Text Classification Via The Fusion Of Hybrid Features For Iot Social Data, Xiong Luo, Zhijian Yu, Zhigang Zhao, Wenbing Zhao, Jenq-Haur Wang
Effective Short Text Classification Via The Fusion Of Hybrid Features For Iot Social Data, Xiong Luo, Zhijian Yu, Zhigang Zhao, Wenbing Zhao, Jenq-Haur Wang
Electrical and Computer Engineering Faculty Publications
Nowadays short texts can be widely found in various social data in relation to the 5G-enabled Internet of Things (IoT). Short text classification is a challenging task due to its sparsity and the lack of context. Previous studies mainly tackle these problems by enhancing the semantic information or the statistical information individually. However, the improvement achieved by a single type of information is limited, while fusing various information may help to improve the classification accuracy more effectively. To fuse various information for short text classification, this article proposes a feature fusion method that integrates the statistical feature and the comprehensive …
A Retrospective On 2022 Cyber Incidents In The Wind Energy Sector And Building Future Cyber Resilience, Megan Egan
A Retrospective On 2022 Cyber Incidents In The Wind Energy Sector And Building Future Cyber Resilience, Megan Egan
Cyber Operations and Resilience Program Graduate Projects
Between February and June 2022, multiple wind energy sector companies were hit by cyber-attacks impacting their ability to monitor and control wind turbines. With projected growth in the United States of 110.66 GW from 2020 to 2030, wind energy will increasingly be a critical source of electricity for the United States and an increasingly valuable target for cyberattacks. This paper shows the importance of redundant remote communications, secure third-party providers, and improving response and recovery processes that would ensure this growth period fulfills its potential as a unique opportunity to build in cyber resilience from the outset of new installations …
Feasibility Of Tracking Human Kinematics With Simultaneous Localization And Mapping (Slam), Sepehr Laal, Paul Vasilyev, Sean Pearson, Mateo Aboy, James Mcnames
Feasibility Of Tracking Human Kinematics With Simultaneous Localization And Mapping (Slam), Sepehr Laal, Paul Vasilyev, Sean Pearson, Mateo Aboy, James Mcnames
Electrical and Computer Engineering Faculty Publications and Presentations
We evaluated a new wearable technology that fuses inertial sensors and cameras for tracking human kinematics. These devices use on-board simultaneous localization and mapping (SLAM) algorithms to localize the camera within the environment. Significance of this technology is in its potential to overcome many of the limitations of the other dominant technologies. Our results demonstrate this system often attains an estimated orientation error of less than 1o and a position error of less than 4 cm as compared to a robotic arm. This demonstrates that SLAM’s accuracy is adequate for many practical applications for tracking human kinematics.
Low Power Multi-Channel Interface For Charge Based Tactile Sensors, Samuel Hansen
Low Power Multi-Channel Interface For Charge Based Tactile Sensors, Samuel Hansen
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Analog front end electronics are designed in 65 nm CMOS technology to process charge pulses arriving from a tactile sensor array. This is accomplished through the use of charge sensitive amplifiers and discrete time filters with tunable clock signals located in each of the analog front ends. Sensors were emulated using Gaussian pulses during simulation. The digital side of the system uses SAR (successive approximation register) ADCs for sampling of the processed sensor signals.
Adviser: Sina Balkır
A Stacking-Based Misbehavior Detection System In Vehicular Communication Networks, Troy Green
A Stacking-Based Misbehavior Detection System In Vehicular Communication Networks, Troy Green
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Over the past few decades communication systems for vehicles have continued to advance. Communications between these vehicles can be classified into safety related and non safety related messages. An example of a safety related message would be one vehicle warning others of an icy road it encountered, where a non safety related communication would be a passenger streaming a movie. In either case it's important to secure the communications so that the system continues to behave as expected. In this thesis we propose a Misbehavior Detection System (MDS), which is a system that monitors messages sent between vehicles, and detects …
A Low-Power, Low-Area 10-Bit Sar Adc With Length-Based Capacitive Dac, Zhili Pan
A Low-Power, Low-Area 10-Bit Sar Adc With Length-Based Capacitive Dac, Zhili Pan
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
A 2.5 V single-ended 10-bit successive-approximation-register analog-to-digital converter (SAR ADC) based on the TSMC 65 nm CMOS process is designed with the goal of achieving low power consumption (33.63 pJ/sample) and small area (2874 µm^2 ). It utilizes a novel length-based capacitive digital-to-analog converter (CDAC) layout to achieve low total capacitance for power efficiency, and a custom static asynchronous logic to free the dependence on a high-frequency external clock source. Two test chips have been designed and the problems found through testing the first chip are analyzed. Multiple improved versions of the ADC with minor variations are implemented on the …
An Overview Of Bidirectional Electric Vehicles Charging System As A Vehicle To Anything (V2x) Under Cyber–Physical Power System (Cpps), Onur Elma, Umit Cali, Murat Kuzlu
An Overview Of Bidirectional Electric Vehicles Charging System As A Vehicle To Anything (V2x) Under Cyber–Physical Power System (Cpps), Onur Elma, Umit Cali, Murat Kuzlu
Engineering Technology Faculty Publications
Nowadays, EVs are rapidly increasing in popularity, and are accepted as the vehicles of the future all over the world. The most important components are their battery and charging systems. The energy capacity of EVs’ batteries has a significant potential to supply different energy requirements. Therefore, EVs must be designed in accordance with bidirectional power flow, and Electric Vehicle Supply Equipment (EVSE) should be upgraded as Electric Vehicle Power Exchange Equipment (EVPE). This power exchange infrastructure can be called Vehicle-to-Anything (V2X). V2X will also be the key solution for energy grids of the future that will turn into a much …
A Fiber-Optic Sensor-Embedded And Machine Learning Assisted Smart Helmet For Multi-Variable Blunt Force Impact Sensing In Real Time, Yiyang Zhuang, Taihao Han, Qingbo Yang, Ryan O'Malley, Aditya Kumar, Rex E. Gerald, Jie Huang
A Fiber-Optic Sensor-Embedded And Machine Learning Assisted Smart Helmet For Multi-Variable Blunt Force Impact Sensing In Real Time, Yiyang Zhuang, Taihao Han, Qingbo Yang, Ryan O'Malley, Aditya Kumar, Rex E. Gerald, Jie Huang
Materials Science and Engineering Faculty Research & Creative Works
Early on-site diagnosis of mild traumatic brain injury (mTBI) will provide the best guidance for clinical practice. However, existing methods and sensors cannot provide sufficiently detailed physical information related to the blunt force impact. In the present work, a smart helmet with a single embedded fiber Bragg grating (FBG) sensor is developed, which can monitor complex blunt force impact events in real time under both wired and wireless modes. The transient oscillatory signal "fingerprint" can specifically reflect the impact-caused physical deformation of the local helmet structure. By combination with machine learning algorithms, the unknown transient impact can be recognized quickly …
Improvement For Mimo Systems By Increasing Antenna Isolation And Shaping Radiation Pattern Using Hybrid Network, Min Li, Yujie Zhang, Fan Jiang, Di Wu, Kwan Lawrence Yeung, Lijun Jiang, Ross Murch
Improvement For Mimo Systems By Increasing Antenna Isolation And Shaping Radiation Pattern Using Hybrid Network, Min Li, Yujie Zhang, Fan Jiang, Di Wu, Kwan Lawrence Yeung, Lijun Jiang, Ross Murch
Electrical and Computer Engineering Faculty Research & Creative Works
In this article, a novel method is proposed to design a hybrid network (HN) to increase isolation and shape radiation patterns for multiple-input multiple-output (MIMO) antenna systems. The HN is a combination of a decoupling feeding network and a defected ground network, which are populated by several surface-mounted reactive components whose reactances are determined by the N-ary optimization algorithm. Two decoupling examples are presented to validate the design methodology and elaborate on the design procedure. Measurement results show that the HN helps to realize impedance matching with reflection coefficients below -10 dB, isolation improvement from -5.4/-8.9 dB to below -20 …
A Statistical Analysis Of Sporadic-E Characteristics Associated With Gnss Radio Occultation Phase And Amplitude Scintillations, Daniel J. Emmons, Dong L. Wu, Nimalan Swarnalingam
A Statistical Analysis Of Sporadic-E Characteristics Associated With Gnss Radio Occultation Phase And Amplitude Scintillations, Daniel J. Emmons, Dong L. Wu, Nimalan Swarnalingam
Faculty Publications
Statistical GNSS-RO measurements of phase and amplitude scintillation are analyzed at the mid-latitudes in the local summer for a 100 km altitude. These conditions are known to contain frequent sporadic-E, and the S4-σϕ trends provide insight into the statistical distributions of the sporadic-E parameters. Joint two-dimensional S4-σϕ histograms are presented, showing roughly linear trends until the S4 saturates near 0.8. To interpret the measurements and understand the sporadic-E contributions, 10,000 simulations of RO signals perturbed by sporadic-E layers are performed using length, intensity, and vertical thickness distributions from previous studies, with the assumption that the sporadic-E layer acts …
Cybersecurity And Dynamic Operation In Practice: Equipment Impacts And Safety Guarantees, Kip Nieman, Dominic Messina, Matthew Wegener, Helen Durand
Cybersecurity And Dynamic Operation In Practice: Equipment Impacts And Safety Guarantees, Kip Nieman, Dominic Messina, Matthew Wegener, Helen Durand
Chemical Engineering and Materials Science Faculty Research Publications
Though dynamic operation of chemical processes has been extensively explored theoretically in contexts such as economic model predictive control or even considering the potential for cyberattacks on control systems creating non-standard operating policies, important practical questions remain regarding dynamic operation. In this work, we look at two of these with particular relevance to process safety: (1) evaluating dynamic operating policies with respect to process equipment fidelity and (2) evaluating procedures for determining the parameters of an advanced control law that can promote both dynamic operation as well as safety if appropriately designed. Regarding the first topic, we utilize computational fluid …
Cocm: Co-Occurrence-Based Consistency Matching In Domain-Adaptive Segmentation, Siyu Zhu, Yingjie Tian, Fenfen Zhou, Kunlong Bai, Xiaoyu Song
Cocm: Co-Occurrence-Based Consistency Matching In Domain-Adaptive Segmentation, Siyu Zhu, Yingjie Tian, Fenfen Zhou, Kunlong Bai, Xiaoyu Song
Electrical and Computer Engineering Faculty Publications and Presentations
This paper focuses on domain adaptation in a semantic segmentation task. Traditional methods regard the source domain and the target domain as a whole, and the image matching is determined by random seeds, leading to a low degree of consistency matching between domains and interfering with the reduction in the domain gap. Therefore, we designed a two-step, three-level cascaded domain consistency matching strategy—co-occurrence-based consistency matching (COCM)—in which the two steps are: Step 1, in which we design a matching strategy from the perspective of category existence and filter the sub-image set with the highest degree of matching from the image …
Passive Cooling Analysis Of An Electronic Chipset Using Nanoparticles And Metal-Foam Composite Pcm: An Experimental Study, Faisal Hassan, Abid Hussain, Furqan Jamil, Adeel Arshad, Hafiz Muhammad Ali
Passive Cooling Analysis Of An Electronic Chipset Using Nanoparticles And Metal-Foam Composite Pcm: An Experimental Study, Faisal Hassan, Abid Hussain, Furqan Jamil, Adeel Arshad, Hafiz Muhammad Ali
Research outputs 2022 to 2026
Thermal management of electronic components is critical for long-term reliability and continuous operation, as the over-heating of electronic equipment leads to decrement in performance. The novelty of the current experimental study is to investigate the passive cooling of electronic equipment, by using nano-enriched phase change material (NEPCM) with copper foam having porosity of 97 %. The phase change material of PT-58 was used with graphene nanoplatelets (GNPs) and magnesium oxide (MgO) nanoparticles (NPs), having concentrations of 0.01 wt. % and 0.02 wt. %. Three power levels of 8 W, 16 W, and 24 W, with corresponding heating inputs of 0.77 …
A Patient-Specific Algorithm For Lung Segmentation In Chest Radiographs, Manawaduge Supun De Silva, Barath Narayanan Narayanan, Russell C. Hardie
A Patient-Specific Algorithm For Lung Segmentation In Chest Radiographs, Manawaduge Supun De Silva, Barath Narayanan Narayanan, Russell C. Hardie
Electrical and Computer Engineering Faculty Publications
Lung segmentation plays an important role in computer-aided detection and diagnosis using chest radiographs (CRs). Currently, the U-Net and DeepLabv3+ convolutional neural network architectures are widely used to perform CR lung segmentation. To boost performance, ensemble methods are often used, whereby probability map outputs from several networks operating on the same input image are averaged. However, not all networks perform adequately for any specific patient image, even if the average network performance is good. To address this, we present a novel multi-network ensemble method that employs a selector network. The selector network evaluates the segmentation outputs from several networks; on …
Computer Engineering Education, Marilyn Wolf
Computer Engineering Education, Marilyn Wolf
CSE Conference and Workshop Papers
Computer engineering is a rapidly evolving discipline. How should we teach it to our students?
This virtual roundtable on computer engineering education was conducted in summer 2022 over a combination of email and virtual meetings. The panel considered what topics are of importance to the computer engineering curriculum, what distinguishes computer engineering from related disciplines, and how computer engineering concepts should be taught.
Transition-Metal Ions In Β-Ga2O3 Crystals: Identification Of Ni Acceptors, Timothy D. Gustafson, Nancy C. Giles, Brian C. Holloway, J. Jesenovec, B. L. Dutton, M. D. Mccluskey, Larry E. Halliburton
Transition-Metal Ions In Β-Ga2O3 Crystals: Identification Of Ni Acceptors, Timothy D. Gustafson, Nancy C. Giles, Brian C. Holloway, J. Jesenovec, B. L. Dutton, M. D. Mccluskey, Larry E. Halliburton
Faculty Publications
Excerpt: Transition-metal ions (Ni, Cu, and Zn) in β-Ga2O3 crystals form deep acceptor levels in the lower half of the bandgap. In the present study, we characterize the Ni acceptors in a Czochralski-grown crystal and find that their (0/−) level is approximately 1.40 eV above the maximum of the valence band.
Long-Distance Propagation Of 162 Mhz Shipping Information Links Associated With Sporadic E, Alex T. Chartier, Thomas R. Hanley, Daniel J. Emmons
Long-Distance Propagation Of 162 Mhz Shipping Information Links Associated With Sporadic E, Alex T. Chartier, Thomas R. Hanley, Daniel J. Emmons
Faculty Publications
This is a study of anomalous long-distance (>1000 km) radio propagation that was identified in United States Coast Guard monitors of automatic identification system (AIS) shipping transmissions at 162 MHz. Our results indicate this long-distance propagation is caused by dense sporadic E layers in the daytime ionosphere, which were observed by nearby ionosondes at the same time. This finding is surprising because it indicates these sporadic E layers may be far more dense than previously thought.
Deepdemod: Bpsk Demodulation Using Deep Learning Over Software-Defined Radio, Arhum Ahmad, Satyam Agarwal, Sam Darshi, Sumit Chakravarty
Deepdemod: Bpsk Demodulation Using Deep Learning Over Software-Defined Radio, Arhum Ahmad, Satyam Agarwal, Sam Darshi, Sumit Chakravarty
Faculty Open Access Publishing Fund Collection
In wireless communication, signal demodulation under non-ideal conditions is one of the important research topic. In this paper, a novel non-coherent binary phase shift keying demodulator based on deep neural network, namely DeepDeMod, is proposed. The proposed scheme makes use of neural network to decode the symbols from the received sampled signal. The proposed scheme is developed to demodulate signal under fading channel with additive white Gaussian noise along with hardware imperfections, such as phase and frequency offset. The time varying nature of hardware imperfections and channel poses a additional challenge in signal demodulation. In order to address this issue, …
Development Of Analytical Models For Photovoltaic Systems, Arjun M
Development Of Analytical Models For Photovoltaic Systems, Arjun M
Interdisciplinary Collection
One of the frequent circumstances in photovoltaic (PV) systems is partial shading, often characterized by multiple peaks in its characteristics. As a result, modelling and delivering peak power is strenuous. Analytical techniques are well-known effective instruments to overcome such challenges by establishing
correlations between variables with the help of non-linear implicit mathematical equations. With an aim to simplify these models, earlier research has focussed on formulating explicit equations by making assumptions/approximations, leading to less accurate results. With today’s fast processing computers, solving nonlinear equations is no longer a problem. Moreover, the application of analytical techniques has only been limited to …
Solid State Lighting/Led Lighting, With Reliability Analysis And Smart Sustainable Energy Solutions, Anjan N. Padmasali Dr.
Solid State Lighting/Led Lighting, With Reliability Analysis And Smart Sustainable Energy Solutions, Anjan N. Padmasali Dr.
Technical Collection
Reliability analysis of LED based lighting solutions used in general applications. Daily use LED luminaire performance analysis at different accelerated conditions and prediction of performance for any other conditions. System and component level reliability study and analysis. Develop LED based solutions for any specific application requirements. Currently working on developing measurements, data analysis and solutions in lines with providing smart and sustainable solution applicable to lighting and also energy usage optimizations in any system.
- https://ieeexplore.ieee.org/document/9537294
- https://journals.sagepub.com/doi/10.1177/1477153520976936
- https://ieeexplore.ieee.org/document/9559924
- https://ieeexplore.ieee.org/document/9108554
- https://ieeexplore.ieee.org/document/8930628