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Articles 1951 - 1980 of 18141
Full-Text Articles in Entire DC Network
Fabrication Of Smooth Sac305 Thin Films Via Magnetron Sputtering And Evaluations Of Microstructure, Creep, And Electrical Resistivity, Manish Ojha
Mechanical & Aerospace Engineering Theses & Dissertations
SAC305 (96.5%Sn-3%Ag-0.5%Cu) is the leading alternative to the traditional Sn-Pb solder eutectic alloy owing to its low melting temperature, better compatibility with other components, and excellent mechanical/structural properties. In the realm of modern electronics, where devices are increasingly miniaturized, the design and characterization of thin solder joints become paramount. The orientation and size of the grains within the solder can influence its ability to withstand mechanical stresses. However, research on SAC thin films remains sparse, and these films present unique challenges and characteristics compared to their bulk counterparts, influenced by factors like interfaces, stresses, thickness, microstructure, and the nature of …
Optics Studies For Multipass Energy Recovery At Cebaf: Er@Cebaf, Isurumali Neththikumara
Optics Studies For Multipass Energy Recovery At Cebaf: Er@Cebaf, Isurumali Neththikumara
Physics Theses & Dissertations
Energy recovery linacs (ERLs), focus on recycling the kinetic energy of electron beam for the purpose of accelerating a newly injected beam within the same accelerating structure. The rising developments in the super conducting radio frequency technology, ERL technology has achieved several noteworthy milestones over the past few decades. In year 2003, Jefferson Lab has successfully demonstrated a single pass energy recovery at the CEBAF accelerator. Furthermore, they conducted successful experiments with IR-FEL demo and upgrades, as well as the UV FEL driver. This multi-pass, multi-GeV range energy recovery demonstration proposed to be carried out at CEBAF accelerator at Jefferson …
Designing A Model Of Solar Photovoltaic Water Pumping System For Off-Grid Localities In Tanzania, Imani Mruma
Designing A Model Of Solar Photovoltaic Water Pumping System For Off-Grid Localities In Tanzania, Imani Mruma
Tanzania Journal of Engineering and Technology (TJET)
Modeling of photovoltaic (PV) water pumping system for rural water localities is vital especially in these modern days, in Tanzania. This is due to the rise of high number of solar-powered rural water projects constructed lacking appropriate design. The fate result into poor and substandard projects delivering below expectations. Kikombo Solar Water Project situated in Dodoma; Tanzania is one among poorly designed solar project chosen as a case study to validate proposed model. The main problem of Kikombo project is unsatisfactory amount of water from domestic points to satisfy population demand. This matter has been raised by pumping-station attendants and …
Mppt Dc-Dc Buck-Boost Converter For Off Grid Hybrid Solar-Wind Battery System In Ikuza Island, Tanzania, Aviti Thadei Mushi
Mppt Dc-Dc Buck-Boost Converter For Off Grid Hybrid Solar-Wind Battery System In Ikuza Island, Tanzania, Aviti Thadei Mushi
Tanzania Journal of Engineering and Technology (TJET)
Ikuza Island in Kagera-Tanzania faces lack of electricity due to cost challenges of extending the grid by marine cables and other transmission facilities. These makes such endeavour not appealing to the supply authority due to those higher charges. Therefore, this paper undertakes to design hybrid renewable energy sources for the island by specifically focusing on the buck-boost converter for the energy conversion from these renewable resources. The design of the bidirectional buck-boost converter for maximum power point tracking in off-grid hybrid renewable energy systems is multifaceted due to the inhomogeneity nature of the renewable energy sources. The bidirectional buck-boost converter, …
Comparison Of End-Point Energies Of Bremsstrahlung Photons From 28 Ghz Ecr Ion Source In Three Measurement Locations, Mwingereza John Kumwenda Dr
Comparison Of End-Point Energies Of Bremsstrahlung Photons From 28 Ghz Ecr Ion Source In Three Measurement Locations, Mwingereza John Kumwenda Dr
Tanzania Journal of Engineering and Technology (TJET)
Bremsstrahlung photons measurement show elevated energy emission beyond critical energy in 28-GHz ECR and its nature is not revealed. Thus, the aim of this study is to unveil the nature of high end-point energies at the three measurement locations. Bremsstrahlung photons from a 28-GHz ECR ion source were measured at Busan center of Korean Basic Science Institute (KBSI). The gamma-ray detection system consists of three round type NaI(Tl) scintillation detectors placed 62 cm radially from the beam axis at the three measurement locations namely injection, centre and extraction sides of an ECR ion source, and a NaI(Tl) scintillation detector placed …
Renewable Energy Potential Assessment For Improving Electric Power Availability In Urban Area: A Case Of Msigani Ward In Ubungo Municipal, Tanzania, Respicius Kiiza
Renewable Energy Potential Assessment For Improving Electric Power Availability In Urban Area: A Case Of Msigani Ward In Ubungo Municipal, Tanzania, Respicius Kiiza
Tanzania Journal of Engineering and Technology (TJET)
The demand for electricity in urban areas of the developing countries like Tanzania is increasing rapidly due to factors such as increasing population, expansion of economic activities and industrialization. Msigani ward is one of the fourteen (14) administrative urban wards in Ubungo Municipal, Dar es Salaam, located at latitude 6.8031 oS and longitude 39.1188 oE. Recently, there has been observed increase in power demand in this ward. This in turn has caused a supply deficit that sometimes led to large number of interruptions caused by frequent power outage and load shedding. The total capacity of the national grid is limited …
A Multitask Learning Framework For Pilot Decontamination In 5g Massive Mimo, Crallet Victor
A Multitask Learning Framework For Pilot Decontamination In 5g Massive Mimo, Crallet Victor
Tanzania Journal of Engineering and Technology (TJET)
Reference signals enable the acquisition of channel state information (CSI) for purposes such as channel estimation, beam selection, precoding, and symbol detection in 5G massive multiple-input multiple output (MAMIMO) systems. Eventually, as more and more users and cells are added, orthogonal reference signals become few which leads to pilot contamination. Pilot contamination limits the performance and occurs when non-orthogonal reference signals occupy time-frequency resources that are alike. Learning-based techniques have been proposed to alleviate it. However, each can only learn to perform a single task namely pilot assignment, power allocation, pilot design, or de-noising for pilot decontamination. In addition, each …
A Radial Basis Function Neural Network Algorithm For The Simultaneous Retrieval Of Two Meteorological Parameters From Solar Radiation, Nicholas W. Nzala, Nicolausi Ssebiyonga, Dennis Muyimbwa, Taddeo Ssenyonga
A Radial Basis Function Neural Network Algorithm For The Simultaneous Retrieval Of Two Meteorological Parameters From Solar Radiation, Nicholas W. Nzala, Nicolausi Ssebiyonga, Dennis Muyimbwa, Taddeo Ssenyonga
Tanzania Journal of Science
Local meteorological parameters are key in understanding the frequency of occurrence of extreme weather conditions such as floods, and droughts, among others. In this study, we present a method for simultaneous retrieval of two weather parameters. The method is based on already measured monthly average values of weather parameters from 2011 to 2016, which were used to train a Feed-forward radial basis function neural network (RBFNN) to obtain a fast and accurate method to compute global solar radiation for specified weather parameters pair. In inverse modelling, a multidimensional unconstrained non-linear optimization was employed to retrieve the weather parameters pair. The …
Enhancing Service Restoration In Tanzanian Power Grid Using Internet Of Things Sensors And Renewable Energy Sources, Rukia J. Mwifunyi, Daudi C. Mnyanghwalo, Shamte J. Kawambwa
Enhancing Service Restoration In Tanzanian Power Grid Using Internet Of Things Sensors And Renewable Energy Sources, Rukia J. Mwifunyi, Daudi C. Mnyanghwalo, Shamte J. Kawambwa
Tanzania Journal of Science
The increased dependence on the electric power grid, coupled with the increasing number of new customers, motivates the need to improve the reliability and resilience of the electric distribution systems. Modern distribution systems are becoming more resilient against power outages due to the increasing integration of Distributed Energy Resources (DERs) and the availability of efficient mechanisms for load shedding. Several studies considered fault detection and Service Restoration (SR) as separate problems without considering the implementation feasibility of integrating both solutions. To ensure the resiliency in the power system, it is important to have proper mechanisms which integrate sensing, detection, and …
Using T-Distributed Stochastic Neighbor Embedding For Visualization And Segmentation Of 3d Point Clouds Of Plants, Heli̇n Dutağaci
Using T-Distributed Stochastic Neighbor Embedding For Visualization And Segmentation Of 3d Point Clouds Of Plants, Heli̇n Dutağaci
Turkish Journal of Electrical Engineering and Computer Sciences
In this work, the use of t-SNE is proposed to embed 3D point clouds of plants into 2D space for plant characterization. It is demonstrated that t-SNE operates as a practical tool to flatten and visualize a complete 3D plant model in 2D space. The perplexity parameter of t-SNE allows 2D rendering of plant structures at various organizational levels. Aside from the promise of serving as a visualization tool for plant scientists, t-SNE also provides a gateway for processing 3D point clouds of plants using their embedded counterparts in 2D. In this paper, simple methods were proposed to perform semantic …
Dynamic Deep Neural Network Inference Via Adaptive Channel Skipping, Meixia Zou, Xiuwen Li, Jinzheng Fang, Hong Wen, Weiwei Fang
Dynamic Deep Neural Network Inference Via Adaptive Channel Skipping, Meixia Zou, Xiuwen Li, Jinzheng Fang, Hong Wen, Weiwei Fang
Turkish Journal of Electrical Engineering and Computer Sciences
Deep neural networks have recently made remarkable achievements in computer vision applications. However, the high computational requirements needed to achieve accurate inference results can be a significant barrier to deploying DNNs on resource-constrained computing devices, such as those found in the Internet-of-things. In this work, we propose a fresh approach called adaptive channel skipping (ACS) that prioritizes the identification of the most suitable channels for skipping and implements an efficient skipping mechanism during inference. We begin with the development of a new gating network model, ACS-GN, which employs fine-grained channel-wise skipping to enable input-dependent inference and achieve a desirable balance …
Joint Intent Detection And Slot Filling For Turkish Natural Language Understanding, Osman Büyük
Joint Intent Detection And Slot Filling For Turkish Natural Language Understanding, Osman Büyük
Turkish Journal of Electrical Engineering and Computer Sciences
Intent detection and slot filling are two crucial subtasks of a text-based goal-oriented dialogue system. In a goal-oriented dialogue system, users interact with the system to complete a goal (or to fulfill their intent) and provide the necessary information (slot values) to achieve that goal. Therefore, a user?s text input includes information about the user?s intent and contains required slot values. Recently, joint models that simultaneously detect the intent and extract the slots are proposed to benefit from the interaction between the two tasks. The proposed methods are usually tested using benchmark data sets in English such as ATIS and …
Transforming Temporal-Dynamic Graphs Into Time-Series Data For Solving Event Detection Problems, Kutay Taşci, Fuat Akal
Transforming Temporal-Dynamic Graphs Into Time-Series Data For Solving Event Detection Problems, Kutay Taşci, Fuat Akal
Turkish Journal of Electrical Engineering and Computer Sciences
Event detection on temporal-dynamic graphs aims at detecting significant events based on deviations from the normal behavior of the graphs. With the widespread use of social media, many real-world events manifest as social media interactions, making them suitable for modeling as temporal-dynamic graphs. This paper presents a workflow for event detection on temporal-dynamic graphs using graph representation learning. Our workflow leverages generated embeddings of a temporal-dynamic graph to reframe the problem as an unsupervised time-series anomaly detection task. We evaluated our workflow on four distinct real-world social media datasets and compared our results with the related work. The results show …
Recognizing Handwritten Digits Using Spiking Neural Networks With Learning Algorithms Based On Sliding Mode Control Theory, Yeşi̇m Öni̇z, Mehmet Ayyildiz
Recognizing Handwritten Digits Using Spiking Neural Networks With Learning Algorithms Based On Sliding Mode Control Theory, Yeşi̇m Öni̇z, Mehmet Ayyildiz
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a spiking neural network (SNN) has been proposed for recognizing the digits written on the LCD screen of an experimental setup. The convergence of the learning algorithm has been ensured by using sliding mode control (SMC) theory and the Lyapunov stability method for the adaptation of the network parameters. The spike response model (SRM) has been utilized in the design of the SNN. The performance of the proposed learning scheme has been evaluated both on the experimental data and on the MNIST dataset. The simulated and experimental results of the SNN structure have been compared with the …
A Machine Learning Approach For Dyslexia Detection Using Turkish Audio Records, Tuğberk Taş, Muhammed Abdullah Bülbül, Abas Haşi̇moğlu, Yavuz Meral, Yasi̇n Çalişkan, Gunay Budagova, Mücahi̇d Kutlu
A Machine Learning Approach For Dyslexia Detection Using Turkish Audio Records, Tuğberk Taş, Muhammed Abdullah Bülbül, Abas Haşi̇moğlu, Yavuz Meral, Yasi̇n Çalişkan, Gunay Budagova, Mücahi̇d Kutlu
Turkish Journal of Electrical Engineering and Computer Sciences
Dyslexia is a learning disorder, characterized by impairment in the ability to read, spell, and decode letters. It is vital to detect dyslexia in earlier stages to reduce its effects. However, diagnosing dyslexia is a time-consuming and costly process. In this paper, we propose a machine-learning model that predicts whether a Turkish-speaking child has dyslexia using his/her audio records. Therefore, our model can be easily used by smart phones and work as a warning system such that children who are likely to be dyslexic according to our model can seek an examination by experts. In order to train and evaluate, …
Direct Pore-Based Identification For Fingerprint Matching Process, Vedat Delican, Behçet Uğur Töreyi̇n, Ege Çeti̇n, Ayli̇n Yalçin Saribey
Direct Pore-Based Identification For Fingerprint Matching Process, Vedat Delican, Behçet Uğur Töreyi̇n, Ege Çeti̇n, Ayli̇n Yalçin Saribey
Turkish Journal of Electrical Engineering and Computer Sciences
Fingerprints are one of the most important scientific proof instruments in solving forensic cases. Identification in fingerprints consists of three levels based on the flow direction of the papillary lines at the first level, the minutiae points at the second level, and the pores at the third level. The inadequacy of existing imaging systems in detecting fingerprints and the lack of pore details at the desired level limit the widespread use of third-level identification. The fact that fingerprints with images based on pores in the unsolved database are not subjected to any evaluation criteria and remain in the database reveals …
Stepwise Dynamic Nearest Neighbor (Sdnn): A New Algorithm For Classification, Deni̇z Karabaş, Derya Bi̇rant, Peli̇n Yildirim Taşer
Stepwise Dynamic Nearest Neighbor (Sdnn): A New Algorithm For Classification, Deni̇z Karabaş, Derya Bi̇rant, Peli̇n Yildirim Taşer
Turkish Journal of Electrical Engineering and Computer Sciences
Although the standard k-nearest neighbor (KNN) algorithm has been used widely for classification in many different fields, it suffers from various limitations that abate its classification ability, such as being influenced by the distribution of instances, ignoring distances between the test instance and its neighbors during classification, and building a single/weak learner. This paper proposes a novel algorithm, called stepwise dynamic nearest neighbor (SDNN), which can effectively handle these problems. Instead of using a fixed parameter k like KNN, it uses a dynamic neighborhood strategy according to the data distribution and implements a new voting mechanism, called stepwise voting. Experimental …
Cognitive Load Detection Using Ci-Ssa For Eeg Signal Decomposition And Nature-Inspired Feature Selection, Jammisetty Yedukondalu, Lakhan Dev Sharma
Cognitive Load Detection Using Ci-Ssa For Eeg Signal Decomposition And Nature-Inspired Feature Selection, Jammisetty Yedukondalu, Lakhan Dev Sharma
Turkish Journal of Electrical Engineering and Computer Sciences
Cognitive load detection is eminent during the mental assignment of neural activity because it indicates how the brain reacts to stimuli. The level of cognitive load experienced during mental arithmetic tasks can be determined using an electroencephalogram (EEG). The EEG data were collected from publicly available datasets, namely, mental arithmetic task (MAT) and simultaneous task workload (STEW). The first phase comprises decomposing the electroencephalogram (EEG) signal into intrinsic mode functions (IMFs) using circulant singular spectrum analysis (Ci-SSA). In the second phase, entropy-based features were evaluated using IMFs. After that, the extracted features were fed to nature-inspired feature selection algorithms: genetic …
Hydrophobicity Optimization Of Cathode Catalyst Layer For Proton Exchange Membrane Fuel Cell, Hao-Jie Chen, Mei-Hua Tang, Sheng-Li Chen
Hydrophobicity Optimization Of Cathode Catalyst Layer For Proton Exchange Membrane Fuel Cell, Hao-Jie Chen, Mei-Hua Tang, Sheng-Li Chen
Journal of Electrochemistry
Hydrophobicity of the cathode catalyst layers (CCLs) crucially determines the performance of proton exchange membrane fuel cells (PEMFCs) by affecting the transports of oxygen and liquid water. In this regard, polytetrafluoroethylene (PTFE) is usually used as a hydrophobic additive to facilitate the oxygen and water transports in CCLs. So far, there remains lacking systematic effort to optimize the addition methods of PTFE in CCLs and the mechanisms behind. In this work, the effects of the approaches for PTFE addition and the distribution of PTFE on the mass transport of oxygen and the proton conduction in CCLs were studied by using …
Asymmetric Electrode-Electrolyte Interfaces For High-Performance Rechargeable Lithium-Sulfur Batteries, Jia Chou, Ya-Hui Wang, Wen-Peng Wang, Sen Xin, Yu-Guo Guo
Asymmetric Electrode-Electrolyte Interfaces For High-Performance Rechargeable Lithium-Sulfur Batteries, Jia Chou, Ya-Hui Wang, Wen-Peng Wang, Sen Xin, Yu-Guo Guo
Journal of Electrochemistry
With a high cell-level specific energy and a low cost, lithium-sulfur (Li-S) battery has been intensively studied as one of the most promising candidates for competing the next-generation energy storage campaign. Currently, the practical use of Li-S battery is hindered by the rapidly declined storage performance during battery operation, as caused by irreversible loss of electroactive sulfide species at the cathode, dendrite formation at the anode and parasitic reactions at the electrode-electrolyte interface due to unfavorable cathode-anode crosstalk. In this perspective, we propose to stabilize the Li-S electrochemistry, and improve the storage performance of battery by designing asymmetric electrode-electrolyte interfaces …
Design And Characterization Of 2.4ghz Antennas For Wireless Sensor Applications, Luis Zogby Brennan
Design And Characterization Of 2.4ghz Antennas For Wireless Sensor Applications, Luis Zogby Brennan
Dissertations and Theses
Wireless sensor networks benefit greatly from advances in circuit integration and miniaturization. However, antennas are bound to specific geometries both in terms of fundamental limits and their response to immediate surroundings. As such, various successful techniques for antenna miniaturization must still be carefully tested and characterized as part of the design process of a sensor system. The work presented here fully characterizes a number of miniaturized 2.4GHz antennas and successfully integrates designs into a sensor system using the highly integrated Single Chip Micro Mote (SCµM), which uses a crystal-less radio design resulting in the requirement of only a …
A Novel Approach For Enhancing Routing In Wireless Sensor Networks Using Aco Algorithm, Sihem Goumiri, Maohamed Amine Riahla, M'Hamed Hamadouche
A Novel Approach For Enhancing Routing In Wireless Sensor Networks Using Aco Algorithm, Sihem Goumiri, Maohamed Amine Riahla, M'Hamed Hamadouche
Emirates Journal for Engineering Research
Wireless Sensors Network (WSN) is an emergent technology that aims to offer innovative capacities. In the last decade, the use of these networks increased in various fields like military, science, and health due to their fast and inexpressive deployment and installation. However, the limited sensor battery lifetime poses many technical challenges and affects essential services like routing. This issue is a hot topic of search, many researchers have proposed various routing protocols aimed at reducing the energy consumption in WSNs. The focus of this work is to investigate the effectiveness of integrating ACO algorithm with routing protocols in WSNs. Moreover, …
Trumpet Directivity From A Rotating Semicircular Array, Samuel D. Bellows, Joseph E. Avila, Timothy W. Leishman
Trumpet Directivity From A Rotating Semicircular Array, Samuel D. Bellows, Joseph E. Avila, Timothy W. Leishman
Directivity
The directivity function of a played musical instrument describes the angular dependence of its acoustic radiation and diffraction about the instrument, musician, and musician’s chair. Directivity influences sound in rehearsal, performance, and recording environments and signals in audio systems. Because high-resolution, spherically comprehensive measurements of played musical instruments have been unavailable in the past, the authors have undertaken research to produce and share such data for studies of musical instruments, simulations of acoustical environments, optimizations of microphone placements, and other applications. The authors acquired the data from repeated chromatic scales produced by a trumpet played at mezzo-forte in an anechoic …
Better Models For High-Stakes Tasks, Jacob Ryan Epifano
Better Models For High-Stakes Tasks, Jacob Ryan Epifano
Theses and Dissertations
The intersection of machine learning and healthcare has the potential to transform medical diagnosis, treatment, and research. Machine learning models can analyze vast amounts of medical data and identify patterns that may be too complex for human analysis. However, one of the major challenges in this field is building trust between users and the model. Due to things like high false alarm rate and the black box nature of machine learning models, patients and medical professionals need to understand how the model arrives at its recommendations. In this work, we present several methods that aim to improve machine learning models …
Comparison Of A Bottom-Up Gnss Radio Occultation Method To Measure D- And E-Region Electron Densities With Ionosondes And Firi, Dylan J. Shaver, Dong L. Wu, Nimalan Swarnalingam, Anthony L. Franz, Eugene V. Dao, Daniel J. Emmons
Comparison Of A Bottom-Up Gnss Radio Occultation Method To Measure D- And E-Region Electron Densities With Ionosondes And Firi, Dylan J. Shaver, Dong L. Wu, Nimalan Swarnalingam, Anthony L. Franz, Eugene V. Dao, Daniel J. Emmons
Faculty Publications
High-frequency skywave propagation can be heavily impacted by D- and E-region dynamics requiring accurate global measurements to optimize performance. A standard measurement technique is to use ionosondes, but they are unable to measure below 1 MHz and are only available at a limited number of land-locked sites around the globe. In contrast, the Global Navigation Satellite System radio occultation (GNSS-RO) bottom-up method is a new approach specifically designed to generate electron density profiles in the D- and E- region ionosphere. It takes advantage of satellite constellations that currently provide over 20,000 daily measurements and global coverage. In this paper, GNSS-RO …
Integrating Glycolysis, Citric Acid Cycle, Pentose Phosphate Pathway, And Fatty Acid Beta‑Oxidation Into A Single Computational Model, Sylwester M. Kloska, Krzysztof Pałczyński, Tomasz Marciniak, Tomasz Talaśka, Beata J. Wysocki, Paul H. Davis, Tadeusz A. Wysocki
Integrating Glycolysis, Citric Acid Cycle, Pentose Phosphate Pathway, And Fatty Acid Beta‑Oxidation Into A Single Computational Model, Sylwester M. Kloska, Krzysztof Pałczyński, Tomasz Marciniak, Tomasz Talaśka, Beata J. Wysocki, Paul H. Davis, Tadeusz A. Wysocki
Department of Electrical and Computer Engineering: Faculty Publications
The metabolic network of a living cell is highly intricate and involves complex interactions between various pathways. In this study, we propose a computational model that integrates glycolysis, the pentose phosphate pathway (PPP), the fatty acids beta-oxidation, and the tricarboxylic acid cycle (TCA cycle) using queueing theory. The model utilizes literature data on metabolite concentrations and enzyme kinetic constants to calculate the probabilities of individual reactions occurring on a microscopic scale, which can be viewed as the reaction rates on a macroscopic scale. However, it should be noted that the model has some limitations, including not accounting for all the …
Harnessing The Power Of Neural Networks For The Investigation Of Solar-Driven Membrane Distillation Systems Under The Dynamic Operation Mode, Pooria Behnam, Masoumeh Zargar, Abdellah Shafieian, Amir Razmjou, Mehdi Khiadani
Harnessing The Power Of Neural Networks For The Investigation Of Solar-Driven Membrane Distillation Systems Under The Dynamic Operation Mode, Pooria Behnam, Masoumeh Zargar, Abdellah Shafieian, Amir Razmjou, Mehdi Khiadani
Research outputs 2022 to 2026
Accurate modeling of solar-driven direct contact membrane distillation systems (DCMD) can enhance the commercialization of these promising systems. However, the existing dynamic mathematical models for predicting the performance of these systems are complex and computationally expensive. This is due to the intermittent nature of solar energy and complex heat/mass transfer of different components of solar-driven DCMD systems (solar collectors, MD modules and storage tanks). This study applies a machine learning-based approach to model the dynamic nature of a solar-driven DCMD system for the first time. A small-scale rig was designed and fabricated to experimentally assess the performance of the system …
Pymaivar: An Open-Source Python Suit For Audio-Image Representation In Human Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar
Pymaivar: An Open-Source Python Suit For Audio-Image Representation In Human Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar
Research outputs 2022 to 2026
We present PyMAiVAR, a versatile toolbox that encompasses the generation of image representations for audio data including Wave plots, Spectral Centroids, Spectral Roll Offs, Mel Frequency Cepstral Coefficients (MFCC), MFCC Feature Scaling, and Chromagrams. This wide-ranging toolkit generates rich audio-image representations, playing a pivotal role in reshaping human action recognition. By fully exploiting audio data's latent potential, PyMAiVAR stands as a significant advancement in the field. The package is implemented in Python and can be used across different operating systems.
Analysis Of Coronal Magnetic Field Parameters During X- And M-Class Solar Flares, Seth H. Garland
Analysis Of Coronal Magnetic Field Parameters During X- And M-Class Solar Flares, Seth H. Garland
Theses and Dissertations
Using Non-Linear Force Free Field (NLFFF) extrapolation, 3D magnetic fields were modeled from the 12-minute cadence Helioseismic and Magnetic Imager (HMI) photospheric vector magnetograms, spanning a time period of one hour before through one hour after the start of 18 X-class flares and 12 M-class flares. Several magnetic field parameters were calculated from the modeled fields directly – as well as from the power spectrum of surface maps generated by summing the fields along the vertical axis – for two different regions: areas with photospheric Bz ≥ 300 G (Active Region – AR) and areas above the photosphere with the …
Brdf Measurements And Physical Optics Modeling Applied To Anisotropic Satellite Solar Cells, Madilynn E. Compean
Brdf Measurements And Physical Optics Modeling Applied To Anisotropic Satellite Solar Cells, Madilynn E. Compean
Theses and Dissertations
Light curve analysis is often used to discern information about satellites in geosynchronous orbits, and since solar panels comprise relatively large surface areas, their reflected energy can contribute greatly to observed light curves. Data was collected using a space qualified solar cell interrogated by a green HeNe laser. The data validated certain aspects from previous work, but also identified multi-slit behavior, showed that the specular term was a second diffraction pattern, and diagnosed the out-of-plane diffraction curvature as the conical diffraction phenomenon. Two physical-optics-based models were developed to incorporate these new features and better predict solar cell BRDF solely from …