Engineering Commons^™

Estimating Cognitive Workload In An Interactive Virtual Reality Environment Using Eeg, Christoph Tremmel, Christain Herff, Tetsuya Sato, Krzysztof Rechowicz, Yusuke Yamani, Dean J. Krusienski

Electrical & Computer Engineering Faculty Publications

With the recent surge of affordable, high-performance virtual reality (VR) headsets, there is unlimited potential for applications ranging from education, to training, to entertainment, to fitness and beyond. As these interfaces continue to evolve, passive user-state monitoring can play a key role in expanding the immersive VR experience, and tracking activity for user well-being. By recording physiological signals such as the electroencephalogram (EEG) during use of a VR device, the user's interactions in the virtual environment could be adapted in real-time based on the user's cognitive state. Current VR headsets provide a logical, convenient, and unobtrusive framework for mounting EEG …

Deposition Of Nb₃Sn Films By Multilayer Sequential Sputtering For Srf Cavity Application, Md. N. Sayeed, Hani E. Elsayed-Ali, U. Pudasaini, G.V. Eremeev, C.E. Reece, M. Burton, A.M. Valente-Feliciano

Electrical & Computer Engineering Faculty Publications

Nb₃Sn is considered as an alternative of Nb for SRF accelerator cavity application due to its potential to obtain higher quality factors and higher accelerating gradients at a higher operating temperature. Magnetron sputtering is one of the effective techniques that can be used to fabricate Nb₃Sn on SRF cavity surface. We report on the surface properties of Nb₃Sn films fabricated by sputtering multiple layers of Nb and Sn on sapphire and niobium substrates followed by annealing at 950°C for 3 h. The crystal structure, film microstructure, composition and surface roughness were characterized by X-ray …

Glioma Grading Using Structural Magnetic Resonance Imaging And Molecular Data, Syed M.S. Reza, Manar D. Samad, Zeina A. Shboul, Karra A. Jones, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

A glioma grading method using conventional structural magnetic resonance image (MRI) and molecular data from patients is proposed. The noninvasive grading of glioma tumors is obtained using multiple radiomic texture features including dynamic texture analysis, multifractal detrended fluctuation analysis, and multiresolution fractal Brownian motion in structural MRI. The proposed method is evaluated using two multicenter MRI datasets: (1) the brain tumor segmentation (BRATS-2017) challenge for high-grade versus low-grade (LG) and (2) the cancer imaging archive (TCIA) repository for glioblastoma (GBM) versus LG glioma grading. The grading performance using MRI is compared with that of digital pathology (DP) images in the …

Carbon Multicharged Ion Generation From Laser-Spark Ion Source, Md. Mahmudur Rahman, Oguzhan Balki, Hani E. Elsayed-Ali

Electrical & Computer Engineering Faculty Publications

Multicharged carbon ions are generated by using a laser-assisted spark-discharge ion source. A Q-switched Nd:YAG laser pulse (1064 nm, 7 ns, ≤ 4.5 × 10⁹ W/cm²) focused onto the surface of a glassy carbon target results in its ablation. The spark-discharge (∼1.2 J energy, ∼1 µs duration) is initiated along the direction of the plume propagation between the target surface and a grounded mesh that is parallel to the target surface. Ions emitted from the laser-spark plasma are detected by their time-of-flight using a Faraday cup. The ion energy-to-charge ratio is analyzed by a three-mesh retarding field …

Feature-Guided Deep Radiomics For Glioblastoma Patient Survival Prediction, Zeina A. Shboul, Mahbubul Alam, Lasitha Vidyaratne, Linmin Pei, Mohamed I. Elbakary, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Glioblastoma is recognized as World Health Organization (WHO) grade IV glioma with an aggressive growth pattern. The current clinical practice in diagnosis and prognosis of Glioblastoma using MRI involves multiple steps including manual tumor sizing. Accurate identification and segmentation of multiple abnormal tissues within tumor volume in MRI is essential for precise survival prediction. Manual tumor and abnormal tissue detection and sizing are tedious, and subject to inter-observer variability. Consequently, this work proposes a fully automated MRI-based glioblastoma and abnormal tissue segmentation, and survival prediction framework. The framework includes radiomics feature-guided deep neural network methods for tumor tissue segmentation; followed …

Transfer Learning Approach To Multiclass Classification Of Child Facial Expressions, Megan A. Witherow, Manar D. Samad, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

The classification of facial expression has been extensively studied using adult facial images which are not appropriate ground truths for classifying facial expressions in children. The state-of-the-art deep learning approaches have been successful in the classification of facial expressions in adults. A deep learning model may be better able to learn the subtle but important features underlying child facial expressions and improve upon the performance of traditional machine learning and feature extraction methods. However, unlike adult data, only a limited number of ground truth images exist for training and validating models for child facial expression classification and there is a …

Detecting Special-Cause Variation 'Events' From Process Data Signatures, Timothy M. Young, Olga Khaliukova, Nicolas André, Alexander Petutschnigg, Timothy G. Rials, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The ability to detect the special-cause variation of incoming feedstocks from advanced sensor technology is invaluable to manufacturers. Many on-line sensors produce data signatures that require further off-line statistical processing for interpretation by operational personnel. However, early detection of changes in variation in incoming feedstocks may be imperative to promote early-stage preventive measures. A method is proposed in this applied study for developing control bands to quantify the variation of data signatures in the context of statistical process control (SPC). Control bands based on pointwise prediction intervals constructed from the Bonferroni Inequality and Bayesian smoothing splines are developed. Applications using …

Initial Implementation Of A Machine Learning System For Srf Cavity Fault Classification At Cebaf, A. Carpenter, K. M. Iftekharuddin, T. Powers, Y. Roblin, A. Solopava Shabalina, C. Tennant, L. Vidyaratne

Electrical & Computer Engineering Faculty Publications

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a high power Continuous Wave (CW) electron accelerator. It uses a mixture of of SRF cryomodules: older, lower energy C20/C50 modules and newer, higher energy C100 modules. The cryomodules are arrayed in two anti-parallel linear accelerators. Accurately classifying the type of cavity faults is essential to maintaining and improving accelerator performance. Each C100 cryomodule contains eight 7-cell cavities. When a cavity fault occurs within a cryomodule, all eight cavities generate 17 waveforms each containing 8192 points. This data is exported from the control system and saved for review. Analysis …

Ignition Of A Plasma Discharge Inside An Electrodeless Chamber: Methods And Characteristics, Mounir Laroussi

Electrical & Computer Engineering Faculty Publications

In this paper the generation and diagnostics of a reduced pressure (300 mTorr to 3 Torr) plasma generated inside an electrodeless containment vessel/chamber are presented. The plasma is ignited by a guided ionization wave emitted by a low temperature pulsed plasma jet. The diagnostics techniques include Intensified Charge Coupled Device (ICCD) imaging, emission spectroscopy, and Langmuir probe. The reduced-pressure discharge parameters measured are the magnitude of the electric field, the plasma electron number density and temperature, and discharge expansion speed.

1995-2005: A Decade Of Innovation In Low Temperature Plasma And Its Applications, Mounir Laroussi

Electrical & Computer Engineering Faculty Publications

Scientific breakthroughs tend to come in spurts when unique societal, economical, and political circumstances conspire (knowingly or unknowingly) and create an environment ripe for creativity. The field of low temperature plasma (LTP) recently experienced such an upheaval, which this paper attempts to relate in some details. There have been “roadmap” papers published before, which look towards the future of the field, but all roads start somewhere and even “new” roads are often paved over older roads that were discovered and traveled by early pioneers. With the sharp decrease in funding for fusion research in the USA in the early 1990s …

Maximizing Performance Under A Power Constraint On Modern Multicore Systems, Vaibhav Sundriyal, Masha Sosonkina, Bryce Westheimer, Mark S. Gordon

Electrical & Computer Engineering Faculty Publications

Energy efficiency and energy-proportional computing have become a central focus in modern supercomputers. These supercomputers should provide high throughput per unit of power to be sustainable in terms of operating cost and failure rates. In this paper, a power-bounded strategy is proposed that maximizes parallel application performance under a given power constraint. The strategy dynamically allocates power to core, uncore, and memory power domains within a node to maximize performance under a given power budget. Experiments on a 20-core Haswell-EP platform for a real-world parallel application GAMESS demonstrate that the proposed strategy delivers performance within 4% of the best possible …

On Board Georeferencing Using Fpga-Based Optimized Second Order Polynomial Equation, Dequan Liu, Guoqing Zhou, Jingjin Huang, Rongting Zhang, Lei Shu, Xiang Zhou, Chun Sheng Xin

Electrical & Computer Engineering Faculty Publications

For real-time monitoring of natural disasters, such as fire, volcano, flood, landslide, and coastal inundation, highly-accurate georeferenced remotely sensed imagery is needed. Georeferenced imagery can be fused with geographic spatial data sets to provide geographic coordinates and positing for regions of interest. This paper proposes an on-board georeferencing method for remotely sensed imagery, which contains five modules: input data, coordinate transformation, bilinear interpolation, and output data. The experimental results demonstrate multiple benefits of the proposed method: (1) the computation speed using the proposed algorithm is 8 times faster than that using PC computer; (2) the resources of the field programmable …

Charge Storage In Wo³ Polymorphs And Their Application As Supercapacitor Electrode Material, Vaibhav Lokhande, Abhishek Lokhande, Gon Namkoong, Jin Hyeok Kim, Taeksoo Ji

Electrical & Computer Engineering Faculty Publications

Tungsten oxide is a versatile material with different applications. It has many polymorphs with varying performance in energy storage application. We report simple and facile way to synthesize four phases of tungsten oxide from same precursor materials only by changing the pH and temperature values. Monoclinic, hexagonal, orthorhombic and tetragonal phase obtained, were analyzed and tested for supercapacitor application. The electrochemical analysis of four phases indicates that the hexagonal phase is best-suited electrode material for supercapacitor. The hexagonal phase exhibits higher specific capacitance (377.5 Fg^-1 at 2 mVs^-1), higher surface capacitive contribution (75%), better stability and rate …

N-I-P Nanocrystalline Hydrogenated Silicon Solar Cells With Rf-Magnetron Sputtered Absorbers, Dipendra Adhikari, Maxwell M. Junda, Corey R. Grice, Sylvain X. Marsillac, Robert W. Collins, Nikolas J. Podraza

Electrical & Computer Engineering Faculty Publications

Nanocrystalline hydrogenated silicon (nc-Si:H) substrate configuration n-i-p solar cells have been fabricated on soda lime glass substrates with active absorber layers prepared by plasma enhanced chemical vapor deposition (PECVD) and radio frequency magnetron sputtering. The cells with nanocrystalline PECVD absorbers and an untextured back reflector serve as a baseline for comparison and have power conversion efficiency near 6%. By comparison, cells with sputtered absorbers achieved efficiencies of about 1%. Simulations of external quantum efficiency (EQE) are compared to experimental EQE to determine a carrier collection probability gradient with depth for the device with the sputtered i-layer absorber. This incomplete …

The Effect Of Tube Geometry On The Chiral Plasma, S. Jin, D. Zou, X. Lu, Mounir Laroussi

Electrical & Computer Engineering Faculty Publications

A chiral plasma plume has recently been reported inside a circular quartz tube without the use of an external magnetic field. It is believed that the quartz tube plays an important role in the formation of the chiral plasma plume. In this paper, to better understand how this interesting structure is generated, the effect of the tube geometry on the chiral plasma is investigated. First, the effect of the thickness of the tube wall on the chiral plasma is investigated. It is interesting to find that a too thin or too thick tube wall is not favorable for generating the …

Computational Modeling Of Trust Factors Using Reinforcement Learning, C. M. Kuzio, A. Dinh, C. Stone, L. Vidyaratne, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

As machine-learning algorithms continue to expand their scope and approach more ambiguous goals, they may be required to make decisions based on data that is often incomplete, imprecise, and uncertain. The capabilities of these models must, in turn, evolve to meet the increasingly complex challenges associated with the deployment and integration of intelligent systems into modern society. Historical variability in the performance of traditional machine-learning models in dynamic environments leads to ambiguity of trust in decisions made by such algorithms. Consequently, the objective of this work is to develop a novel computational model that effectively quantifies the reliability of autonomous …

Special Issue On Low Temperature Plasma Jets, Mounir Laroussi

Electrical & Computer Engineering Faculty Publications

[Introduction] Low temperature plasma jets are unique plasma sources capable of delivering plasma outside of the confinement of electrodes and away from gas enclosures/chambers. With these jets plasma can be easily delivered to a target located at some distance from the plasma generation region [1].

Ultrafast Time-Resolved Structural Changes Of Thin-Film Ferromagnetic Metal Heated With Femtosecond Optical Pulses, Runze Li, Hani Elsayed-Ali, Jie Chen, Dinesh Dhankhar, Arjun Krishnamoorthi, Peter M. Rentzepis

Electrical & Computer Engineering Faculty Publications

As a classic ferromagnetic material, nickel has been an important research candidate used to study dynamics and interactions of electron, spin, and lattice degrees of freedom. In this study, we specifically chose a thick, 150 nm ferromagnetic nickel (111) single crystal rather than 10–20 nm thin crystals that are typically used in ultrafast studies, and we revealed both the ultrafast heating within the skin depth and the heat transfer from the surface (skin) layer to the bulk of the crystal. The lattice deformation after femtosecond laser excitation was investigated by means of 8.04 keV subpicosecond x-ray pulses, generated from a …

Compact -300 Kv Dc Inverted Insulator Photogun With Biased Anode And Alkali-Antimonide Photocathode, C. Hernandez-Garcia, P. Adderley, B. Bullard, J. Benesch, J. Grames, J. Gubeli, F. Hannon, J. Hansknecht, J. Jordan, R. Kazimi, G. A. Krafft, M. A. Mamun, M. Poelker, M. L. Stutzman, R. Suleiman, M. Tiefenback, Y. Wang, S. Zhang, H. Baumgart, G. Palacios-Serrano, S. Wijethunga, J. Yoskowitz, C. A. Valerio Lizarraga, R. Montoya Soto, A. Canales Ramos

Electrical & Computer Engineering Faculty Publications

This contribution describes the latest milestones of a multiyear program to build and operate a compact −300  kV dc high voltage photogun with inverted insulator geometry and alkali-antimonide photocathodes. Photocathode thermal emittance measurements and quantum efficiency charge lifetime measurements at average current up to 4.5 mA are presented, as well as an innovative implementation of ion generation and tracking simulations to explain the benefits of a biased anode to repel beam line ions from the anode-cathode gap, to dramatically improve the operating lifetime of the photogun and eliminate the occurrence of micro-arc discharges.

Microstructural Evaluation Of Aluminium Alloy A365 T6 In Machining Operation, Bankole I. Oladapo, S. Abolfazl Zahedi, Francis T. Omigbodun, Edwin A. Oshin, Victor A. Adebiyi, Olaoluwa B. Malachi

Electrical & Computer Engineering Faculty Publications

The optimum cutting parameters such as cutting depth, feed rate, cutting speed and magnitude of the cutting force for A356 T6 was determined concerning the microstructural detail of the material. Novel test analyses were carried out, which include mechanical evaluation of the materials for density, glass transition temperature, tensile and compression stress, frequency analysis and optimisation as well as the functional analytic behaviour of the samples. The further analytical structure of the particle was performed, evaluating the surface luminance structure and the profile structure. The cross-sectional filter profile of the sample was extracted, and analyses of Firestone curve for the …

End-To-End Learning Via A Convolutional Neural Network For Cancer Cell Line Classification, Darlington A. Akogo, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Purpose: Computer vision for automated analysis of cells and tissues usually include extracting features from images before analyzing such features via various machine learning and machine vision algorithms. The purpose of this work is to explore and demonstrate the ability of a Convolutional Neural Network (CNN) to classify cells pictured via brightfield microscopy without the need of any feature extraction, using a minimum of images, improving work-flows that involve cancer cell identification.

Design/methodology/approach: The methodology involved a quantitative measure of the performance of a Convolutional Neural Network in distinguishing between two cancer lines. In their approach, they trained, validated and …

A Review: Thermal Stability Of Methylammonium Lead Halide Based Perovskite Solar Cells, Tanzila Tasnim Ava, Abdullah Al Mamun, Sylvain Marsillac, Gon Namkoong

Electrical & Computer Engineering Faculty Publications

Perovskite solar cells have achieved photo-conversion efficiencies greater than 20%, making them a promising candidate as an emerging solar cell technology. While perovskite solar cells are expected to eventually compete with existing silicon-based solar cells on the market, their long-term stability has become a major bottleneck. In particular, perovskite films are found to be very sensitive to external factors such as air, UV light, light soaking, thermal stress and others. Among these stressors, light, oxygen and moisture-induced degradation can be slowed by integrating barrier or interface layers within the device architecture. However, the most representative perovskite absorber material, CH_{3 …}