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Full-Text Articles in Engineering

Deep Learning For Multi-Structured Javanese Gamelan Note Generator, Arik Kurniawati, Eko Mulyanto Yuniarno, Yoyon Kusnendar Suprapto Jul 2023

Deep Learning For Multi-Structured Javanese Gamelan Note Generator, Arik Kurniawati, Eko Mulyanto Yuniarno, Yoyon Kusnendar Suprapto

Knowledge Engineering and Data Science

Javanese gamelan, a traditional Indonesian musical style, has several song structures called gendhing. Gendhing (songs) are written in conventional notation and require gamelan musicians to recognize patterns in the structure of each song. Usually, previous research on gendhing focuses on artistic and ethnomusicological perspectives, but this study is to explore the correlation between gendhing as traditional music in Indonesia and deep learning technology that replaces the task of gamelan composers. This research proposes CNN-LSTM to generate notation of ricikan struktural instruments as an accompaniment to Javanese gamelan music compositions based on balungan notation, rhythm, song structure, and gatra …


Band Alignments Of Metal/Oxides-Water Interfaces Using Ab Initio Molecular Dynamics, Yong-Bin Zhuang, Jun Cheng Jul 2023

Band Alignments Of Metal/Oxides-Water Interfaces Using Ab Initio Molecular Dynamics, Yong-Bin Zhuang, Jun Cheng

Journal of Electrochemistry

Band alignments of electrode-water interfaces are of crucial importance for understanding electrochemical interfaces. In the scenario of electrocatalysis, applied potentials are equivalent to the Fermi levels of metals in the electrochemical cells; in the scenario of photo(electro)catalysis, semiconducting oxides under illumination have chemical reactivities toward redox reactions if the redox potentials of the reactions straddle the conduction band minimums (CBMs) or valence band maximums (VBMs) of the oxides. Computational band alignments allow us to obtain the Fermi level of metals, as well as the CBM and VBM of semiconducting oxides with respect to reference electrodes. In this tutorial, we describe …


Recent Progress Of Bifunctional Electrocatalysts For Oxygen Electrodes In Unitized Regenerative Fuel Cells, Tian-Long Zheng, Ming-Yu Ou, Song Xu, Xin-Biao Mao, Shi-Yi Wang, Qing-Gang He Jul 2023

Recent Progress Of Bifunctional Electrocatalysts For Oxygen Electrodes In Unitized Regenerative Fuel Cells, Tian-Long Zheng, Ming-Yu Ou, Song Xu, Xin-Biao Mao, Shi-Yi Wang, Qing-Gang He

Journal of Electrochemistry

Unitized regenerative fuel cells (URFCs), which oxidize hydrogen to water to generate electrical power under thefuel cells (FCs) mode and electrolyze water to hydrogen under the water electrolysis (WE) mode for recycling, areknown as clean and sustainable energy conversion devices. In contrast to the hydrogen oxidation reaction (HOR) andhydrogen evolution reaction (HER) on the hydrogen electrode side, the sluggish kinetics of oxygen reduction reaction(ORR) and oxygen evolution reaction (OER) on the oxygen electrode side requires highly efficient bifunctional oxygencatalysts. Conventional precious metal oxygen catalysts combine Pt and IrO2 with excellent ORR and OER activities toachieve bifunctional electrocatalysis performance, but …


Machine Learning-Based Drone And Aerial Threat Detection For Increased Turret Gunner Survivability, Nikolas Koutsoubis Jul 2023

Machine Learning-Based Drone And Aerial Threat Detection For Increased Turret Gunner Survivability, Nikolas Koutsoubis

Theses and Dissertations

The introduction of aerial drones on the modern battlefield has transformed combat operations, posing a significant threat to ground-based military operations. Detecting drones in safety scenarios is crucial. However, modern machine learning (ML)-based object detectors struggle to detect small objects like drones. This thesis presents three main contributions: (a) data and algorithmic modifications to improve small object detection in YOLO to aid in drone detection, (b) the development of a benchmark drone detection dataset called DyViR, and (c) the implementation of explainable artificial intelligence (XAI) to ensure transparent and trustworthy decision-making. To boost the performance of small object detection, we …


Design Of Asic Based Electrical Impedance Tomography Microendoscopic System For Prostate Cancer Surgical Marginal Assessment, Mohsen Shahghasemi Jul 2023

Design Of Asic Based Electrical Impedance Tomography Microendoscopic System For Prostate Cancer Surgical Marginal Assessment, Mohsen Shahghasemi

Dartmouth College Ph.D Dissertations

Prostate cancer is the second most common cancer in the United States. It is typically treated by surgically excising the cancerous section of the prostate. Because there is not always a visible distinction between the healthy and cancerous sections, surgery often leaves some cancerous tissue behind. This is referred to as a positive surgical margin and it requires adjuvant treatment with adverse side effects. Electrical impedance tomography (EIT) is a low-cost low-form-factor method that can be used to assess surgical marginal intraoperatively to ensure that no cancerous tissue is left behind. EIT-based surgical margin assessment works on the principle that …


Designing Intelligent Energy Efficient Scheduling Algorithm To Support Massive Iot Communication In Lora Networks, Jui Mhatre Jul 2023

Designing Intelligent Energy Efficient Scheduling Algorithm To Support Massive Iot Communication In Lora Networks, Jui Mhatre

Master of Science in Computer Science Theses

We are about to enter a new world with sixth sense ability – “Network as a sensor -6G”. The driving force behind digital sensing abilities is IoT. Due to their capacity to work in high frequency, 6G devices have voracious energy demand. Hence there is a growing need to work on green solutions to support the underlying 6G network by making it more energy efficient. Low cost, low energy, and long-range communication capability make LoRa the most adopted and promising network for IoT devices. Since LoRaWAN uses ALOHA for multi-access of channels, collision management is an important task. Moreover, in …


Using Machine Learning To Assist Auditory Processing Evaluation, Hasitha Wimalarathna, Sangamanatha Veeranna, Minh Vu Duong, Chris Allan Prof, Sumit K. Agrawal, Prudence Allen, Jagath Samarabandu, Hanif M. Ladak Jul 2023

Using Machine Learning To Assist Auditory Processing Evaluation, Hasitha Wimalarathna, Sangamanatha Veeranna, Minh Vu Duong, Chris Allan Prof, Sumit K. Agrawal, Prudence Allen, Jagath Samarabandu, Hanif M. Ladak

Electrical and Computer Engineering Publications

Introduction: Approximately 0.2–5% of school-age children complain of listening difficulties in the absence of hearing loss. These children are often referred to an audiologist for an auditory processing disorder (APD) assessment. Adequate experience and training is necessary to arrive at an accurate diagnosis due to the heterogeneity of the disorder.

Objectives: The main goal of the study was to determine if machine learning (ML) can be used to analyze data from the APD clinical test battery to accurately categorize children with suspected APD into clinical sub-groups, similar to expert labels.

Methods: The study retrospectively collected data from 134 children referred …


Adaptive Gps Antenna Array Beam Nulling Effectiveness Under Varying Antenna Element Positioning, Aadesh Neel Jul 2023

Adaptive Gps Antenna Array Beam Nulling Effectiveness Under Varying Antenna Element Positioning, Aadesh Neel

Electrical and Computer Engineering ETDs

Global Positioning System (GPS) is an essential part of modern life but is susceptible to same frequency jamming. GPS jamming can add excessive noise to a received low power signal and have the capability to change or completely distort information being sent through the GPS signal. Adaptive antenna arrays have long since been a solution to mitigating GPS jamming via beamnulling algorithms. However, there is little research on the effectiveness of these beamnulling algorithms under varying element positioning. In this work, an adaptive antenna array, consisting of Right-Hand Circularly Polarized (RHCP) nearly square GPS antenna elements, was constructed and tested …


A Machine Learning Approach For The Early Detection Of Bronchopulmonary Dysplasia (Bpd) In Preterm Infants Using Inter Hypoxemia Intervals, Ratri Mukherjee Jul 2023

A Machine Learning Approach For The Early Detection Of Bronchopulmonary Dysplasia (Bpd) In Preterm Infants Using Inter Hypoxemia Intervals, Ratri Mukherjee

Electrical Engineering Theses

Preterm birth is a significant global public health concern, affecting millions of babies yearly. Despite advancements in medical care that have improved the survival rates of preterm infants, preterm birth remains a leading cause of neonatal morbidity and mortality worldwide. It has both short-term and long-term health consequences that can profoundly impact the child's growth and development, as well as their family and society.

One of the challenges preterm infants face is their underdeveloped immune system, which makes them more vulnerable to infections and other health problems. Their delicate condition requires specialized care, often provided in a Neonatal Intensive Care …


Flux-Quanta Injection For Nonreciprocal Current Control In A Two-Dimensional Noncentrosymmetric Superconducting Structure, Serafim Teknowijoyo, Sara Chahid, Armen Gulian Jul 2023

Flux-Quanta Injection For Nonreciprocal Current Control In A Two-Dimensional Noncentrosymmetric Superconducting Structure, Serafim Teknowijoyo, Sara Chahid, Armen Gulian

Mathematics, Physics, and Computer Science Faculty Articles and Research

We designed and experimentally demonstrated a four-terminal superconducting device, a “quadristor,” that can function as a nonlatching (reversible) superconducting switch from the diode regime to the resistive state by application of a control current much smaller than the main transport current. The device uses a vortex-based superconducting-diode mechanism that is switched back and forth via the injection of flux quanta through auxiliary current leads. Our finding opens a new research area in the field of superconducting electronics.


A Natural Organic Artificial Synaptic Device Made From A Honey And Carbon Nanotube Admixture For Neuromorphic Computing, Md Mehedi Hasan Tanim, Zoe Templin, Kaleb Hood, Jun Jiao, Feng Zhao Jul 2023

A Natural Organic Artificial Synaptic Device Made From A Honey And Carbon Nanotube Admixture For Neuromorphic Computing, Md Mehedi Hasan Tanim, Zoe Templin, Kaleb Hood, Jun Jiao, Feng Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

Artificial synaptic devices are the essential hardware component in emerging neuromorphic computing systems by mimicking biological synapse and brain functions. When made from natural organic materials such as protein and carbohydrate, they have potential to improve sustainability and reduce electronic waste by enabling environmentally friendly disposal. In this paper, a new natural organic memristor based artificial synaptic device is reported with the memristive film processed by a honey and carbon nanotube (CNT) admixture, that is, honey-CNT memristor. Optical microscopy, scanning electron microscopy, and micro-Raman spectroscopy are employed to analyze the morphology and chemical structure of the honey-CNT film. The device …


Ki-Cook: Clustering Multimodal Cooking Representations Through Knowledge-Infused Learning, Revathy Venkataramanan, Swati Padhee, Saini Rohan Rao, Ronak Kaoshik, Anirudh Sundara Rajan, Amit Sheth Jul 2023

Ki-Cook: Clustering Multimodal Cooking Representations Through Knowledge-Infused Learning, Revathy Venkataramanan, Swati Padhee, Saini Rohan Rao, Ronak Kaoshik, Anirudh Sundara Rajan, Amit Sheth

Publications

Cross-modal recipe retrieval has gained prominence due to its ability to retrieve a text representation given an image representation and vice versa. Clustering these recipe representations based on similarity is essential to retrieve relevant information about unknown food images. Existing studies cluster similar recipe representations in the latent space based on class names. Due to inter-class similarity and intraclass variation, associating a recipe with a class name does not provide sufficient knowledge about recipes to determine similarity. However, recipe title, ingredients, and cooking actions provide detailed knowledge about recipes and are a better determinant of similar recipes. In this study, …


A Unified Switched Nonlinear Dynamic Model Of An Electric Vehicle For Performance Evaluation, Dibyendu Khan, Kuntal Mandal, Anjan Kumar Ray, Abdelali El Aroudi Jul 2023

A Unified Switched Nonlinear Dynamic Model Of An Electric Vehicle For Performance Evaluation, Dibyendu Khan, Kuntal Mandal, Anjan Kumar Ray, Abdelali El Aroudi

Department of Electrical and Computer Engineering: Faculty Publications

The advanced modeling and estimation of overall system dynamics play a vital role in electric vehicles (EVs), as the selection of components in the powertrain and prediction of performance are the key market qualifiers. The state-space averaged model and small-signal transfer function model are useful for assessing long-term behavior in system-level analysis and for designing the controller parameters, respectively. Both models take less computation time but ignore the high-frequency switching dynamics. Therefore, these two models could be impractical for the development and testing of EV prototypes. On the other hand, the multi-domain model in available simulation tools gives in-depth information …


Nasa Weather Data Based Neural Network Grid Connected Pv System Maximum Power Point Tracking, Oluwatobiloba Mausi Johnson Jul 2023

Nasa Weather Data Based Neural Network Grid Connected Pv System Maximum Power Point Tracking, Oluwatobiloba Mausi Johnson

Theses and Dissertations

Research and development for alternative energy sources that are cleaner, renewable, and have little to no environmental impact have been pushed by the ongoing rise in energy demand, the possibility of a decline in the use of conventional petroleum fuels, and concerns about environmental degradation. Electricity from photovoltaic (PV) systems is significantly better regarded among these alternative sources as a renewable energy source such as wind power, bioenergy, tidal energy, and hydroelectric with a wide application range because it is clean, accessible, and abundant with little to no environmental effect. However, solar energy usage is significantly impacted by the landscape, …


Is There A “Nationwide System” In Field Of Science And Technology In Japan?—Survey Of Semiconductor Technology, Huimin Li, Rongping Mu, Yue Hao Jul 2023

Is There A “Nationwide System” In Field Of Science And Technology In Japan?—Survey Of Semiconductor Technology, Huimin Li, Rongping Mu, Yue Hao

Bulletin of Chinese Academy of Sciences (Chinese Version)

Different scholars interpret the connotations and characteristics of the “Nationwide System” in quite different ways and fail to reach a consensus about whether some measures that Japan implements to tackle key problems are attributed to a “Nationwide System”. On this basis, the work started with the connotations and characteristics of the “Nationwide System” in the field of science and technology, conducted a case study of measures taken by Japan to tackle key technical problems in the semiconductor technology, and analyzed whether these measures embody relevant characteristics of the “Nationwide System” from an empirical perspective, so as to demonstrate whether there …


An Ai-Based Intervention For Improving Undergraduate Stem Learning, Mohammad Rashedul Hasan, Bilal Khan Jul 2023

An Ai-Based Intervention For Improving Undergraduate Stem Learning, Mohammad Rashedul Hasan, Bilal Khan

Department of Electrical and Computer Engineering: Faculty Publications

We present results from a small-scale randomized controlled trial that evaluates the impact of just-in-time interventions on the academic outcomes of N = 65 undergraduate students in a STEM course. Intervention messaging content was based on machine learning forecasting models of data collected from 537 students in the same course over the preceding 3 years. Trial results show that the intervention produced a statistically significant increase in the proportion of students that achieved a passing grade. The outcomes point to the potential and promise of just-in-time interventions for STEM learning and the need for larger fully-powered randomized controlled trials.


An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif Jul 2023

An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif

Future Computing and Informatics Journal

This study aims to enhance Adaptive Learning Systems (ALS) in Petroleum Sector in Egypt by using the Microservice Architecture and measure the impact of enhancing ALS by participating ALS users through a statistical study and questionnaire directed to them if they accept to apply the Cloud Computing Service “Microservices” to enhance the ALS performance, quality and cost value or not. The study also aims to confirm that there is a statistically significant relationship between ALS and Cloud Computing Service “Microservices” and prove the impact of enhancing the ALS by using Microservices in the cloud in Adaptive Learning in the Egyptian …


Visual Question Answering: A Survey, Gehad Assem El-Naggar Jul 2023

Visual Question Answering: A Survey, Gehad Assem El-Naggar

Future Computing and Informatics Journal

Visual Question Answering (VQA) has been an emerging field in computer vision and natural language processing that aims to enable machines to understand the content of images and answer natural language questions about them. Recently, there has been increasing interest in integrating Semantic Web technologies into VQA systems to enhance their performance and scalability. In this context, knowledge graphs, which represent structured knowledge in the form of entities and their relationships, have shown great potential in providing rich semantic information for VQA. This paper provides an abstract overview of the state-of-the-art research on VQA using Semantic Web technologies, including knowledge …


Systematic Characterization Of Power Side Channel Attacks For Residual And Added Vulnerabilities, Aurelien Tchoupou Mozipo Jul 2023

Systematic Characterization Of Power Side Channel Attacks For Residual And Added Vulnerabilities, Aurelien Tchoupou Mozipo

Dissertations and Theses

Power Side Channel Attacks have continued to be a major threat to cryptographic devices. Hence, it will be useful for designers of cryptographic systems to systematically identify which type of power Side Channel Attacks their designs remain vulnerable to after implementation. It’s also useful to determine which additional vulnerabilities they have exposed their devices to, after the implementation of a countermeasure or a feature. The goal of this research is to develop a characterization of power side channel attacks on different encryption algorithms' implementations to create metrics and methods to evaluate their residual vulnerabilities and added vulnerabilities. This research studies …


Field Studies Of Perc And Al-Bsf Pv Module Performance Loss Using Power And I-V Timeseries, Alan J. Curran, Xuanji Yu, Jiqi Liu, Laura S. Bruckman, Roger H. French Jul 2023

Field Studies Of Perc And Al-Bsf Pv Module Performance Loss Using Power And I-V Timeseries, Alan J. Curran, Xuanji Yu, Jiqi Liu, Laura S. Bruckman, Roger H. French

Faculty Scholarship

We have studied the degradation of both full-sized modules and minimodules with PERC and Al-BSF cell variations in fields while considering packaging strategies. We demonstrate the implementations of data-driven tools to analyze large numbers of modules and volumes of timeseries data to obtain the performance loss and degradation pathways. This data analysis pipeline enables quantitative comparison and ranking of module variations, as well as mapping and deeper understanding of degradation mechanisms. The best performing module is a half-cell PERC, which shows a performance loss rate (PLR) of −0.27 ± 0.12% per annum (%/a) after initial losses have stabilized. Minimodule studies …


Ecg Recordings As Predictors Of Very Early Autism Likelihood: A Machine Learning Approach, Deepa Tilwani, Jessica Bradshaw, Amit Sheth, Christian O'Reilly Jul 2023

Ecg Recordings As Predictors Of Very Early Autism Likelihood: A Machine Learning Approach, Deepa Tilwani, Jessica Bradshaw, Amit Sheth, Christian O'Reilly

Publications

In recent years, there has been a rise in the prevalence of autism spectrum disorder (ASD). The diagnosis of ASD requires behavioral observation and standardized testing completed by highly trained experts. Early intervention for ASD can begin as early as 1–2 years of age, but ASD diagnoses are not typically made until ages 2–5 years, thus delaying the start of intervention. There is an urgent need for non-invasive biomarkers to detect ASD in infancy. While previous research using physiological recordings has focused on brain-based biomarkers of ASD, this study investigated the potential of electrocardiogram (ECG) recordings as an ASD biomarker …


Learning Dynamic Information Of High-Dimensional Signal Time-Series Using Advanced Machine Learning/Artificial Intelligence, Guannan Liu Jul 2023

Learning Dynamic Information Of High-Dimensional Signal Time-Series Using Advanced Machine Learning/Artificial Intelligence, Guannan Liu

LSU Doctoral Dissertations

In this dissertation, we propose a novel simulation-based device-free indoor localization and tracking system using the received signal strength indicators (RSSIs) of WiFi signals as the input features. The Feko channel-propagation simulation software is used to process the RSSI maps of the given arbitrary indoor geometry. In order to learn the dynamic information of high-dimensional RSSI time-series, we propose three procedures for the localization and dynamic tracking system.

First, The indoor geometry is partitioned into several equi-size zones and the localization problem is treated as the typical \multi-classification" problem. The advanced machine-learning techniques such as decision tree (DT) classifier, random …


Generation Of Vector Vortex Wave Modes In Cylindrical Waveguides, Md Khadimul Islam, Pawan Gaire, Arjuna Madanayake, Shubhendu Bhardwaj Jul 2023

Generation Of Vector Vortex Wave Modes In Cylindrical Waveguides, Md Khadimul Islam, Pawan Gaire, Arjuna Madanayake, Shubhendu Bhardwaj

Department of Electrical and Computer Engineering: Faculty Publications

In this paper, we propose a method to generate Vector Vortex Modes (VVM) inside a metallic cylindrical waveguide at microwave frequencies and demonstrate the experimental validation of the concept. Vector vortex modes of EM waves can carry both spin and orbital angular momentum as they propagate within a tubular medium. The existence of such waves in tubular media can be beneficial to wireless communication in such structures. These waves can carry different orbital angular momentum and spin angular momentum, and therefore, they feature the ability to carry multiple orthogonal modes at the same frequency due to spatial structure of the …


Politicians, Pundits, And Platform Migration: A Comparison Of Political Polarization On Parler And Twitter, Abigial Matthews, Jacqueline M. Otala, Esma Wali, Gillian Kurtic, Lynden Millington, Michael Simpson, Jeanna Matthews, Golshan Madraki Jul 2023

Politicians, Pundits, And Platform Migration: A Comparison Of Political Polarization On Parler And Twitter, Abigial Matthews, Jacqueline M. Otala, Esma Wali, Gillian Kurtic, Lynden Millington, Michael Simpson, Jeanna Matthews, Golshan Madraki

Northeast Journal of Complex Systems (NEJCS)

Parler, a self-proclaimed free speech social media platform founded in 2018, attracted a large influx of new members in 2020 as the result of a highly visible platform migration campaign. Parler usage was linked to the planning of the Jan. 6, 2021 attack on the United States Capitol building, leading to a shutdown of the Parler platform. Parler, which is now back online, offers an important lens through which to examine the broader attempts at platform migration in response to changing content moderation and platform governance policies and their impact on political polarization. We begin by examining the network connections …


Optimizing High-Performance Computing Design: The Impacts Of Bandwidth And Topology Across Workloads For Distributed Shared Memory Systems, Jonathan A. Milton Jul 2023

Optimizing High-Performance Computing Design: The Impacts Of Bandwidth And Topology Across Workloads For Distributed Shared Memory Systems, Jonathan A. Milton

Electrical and Computer Engineering ETDs

With the complexity of high-performance computing designs continuously increasing, the importance of evaluating with simulation also grows. One of the key design aspects is the network architecture; topology and bandwidth greatly influence the overall performance and should be optimized. This work uses simulations written to run in the Structural Simulation Toolkit software framework to evaluate a variety of architecture configurations, identify the optimal design point based on expected workload, and evaluate the changes with increased scale. The results show that advanced topologies outperform legacy architectures justifying the additional design complexity; and that after a certain point increasing the bandwidth provides …


List Of 121 Papers Citing One Or More Skin Lesion Image Datasets, Neda Alipour Jul 2023

List Of 121 Papers Citing One Or More Skin Lesion Image Datasets, Neda Alipour

Other resources

No abstract provided.


Compact Flexible Heart Rate Monitor Simulations, Jack Ellingson, Dean Arakaki Jul 2023

Compact Flexible Heart Rate Monitor Simulations, Jack Ellingson, Dean Arakaki

Electrical Engineering

Cardiovascular disease is a global health concern; heart rate monitors can help assess cardiac health. Sensors must be effective and non-invasive. This project develops and characterizes flexible substrate antennas for heart beat detection through reflection coefficient measurements. Antenna substrate printing and sensor applications are through external collaborations. The project includes curved ground plane and substrate HFSS models to determine reflection coefficient responses to chest expansions.


Design And Analysis Of 3d Cassegrain Antenna Using Hfss, Andrew Wu, Dean Arakaki Jul 2023

Design And Analysis Of 3d Cassegrain Antenna Using Hfss, Andrew Wu, Dean Arakaki

Electrical Engineering

Parabolic antennas offer high gain and narrow beamwidth by employing a reflector to collimate radio waves. Dual reflectors reduce antenna system size over single reflectors and increase design optimization options. This paper introduces a detailed HFSS-based Cassegrain dual reflector design procedure for antenna design engineers. A stripline power splitter excites a 4x4 patch feed array. The parameterized model illustrates performance tradeoffs to meet system operating requirements.


Detection Of Critical Cancer Cells In Human Organs Using Dual Demodulation Photonic Crystal Fiber: Numerical Study, Farhan Mumtaz Jul 2023

Detection Of Critical Cancer Cells In Human Organs Using Dual Demodulation Photonic Crystal Fiber: Numerical Study, Farhan Mumtaz

Electrical and Computer Engineering Faculty Research & Creative Works

This study reports a novel approach for early detection of malignant cancer cells in human organs using a birefringent photonic crystal fiber (PCF)-based optical sensor with dual demodulation. The PCF injects light into the middle hole, enhancing the radiated evanescent field. Analytes injected through the core cause a wavelength shift, measured by peak or dip shift. The proposed sensor has an optimal sensitivity of −7,940 nm/RIU, −8,265 nm/RIU, −9,747 nm/RIU, −9,006 nm/RIU, and −8,994 nm/RIU by peak shift and −8,745 nm/RIU, −10,728 nm/RIU, −8,721 nm/RIU, −10,113 nm/RIU, and −11,150 nm/RIU by dip shift for CRT-(Cervical tissue), BLD-(Blood), ADG-(Adrenal gland), BRT-(Breast) …


Cu2o Heterojunction Solar Cell With Photovoltaic Properties Enhanced By A Ti Buffer Layer, Binghao Wang, Zhiqiang Chen, Feng Zhao Jul 2023

Cu2o Heterojunction Solar Cell With Photovoltaic Properties Enhanced By A Ti Buffer Layer, Binghao Wang, Zhiqiang Chen, Feng Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

In this study, semiconductor oxide cuprite (Cu2O) and indium tin oxide (ITO) heterojunction solar cells with and without a 10 nm thick titanium (Ti) thin film as the buffer layer were fabricated and characterized for comparison. The Cu2O film was formed by low-cost electrodeposition, and Ti and ITO layers were deposited on a glass substrate by sputtering. The interfacial microstructures, surface topology, and electrical and photovoltaic properties of both solar cells were investigated. The test results showed that the Ti buffer layer changed the surface morphology, resistivity, and contact potential of the electrodeposited Cu2O …