Digital Commons Network^™

Tutorial: Neuro-Symbolic Ai For Mental Healthcare, Kaushik Roy, Usha Lokala, Manas Gaur, Amit Sheth

Publications

Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …

Improving Wireless Networking From The Learning And Security Perspectives, Zhe Qu

USF Tampa Graduate Theses and Dissertations

Due to the high development of wireless networking and artificial intelligence, most of the data are generated from mobile devices, which distribute in different environments. As such, how to improve the performance of machine learning-based networking and its security should be carefully considered. To reduce the communication burden and protect private information from users, Federated Learning (FL) is a possible solution for learning-based wireless networking. Although FL achieves much success until now, it also remains some specific issues to be solved. In this dissertation, we propose two FL wireless networking frameworks and discuss two potential security issues.

In the FL …

Software Protection And Secure Authentication For Autonomous Vehicular Cloud Computing, Muhammad Hataba

Dissertations

Artificial Intelligence (AI) is changing every technology we deal with. Autonomy has been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected coined as Autonomous Vehicles (AVs). Moreover, researchers found a way to make more use of these enormous capabilities and introduced Autonomous Vehicles Cloud Computing (AVCC). In these platforms, vehicles can lend their unused resources and sensory data to join AVCC.

In this dissertation, we investigate security and privacy issues in AVCC. As background, we built our …

Analysis Of Functionality Of Statistical Data In Geovisualization Of Population Dynamics, L Gulyamova, M Sh Shafkarova, D N. Rakhmonov

Technical science and innovation

The article deals with the analysis of population density with the help of geo information programs, the process of visualization of the integration of statistical and geographical data, the structure of the technological sequence. One of the methods for describing the relative productivity of land data is considered. Geo information systems can support the decision-making process in the design and selection phase with limited capabilities, and these systems provide a very static modeling environment. This limits their scope as a decision support tool, especially at stages where collaborative problem solving decisions are required.

Method Of Intelligent Control Of The Process Of Rectification Of Multicomponent Mixtures, N R. Yusupbekov, Y Sh Avazov

Technical science and innovation

An intelligent method of controlling a rectification column, which implements the technological process of separation of multicomponent mixtures by rectification method, is proposed. The advantage of the method is that it uses an advanced process control system (APC-system) and a distributed control system at the same time. The proposed intellectual method of controlling the process of rectification of multicomponent mixtures for the application of APC-systems and a net model of situational control allows to increase the quality of the product coming from the rectification column, and the efficiency of the rectification of the mixture column, to increase the quality of …

Novel Texture-Based Probabilistic Object Recognition And Tracking Techniques For Food Intake Analysis And Traffic Monitoring, Robert Jacob Dibiano

LSU Doctoral Dissertations

More complex image understanding algorithms are increasingly practical in a host of emerging applications. Object tracking has value in surveillance and data farming; and object recognition has applications in surveillance, data management, and industrial automation. In this work we introduce an object recognition application in automated nutritional intake analysis and a tracking application intended for surveillance in low quality videos. Automated food recognition is useful for personal health applications as well as nutritional studies used to improve public health or inform lawmakers. We introduce a complete, end-to-end system for automated food intake measurement. Images taken by a digital camera are …

Hybrid Sensors, Kv Santhosh

Technical Collection

With the ever increasing demand of quality product, efficient automation is of prime requirement. Automation involves the process of monitoring and control. Efficient monitoring is only possible with the best sensing mechanism. Conventional characteristics of sensors like accuracy, range, sensitivity, etc is not just sufficient for achieving the desired objective. Characteristics like cooperation, competition and complementary is the need of the hour.

Concept of a hybrid sensor involves the implementation of multi-sensor system architecture, such that each of the sensors will compliment and/or cooperate and/or compete with each of the other sensor to achieve the complete and efficient monitoring.

Research …

Interleaved Honeypot-Framing Model With Secure Mac Policies For Wireless Sensor Networks, Rajasoundaran Soundararajan, Maheswar Rajagopal, Akila Muthuramalingam, Eklas Hossain, Jaime Lloret

Electrical and Computer Engineering Faculty Publications and Presentations

The Wireless Medium Access Control (WMAC) protocol functions by handling various data frames in order to forward them to neighbor sensor nodes. Under this circumstance, WMAC policies need secure data communication rules and intrusion detection procedures to safeguard the data from attackers. The existing secure Medium Access Control (MAC) policies provide expected and predictable practices against channel attackers. These security policies can be easily breached by any intelligent attacks or malicious actions. The proposed Wireless Interleaved Honeypot-Framing Model (WIHFM) newly implements distributed honeypot-based security mechanisms in each sensor node to act reactively against various attackers. The proposed WIHFM creates an …

Impulse, Fall 2022, University Marketing And Communications, Jerome J. Lohr College Of Engineering

Impulse (Jerome J. Lohr College of Engineering Publication)

2 | Sanjeev Kumar Takes Helm as College’s 12th Dean
5 | College Develops Partnerships in India, Turkey
6 | Faculty News
8 | Aerofly — Profs, Alum Partner To Build Unique Drone
10 | Researchers Find Way to Extend Produce Shelf Life
12 | SDSU Claims National Title in Quarter-Scale Tractors
14 | Nation’s Top ASCE Chapter Housed at SDSU
16 | National Geo-Video Title Won By State Students
18 | Summer Brings Engineering Camps to Campus
20 | Haleigh Timmer — Money on the Court, In Classroom
22 | Daniel Burkhalter — Day in the Life of Student-Athlete …

Rewards And Challenges In Adopting Agility In An Academic Department, Massood Towhidnejad, Omar Ochoa, James J. Pembridge, Radu Babiceanu, Carlos Castro

Posters

Introducing agility into department processes may be challenging especially when interfacing with a non-agile environment. While frequent meetings can add more time constraints, the team environment emphasizes more communication, transparency, and accountability in completing the products leading to a higher sense of ownership of the completed work.

Quantum Algorithm For Variant Maximum Satisfiability, Abdirahman Alasow, Peter Jin, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

In this paper, we proposed a novel quantum algorithm for the maximum satisfiability problem. Satisfiability (SAT) is to find the set of assignment values of input variables for the given Boolean function that evaluates this function as TRUE or prove that such satisfying values do not exist. For a POS SAT problem, we proposed a novel quantum algorithm for the maximum satisfiability (MAX-SAT), which returns the maximum number of OR terms that are satisfied for the SAT-unsatisfiable function, providing us with information on how far the given Boolean function is from the SAT satisfaction. We used Grover’s algorithm with a …

A Design Flow For Additively Manufactured 3d Metasurface Antennas​, Justin Parkhurst

Doctoral Dissertations and Master's Theses

Metasurface (MTS) antennas are complex arrays consisting of hundreds or thousands of individual elements that each exert their own influence on the performance of the antenna. Due to this, the process of designing and developing a MTS antenna can be intensive in terms of both the time to understand the how these antennas operate and time running calculations that achieve optimal performance. Through the use of automation for geometry creation in ANSYS HFSS, the work involved in making a MTS antenna can be greatly simplified. The overall objective of this thesis is to reduce the burden of constructing a MTS …

Study Of Stochastic Market Clearing Problems In Power Systems With High Renewable Integration, Saumya Sakitha Sashrika Ariyarathne

Operations Research and Engineering Management Theses and Dissertations

Integrating large-scale renewable energy resources into the power grid poses several operational and economic problems due to their inherently stochastic nature. The lack of predictability of renewable outputs deteriorates the power grid’s reliability. The power system operators have recognized this need to account for uncertainty in making operational decisions and forming electricity pricing. In this regard, this dissertation studies three aspects that aid large-scale renewable integration into power systems. 1. We develop a nonparametric change point-based statistical model to generate scenarios that accurately capture the renewable generation stochastic processes; 2. We design new pricing mechanisms derived from alternative stochastic programming …

A Symmetric Matrix-Aided Mimo To Improve Reliability For Maritime Visible Light Communications, You Zhang, Yan Feng, Lin Zhang, Zhiqiang Wu

Electrical Engineering Faculty Publications

Turbulence in natural environments affects the reliability of communication. In this paper, we propose a symmetric matrix-assisted multiple-input multiple-output (MIMO) maritime visible light communication (VLC) system to confront turbulence and improve reliability. In our design, by exploiting the repeatability of elements in the symmetric matrix, the matrix can expand the Euclidean distance between signals and effectively restrains the interference between signals, thus improving the reliability of maritime VLC systems. In addition, we derive the theoretical symbol error rate (SER) of the proposed scheme. Then, simulation results are provided to validate the theoretical SER. In addition, the SER performances of the …

Pulse Width Modulation-Based Voltage Balancing And Circulating Current Control For Modular Multilevel Converters, Md Multan Biswas

Theses and Dissertations

In the last decade, because of some key features and advantages of Modular Multilevel Converter (MMC), it is widely applied for various Medium Voltage (MV) and High Voltage (HV) power electronic interfacing applications. The structure of MMCs varies by application but in general, they are composed of multiple Sub-Modules (SMs) which each contains a floating capacitor. For the operation of MMCs, capacitor voltages are required to remain equally set. This is referred to as the balanced condition and requires a method for SM Capacitor Voltage Balancing (CVB). Connections of SMs for most of the common MMC configurations result in additional …

Closed Form Implicitly Integrated Models For Computationally Efficient Simulation Of Power Electronics, Andrew Wunderlich

Theses and Dissertations

This work describes novel closed-form, implicitly integrated (CF-implicit) models of switched-mode power converters which feature implicit integration but require no iterative numerical solving algorithm for evaluation because they are explicitly solved prior to model execution. The derived models capture the large-signal dynamic behavior of the power converters, so their use and accuracy are not limited to any one set of operating conditions. These models can be implemented in any computational environment, including directly on an existing embedded controller as a digital twin. Since no iterative solver is required, the models are highly computationally efficient and have a very predictable worst-case …

Mimo Antenna Systems For Wireless Handheld Devices, Ahmed H. Abdelgawwad

Theses and Dissertations

Mobile communications have seen tremendous growths in the last decades in the form of smartphones, watches, wireless enabled Personal Digital Assistants (PDAs) and so on. The current and future wireless communication systems require high data-rate capabilities to support high speed needs of users in modern applications. Multiple-input multiple-output (MIMO) antenna systems have become the most promising candidate to support the increased data demand. Therefore, they have emerged as an integral part of the new 5G wireless standard. One key challenge regarding MIMO systems for the handheld is to be able to successfully accommodate multiple miniature platform integrated antennas within a …

Multi-Tasking Memcapacitive Networks, Dat Tran, Christof Teuscher

Electrical and Computer Engineering Faculty Publications and Presentations

Recent studies have shown that networks of memcapacitive devices provide an ideal computing platform of low power consumption for reservoir computing systems. Random, crossbar, or small-world power-law (SWPL) structures are common topologies for reservoir substrates to compute single tasks. However, neurological studies have shown that the interconnections of cortical brain regions associated with different functions form a rich-club structure. This structure allows human brains to perform multiple activities simultaneously. So far, memcapacitive reservoirs can perform only single tasks. Here, we propose, for the first time, cluster networks functioning as memcapacitive reservoirs to perform multiple tasks simultaneously. Our results illustrate that …

Learning To Automate Follow-Up Question Generation Using Process Knowledge For Depression Triage On Reddit Posts, Shrey Gupta, Anmol Agarwal, Manas Gaur, Kaushik Roy, Vignesh Narayanan, Ponnurangam Kumaraguru, Amit Sheth

Publications

Conversational Agents (CAs) powered with deep language models (DLMs) have shown tremendous promise in the domain of mental health. Prominently, the CAs have been used to provide informational or therapeutic services (e.g., cognitive behavioral therapy) to patients. However, the utility of CAs to assist in mental health triaging has not been explored in the existing work as it requires a controlled generation of follow-up questions (FQs), which are often initiated and guided by the mental health professionals (MHPs) in clinical settings. In the context of `depression', our experiments show that DLMs coupled with process knowledge in a mental health questionnaire …

Advanced Manufacturing And Dielectric Material Characterization Techniques For High-Temperature Mm-Wave Antennas, Seng Loong Yu

Doctoral Dissertations and Master's Theses

As traditional monitoring data sensors in high temperature environments such as gas turbine engines and aerospace applications are being replaced by wireless equivalents in recent years, there is a need for low-cost, low-time, and low-infrastructure alternatives to further push the state of the art. In this work, two aspects of high temperature materials in the above context are explored: (a) the development of advanced manufacturing techniques for high temperature materials that is lowcost, low-time, and low-infrastructure, and (b) the development of material characterization techniques that can be integrated with the manufacturing processes of high temperature materials. Additive manufacturing has been …

Backscattering Analysis Utilizing Relaxed Hierarchical Equivalent Source Algorithm (Rhesa) For Scatterers In Vegetation Medium, Syabeela Syahali, Hong Tat Ewe, Gobi Vetharatnam, Li (Lijun) Jun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

The backscattering cross section of cylindrical and elliptical disk-shaped scatterers was investigated in this study, utilising a new numerical solution method called the relaxed hierarchical equivalent source algorithm (RHESA). The results were compared with the backscattering cross section of similar cases, using analytical method validation from literature. The objective of this research was to look into the possibility of replacing analytical methods with the RHESA in volume scattering calculations, and integrating it into modelling the backscattering of layers of dense media for microwave remote sensing in vegetation; as RHESA provides the freedom to model any shape of scatterer, as opposed …

A Comprehensive Characterization Of Hollow Conductor Additively Manufactured Coils And Thermal Management System For A 250 Kw Spm Machine, Sina Vahid, Salar Koushan, Towhid Islam Chowdhury, Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

This paper provides an extensive and comprehensive analysis on characterization of additively manufactured coils and heat pipe based liquid cooling thermal management system, for a 250 kW and 5,000 rpm machine. AC and DC electrical tests at 140 Arms and 70 ADC are conducted on AlSi10Mg additively manufactured coils to extract their thermal and electrical characteristics. Heat pipes and liquid cooling test setups are described and discussed. The thermal discussion is concluded by experimental results showing the effectiveness of the thermal management system proposed in this paper. FEA are performed on the coils using ANSYS Maxwell to accurately predict the …

Monocular Camera Viewpoint-Invariant Vehicular Traffic Segmentation And Classification Utilizing Small Datasets, Amr Yousef, Jeff Flora, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

The work presented here develops a computer vision framework that is view angle independent for vehicle segmentation and classification from roadway traffic systems installed by the Virginia Department of Transportation (VDOT). An automated technique for extracting a region of interest is discussed to speed up the processing. The VDOT traffic videos are analyzed for vehicle segmentation using an improved robust low-rank matrix decomposition technique. It presents a new and effective thresholding method that improves segmentation accuracy and simultaneously speeds up the segmentation processing. Size and shape physical descriptors from morphological properties and textural features from the Histogram of Oriented Gradients …

Preface To Special Issue On Water Electrolysis For Hydrogen Production, Li Li, Jin-Song Hu, Zi-Dong Wei

Journal of Electrochemistry

No abstract provided.

Perovskite-Type Water Oxidation Electrocatalysts, Xiao Liang, Ke-Xin Zhang, Yu-Cheng Shen, Ke Sun, Lei Shi, Hui Chen, Ke-Yan Zheng, Xiao-Xin Zou

Journal of Electrochemistry

The development of energy conversion/storage technologies can achieve the reliable and stable renewable energy supply, and bring us a sustainable future. As the core half-reaction of many energy-related systems, water oxidation is the bottleneck due to its sluggish kinetics of the four-concerted proton-electron transfer (CPET) process. This necessitates the exploitation of low cost, highly active and stable water oxidation electrocatalysts. Perovskite-type oxides possess diverse crystal structures, flexible compositions and unique electronic properties, enabling them ideal material platform for the optimization of catalytic performance. In this review, we provide a comprehensive summary for the crystal structures, electronic structures and synthetic methods …

The Rapid Preparation Of Efficient Mofeco-Based Bifunctional Electrocatalysts Via Joule Heating For Overall Water Splitting, Ao Zhou, Wei-Jian Guo, Yue-Qing Wang, Jin-Tao Zhang

Journal of Electrochemistry

Water electrolysis is an available way to obtain green hydrogen. The development of highly efficient electrocatalysts is a current research hotspot for water splitting, but it remains challenging. Herein, we demonstrate the synthesis of a robust bifunctional multi-metal electrocatalysts toward water splitting via the rapid Joule-heating conversion of metal precursors. The composition and morphology were well regulated via altering the ratio of metal precursors. In particular, the trimetal MoC/FeO/CoO/carbon cloth (CC) electrode revealed the outstanding bifunctional electrocatalytic performance due to the unique composition and large electrochemical active surface area. Typically, the MoC/FeO/CoO/CC catalyst needed low overpotentials of 121 and 268 …

Recent Development Of Low Iridium Electrocatalysts Toward Efficient Water Oxidation, Jing Ni, Zhao-Ping Shi, Xian Wang, Yi-Bo Wang, Hong-Xiang Wu, Chang-Peng Liu, Jun-Jie Ge, Wei Xing

Journal of Electrochemistry

Developing high-performance and low-cost electrocatalysts for oxygen evolution reaction (OER) is the key to implementing polymer electrolyte membrane water electrolyzer (PEMWE) for hydrogen production. To date, iridium (Ir) is the state-of-the-art OER catalyst, but still suffers from the insufficient activity and scarce earth abundance, which results in high cost both in stack and electricity. Design low-Ir catalysts with enhanced activity and stability that can match the requirements of high current and long-term operation in PEMWE is thus highly desired, which necessitate a deep understanding of acidic OER mechanisms, unique insights of material design strategies, and reliable performance evaluation norm, especially …

A Co Porphyrin With Electron-Withdrawing And Hydrophilic Substituents For Improved Electrocatalytic Oxygen Reduction, Hong-Bo Guo, Ya-Ni Wang, Kai Guo, Hai-Tao Lei, Zuo-Zhong Liang, Xue-Peng Zhang, Rui Cao

Journal of Electrochemistry

Understanding factors that influence the catalyst activity for oxygen reduction reaction (ORR) is essential for the rational design of efficient ORR catalysts. Regulating catalyst electronic structure is commonly used to fine-tune electrocatalytic ORR activity. However, modifying the hydrophilicity of catalysts has been rarely reported to improve ORR, which happens at the liquid/gas/solid interface. Herein, we report on two Co porphyrins, namely, NO₂-CoP (Co complex of 5,10,15,20-tetrakis(4-nitrophenyl)porphyrin) and 5F-CoP (Co complex of 5,10,15,20-tetrakis(pentafluorophenyl)porphyrin), and their electrocatalytic ORR features. By simultaneously controlling the electronic structure and hydrophilic property of the meso-substituents, the NO₂-CoP showed higher electrocatalytic activity than …

Surface Structure Engineering Of Feni-Based Pre-Catalyst For Oxygen Evolution Reaction: A Mini Review, Jia-Xin Li, Li-Gang Feng

Journal of Electrochemistry

Nitrite, a widespread raw material, is harmful to human health for long-term consumption. At present, the detection methods of nitrite mainly include chemical analysis, fluorescence, ultraviolet spectrophotometry and chromatography. These methods have ideal sensitivity and selectivity, but also have some characteristics: cumbersome operation, expensive equipment and professional personnel. Therefore, the development of a simple and sensitive nitrite assay is of great significance. In this paper, the Au/rGO/FeOOH composite materials, which revealed good synergistic catalytic performance among the three elements in the composite, were prepared by simple hydrothermal method and reduction method for the first time with large specific surface area …

A Machine Learning Framework For Automatic Speech Recognition In Air Traffic Control Using Word Level Binary Classification And Transcription, Fowad Shahid Sohail

Theses and Dissertations

Advances in Artificial Intelligence and Machine learning have enabled a variety of new technologies. One such technology is Automatic Speech Recognition (ASR), where a machine is given audio and transcribes the words that were spoken. ASR can be applied in a variety of domains to improve general usability and safety. One such domain is Air Traffic Control (ATC). ASR in ATC promises to improve safety in a mission critical environment. ASR models have historically required a large amount of clean training data. ATC environments are noisy and acquiring labeled data is a difficult, expertise dependent task. This thesis attempts to …