Engineering Commons^™

The Effects Of Dental Hygiene Instrument Handles On Muscle Activity Production, Jessica R. Suedbeck, Daniel Russell, Cortney Armitano Lago, Emily A. Ludwig

Dental Hygiene Faculty Publications

Purpose The objective of this study was to compare the effects of ten commercially available instrument handle designs’ mass and diameter on forearm muscle activity during a simulated periodontal scaling experience.

Methods A convenience sample of 25 registered dental hygienists were recruited for this IRB-approved study. Ten commercially available instruments were categorized into four groups based on their masses and diameters: large diameter/light mass, small diameter/light mass, large diameter/heavy mass, and small diameter/heavy mass. Participants were randomized to four instruments with one from each group. Participants scaled with each instrument in a simulated oral environment while muscle activity was collected …

Probabilistic Invariance For Gaussian Process State Space Models, Paul Griffioen, Alex Devonport, Murat Arcak

Faculty Work Comprehensive List

Gaussian process state space models are becoming common tools for the analysis and design of nonlinear systems with uncertain dynamics. When designing control policies for these systems, safety is an important property to consider. In this paper, we provide safety guarantees for Gaussian process state space models in the form of probabilistic invariant sets, where the state trajectory is guaranteed to lie within an invariant set for all time with a particular probability. We provide a sufficient condition in the form of a linear matrix inequality to evaluate the probabilistic invariance of the system, and we demonstrate our contributions with …

A Synthesized Dual-Polarized Planar Slotted Antenna Array For Sar Sensors, Ahmed E. Gohar, Haythem H. Abdullah, Mohy El Din Abo El-Soud

Mansoura Engineering Journal

A synthetic aperture radar (SAR) sensor antenna is the main concern in this research work. The antenna specifications are settled according to the link budget of a project funded by the Egyptian Space Agency. The antenna should achieve a 30 dBi gain and an SLL of less than -27 dB with a low-profile and simple structure. The proposed antenna is an array of 16 x 18 planar elements that based on microstrip technology. The 16 x 18 antenna array consists of 16 linear antenna arrays of 18 elements each. Each element of the antenna array has two orthogonal slots with …

Effects Of Power Stations Emissions On Air Quality In Kuwait, Abdullah F.M. Al-Rukaibi, I. G. Rashed, M.M. El-Halwany, O. Hamed

Mansoura Engineering Journal

The research describes the Gaussian plume model used to estimate the concentration of pollutants emitted from power plants and dispersed in the atmosphere. The object of the research is to compare the air quality between areas which is near to source station and away from the source station. The research estimates the concentrations of pollutants released from six electric power stations in Kuwait using the Gaussian plume model. A power plant with a stack height of 100 m, stack diameter of 2 m, and an emission rate of 1 kg/s for each station is considered. The Pasquill-Gifford stability categories are …

Design And Analysis Of Advanced Low Power Consumption Hybrid Switch With Experimental Verification, A. Hussein, M. Abd-Elazzem, M. Abo-Elsoud, Mahmoud M. Saafan

Mansoura Engineering Journal

This paper presents a hardware implementation for a hybrid switch (HS) that can be used successfully as a fast switch in industrial power factor correction (PFC) panels and for electrical transformers. The main components of HS are a semiconductor switch as Silicon Controlled Rectifier (SCR) or thyristor and a mechanical switch as a relay. In the conventional PFC solution, the correction process is based on traditional electromagnetic contactors so, a huge current will appear during the turn-on operation In addition there is frequently a spark. Due to the parallel technique between SCR and latched relay, the proposed HS can inhibit …

Comparison Between Different Codes In Design Cold-Formed Steel Lipped Channel Section Subjected To Axial Load Or Bending Moment, Samar El-Sayed Ibrahim Atya, Ahmed Hussain Ali Abdelrahman, Fikry Abdo Salem, Nabil Sayed Mahmoud, Mohamed Ghannam

Mansoura Engineering Journal

This paper presents a comparative analysis between Eurocode3 (EC3), the North American Specification (AISI), and the Egyptian Code of Practice (ECP-205) to design Cold-Formed Steel (CFS) compression and flexural members with channel profiles. The research recognizes similarities and variations in strength measures to facilitate the learning process in the design codes, as well as the expressions and limits provided in the ECP, EC3, and AISI design codes. A computer program was designed to improve the speed of the calculation process. The software was created utilizing the C+ programming language and was programmed to calculate the axial load and bending moment …

A Relativistic Geodetic Approach To Unify The Height System For Africa, Mostafa Ashry, Wen-Bin Shen, Abdelrahim Ruby, Zhang Pengfei, Ziyu Shen, Hussein A. Abd-Elmotaal, Mostafa Abd-Elbaky, Atef A. Makhloof

Mansoura Engineering Journal

This study focuses on the establishment of a unified height system for Africa called AFRUHS (African Unified Height System) by utilizing atomic 8 clocks and clock networks. The International Association of Geodesy (IAG) has 9 long aims to construct an International Height Reference Frame (IHRF), but the lack of accurate and globally harmonized vertical coordinates, particularly in Africa, has posed a challenge. To overcome this, the researchers propose using clock networks to determine geopotential or elevation differences between distant stations by measuring the gravitational redshift (GR) through clock frequency comparisons. The research employs simulation studies using the ACES (Atomic Clock …

Indoor Pedestrian Navigation Using Pdr/Wi-Fi Integration, Ahmad Yhaya, Ehab H. Abdelhay, Mohammed A. H. Abozied, Ahmed Shaaban Samra

Mansoura Engineering Journal

Positioning of pedestrians is a challenging problem. Especially, in case of global positioning system (GPS) signal outage inside buildings. The inertial navigation system (INS) systems are always used to detect the motion of the human body by placing inertial measurement unit (IMU) in a specific part of the human body. However, using IMU alone will not produce proper navigation solution with sufficient accuracy due to gradually accumulated errors of IMU stochastic drift, noise, and state integration with time. Which lead the recent researchers to enhance the performance of indoor navigation systems using aiding sources such as received signal strength (RSS) …

Modular Pandemic Hospitals: A Challenge For Living, Mona Y. Shedid, Eman M. O. Mokhtar

Mansoura Engineering Journal

Over the last several months, the COVID-19 pandemic has globally affected millions of humans and has changed every aspect of our daily life. Hospitals play a major role to combat this pandemic disease however; they are struggling as they are confronted with sudden influx of patients and are jammed to capacity with a lack of available beds and treatment spaces. In managing this health crisis, a rapid resolution concerning our perception and future hospital designs needs to change to save as many lives as possible. According to a pilot study with experts in architecture, four problems during the design of …

Usage Of Virtual Reality Techniques In Revival Of Heritage Religious Buildings (Study Examples From The Unesco Tentative List In Egypt), Reham Ezzat Elsayad, Medhat A. Samra

Mansoura Engineering Journal

The research focuses on the architectural documentation of religious buildings with architectural value and the role of this process in reviving heritage values. Every architectural detail had told us a story which is collected as the identity of the city. The fragility of these buildings and their artifacts, natural disasters, climate change, visitors' impact and lack of information usually leads to the inaccessibility of these buildings. But, due to the historical and touristic value of the religious buildings, the documentation process become necessary to benefit both visitors and researchers by availability and ease of access to information.

The traditional documentation …

Computational Fluid Dynamics Investigation Of Flow Through Pneumatic Control Valve, Wael Elmayyah

Mansoura Engineering Journal

Low-cost on-off pneumatic directional control valves are widely used with digital control circuits to control the position or the speed of pneumatic actuators. These valves have a limited flow capacity that hinders the system fast response. Therefore, deeper understanding of the internal air flow through the valve and its interaction with valve geometry will allow further performance improvement according to the required application.

In this paper, a Computational Fluid Dynamics (CFD) model for a low-cost internal pilot, electrically operated pneumatic 3/2 directional control valve has been developed to investigate the effect of the valve's geometry on the valve's outlet flow …

Ierl: Interpretable Ensemble Representation Learning - Combining Crowdsourced Knowledge And Distributed Semantic Representations, Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Manas Gaur, Amit Sheth

Publications

Large Language Models (LLMs) encode meanings of words in the form of distributed semantics. Distributed semantics capture common statistical patterns among language tokens (words, phrases, and sentences) from large amounts of data. LLMs perform exceedingly well across General Language Understanding Evaluation (GLUE) tasks designed to test a model’s understanding of the meanings of the input tokens. However, recent studies have shown that LLMs tend to generate unintended, inconsistent, or wrong texts as outputs when processing inputs that were seen rarely during training, or inputs that are associated with diverse contexts (e.g., well-known hallucination phenomenon in language generation tasks). Crowdsourced and …

Cooperative Deep Q -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan

Publications

In this article, we address two key challenges in deep reinforcement learning (DRL) setting, sample inefficiency, and slow learning, with a dual-neural network (NN)-driven learning approach. In the proposed approach, we use two deep NNs with independent initialization to robustly approximate the action-value function in the presence of image inputs. In particular, we develop a temporal difference (TD) error-driven learning (EDL) approach, where we introduce a set of linear transformations of the TD error to directly update the parameters of each layer in the deep NN. We demonstrate theoretically that the cost minimized by the EDL regime is an approximation …

A Semantic Web Approach To Fault Tolerant Autonomous Manufacturing, Fadi El Kalach, Ruwan Wickramarachchi, Ramy Harik, Amit Sheth

Publications

The next phase of manufacturing is centered on making the switch from traditional automated to autonomous systems. Future factories are required to be agile, allowing for more customized production, and resistance to disturbances. Such production lines would be able to reallocate resources as needed and minimize downtime while keeping up with market demands. These systems must be capable of complex decision-making based on parameters such as machine status, sensory/IoT data, and inspection results. Current manufacturing lines lack this complex capability and instead focus on low-level decision-making on the machine level without utilizing the generated data to its full extent. This …

Knowledge Graph Guided Semantic Evaluation Of Language Models For User Trust, Kaushik Roy, Tarun Garg, Vedant Palit, Yuxin Zi, Vignesh Narayanan, Amit Sheth

Publications

A fundamental question in natural language processing is - what kind of language structure and semantics is the language model capturing? Graph formats such as knowledge graphs are easy to evaluate as they explicitly express language semantics and structure. This study evaluates the semantics encoded in the self-attention transformers by leveraging explicit knowledge graph structures. We propose novel metrics to measure the reconstruction error when providing graph path sequences from a knowledge graph and trying to reproduce/reconstruct the same from the outputs of the self-attention transformer models. The opacity of language models has an immense bearing on societal issues of …

Acm Web Conference 2023, Usha Lokala, Kaushik Roy, Utkarshani Jaimini, Amit Sheth

Publications

Improving the performance and explanations of ML algorithms is a priority for adoption by humans in the real world. In critical domains such as healthcare, such technology has significant potential to reduce the burden on humans and considerably reduce manual assessments by providing quality assistance at scale. In today’s data-driven world, artificial intelligence (AI) systems are still experiencing issues with bias, explainability, and human-like reasoning and interpretability. Causal AI is the technique that can reason and make human-like choices making it possible to go beyond narrow Machine learning-based techniques and can be integrated into human decision-making. It also offers intrinsic …

L3 Ensembles: Lifelong Learning Approach For Ensemble Of Foundational Language Models*, Aidin Shiri, Kaushik Roy, Amit Sheth, Manas Gaur

Publications

Fine-tuning pre-trained foundational language models (FLM) for specific tasks is often impractical, especially for resource-constrained devices. This necessitates the development of a Lifelong Learning (L3) framework that continuously adapts to a stream of Natural Language Processing (NLP) tasks efficiently. We propose an approach that focuses on extracting meaningful representations from unseen data, constructing a structured knowledge base, and improving task performance incrementally. We conducted experiments on various NLP tasks to validate its effectiveness, including benchmarks like GLUE and SuperGLUE. We measured good performance across the accuracy, training efficiency, and knowledge transfer metrics. Initial experimental results show that the proposed L3 …

The Troubling Emergence Of Hallucination In Large Language Models--An Extensive Definition, Quantification, And Prescriptive Remediations, Vipula Rawte, Swagata Chakraborty, Agnibh Pathak, Anubhav Sarkar, S.M Towhidul Islam Tonmoy, Aman Chadha, Amit Sheth, Amitava Das

Publications

The recent advancements in Large Language Models (LLMs) have garnered widespread acclaim for their remarkable emerging capabilities. However, the issue of hallucination has parallelly emerged as a by-product, posing significant concerns. While some recent endeavors have been made to identify and mitigate different types of hallucination, there has been a limited emphasis on the nuanced categorization of hallucination and associated mitigation methods. To address this gap, we offer a finegrained discourse on profiling hallucination based on its degree, orientation, and category, along with offering strategies for alleviation. As such, we define two overarching orientations of hallucination: (i) factual mirage (FM) …

Light Auditor: Power Measurement Can Tell Private Data Leakage Through Iot Covert Channels, Woosub Jung, Kailai Cui, Kenneth Koltermann, Junjie Wang, Chunsheng Xin, Gang Zhou

Electrical & Computer Engineering Faculty Publications

Despite many conveniences of using IoT devices, they have suffered from various attacks due to their weak security. Besides well-known botnet attacks, IoT devices are vulnerable to recent covert-channel attacks. However, no study to date has considered these IoT covert-channel attacks. Among these attacks, researchers have demonstrated exfiltrating users' private data by exploiting the smart bulb's capability of infrared emission.

In this paper, we propose a power-auditing-based system that defends the data exfiltration attack on the smart bulb as a case study. We first implement this infrared-based attack in a lab environment. With a newly-collected power consumption dataset, we pre-process …

Mwirgan: Unsupervised Visible-To Mwir Image Translation With Generative Adversarial Network, Mohammad Shahab Uddin, Chiman Kwan, Jiang Li

Electrical & Computer Engineering Faculty Publications

Unsupervised image-to-image translation techniques have been used in many applications, including visible-to-Long-Wave Infrared (visible-to-LWIR) image translation, but very few papers have explored visible-to-Mid-Wave Infrared (visible-to-MWIR) image translation. In this paper, we investigated unsupervised visible-to-MWIR image translation using generative adversarial networks (GANs). We proposed a new model named MWIRGAN for visible-to-MWIR image translation in a fully unsupervised manner. We utilized a perceptual loss to leverage shape identification and location changes of the objects in the translation. The experimental results showed that MWIRGAN was capable of visible-to-MWIR image translation while preserving the object’s shape with proper enhancement in the translated images and …

Ultrasensitive Tapered Optical Fiber Refractive Index, Erem Ujah, Meimei Lai, Gymama Slaughter

Electrical & Computer Engineering Faculty Publications

Refractive index (RI) sensors are of great interest for label-free optical biosensing. A tapered optical fiber (TOF) RI sensor with micron-sized waist diameters can dramatically enhance sensor sensitivity by reducing the mode volume over a long distance. Here, a simple and fast method is used to fabricate highly sensitive refractive index sensors based on localized surface plasmon resonance (LSPR). Two TOFs (l = 5 mm) with waist diameters of 5 µm and 12 µm demonstrated sensitivity enhancement at λ = 1559 nm for glucose sensing (5-45 wt%) at room temperature. The optical power transmission decreased with increasing glucose concentration due …

The Effect Of The Width Of The Incident Pulse To The Dielectric Transition Layer In The Scattering Of An Electromagnetic Pulse — A Qubit Lattice Algorithm Simulation, George Vahala, Linda Vahala, Abhay K. Ram, Min Soe

Electrical & Computer Engineering Faculty Publications

The effect of the thickness of the dielectric boundary layer that connects a material of refractive index n₁ to another of index n₂is considered for the propagation of an electromagnetic pulse. A qubit lattice algorithm (QLA), which consists of a specially chosen non-commuting sequence of collision and streaming operators acting on a basis set of qubits, is theoretically determined that recovers the Maxwell equations to second-order in a small parameter ϵ. For very thin boundary layer the scattering properties of the pulse mimics that found from the Fresnel jump conditions for a plane wave - except that …

Toward Real-Time, Robust Wearable Sensor Fall Detection Using Deep Learning Methods: A Feasibility Study, Haben Yhdego, Christopher Paolini, Michel Audette

Electrical & Computer Engineering Faculty Publications

Real-time fall detection using a wearable sensor remains a challenging problem due to high gait variability. Furthermore, finding the type of sensor to use and the optimal location of the sensors are also essential factors for real-time fall-detection systems. This work presents real-time fall-detection methods using deep learning models. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. First, we developed and compared different data-segmentation techniques for sliding windows. Next, we implemented various techniques to balance the datasets because collecting fall datasets in the real-time setting has …

Class Activation Mapping And Uncertainty Estimation In Multi-Organ Segmentation, Md. Shibly Sadique, Walia Farzana, Ahmed Temtam, Khan Iftekharuddin, Khan Iftekharuddin (Ed.), Weijie Chen (Ed.)

Electrical & Computer Engineering Faculty Publications

Deep learning (DL)-based medical imaging and image segmentation algorithms achieve impressive performance on many benchmarks. Yet the efficacy of deep learning methods for future clinical applications may become questionable due to the lack of ability to reason with uncertainty and interpret probable areas of failures in prediction decisions. Therefore, it is desired that such a deep learning model for segmentation classification is able to reliably predict its confidence measure and map back to the original imaging cases to interpret the prediction decisions. In this work, uncertainty estimation for multiorgan segmentation task is evaluated to interpret the predictive modeling in DL …

Transfer Learning Using Infrared And Optical Full Motion Video Data For Gender Classification, Alexander M. Glandon, Joe Zalameda, Khan M. Iftekharuddin, Gabor F. Fulop (Ed.), David Z. Ting (Ed.), Lucy L. Zheng (Ed.)

Electrical & Computer Engineering Faculty Publications

This work is a review and extension of our ongoing research in human recognition analysis using multimodality motion sensor data. We review our work on hand crafted feature engineering for motion capture skeleton (MoCap) data, from the Air Force Research Lab for human gender followed by depth scan based skeleton extraction using LIDAR data from the Army Night Vision Lab for person identification. We then build on these works to demonstrate a transfer learning sensor fusion approach for using the larger MoCap and smaller LIDAR data for gender classification.

Long-Range Aceo Phenomena In Microfluidic Channel, Diganta Dutta, Keifer Smith, Xavier Palmer

Electrical & Computer Engineering Faculty Publications

Microfluidic devices are increasingly utilized in numerous industries, including that of medicine, for their abilities to pump and mix fluid at a microscale. Within these devices, microchannels paired with microelectrodes enable the mixing and transportation of ionized fluid. The ionization process charges the microchannel and manipulates the fluid with an electric field. Although complex in operation at the microscale, microchannels within microfluidic devices are easy to produce and economical. This paper uses simulations to convey helpful insights into the analysis of electrokinetic microfluidic device phenomena. The simulations in this paper use the Navier–Stokes and Poisson Nernst–Planck equations solved using COMSOL …

Deep-Learning-Based Classification Of Digitally Modulated Signals Using Capsule Networks And Cyclic Cumulants, John A. Snoap, Dimitrie C. Popescu, James A. Latshaw, Chad M. Spooner

Electrical & Computer Engineering Faculty Publications

This paper presents a novel deep-learning (DL)-based approach for classifying digitally modulated signals, which involves the use of capsule networks (CAPs) together with the cyclic cumulant (CC) features of the signals. These were blindly estimated using cyclostationary signal processing (CSP) and were then input into the CAP for training and classification. The classification performance and the generalization abilities of the proposed approach were tested using two distinct datasets that contained the same types of digitally modulated signals, but had distinct generation parameters. The results showed that the classification of digitally modulated signals using CAPs and CCs proposed in the paper …

Continuity Of Formal Power Series Products In Nonlinear Control Theory, W. Steven Gray, Mathias Palmstrøm, Alexander Schmeding

Electrical & Computer Engineering Faculty Publications

Formal power series products appear in nonlinear control theory when systems modeled by Chen–Fliess series are interconnected to form new systems. In fields like adaptive control and learning systems, the coefficients of these formal power series are estimated sequentially with real-time data. The main goal is to prove the continuity and analyticity of such products with respect to several natural (locally convex) topologies on spaces of locally convergent formal power series in order to establish foundational properties behind these technologies. In addition, it is shown that a transformation group central to describing the output feedback connection is in fact an …

A Survey Of Using Machine Learning In Iot Security And The Challenges Faced By Researchers, Khawlah M. Harahsheh, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The Internet of Things (IoT) has become more popular in the last 15 years as it has significantly improved and gained control in multiple fields. We are nowadays surrounded by billions of IoT devices that directly integrate with our lives, some of them are at the center of our homes, and others control sensitive data such as military fields, healthcare, and datacenters, among others. This popularity makes factories and companies compete to produce and develop many types of those devices without caring about how secure they are. On the other hand, IoT is considered a good insecure environment for cyber …

Ultra-Low Intensity Post-Pulse Affects Cellular Responses Caused By Nanosecond Pulsed Electric Fields, Kamal Asadipour, Carol Zhou, Vincent Yi, Stephen J. Beebe, Shu Xiao

Electrical & Computer Engineering Faculty Publications

High-intensity nanosecond pulse electric fields (nsPEF) can preferentially induce various effects, most notably regulated cell death and tumor elimination. These effects have almost exclusively been shown to be associated with nsPEF waveforms defined by pulse duration, rise time, amplitude (electric field), and pulse number. Other factors, such as low-intensity post-pulse waveform, have been completely overlooked. In this study, we show that post-pulse waveforms can alter the cell responses produced by the primary pulse waveform and can even elicit unique cellular responses, despite the primary pulse waveform being nearly identical. We employed two commonly used pulse generator designs, namely the Blumlein …