Operations Research, Systems Engineering and Industrial Engineering Commons^™

Cyber Forensics With Deep Learning Recurrent Neural Networks, Pfautch Ric, Dagli Cihan, Ashiku Lirim

Engineering Management and Systems Engineering Faculty Research & Creative Works

Detection of anomalies and anti-patterns is essential for adaptive systems with the ability to perform without foreknowledge. Some problems require both classification and regression along with sensitivity tuning and explainability. Some have highly dimensional datasets that are time dependent. This research offers results for Long-Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) algorithms using the BETH dataset. It unpacks metadata attributes and stages a unique approach via Abstract-Feature Analysis (AFA), hyper parameter tuning, and Principal Component Analysis (PCA) within the RNN model. By removing foreknowledge, this research offers insights into RNN anomaly detection performance when an event absent in training …

A Comprehensive Academic And Industrial Survey Of Blockchain Technology For The Energy Sector Using Fuzzy Einstein Decision-Making, Umit Cali, Annabelle Lee, Barry Hayes, Claudio Lima, D. Jonathan Sebastian-Cardenas, David Flynn, Emre Kantar, Farrokh Rahimi, Kaung Si Thu, Marco Pasetti, Marthe Fogstad Dynge, Merlinda Andoni, Muhammet Deveci, Murat Kuzlu, Raquel Alanso, Kim-Kwang Raymond Choo, Sambeet Mishra, Shammya Shananda Saha, Sonam Norbu, Srinikhil Gourisetti, Ugur Halden, Vahid Hosseinezhad, Valentin Robu

Engineering Technology Faculty Publications

The global energy sector is undergoing a significant transformation driven by decarbonization and digitalization, leading to the emergence of Distributed Ledger Technology (DLT) — particularly blockchain — as a promising tool for enhancing transparency, security, and efficiency in modern power systems. This study aims to provide a comprehensive academic and industrial survey of blockchain applications in the energy sector and develop a robust decision-making framework to identify and prioritize the most promising real-world use cases based on multidisciplinary criteria. A three-stage methodology was adopted: (i) a literature and market review encompassing over 300 academic publications and commercial blockchain initiatives in …

Multiphysics Modeling Of Solid Oxide Fuel Cells For Gradient Minimization And Inductive Loop Analysis In Impedance Spectroscopy Using Machine Learning-Based Microstructural Property Estimation, Muhammad Usman Khan

College of Graduate Studies: Theses & Dissertations

Solid oxide fuel cells have significant advantages in renewable energy utilization due to their high efficiency, fuel flexibility, and low emissions. However, despite the numerous efforts of technology, thermal and current density gradients and impedance behavior fluctuations are still causing performance degradation. A combined computational framework that integrates machine learning and three-dimensional Multiphysics modeling is needed to investigate and optimize the performance of solid oxide fuel cells. A machine learning model, trained on synthetic microstructure data by percolation analysis, is used to predict important microstructural parameters like triple phase boundary density and geometric tortuosity. These are then employed in a …

Out Of Order And Causally Correct: Ready-Event Discovery Through Data-Dependence Analysis, Erik John Jensen, James Leathrum Jr., Christopher Lynch, Katherine Smith, Ross Gore

Electrical & Computer Engineering Faculty Publications

Data-dependence analysis can identify causally-unordered events in a pending event set. The execution of these events is independent from all other scheduled events, making them ready for execution. These events can be executed out of order or in parallel. This approach may find and utilize more parallelism than spatial-decomposition parallelization methods, which are limited by the number of subdomains and by synchronization methods. This work provides formal definitions that use data-dependence analysis to find causally-unordered events and uses these definitions to measure parallelism in several discrete-event simulation models. A variant of the event-graph formalism is proposed, which assists with identifying …

Input Independent Observers For Bilinear Systems Using Convex Optimization, M. Aminul Haq, W. Steven Gray

Electrical & Computer Engineering Faculty Publications

An asymptotic state variable observer is proposed for a continuous-time bilinear dynamical system with the distinguishing feature that the error dynamics are globally asymptotically stable and independent of the applied input. Only the speed of convergence of the error dynamics may be input dependent. The approach is to apply classical Lyapunov stability theory using a convex optimization algorithm and linear matrix inequality (LMI) tools to in effect isolate the stability property of the error dynamics from the input. The LMIs are used to turn the nonconvex problem into a convex problem. The method is demonstrated on an induction motor drive.

Age Of Information-Based Optimal Scheduling With Energy Cost Trade-Off For Smart Warehouse: A Deep Reinforcement Learning-Based Approach, Sandip Roy, Abhishek Bisht, Ashok Kumar Das, Sachin Shetty

VMASC Publications

Recent advances in the integration of high-speed mobile networks and real-time IoT devices have facilitated in building of smart warehouses, where a set of beacons and Internet of Things (IoT) devices (or source nodes) can monitor the status of various physical processes in a time-critical way. In real-time status monitoring systems, like smart warehouses, quantifying the freshness of the Internet of Things (IoT) data based on the age of information (AoI) metrics becomes quite crucial. As source nodes are battery-constrained, a balanced trade-off between AoI minimization and preservation of source node battery energy is essential. In this paper, in a …

Cognitive Fatigue Detection Using Photoplethysmography (Ppg) And Reaction Time Data, Anhar Sami Mohammed, Prajoy Podder, Maciej Jan Zawodniok, Cihan Dagli

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a framework for real-time cognitive fatigue detection among shift workers using an integrated approach that combines photoplethysmography (PPG) data and reaction time analysis with advanced deep learning models, including Long Short-Term Memory (LSTM) networks and Feedforward Neural Networks (FNNs). The system leverages heart rate variability (HRV) and reaction time data to identify fatigue indicators. The results demonstrate significant performance, with the first FNN model achieving a test accuracy of 98.94% and a loss of 0.2928, while the second FNN model achieved the same accuracy with a slightly higher loss of 0.3089. The LSTM model, designed for sequential …

Improving System-Level Outcomes Via Artificial Intelligence Decision Support In Kidney Utilization, Casey I. Canfield, Cihan H. Dagli, Daniel Burton Shank, Krista Lentine, Mark Schnitzler, Henry Randall, V. Sriram Siddhardh Nadendla, Brendon Cummiskey

Engineering Management and Systems Engineering Faculty Research & Creative Works

Transplantation provides patients suffering from end-stage kidney disease a better quality of life and long-term survival. However, over 20% of deceased donor kidneys are not utilized and never transplanted. While this is sometimes medically appropriate, this also reflects missed opportunities. We are designing Artificial Intelligence decision support for the kidney offer process to support both demand at the transplant center and supply at the organ procurement organization. This includes (1) developing deep learning models, (2) evaluating the effect of explainable interfaces, (3) improving fairness in the model output, (4) identifying factors that influence adoption decisions, and (5) conducting a randomized …

Model Reference Adaptive Control For Mobile Manipulators And Beyond, Srivatsan Srinivasan

All Dissertations

In recent years, robotics has expanded into various sectors, including manufacturing, transportation, and household services, making the integration of autonomy a critical area of research. This shift aims to ensure safety and enhance the utility of autonomous systems. Traditionally, robotic applications focused separately on mobility, like automated guided vehicles, and manipulation, such as serial-chain arms in manufacturing. Today, however, we see a merging of these capabilities in the growing field of mobile manipulator robots that combine movement with purposeful interactive functionalities.

A typical mobile manipulator is a robotic arm mounted on a wheeled base. This thesis focuses on advancing control …

Security Of Mobile Radiological Sources: Overview Of Industry Applied Technologies, Ann M. Archer, Ashleigh Wickham

International Journal of Nuclear Security

Small radiological sources used in industrial settings recurrently require transit between job sites. Securing these sources, while stationary, can be addressed with standard security approaches and equipment. Transport of these sources increases the risk and complexity of managing and maintaining control of these sources. Implementing methodologies to securely monitor and locate sources improves response and resolution of anomalous events during transit. The Mobile Source Transit Security (MSTS) system was developed to improve security and provide situational awareness of these mobile sources throughout their job cycle. The MSTS development effort focused on creating a set of systems that could be successfully …

Motivating Sustainability Through The State Of Biologically Inspired Design, Bryan Watson

Sustainability Conference

There are multiple arguements for sustainability, but one that resonates with environmentalists and the public alike is the need for preservation to all us to discovery natural solutions to our problems. Common examples often given include medical discoveries, unique mechanisms, and new materials. This presentation focuses on two ideas to motivate sustainability. First, what is the current state of biologically inspired design? Is there more to learn from nature? To answer these questions, recent research is presented which examined 660 Biologically Inspired Design samples from three data sources: Google Scholar, Google News, and the Asknature.org “Innovations” database. The data were …

Strategies To Alleviate Flickering: Bayesian And Smoothing Methods For Deep Learning Classification In Video, Noah Miller, Glen Ryan Drumm, Lance Champagne, Bruce A. Cox, Trevor Bihl

Faculty Publications

Excerpt: Increasing reliance on autonomous systems requires confidence in the accuracies produced from computer vision classification algorithms. Computer vision (CV) for video classification provides phenomenal abilities, but it often suffers from “flickering” of results. Flickering occurs when the CV algorithm switches between declared classes over successive frames. Such behavior causes a loss of trust and confidence in their operations.

Enhancing Resilience In Complex Energy Systems Through Real-Time Anomaly Detection: A Systematic Literature Review, Ali Aghazadeh Ardebili, Oussama Hasidi, Ahmed Bendaouia, Adem Khalil, Sabri Khalil, Dalila Luceri, El Hassan Abdelwahed, Sara Qassimi, Antonio Ficarella

Manufacturing & Industrial Engineering Faculty Publications

As real-time data sources expand, the need for detecting anomalies in streaming data becomes increasingly critical for cutting edge data-driven applications. Real-time anomaly detection faces various challenges, requiring automated systems that adapt continuously to evolving data patterns due to the impracticality of human intervention. This study focuses on energy systems (ES), critical infrastructures vulnerable to disruptions from natural disasters, cyber attacks, equipment failures, or human errors, leading to power outages, financial losses, and risks to other sectors. Early anomaly detection ensures energy supply continuity, minimizing disruption impacts, an enhancing system resilience against cyber threats. A systematic literature review (SLR) is …

Utilizing Deep Learning In Smart Glass System To Assist The Blind And Visually Impaired, Asmaa A. Hekal, Mohamed S. Sharaf, Ahmed A. Sayed, Ibrahim R. Abdelrahman, Ahmed A. Salem, Ahmed M. Elhussieny, Saeed Y. Kouta, Eman S. Abass

Future Engineering Journal

This paper presents a groundbreaking assistive technology designed to empower visually impaired individuals in their daily lives. With an estimated global population of 2.2 billion facing visual impairments, addressing the challenges they encounter is of paramount importance. The research introduces a comprehensive electronic device integrating advanced computer vision and deep learning techniques. The system incorporates real-time object detection, robust facial recognition, and precise currency denomination identification. Powered by a Raspberry Pi 4 Model B+ and an ESP32-CAM Development Board, the device offers users unparalleled environmental awareness. Utilizing YOLOv4-tiny for object detection and a hybrid face recognition model combining HaarCascades, Histogram …

An Analysis Of Electrical Energy Resilience Technologies As Applied To Air Force Operations, Eric D. Danko

Theses and Dissertations

An analysis of 46 Resilient Energy Devices and Technology Concepts was conducted to determine their suitability for use in supporting Air Force Operations both at home station and abroad. The research consisted of two endeavors: an extensive literature review and a rank-ordering matrix. The dual nature of the efforts was designed to maximize usability and understanding for the End User, who may not be familiar with some principles of energy technologies, resilience, or design. The results showed the superiority of novel Solid (Metal) Fuels and Lead-Acid Batteries for Energy Storage and Thermoelectric Generators, Solar Photovoltaic Panels, Geothermal Extraction, Diesel Generators, …

Investigation Of The Parameters Of Semicylindrical Capacitive Sensor, Erkin Uljaev, Elyor Faxriddinovich Khudoyberdiev, Shohrukh Nurali O‘G‘Li Narzullayev

Chemical Technology, Control and Management

This study introduces a semicylindrical capacitive sensor, featuring an internal dielectric insulator, designed to measure moisture levels in bulk and other materials while in motion. The research employs numerical analysis to explore the sensor's capacitance variation and evaluate its performance. The change in capacitance of the semicylindrical capacitive sensor in the picofarad range is easily converted into a change in the frequency of the generator, which is implemented on an operational amplifier with feedback. The generator circuit is quite compact, and its output can be connected directly to the discrete input of a microcontroller without a matching element. Using the …

Experimental Study Of The Ultrasonic Extraction Process Of Plant Raw Materials, Azamat Bakir Ogli Usenov, Doston Ishmuxammat Ogli Samandarov, Qobil Akmal Ogli Mukhiddinov, Jasur Esirgapovich Safarov Dcs

Chemical Technology, Control and Management

In-depth scientific research is being conducted around the world aimed at developing the scientific and methodological foundations of energy-saving extractors, processing medicinal plants, increasing the efficiency of modern technologies, processes and equipment for obtaining high-quality pharmaceutical raw materials rich in biologically active substances. Energy-saving extractors, developed in conjunction with the extraction process of medicinal plants, are introduced into the industry using scientifically proven technology. At the global level, special attention is paid to the creation of intelligent designs of innovative extraction plants that operate using ultrasonic waves, allowing the extraction of medicinal components of plants.

Clustering Algorithm Based On Similarity Of Objects, Akhram Khasanovich Nishanov, Alisher Tulkunovich Tursunov, Fayzullo Farhod O'G'Li Ollamberganov

Chemical Technology, Control and Management

The article discusses the problem of drug clustering. Initially, k classes are randomly formed and the resulting training sample is preprocessed, then the similarity between objects of each class is assessed based on the proximity function and the criterion for assessing the contribution of objects to the formation of their own class. It is usually expressed as a percentage and represents the degree of mutual similarity of objects of each class. In the next steps of the algorithm, first one object is taken from the first class and by adding it to all k classes, the contribution of this object …

Capacitive Sensors With Ultra-Small Capacitance For Smart Measurement And Control Systems, Rustam Baratov, Farrux Jabbor O'G'Li Ko'charov

Chemical Technology, Control and Management

This article discusses methods of low capacitance measurement of capacitive sensors. The results of the study of the amplitude-frequency (AF) and phase-frequency (PF) response of measurement circuits of capacitive sensors for low capacitances measurement, consisting of RC - differentiating elements are presented. The input and output parameters of the differentiating circuit and the complex transfer function are analyzed. The research results show that low capacitances measurement by measuring the rectangular pulses duration is the most effective measurement method.

Developing Decision-Making Models And Algorithms To Help Prevent Emergencies, Mizaakbar Xakkulmirzayevich Hudayberdiyev, Oybek Zokirovich Koraboshev

Chemical Technology, Control and Management

The article is devoted to the solution of the scientific issue of decision-making support for the prevention and elimination of the consequences of emergency situations. The relevance of this issue is related to the need to develop a theoretical basis for optimizing the risk of adverse effects on human health and the environment in connection with emergency situations, and a predictive model for the development of emergency situations and their prevention or elimination of their consequences. The optimization of the importance measure of signs for predicting the values of the factors of fire conditions has been carried out. In addition, …

Mathematical Modelling Of The Solar Drying Of Apricot, Sarvar Rejabov, Botir Shukurillayevich Usmonov, Asqar Artikov, Komil Usmanov

Chemical Technology, Control and Management

Agricultural products provide significant growth in export earnings for many countries and provide food globally. Fruits and vegetables are perishable foods due to their high moisture content. Therefore, most agricultural products require post-harvest processing such as drying to extend the shelf life of fruits and vegetables and maintain nutrient quality. Solar drying is widely used for this purpose. Ambient temperature, humidity and solar radiation affect the drying time and quality of agricultural products, especially apricots, in solar dryers. The experiments were carried out in the same place (Tashkent, Uzbekistan) and in the same time interval. When the mass of apricots …

Investigations Of Cell Tower Antennas Parameters On Reduction Of Radio Frequency Radiation Levels From Radio Base Stations, Florence U. Rashidi

Tanzania Journal of Engineering and Technology (TJET)

The widespread deployment of mobile cellular base stations in populated areas has raised public health concerns due to increased exposure to radio frequency (RF) radiation emissions. Exposure to high levels of RF radiation can have potential thermal and non-thermal biological effects. Optimizing the configuration of cell tower antenna parameters is crucial for mitigating these radiation levels. This study therefore aims at systematically investigating the influence of different cell tower antenna parameters on reducing the RF radiation levels from mobile base stations. Field measurements were conducted at two cell sites shared by multiple mobile operators. Electric field strengths were measured at …

Evaluation Of Business-Driven Reference Architecture For Big Data Analytics Implementation By Public Sector Organizations In Resource-Constrained Setting: A Case Study Of Uganda, Matendo Didas

Tanzania Journal of Engineering and Technology (TJET)

Big Data Analytics (BDA) is a new area at the nexus of agenda, public sector organizations, and government business. It may satisfy the growing need for trustworthy, cost-effective services in the public sector for better, more informed decision-making processes. BDA has been proposed on the planning schedules of several public sector organizations and the government. Therefore, from the previous work, using Uganda as a case study, specifically the Uganda Bureau of Statistics (UBOS), Ministry of Health (MoH), and Ministry of Education and Sports (MoES), this study aims to evaluate a designed Business-Driven Reference Architecture for Big Data Analytics Implementation (BRABDAI) …

Assessment Of The Factors Affecting The National Ict Broadband Backbone (Nictbb) Systems Restoration Time, Victoria Mahabi

Tanzania Journal of Engineering and Technology (TJET)

This study investigates the factors affecting the prolonged system restoration time when national ICT broadband backbone (NICTBB) services are affected by breakdown incidents. NICTBB is the government-owned backbone infrastructure constructed nationally by the Republic of Tanzania to increase the usage of ICT for equitable and sustainable socio-economic development and accelerate poverty reduction. This study utilised a mixture of exploratory and descriptive study approaches. The sample size determination was executed using purposing and simple random sampling, thus involving 289 respondents. The data reliability test was undertaken. It was followed by factor analysis, analysis of variances (ANOVA), linear regression analysis, and confirmed …

Necessity Of Education For Efficient And Sustainable Production And Consumption Of Energy In Tanzania, George Kahangwa

Tanzania Journal of Engineering and Technology (TJET)

This paper reports the findings of a study that was conducted in Tanzania to grasp how the policies, plans and curricula at different levels of education accommodate knowledge gathered on energy to support the fostering of energy education. The study interrogated what necessitates the inclusion of energy education into the curricula in Tanzania. Subscribing to a qualitative approach, the study employed a desk research method to review curricula and other documents guiding secondary and university level education in the country. The study found out that heightening people’s consumption of energy for domestic and industrial purposes constituted the main issue that …

Authenticated Diagnosing Of Covid-19 Using Deep Learning-Based Ct Image Encryption Approach, Mohamed Attia Abdelgwad, Amira Hassan Abed, Mahmoud Bahloul

Future Computing and Informatics Journal

Researchers are motivated to use artificial intelligence in biometrics, medical imaging encryption, as well as cybersecurity due to its rapid progress. An encryption method for CT scans—which are used to diagnose COVID-19 disease—is proposed in this study. The suggested encryption method creates a connection among an individual's face picture and CT image to increase confidentiality. The simple CT picture is first enhanced with a host image. An encryption key is multiplied by the final result. This key is produced by applying a Convolutional Neural Network (CNN) to recognize characteristics from people's face photographs. Additionally, a straightforward CNN with three convolutional …

Algorithms And Models For Synthesis Of Elements Of Digital Information Systems, Odil Abdujalilovich Jumaev, M.T. Ismoilov, V.B. Pulatov, G.X. Rashidov

Chemical Technology, Control and Management

The development of algorithms for noise-tolerant and high-speed measurement systems involves an integrated approach that encompasses methods of data processing and transmission, as well as mechanisms for rapid response to changes. This paper presents the key principles and techniques used in such technologies. The information systems are thoroughly analyzed, including the use of signal processing techniques and their identification, filtering using various statistical techniques to determine signal parameters and the development of algorithms to analyze and classify signals. Critical aspects of the system such as performance, reliability, security and scalability are also evaluated. The paper discusses information system structures and …

Ultrasonic Flow Meter Calibration Via The Internet Using An Analog-To-Digital Converter, Aliev Ravshan, A.U. Djalilov

Chemical Technology, Control and Management

The purpose of scientific research work is remote control of improving the metrological properties of the water flow measuring device. Therefore, the Arduino platform with an additional ESP8266 NodeMcu v3 and analog-to-digital converter, module was installed in the scientific article for automatic calibration/checking of ultrasonic flow meters used in irrigation networks. The module is integrated into a 32-bit microcontroller with low power consumption. The ESP8266 NodeMcu v3 module operates at 80 and 160 MHz clock frequencies, supports real-time operating system (RTOS), built-in Wi-Fi, and has a microstrip antenna on board. Through this, the data exchange between the computing equipment and …

Research Of The Fuzzy Control System For Adjusting Thread Tension During The Warping Process, To'xtamurod Hayitmurodovich Avezov, Zokhid Ergashboyevich Iskandarov

Chemical Technology, Control and Management

The paper considered issues of research into a fuzzy control system for the warping process. During the warping process, the reasons that cause defects in the final finished product have been studied, firstly (remove this word) which are thread breakage, thread tangling, the formation of loops on or under the belt, hanging loose threads and similar factors. To study the warping process, its mathematical model is constructed. Kinematic parameters of stationary movement corresponding to the equilibrium mode were determined by solving the nonlinear functional matrix - equation of movement. The process of breakage the warp of the threads under oscillation …

Research Of A New Technological Flowsheet Parameters For Uranium Mining From Technogenic Uranium Ores, Nazarov Jamol, G.M. Allaberganova, H.L. Pulatov, A.M. Muzafarov

Chemical Technology, Control and Management

This paper presents the results of a study of the parameters of a new technological scheme for the extraction of uranium from technogenic uranium ores. The results of the analytical determination of the concentration of parent - ²³⁸U and daughter radionuclides - ²³⁴U , ²³⁰Th , ²²⁶Ra , ²²²Rn , ²¹⁸Pa , ²¹⁴Pb , etc. are presented . in the studied technogenic uranium ores. The principal scheme of the new uranium extraction technology from technogenic uranium ores is presented. The use of the classifier in a new scheme for separating granules of technogenic …