Operations Research, Systems Engineering and Industrial Engineering Commons^™

Research On Visual Place Recognition Algorithms For Complex Urban Environments, Peijin Liu, Minxin Zhang, Lin He, Yige Sun, Tingqi Su

Journal of System Simulation

Abstract: Dynamic factors such as traffic flow and crowd density in complex urban environments reduce the accuracy of visual place recognition (VPR) algorithms. To solve these problems, a semantic-guided visual place recognition (SG-VPR) algorithm was proposed. A semantic-guided feature suppression module was designed. A semantic-guided module and feature suppression layer were constructed to reduce the dynamic object interference and more accurately extract the key static features. An adaptive triplet margin loss function (ATML) was proposed by improving the traditional triplet margin loss. The margins were adaptively adjusted according to the sample distribution, solving the problem of suboptimal solution convergence …

Scenarioxp: A Complete Scenario–Based Testing Framework For The Exploration And Exploitation Of Autonomous Vehicle Validation Scenarios, Quentin Goss

Student Research Symposium (SRS)

Today is an age of exiting emerging technology where cutting-edge research in autonomous vehicles (AVs) reduces the active human participation in driving and extends awareness beyond human limitations of perception and reaction, improving driving safety and quality of the user experience as a result. The ever-increasing complexity of these autonomous systems poses many challenges towards the validation and verification (V\&V) of these complex systems under time and resource constraints, as the use of artificial intelligence and also the intricacy of the operating environment means that these systems are also black-box and non-deterministic. Scenario-based V\&V testing of such systems, which involves …

Ergonomics Of A Pilot Workstation And Aircraft Interactions On A Cessna 172 Nav Iii, Nicole Beaulieu

Student Research Symposium (SRS)

This study analyzes the ergonomic aspects of the Cessna 172 Navigator III, a common flight training aircraft. The research investigated the interactions between pilots and the aircraft, focusing on pilot fatigue, workstation design, anthropometric data, and pilot interactions with controls. The study included surveys, interviews, and anthropometric measurements involving three pilots with varying experience levels, alongside physical measurements of the cockpit and a workstation ergonomic assessment.. Participants reported issues with limited physical space, particularly impactful to the pilot’s posture and ability to manipulate controls. Display visibility and interaction were areas of concern, often requiring pilots to lean in awkward postures. …

Layer-Wise Printing Parameter Optimization For Laser Powder Bed Fusion, Chaoran Dou, Rongxuan Wang, Raghav Gnanasambandam, Jianzhi Li, Zhenyu James Kong

Manufacturing & Industrial Engineering Faculty Publications

Additive manufacturing (AM) is a transformative technology that enables the fabrication of complex geometries layer by layer. However, metal parts produced via AM processes such as laser powder bed fusion (LPBF) are prone to various defects, including porosity and deformation. These defects often result from suboptimal printing parameter settings. Traditional approaches typically aim to reduce defects by optimizing a fixed set of parameters for the entire part. However, such methods do not account for layer-wise variations in printing conditions caused by changes in geometry, heat transfer, and re-heating effects. While optimizing parameters for each layer could improve part quality, it …

Reinforcement Learning For Imbalanced Data In Robotic Anomaly Detection Within Autonomous Manufacturing, Salma Messaoudi, Ahmed Bendaouia, El Hassan Abdelwahed, Mohammed Ameksa, Hajar Mousannif, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

Ensuring reliable anomaly detection in industrial robots is critical for safe and autonomous manufacturing operations. However, it remains challenging due to temporal dependencies and class imbalance in sensor data. This study presents a reinforcement learning approach using Deep Q-Network (DQN) enhanced with Long Short-Term Memory (LSTM) and Gradient Boosting Machine (GBM) for robust anomaly detection in robotic systems. The proposed framework integrates an LSTM into the DQN policy to capture temporal patterns. It also introduces a novel GBM-based reward mechanism that mitigates class imbalance by applying SMOTE (Synthetic Minority Over-sampling Technique) after removing temporal dependencies. Experimental results demonstrate that this …

Research Of Logic Elements Based On Complementary Bipolar Transistors, Nodira Batirdjanovna Alimova, Nilufar Baxtiyorovna Gulyamova

Chemical Technology, Control and Management

Important parameters for any type of inverter – a NOT logic gate – are the power consumption during switching and the supply voltage. The proposed connection of complementary (two different types) bipolar transistors reduces the current consumption and supply voltage by simultaneously using the cutoff and saturation modes of the bipolar transistors. It has been theoretically and experimentally established that an inverter using complementary bipolar transistors operates at low supply voltages, approximately 0.7 V. Power consumption is virtually independent of the inverter's static state. A method for calculating the transfer characteristic of an inverter using complementary bipolar transistors is developed, …

Algorithms Of Stable Adaptive Observation Of A Multidimensional Undefinite Object, Tursunova Sadoqat Abdusalom Qizi

Chemical Technology, Control and Management

This article presents an algorithm for simultaneously estimating the parameters and state coordinates of a multidimensional control object when some of its state variables are not directly measured. The inability to measure all state variables (coordinates) of an object is a well-known drawback of identification schemes. Such conditions require the construction of adaptive state observers. This work demonstrates that when identifying the parameters of a mathematical model for an uncertain multidimensional object, the asymptotic stability of the object and the convergence of its parameters to the model parameters are ensured, provided the input vector is sufficiently informative. The construction of …

Analysis Of The Carbonization Process Of Ammoniated Brine In Ammonia-Soda Production, Nadirbek Rustambekovich Yusupbekov, Djalolitdin Paxritdinovich Mukhitdinov, Fotima Faxritdinovna Iskhakova

Chemical Technology, Control and Management

The work provides an analytical review of the current state of modeling and controlling the carbonization process of ammoniated brine. It analyzes modern methods of mathematical, simulation, and intelligent modeling of heat and mass transfer, hydrodynamics, carbonation kinetics, and crystallization. The paper considers the potential of using digital twins, neural network models, fuzzy logic devices, and hybrid models to improve forecasting accuracy and the adaptability of process solutions. Modern carbonation process control strategies are also considered. A detailed analysis is provided of predictive control (MPC), neuro-fuzzy controllers, decentralized and multivariate control systems that ensure stable column operation under disturbances, optimize …

Inductive Transducers For Measuring Vibrations, S.F. Amirov, A.Kh. Sulliev, A.A. Shoimkulov

Chemical Technology, Control and Management

A new design of an induction transducer has been developed for measuring linear and torsional vibrations in different directions with high sensitivity by constructing an inertial element consisting of four mutually perpendicular sectors and making the masses of two adjacent sectors different from the masses of the other two adjacent sectors. By constructing an inertial element in the form of a sector with two mutually diametric magnetic cores and different masses, and placing it between the horizontal and vertical axes, a design of an induction transducer has been developed that highly sensitively measures linear and torsional vibrations in different directions, …

The Main Errors Of The Ultrasonic Sensor In Measuring Water Flow In Open Channels, Anvar Urolovich Djalilov

Chemical Technology, Control and Management

This article analyzes the use of ultrasonic sensors in measuring water flow and the main errors that may occur in this process. In the conducted scientific research, a time-pulse ultrasonic sensor was tested. The absolute, relative and repeatability errors of the sensor during water flow measurement were studied. The absolute error represents the largest difference between the value recorded by the sensor and the real value, affecting the overall accuracy of the measurement system. This error can vary depending on environmental factors, the design and operating principles of the sensor. During the experiment, the performance of this sensor was …

Synthesis Of An Adaptive Synergistic Fuzzy Discrete Controller For Nonlinear Systems, Isamidin Xakimovich Sidikov, Gulruxsor Murot Qizi Nashvandova, Feruzakhon Botirxon Qizi Sodiqova

Chemical Technology, Control and Management

The paper considers the issues of synthesizing an adaptive fuzzy synergetic controller with discrete time for nonstationary nonlinear dynamic objects. The proposed approach is based on the integrated use of synergetic control principles and fuzzy logic methods, which ensure the formation of a control law for nonlinear dynamic objects that provides asymptotic stability of the control system. Such a hybrid combination makes it possible to guarantee the asymptotic stability of the closed-loop system and to shape the required dynamic behavior of the object over a wide range of operating modes. In addition, this approach provides the ability to adapt to …

Adaptive-Robust Control Of Dynamic Systems Using Generalized Predictive Methods, Shuxrat Tulyaganov

Chemical Technology, Control and Management

This paper considers an approach to adaptive-robust control of dynamic systems using generalized anticipation, where the object is described by a locally linearized model. Known self-tuning algorithms show insufficient stability to inaccurate selection of delay or model order. A generalized predictive control approach is suggested, with simulation outcomes showing superiority over traditional methods like generalized minimum variance control and pole assignment.This sliding horizon algorithm is based on predicting future system output signals several steps ahead, based on assumptions about subsequent control actions. One effective assumption is the presence of a “control horizon,” beyond which control signal increments are assumed to …

Review Of Modern Methods For Identification, Forecasting, And Intelligent Control Of Wastewater Biological Treatment Processes, Mirkhalil Agzamovich Ismailov, Boburbek Zokirjon O'G'Li Mannobjonov

Chemical Technology, Control and Management

This article presents a comprehensive review of contemporary approaches to the automation and intelligent control of wastewater biological treatment processes. Particular emphasis is placed on the digitalisation of wastewater treatment plants, ranging from the implementation of automated process control systems (APCS/SCADA-based solutions) to the application of predictive algorithms and the development of digital twins of bioreactors.

Special attention is devoted to mathematical models that underpin the control of bioprocesses. The evolution of the most widely used activated sludge models—ASM1, ASM2d, and ASM3—is examined, as these models describe key processes such as microbial community growth, nitrification, denitrification, and phosphorus removal. It …

A Knowledge Transfer-Based Membrane Evolutionary Algorithm For Solving Large-Scale Sorted Waste Collection Problem With Timeliness, Wenxue Zhang, Boquan Gao, Aldy Gunawan, Yunyun Niu, Jianhua Xiao

Research Collection School Of Computing and Information Systems

The sorted collection of municipal solid waste has emerged as an effective waste management strategy due to varying timeliness requirements across different waste types, giving rise to the critical research challenge of timeliness-based waste collection. While existing algorithms primarily focus on small-scale versions of this problem, solving large-scale timeliness-based waste collection problems remains particularly challenging. To tackle this issue, this paper proposes a knowledge transfer-based membrane evolutionary algorithm. Specifically, the original problem and simplified problem are constructed in different membranes respectively, and the knowledge transfer learning mechanism is incorporated into the membrane evolutionary algorithm, enabling effective information exchange between the …

A Unified Methodological Framework For Generating Digital Twins Of Multi Class Uncrewed Systems (Uxs), Sai Raghava Pathuri

Shelby Hall Graduate Research Forum Presentations

No abstract provided.

Modeling Advanced Complex And Evolutionary Systems Utilizing End-To-End (E2e) Mbse Framework, Joshua Adelabu

Shelby Hall Graduate Research Forum Posters

Modern Systems Engineering (SE) practices dearth full-cycle framework for next generation systems.

Ai Agent For Healthcare Education, Sudhanshu Tarale

Shelby Hall Graduate Research Forum Presentations

No abstract provided.

Conceptual Architecture For Digital Twin (Dt) In Disaster Response Applications, Sai Raghava Pathuri

Shelby Hall Graduate Research Forum Posters

Digital Twin Enabled Artificial Intelligence Uncrewed System (Model-Based Systems Engineering) Artificial Intelligence Digital Twin (DT)+Cyber Physical System. The goal was to create DTs of Multi Class UxS. The system of interest was the Uncrewed Ground Vehicle (UGV) and Uncrewed Aerial Vehicle (UAV). The modeling language used SysML v2.

Calibration Of Time-Domain Impedance Probe (Tdip) To Investigate Space Plasma Dynamics During Periods Of Ionospheric Instability, Piyas Chowdhury, Soumyajit Dey, Edmund A. Spencer

Shelby Hall Graduate Research Forum Posters

The traditional Plasma Impedance Probe (PIP) is popular for diagnosing parameters of the ionospheric plasma to study the space environment. However, the resolution of data measurements of existing PIP instruments, operating at higher frequencies, limits the analysis to studying the plasma features at electron scales. Studying plasma ion parameters is essential to understanding the ionospheric instability growth rates. This can only be accomplished by operating a diagnosing instrument at lower frequencies corresponding to ion scales. A recently developed Time Domain Impedance Probe (TDIP) is implementable for fast moving spacecraft using a time domain approach. The instrument has higher measurement resolution …

Ai Driven Assessment For Clinical Scenarios, Sudhanshu Tarale, Bhushan Lohar, Ninad Pandit

Shelby Hall Graduate Research Forum Posters

Beta 1 captured granular data to validate the system’s ability to measure clinical thoroughness and deliver real-time feedback. Data collection formally approved by the USA IRB (Protocol 25 037; #22849172).