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Articles 211 - 240 of 756
Full-Text Articles in Industrial Technology
Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston
Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston
Theses and Dissertations
Studies have shown a connection between early catastrophic engine failures with microtexture regions (MTRs) of a specific size and orientation on the titanium metal engine components. The MTRs can be identified through the use of Electron Backscatter Diffraction (EBSD) however doing so is costly and requires destruction of the metal component being tested. A new methodology of characterizing MTRs is needed to properly evaluate the reliability of engine components on live aircraft. The Air Force Research Lab Materials Directorate (AFRL/RX) proposed a solution of supplementing EBSD with two non-destructive modalities, Eddy Current Testing (ECT) and Scanning Acoustic Microscopy (SAM). Doing …
Model For Calculating The Static Characteristics Of Hydraulic Systems Of Hydro Technical Buildings, Mirkhalil Ismailov, Dong Zhang, Farkhod Kasimov
Model For Calculating The Static Characteristics Of Hydraulic Systems Of Hydro Technical Buildings, Mirkhalil Ismailov, Dong Zhang, Farkhod Kasimov
Chemical Technology, Control and Management
Hydraulic mechanisms that actuate flat gates, widely used in hydraulic structures, are studied as hydraulic actuators of the system. Their static mathematical models are developed using an integrated methodology with a hydraulic pump, inlet and suction pipes, and internal and external resistance factors. Unlike existing mathematical models, the model developed in this paper allows a detailed description of the characteristics of hydraulic drives due to the fact that pressure losses in the throttle, regulator, and power amplifier, as well as local resistances in hydraulic pipelines, are taken into account.
Synchronization Of The Training Of Specialists In The Automation Of Technological Processes In Accordance With The Dynamics Of The Taxonomy Of Learning Goals, Yusuf Shodievich Avazov, Kamola Abdullaeva
Synchronization Of The Training Of Specialists In The Automation Of Technological Processes In Accordance With The Dynamics Of The Taxonomy Of Learning Goals, Yusuf Shodievich Avazov, Kamola Abdullaeva
Chemical Technology, Control and Management
Changes in the characteristics of modern ones, reflecting them as the "digital generation", inevitably necessitate electronic interactive, mobile and mixed, machine learning, especially in the field of automation and control of technological processes and production. As a consequence of reflecting these realities, there have been parallel changes in the taxonomy of learning objectives - from the classical to the revised rethought and digital.
In order to study the problem of synchronizing the training of future specialists in the field of automation and control of technological processes and production and funny knowledge in accordance with the dynamics of the taxonomy of …
Analysis Of Vegetable Oil Refining Technology, Elyor Samadov
Analysis Of Vegetable Oil Refining Technology, Elyor Samadov
Chemical Technology, Control and Management
Innovative technologies for refining vegetable oils are presented, as well as the qualitative characteristics of raw vegetable oils obtained by extraction and mechanical methods. A general review of the chemical composition and impurities of vegetable oils resulting from the reaction between glycerol and fatty acids is carried out, and a brief review of the study to determine the effect of refining on biologically active components.
The analytical review is devoted to a comparative comparison of two types of refining - chemical and physical refining.
Research Of Three-Phases Current’S Transducers Of Filter-Compensation Devices For Control Reactive Power’S Consumption Of Asynchronous Motor, Ilkhomjon Khakimovich Siddikov, Dilyorbek Karimjonov Doniyorbek O'G'Li -, Abdumutal Abdikarimovich Abdigapirov
Research Of Three-Phases Current’S Transducers Of Filter-Compensation Devices For Control Reactive Power’S Consumption Of Asynchronous Motor, Ilkhomjon Khakimovich Siddikov, Dilyorbek Karimjonov Doniyorbek O'G'Li -, Abdumutal Abdikarimovich Abdigapirov
Chemical Technology, Control and Management
In the article given materials of developing of three-phase electromagnetic current transducers of reactive power, using with asynchronous motor, methods connecting of two sensing element, series, parallel and differential and loops suitable for each phase, dynamic characteristics of output signals of three-phase electromagnetic current transducers asynchronous motor.
On the basis of modern calculation and design complexes are of great importance in the research variable sizes of three-phase current electromagnetic transducers of filter-compensation devices of reactive power of asynchronous motors. Presented mathematical model of research of electrical, electromagnetic and magnetic elements of electromagnetic current transducers in the …
Modeling Of The Process Of Measuring Conversion Of The Flow Of Liquid And Gaseous Media By The Method Of Variable Pressure Drop, Shukhrat Manapovich Gulyamov, Elbek Elmirza O'G'Li Ortiqov
Modeling Of The Process Of Measuring Conversion Of The Flow Of Liquid And Gaseous Media By The Method Of Variable Pressure Drop, Shukhrat Manapovich Gulyamov, Elbek Elmirza O'G'Li Ortiqov
Chemical Technology, Control and Management
On the basis of material and heat balances, taking into account the initial and boundary conditions, a mathematical model of the process of measuring the transformation of liquid and gaseous technological media by the method of variable pressure drop is constructed. The analysis of the results of studying the influence of non-stationary flows of a controlled medium on the uncertainty of the results of measuring the flow rate of liquids and gaseous mixtures with a changing hydrodynamic structure of the flow of a controlled medium is performed. A comparative analysis of the calculated and experimental transient processes in the measuring …
Virtual Potassium Chloride Analyzer In The System Of Advanced Control Of Potash Fertilizer Production Processes, Umidjon Ruziev, Jahongir Sherboyevich Bekqulov
Virtual Potassium Chloride Analyzer In The System Of Advanced Control Of Potash Fertilizer Production Processes, Umidjon Ruziev, Jahongir Sherboyevich Bekqulov
Chemical Technology, Control and Management
It is proposed to include virtual instrumental quality analyzers of potash fertilizers in the composition of the advanced (advanced) management system. The structure of the virtual analyzer is substantiated using mathematical models of the technological process of drying potassium chloride in its composition. Based on the results of fuzzy clustering, the parameters of the modes of the technological process of drying potassium chloride are determined.
Influence Of Magnetomechanical Properties Of Ferromagnetic Materials On The Sensitivity Of A Magnetoelastic Sensor, Sulton Amirov, Kamila Komilovna Jurayeva
Influence Of Magnetomechanical Properties Of Ferromagnetic Materials On The Sensitivity Of A Magnetoelastic Sensor, Sulton Amirov, Kamila Komilovna Jurayeva
Chemical Technology, Control and Management
The requirements of high operational reliability are most fully met by automated monitoring and control systems, the elements of which are magnetoelastic sensors. Such sensors, due to their metrological characteristics, have found application in electrified railway transport, in the metallurgical, metalworking, mining and other industries. The principle of operation of such sensors is based on the fact that in the process of influencing the magnetic core of the sensor by force, there is a change in the magnetic permeability of the material, a change in the magnetic resistance of the circuit, a change in the mutual inductance coefficient of the …
Algorithmic Methods For Developing The Structure Of A Thyristor Electric Drive For Mining Machines, N.R Yusupbekov, O.A. Jumaev, S.S. Turaev
Algorithmic Methods For Developing The Structure Of A Thyristor Electric Drive For Mining Machines, N.R Yusupbekov, O.A. Jumaev, S.S. Turaev
Chemical Technology, Control and Management
The article discusses the creation of algorithmic structures and the development of digital control systems for electric drives of mine-lifting machines, provides some concepts for creating digital control systems using thyristor converters. The analysis of the static volt-ampere characteristics of the thyristor is given, some calculations of the circuits and circuits of the thyristor converter (TP) corresponding to the different modes of operation of the TP are given, and also, based on the synthesis of the dynamic properties and characteristics of the thyristor, an algorithmic structure of the model of the thyristor converter is proposed.
Algorithms For Multi-Factory Polynomial Modeling Of Technological Processes, Farrukh Do'stmirzayevich Jo'rayev, Murodjon Ashurqulovich Ochilov
Algorithms For Multi-Factory Polynomial Modeling Of Technological Processes, Farrukh Do'stmirzayevich Jo'rayev, Murodjon Ashurqulovich Ochilov
Chemical Technology, Control and Management
The article reveals the meaning and essence of the modeling method in the study of complex technological processes based on the problematic aspects of building multifactorial relationships and the principles for their elimination. In the case of non-linearity of multifactorial connections of a complex system, the expediency of approximating such functions by polynomials is substantiated. The authors' ideas about the increasing importance of interpolation methods in practice against the background of the possibility of simplification based on the use of modern mathematical hardware and software for integration into the process of modeling and optimizing technological processes due to the complexity …
Structural Model Of The Technological Process Of Storage And Processing Of Oil Raw Materials, N.A Kabulov
Structural Model Of The Technological Process Of Storage And Processing Of Oil Raw Materials, N.A Kabulov
Chemical Technology, Control and Management
The technological method of storing and processing oilseed raw materials is structurally modelled in the article. Additionally, it is suggested that the generalized structure be presented as a three-part scheme, consisting of a raw material department, a processing shop, and transportation networks. On the basis of a thorough examination of the characteristics of the constituent parts of the technological complex, a practical model for the problem of the general characteristics of the technological complex is proposed.
The Future Of Enterprise Information Systems, Ali Sunyaev, Tobias Dehling, Susanne Strahringer, Li Da Xu, Martin Heinig, Michael Perscheid, Rainer Alt, Matti Rossi
The Future Of Enterprise Information Systems, Ali Sunyaev, Tobias Dehling, Susanne Strahringer, Li Da Xu, Martin Heinig, Michael Perscheid, Rainer Alt, Matti Rossi
Information Technology & Decision Sciences Faculty Publications
[First paragraph] Enterprise information systems (EIS) have been important enablers of crossfunctional processes within businesses since the 1990s. Often referred to as enterprise resource planning (ERP) systems, they were extended in line with electronic businesses to integrate with suppliers as well as customers. Today, EIS architectures comprise not only ERP, supply chain, and customer relationship management systems, but also business intelligence and analytics. Recently, the move towards decentralized technologies has created new perspectives for EIS. Information systems (IS) research has already addressed opportunities and challenges of these developments quite well, but what will be the pressing opportunities and challenges for …
Generalizable And Adaptable Data-Driven Methods For Overcoming Barriers To Practical Industrial Condition Monitoring, Matthew B. Russell
Generalizable And Adaptable Data-Driven Methods For Overcoming Barriers To Practical Industrial Condition Monitoring, Matthew B. Russell
Theses and Dissertations--Electrical and Computer Engineering
The future of smart manufacturing relies on predictive maintenance systems that intelligently minimize expensive downtime through timely assessment of machine condition. Deep Learning (DL) has achieved excellent performance in industrial condition monitoring experiments, but the constraints of the manufacturing environment prevent many algorithms from being practically deployed on the factory floor. Ubiquitous sensing from online machines generates high velocity data streams that require new techniques for efficient transmission and storage. Despite these ever-increasing data lakes, many applications still lack the data needed for training DL fault diagnosis and wear tracking models since most data is unlabeled and only from nominal …
An Unmanned Aircraft System For Marking Live Power Lines To Prevent Bird Collisions, Mattheuns D. Pretorius, Lourens Leeuwner, Kaajial Durgapersad, Constant Hoogstad, Peter Beckedahl, Michael D. Michael, Kishaylin Chetty
An Unmanned Aircraft System For Marking Live Power Lines To Prevent Bird Collisions, Mattheuns D. Pretorius, Lourens Leeuwner, Kaajial Durgapersad, Constant Hoogstad, Peter Beckedahl, Michael D. Michael, Kishaylin Chetty
Human–Wildlife Interactions
Collisions with overhead power lines represent a significant cause of mortality for a number of large bird species worldwide. Certain threatened species are severely impacted by power line collisions, particularly those for which there are no other known significant threats. In South Africa, bird collisions with overhead power line cables, including collisions with phase conductors and shield wires, contribute significantly to annual threatened bird species mortalities associated with Eskom power lines. The most practical mitigation measure is to attach bird anti-collision devices as markers on the cables. Current marking methods involve installations by hand, where linemen are hoisted up to …
Evaluating Electrification Of Fossil Fuel-Fired Boilers For Decarbonization Using Discrete Event Simulation, Nahian Ismail Chowdhury
Evaluating Electrification Of Fossil Fuel-Fired Boilers For Decarbonization Using Discrete Event Simulation, Nahian Ismail Chowdhury
Graduate Theses, Dissertations, and Problem Reports (ETD)
Decarbonizing fossil fuel usage is crucial in mitigating the impacts of climate change. CO2, which comprises the major portion of greenhouse gas, is emitted from burning fossil fuels. One of the significant sources of fossil fuel user is industrial process heating, and most of the heating in industrial processes is achieved through boilers. Electrification is a promising solution for decarbonizing these boilers, as it enables renewable energy sources to generate electricity, which can then be used to power the electric boilers. The electrification of boilers can reduce greenhouse gas emissions, improve air quality, and increase energy efficiency. However, it requires …
Ex-Ante Cost-Benefit Analysis Of High-End And Low-Cost Wireless Sensor Network (Wsn) Technology Packages For Efficient Irrigation Water Management In The Philippines, Marielle Q. Aringo, Victor B. Ella, Camille G. Martinez, Gamiello S. Pereira
Ex-Ante Cost-Benefit Analysis Of High-End And Low-Cost Wireless Sensor Network (Wsn) Technology Packages For Efficient Irrigation Water Management In The Philippines, Marielle Q. Aringo, Victor B. Ella, Camille G. Martinez, Gamiello S. Pereira
Journal of Economics, Management and Agricultural Development
Four wireless sensor network (WSN) technology packages developed for efficient irrigation water management in the Philippines were subjected to ex-ante cost-benefit analysis (CBA) to assess their financial viability. The WSN technologies include high-end and low-cost wireless sensors for upland crop production with drip irrigation system and lowland crop production with alternate wetting and drying (AWD). Results showed that the high-end WSN technology packages are only viable for high-value crops such as red onion, bell pepper, and hot pepper. The low-cost WSN technology packages are viable for all selected crops except sweet corn. Minimum areas were also generated for each crop …
A Multi-Criteria Ranking System For Prioritizing Maintenance Of Levee Systems In Arkansas, Nguyen Danh Phan
A Multi-Criteria Ranking System For Prioritizing Maintenance Of Levee Systems In Arkansas, Nguyen Danh Phan
Graduate Theses and Dissertations
There are 208,009 properties in Arkansas that have more than a 26% chance of being severely affected by flooding over the next 30 years, which represents 13% of all properties in the state. A levee system is designed to reduce the flooding risk for urban and rural communities; however, most of the state's levees have been significantly outdated or built with engineering standards less rigorous than current best practices. The Levee Safety Action Classification (LSAC), as recorded in the National Levee Database (NLD), communicates the risk associated with living behind a particular levee and assists local, state, and federal stakeholders …
Using Reinforcement Learning To Improve Network Reliability Through Optimal Resource Allocation, Henley Wells
Using Reinforcement Learning To Improve Network Reliability Through Optimal Resource Allocation, Henley Wells
Graduate Theses and Dissertations
Networks provide a variety of critical services to society (e.g. power grid, telecommunication, water, transportation) but are prone to disruption. With this motivation, we study a sequential decision problem in which an initial network is improved over time (e.g., by adding or increasing the reliability of edges) and rewards are gained over time as a function of the network’s all-terminal reliability. The actions during each time period are limited due to availability of resources such as time, money, or labor. To solve this problem, we utilized a Deep Reinforcement Learning (DRL) approach implemented within OpenAI-Gym using Stable Baselines. A Proximal …
Advancing Statistical Learning And Decision Modeling Using Irregularly-Sampled Multivariate Data For Managing Respiratory Diseases, Maryam Alimohammadi
Advancing Statistical Learning And Decision Modeling Using Irregularly-Sampled Multivariate Data For Managing Respiratory Diseases, Maryam Alimohammadi
Graduate Theses and Dissertations
Complex healthcare systems require efficient and effective data-driven decision making in various aspects. As patient data becomes more available, advanced statistical learning and machine learning techniques are applied to improve data-driven decision making. However, patient health data, including clinical trial data, medical records, and electronic health records, are associated with several challenges. Patient health data includes medical information of a patient that may includedemographics, information relating to their health or illness, medications and treatments, etc. They are a combination of static and time series variables, with many censoring and missingness in the data, and are irregularly sampled in most cases. …
Machine Learning For Early Detection Of Pediatric Sepsis, Glory Manson-Endeboh
Machine Learning For Early Detection Of Pediatric Sepsis, Glory Manson-Endeboh
Graduate Theses and Dissertations
Sepsis is a host response to infection in both adults and children. It contributes to approximately 1.7 million cases annually with nearly 270,000 annual deaths in the United States. In the United States, the financial burden of sepsis on survivors and their families including the hospitals is over $4.8 billion, at approximately $64,280 per hospitalization. The first goal of this thesis research is to develop efficient machine learning models to predict pediatric sepsis accurately for inpatients. The second objective is to develop machine learning methods to determine how early sepsis can be detected to mitigate mortality. We examine data collected …
Smart Manufacturing—Theories, Methods, And Applications, Zhuming Bi, Lida Xu, Puren Ouyang
Smart Manufacturing—Theories, Methods, And Applications, Zhuming Bi, Lida Xu, Puren Ouyang
Information Technology & Decision Sciences Faculty Publications
(First paragraph) Smart manufacturing (SM) distinguishes itself from other system paradigms by introducing ‘smartness’ as a measure to a manufacturing system; however, researchers in different domains have different expectations of system smartness from their own perspectives. In this Special Issue (SI), SM refers to a system paradigm where digital technologies are deployed to enhance system smartness by (1) empowering physical resources in production, (2) utilizing virtual and dynamic assets over the internet to expand system capabilities, (3) supporting data-driven decision making at all domains and levels of businesses, or (4) reconfiguring systems to adapt changes and uncertainties in dynamic environments. …
Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson
Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson
Graduate Theses and Dissertations
This research proposes problems, models, and solutions for the scheduling of space robot on-orbit servicing. We present the Multi-Orbit Routing and Scheduling of Refuellable On-Orbit Servicing Space Robots problem which considers on-orbit servicing across multiple orbits with moving tasks and moving refuelling depots. We formulate a mixed integer linear program model to optimize the routing and scheduling of robot servicers to accomplish on-orbit servicing tasks. We develop and demonstrate flexible algorithms for the creation of the model parameters and associated data sets. Our first algorithm creates the network arcs using orbital mechanics. We have also created a novel way to …
Ensemble Tree-Based Machine Learning For Imaging Data, Reza Iranzad
Ensemble Tree-Based Machine Learning For Imaging Data, Reza Iranzad
Graduate Theses and Dissertations
In particular medical imaging data, such as positron emission tomography (PET), computed tomography (CT), and fluorescence intravital microscopy (IVM), have become prevalent for use in a wide variety of applications, from diagnostic purposes, tracking diseases' progress, and monitoring the effectiveness of treatments to decision-making processes. The detailed information generated by medical imaging has enabled physicians to provide more comprehensive care. Although numerous machine learning algorithms, especially those used for imaging data, have been developed, dealing with unique structures in imaging data remained a big challenge. In this dissertation, we are proposing novel statistical tree-based methods with more efficient and more …
Generating Sex Trafficking Networks From Text Documents, Maria Diaz
Generating Sex Trafficking Networks From Text Documents, Maria Diaz
All Theses
Qualitative coding is a long and strenuous process that requires a well-skilled investigator. Natural language processing techniques have made leaps and bounds as far as usability and application domain, although it does not work for every task. In this work, we have created a natural language processing framework to help qualitative coders automatically obtain the nodes and node arcs from federal case files, dockets, and indictments within a sex trafficking network. The produced nodes and arcs allows us to perform network modeling by providing us with the information needed to create network structures that can then be used for interdiction …
Cyberpunk As An Evolution From Science-Fiction And Its Social Critiques, William C. Svihla
Cyberpunk As An Evolution From Science-Fiction And Its Social Critiques, William C. Svihla
University Honors Program
In this paper, I will take an investigative deep dive into all that is the literary genre of cyberpunk. I will touch on the origins and development of science-fiction, the genre that birthed cyberpunk, and how science-fiction led up to cyberpunk’s birth. I discuss the origins of cyberpunk and where and when it first entered the scene. The literary differences between the two genres. And the main areas of social critique that are focused on for each as well. For science-fiction’s areas of social critique, I discuss their ever-present use of the dangers of man’s hubris first made present in …
Analyzing Vulnerabilities In The Northwest Arkansas Highway Network Using Mathematical Optimization, Brandon Jerome
Analyzing Vulnerabilities In The Northwest Arkansas Highway Network Using Mathematical Optimization, Brandon Jerome
Industrial Engineering Undergraduate Honors Theses
The highway and bridge network is a critical infrastructure that allows for the free transportation of citizens and enables truck-borne freight transportation. Disruption of this system could be caused by a terrorist attack, natural disaster, growth of population, required repairs and upgrades, or collapse caused by old age or malfunction. In the event of a disruption cities and regions can experience increased traffic and supply chain shortages, thus causing cascading effects throughout surrounding areas. With this motivation, we develop a network interdiction optimization model to identify a limited subset of roads that, if disrupted, causes the greatest increase in the …
Implementing The Cms+ Sports Rankings Algorithm In A Javafx Environment, Luke Welch
Implementing The Cms+ Sports Rankings Algorithm In A Javafx Environment, Luke Welch
Industrial Engineering Undergraduate Honors Theses
Every year, sports teams and athletes get cut from championship opportunities because of their rank. While this reality is easier to swallow if a team or athlete is distant from the cut, it is much harder when they are right on the edge. Many times, it leaves fans and athletes wondering, “Why wasn’t I ranked higher? What factors when into the ranking? Are the rankings based on opinion alone?” These are fair questions that deserve an answer. Many times, sports rankings are derived from opinion polls. Other times, they are derived from a combination of opinion polls and measured performance. …
Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn
Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn
Graduate Theses and Dissertations
Machine learning approaches for prediction play an integral role in modern-day decision supports system. An integral part of the process is extracting interest variables or features to describe the input data. Then, the variables are utilized for training machine-learning algorithms to map from the variables to the target output. After the training, the model is validated with either validation or testing data before making predictions with a new dataset. Despite the straightforward workflow, the process relies heavily on good feature representation of data. Engineering suitable representation eases the subsequent actions and copes with many practical issues that potentially prevent the …
Predicting The Likelihood And Scale Of Wildfires In California Using Meteorological And Vegetation Data, Matthew Walters
Predicting The Likelihood And Scale Of Wildfires In California Using Meteorological And Vegetation Data, Matthew Walters
Graduate Theses and Dissertations
Wildfires have devastating ecological, environmental, economical, and public health impacts through the deterioration of water and air quality, CO2 emissions, property damage, and lung illnesses. The early detection and prevention of wildfires allow for the minimization of these risks. The use of Artificial Intelligence (AI) in wildfire detection and prediction has been highly researched as a tool to assist firefighters in stopping wildfires in its early stages. The three common wildfire prediction categories include image and video detection, behavior prediction, and susceptibility prediction. Data such as climate, weather, vegetation, satellite images, and historical wildfire data is most commonly used. Many …
Fathom In Color: Expansion Of Reproduceable Color In Interference Pattern-Based Printed Motion And Depth Effects, Dovie Jeffcoat
Fathom In Color: Expansion Of Reproduceable Color In Interference Pattern-Based Printed Motion And Depth Effects, Dovie Jeffcoat
All Theses
Value-added printed embellishments are increasingly sought after as brands compete for consumer attention. Fathom Optics’ method for printing motion and depth effects provides a cost-efficient, reduced waste embellishment option. One of Fathom’s current limitations is producing effects with vibrant color. The current standard practice for producing color Fathom Effects tends to darken and desaturate the final embellishment’s color. This study endeavors to determine how an ink color's components (hue, value and chroma) may determine a Fathom Effect’s contrast or intensity. To achieve this, fifteen color inks were selected to flexographically print the effect patterns. Samples were taken from each color …