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Structural Model Of The Technological Process Of Storage And Processing Of Oil Raw Materials, N.A Kabulov 2023 Tashkent State Technical University, Address: 2 Universitetskaya st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: [email protected].

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 2023 Karlsruhe Institute of Technology

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 2023 University of Kentucky

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 2023 Endangered Wildlife Trust

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 2023 West Virginia University

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 2022 Center for Agri-fisheries and Biosystems Mechanization, College of Engineering and Agro-industrial Technology (CEAT), University of the Philippines Los Baños (UPLB)

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 2022 University of Arkansas, Fayetteville

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 2022 University of Arkansas, Fayetteville

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 2022 University of Arkansas, Fayetteville

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 2022 University of Arkansas, Fayetteville

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 2022 Old Dominion University

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 2022 University of Arkansas, Fayetteville

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 2022 University of Arkansas, Fayetteville

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 2022 Clemson University

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 2022 Indiana State University

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 2022 University of Arkansas, Fayetteville

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 2022 University of Arkansas, Fayetteville

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 2022 University of Arkansas, Fayetteville

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 2022 University of Arkansas, Fayetteville

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 2022 Clemson University

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 …


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