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Missouri University of Science and Technology
Engineering Management and Systems Engineering Faculty Research & Creative Works
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- Infrastructure (2)
- Trading strategies (2)
- Action recognition (1)
- Calibration (1)
- Convolutional Neural Network (CNN) (1)
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- Convolutional neural network (1)
- Cyber Physical Systems (1)
- Cyber-physical systems (1)
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- Daily stock return forecasting (1)
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- Deception detection (1)
- Deep Learning (DL) (1)
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- Flood management (1)
- Hazardous material (1)
- Hedge fund replication (1)
- Hedge funds (1)
- Hierarchical clustering (1)
- Hybrid machine learning algorithms (1)
- Independent System Operator (1)
- Manufacturing load (1)
- Phishing (1)
- Real-time monitoring (1)
- Regression (1)
- Resilience (1)
Articles 1 - 14 of 14
Full-Text Articles in Engineering
Hedge Fund Replication Using Strategy Specific Factors, Sujit Subhash, David Lee Enke
Hedge Fund Replication Using Strategy Specific Factors, Sujit Subhash, David Lee Enke
Engineering Management and Systems Engineering Faculty Research & Creative Works
Hedge funds have traditionally served wealthy individuals and institutional investors with the promise of delivering protection of capital and uncorrelated positive returns irrespective of market direction, allowing them to better manage portfolio risk. However, the financial crisis of 2008 has heightened investor sensitivity to the high fees, illiquidity, lack of transparency, and lockup periods typically associated with hedge funds. Hedge fund replication products, or clones, seek to answer these challenges by providing daily liquidity, transparency, and immediate exposure to a desired hedge fund strategy. Nonetheless, although lowering cost and adding simplicity by using a common set of factors, traditional replication …
Predicting The Daily Return Direction Of The Stock Market Using Hybrid Machine Learning Algorithms, X. Zhong, David Lee Enke
Predicting The Daily Return Direction Of The Stock Market Using Hybrid Machine Learning Algorithms, X. Zhong, David Lee Enke
Engineering Management and Systems Engineering Faculty Research & Creative Works
Big data analytic techniques associated with machine learning algorithms are playing an increasingly important role in various application fields, including stock market investment. However, few studies have focused on forecasting daily stock market returns, especially when using powerful machine learning techniques, such as deep neural networks (DNNs), to perform the analyses. DNNs employ various deep learning algorithms based on the combination of network structure, activation function, and model parameters, with their performance depending on the format of the data representation. This paper presents a comprehensive big data analytics process to predict the daily return direction of the SPDR S&P 500 …
Better Beware: Comparing Metacognition For Phishing And Legitimate Emails, Casey I. Canfield, Baruch Fischhoff, Alex Davis
Better Beware: Comparing Metacognition For Phishing And Legitimate Emails, Casey I. Canfield, Baruch Fischhoff, Alex Davis
Engineering Management and Systems Engineering Faculty Research & Creative Works
Every electronic message poses some threat of being a phishing attack. If recipients underestimate that threat, they expose themselves, and those connected to them, to identity theft, ransom, malware, or worse. If recipients overestimate that threat, then they incur needless costs, perhaps reducing their willingness and ability to respond over time. In two experiments, we examined the appropriateness of individuals' confidence in their judgments of whether email messages were legitimate or phishing, using calibration and resolution as metacognition metrics. Both experiments found that participants had reasonable calibration but poor resolution, reflecting a weak correlation between their confidence and knowledge. These …
Correction To: Better Beware: Comparing Metacognition For Phishing And Legitimate Emails (Metacognition And Learning, (2019), 14, 3, (343-362), 10.1007/S11409-019-09197-5), Casey I. Canfield, Baruch Fischhoff, Alex Davis
Correction To: Better Beware: Comparing Metacognition For Phishing And Legitimate Emails (Metacognition And Learning, (2019), 14, 3, (343-362), 10.1007/S11409-019-09197-5), Casey I. Canfield, Baruch Fischhoff, Alex Davis
Engineering Management and Systems Engineering Faculty Research & Creative Works
The article "Better beware: comparing metacognition for phishing and legitimate emails", written by Casey Inez Canfield, Baruch Fischhoff and Alex Davis, was originally published electronically on the publisher's internet portal (currently SpringerLink) on 20 July 2019 without open access.
Opportunities And Challenges For Rural Broadband Infrastructure Investment, Casey I. Canfield, Ona Egbue, Jacob Hale, Suzanna Long
Opportunities And Challenges For Rural Broadband Infrastructure Investment, Casey I. Canfield, Ona Egbue, Jacob Hale, Suzanna Long
Engineering Management and Systems Engineering Faculty Research & Creative Works
Insufficient internet access is holding back local economies, reducing educational outcomes, and creating health disparities in rural areas of the U.S. At present, federal and state funding is available for rural broadband infrastructure deployment, but existing efforts have not invested in analytical work to maximize efficiency and minimize cost. In this study, we use a state-of-the-art matrix (SAM) to identify key challenges and opportunities facing rural broadband infrastructure from previous research and government reports. We focus on six themes: (1) technology, (2) hardware costs, (3) financing, (4) adoption, (5) regulatory/legal, and (6) management. We highlight key issues to be addressed …
A Mixed Method Study Of Infrastructure Resilience Education And Instruction, John Richards, Suzanna Long
A Mixed Method Study Of Infrastructure Resilience Education And Instruction, John Richards, Suzanna Long
Engineering Management and Systems Engineering Faculty Research & Creative Works
As the frequency and severity of natural and man-made disasters increases, the importance of improving the resilience of complex infrastructure systems in an uncertain environment is increasingly critical. Proper training and education are key components to addressing this issue, but it is unclear how and where modeling under uncertainty, infrastructure systems management, and resilient systems are integrated into the standard undergraduate and graduate engineering management curriculum. This research uses a mixed method to determine whether and at what level engineering managers receive instruction regarding the implementation of tools and techniques to improve infrastructure resilience. A review of current courses and …
Flood Management Deep Learning Model Inputs: A Review Of Necessary Data And Predictive Tools, Jacob Hale, Suzanna Long, Steven Corns, Tom Shoberg
Flood Management Deep Learning Model Inputs: A Review Of Necessary Data And Predictive Tools, Jacob Hale, Suzanna Long, Steven Corns, Tom Shoberg
Engineering Management and Systems Engineering Faculty Research & Creative Works
Current flood management models are often hampered by the lack of robust predictive analytics, as well as incomplete datasets for river basins prone to heavy flooding. This research uses a State-of-the-Art matrix (SAM) analysis and integrative literature review to categorize existing models by method and scope, then determines opportunities for integrating deep learning techniques to expand predictive capability. Trends in the SAM analysis are then used to determine geospatial characteristics of the region that can contribute to flash flood scenarios, as well as develop inputs for future modeling efforts. Preliminary progress on the selection of one urban and one rural …
Risk Awareness Enhancement Systems For Hazmat Transportation: Prototyping And Technology Evaluation, Jian Xue, Katherine Linville, Yu Li, Pranav Nitin Godse, Suzanna Long, Ruwen Qin
Risk Awareness Enhancement Systems For Hazmat Transportation: Prototyping And Technology Evaluation, Jian Xue, Katherine Linville, Yu Li, Pranav Nitin Godse, Suzanna Long, Ruwen Qin
Engineering Management and Systems Engineering Faculty Research & Creative Works
Workers of hazardous material (hazmat) transportation have a higher chance than other workers to be exposed to various risks in their workplace. Assisting them to safely operate in their workplace in a near real-time manner is in particular need. This paper presents a study of designing, prototyping and developing feedback systems to help increase the risk awareness of workers in the loading and uploading phases of hazmat transportation. The first system was prototyped on an Arduino board, serving as the reference for system development. Then, the second system, named a Bluetooth Low Energy (BLE) beacon based system, was designed as …
A Framework Of Integrating Manufacturing Plants In Smart Grid Operation: Manufacturing Flexible Load Identification, Md. Monirul Islam, Zeyi Sun, Wenqing Hu, Cihan H. Dagli
A Framework Of Integrating Manufacturing Plants In Smart Grid Operation: Manufacturing Flexible Load Identification, Md. Monirul Islam, Zeyi Sun, Wenqing Hu, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
In the deregulated electricity markets run by Independent System Operator (ISO), a two-settlement (day-ahead and real-time) process is typically used to determine the electricity price to the end-use customers at different buses. In the day-ahead settlement, the demand is predicted at each bus based on the previous consumption behavior of the consumers and thus, Locational Marginal Price (LMP) can be determined and shared to the consumers. A significant gap is usually observed between the planned and real-time demands due to the uncertainties of the weather (temperature, wind-speed etc.), the intensity of business, and everyday activities. Therefore, a large price variation …
Preface, Cihan H. Dagli, Gursel A. Suer
Preface, Cihan H. Dagli, Gursel A. Suer
Engineering Management and Systems Engineering Faculty Research & Creative Works
No abstract provided.
System Of Systems (Sos) Architecture For Digital Manufacturing Cybersecurity, Lirim Ashiku, Cihan H. Dagli
System Of Systems (Sos) Architecture For Digital Manufacturing Cybersecurity, Lirim Ashiku, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
Technology advancements of real time connectivity and computing powers has evolved the way people manage activities triggering heavy reliance on smart devices. This has reshaped the ability to memorize crucial information, instead accumulate the information into devices allowing real-time fingertip access when needed. Inability to access such information when needed is routinely assumed with device malfunctioning bypassing the probability of compromise, but what if the information is now being accessed by adversaries depriving the data-owner access to crucial information? Cyber manufacturing systems are not immune from these issues. It is possible to approach this problem as generating SoS meta-architecture. In …
Vision Sensor Based Action Recognition For Improving Efficiency And Quality Under The Environment Of Industry 4.0, Zipeng Wang, Ruwen Qin, Jihong Yan, Chaozhong Guo
Vision Sensor Based Action Recognition For Improving Efficiency And Quality Under The Environment Of Industry 4.0, Zipeng Wang, Ruwen Qin, Jihong Yan, Chaozhong Guo
Engineering Management and Systems Engineering Faculty Research & Creative Works
In the environment of industry 4.0, human beings are still an important influencing factor of efficiency and quality which are the core of product life cycle management. Hence, monitoring and analyzing humans' actions are essential. This paper proposes a vision sensor based method to evaluate the accuracy of operators' actions. Each action of operators is recognized in real time by a Convolutional Neural Network (CNN) based classification model in which hierarchical clustering is introduced to minimize the effects of action uncertainty. Warnings are triggered when incorrect actions occur in real time and applications of action analysis of workers on a …
System Architecting Approach For Designing Deep Learning Models, Ram Deepak Gottapu, Cihan H. Dagli
System Architecting Approach For Designing Deep Learning Models, Ram Deepak Gottapu, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
Deep Learning (DL) models have proven to be very effective in solving many challenging problems, especially, those related to computer vision, text, and speech. However, the design of such models is challenging because of the vast search space and computational complexity that needs to be explored. Our goal in this paper is to reduce the human effort required to design architectures by using a system architecture development process that allows the exploration of large design space by automating certain model construction, alternative generation, and assessment. The proposed framework is generic and targeted at all deep learning architectures that can be …
Supply Chain Infrastructure Restoration Calculator Software Tool -- Developer Guide And User Manual, Akhilesh Ojha, Bhanu Kanwar, Suzanna Long, Thomas G. Shoberg, Steven Corns
Supply Chain Infrastructure Restoration Calculator Software Tool -- Developer Guide And User Manual, Akhilesh Ojha, Bhanu Kanwar, Suzanna Long, Thomas G. Shoberg, Steven Corns
Engineering Management and Systems Engineering Faculty Research & Creative Works
This report describes a software tool that calculates costs associated with the reconstruction of supply chain interdependent critical infrastructure in the advent of a catastrophic failure by either outside forces (extreme events) or internal forces (fatigue). This tool fills a gap between search and recover strategies of the Federal Emergency Management Agency (or FEMA) and construction techniques under full recovery. In addition to overall construction costs, the tool calculates reconstruction needs in terms of personnel and their required support. From these estimates, total costs (or the cost of each element to be restored) can be calculated. Estimates are based upon …