Engineering Commons^™

Integrated Dynamic Airline Route And Schedule Optimization, Bayan Begaliyeva

Student Works

By harnessing real-time and historical data in conjunction with advanced AI technologies, this project revolutionizes route and schedule planning, leading to enhanced efficiency, cost reduction, and an improved passenger experience.

Introduction To The Special Issue On Gala Conf 2021, Francesca De Rosa, Jannicke Baalsrud Hauge, Pierpaolo Dondio, Isa Marfizi-Schottman, Margarida Romero, Francesco Bellotti

Articles

This special issue of the International Journal of Serious Games is dedicated to the selected best papers of the 2021 edition of the GALA conference. This edition was organized by Francesca De Rosa and her team at NATO Centre for Maritime Research and Experimen-tation (CMRE), La Spezia, Italy. Because of the Covid-19 pandemic, it was held online, for the second year. The three papers published in this special issue were first selected for a content exten-sion, so to make them suitable as journal papers, then underwent the regular IJSG peer-review process, which, on the other hand, discarded other three selected …

Bibliometric Study On Analysing Impact Of Newly Launched Products Over Existing Ones Through Ai, Dipak Sharma, Vageesh Devrath, Abhinav Rajput, Gouranga Jyoti Kataky, Priyanka Tupe-Waghmare, Ismail Akbani

Library Philosophy and Practice (e-journal)

Different analysis models like Conditional Mean Analysis, Trend Analysis, Correlation Analysis helps us to analyse the delicate equilibrium between businesses that gets impacted when a new product is launched in a cluster. This paper shows a statistical report of research done on the businesses in a cluster based on ongoing trends and current customer needs . There is surplus data present on various platforms related to every product following the ongoing trends in the form of customer reviews.The research mainly speculates mainly how the businesses get impacted with change in consumer needs, wants and demands. With the help of datasets …

Save-T: Safety Analysis Visualization And Evaluation Tool, Yuan Zhu, Sami Demiroluk, Kaan Ozbay, Kun Xie, Hong Yang, Di Sha

Civil & Environmental Engineering Faculty Publications

Traffic crashes are one of the biggest issues which constitute a threat to lives of the motorists and disrupt operations of the transportation system. To reduce the number of crashes and alleviate their impacts, it is necessary to scrutinize the factors contributing to the risk of traffic crashes. Lately, visual analytics tools become very popular for data exploration and obtaining insights from the data. In this paper, a new web-based data visualization tool called Safety Analysis Visualization and Evaluation Tool (SAVE-T) was introduced. This tool enables users to interactively create queries and visually explore the results. By utilizing an online …

Hr Process Automation: A Bibliometric Analysis, Shubham Mishra, Monica Kunte, Netra Neelam, Sanjay Bhattacharya, Preeti Mulay

Library Philosophy and Practice (e-journal)

Automation is interpreted as the replacement of manual operations by electronics and computer-controlled systems. Human resource management is an indispensable part of every firm be it the space of retail, healthcare, education or any other sector. Activities such as hiring new workers, training, or making sure that local labour laws are obeyed with HR processes and are a crucial part of every organisation. HR has typically been believed of as an extremely manual department procedure. Employees are accustomed to doing this manually and getting the job done themselves. But everything around the HR processes are changing rapidly. HR Automation is …

Sports Analytics: Putting The Fun Back Into Analytics, Walt Degrange

Operations Management Presentations

With the recent success of sports teams heavily using analytics (Dodgers, Patriots, Capitals, Warriors, Leicester City F.C.), does this mean that analytics has gained a foothold in the sports world? I use a k-means clustering model to determine if performance since 2015 in the four major US sports can support this question. And is there a career path that a high school student can use to become a sports analytics professional? This presentation attempts to answer that question by exploring all the areas of the application of analytics in sports. The final point the brief makes is that by using …

Characterizing Statin Use Among Prediabetic Patients With Predictive Analytics, Alexandra Gentile

Industrial Engineering Undergraduate Honors Theses

Diabetes is one of the leading causes of death in the United States and can cause severe impairments to those diagnosed. Prediabetes is a state when a patient has higher fasting plasma glucose levels than a non-diabetic person but is not quite high enough to be considered diabetes. Both diabetic and prediabetic patients are at higher risk for cardiovascular diseases (CVD), which is the leading cause of death in the United States. The primary form for prevention and treatment of CVD is through statin therapy. Statins are a class of medications used to treat and prevent CVD by limiting cholesterol …

Machine Learning In Manufacturing: Review, Synthesis, And Theoretical Framework, Ajit Sharma, Zhibo Zhang, Rahul Rai

Business Administration Faculty Research Publications

There has been a paradigmatic shift in manufacturing as computing has transitioned from the programmable to the cognitive computing era. In this paper we present a theoretical framework for understanding this paradigmatic shift in manufacturing and the fast evolving role of artificial intelligence. Policy, Strategic and Operational implications are discussed. Implications for the future of strategy and operations in manufacturing are also discussed. Future research directions are presented.

Depressiongnn: Depression Prediction Using Graph Neural Network On Smartphone And Wearable Sensors, Param Bidja

Honors Scholar Theses

Depression prediction is a complicated classification problem because depression diagnosis involves many different social, physical, and mental signals. Traditional classification algorithms can only reach an accuracy of no more than 70% given the complexities of depression. However, a novel approach using Graph Neural Networks (GNN) can be used to reach over 80% accuracy, if a graph can represent the depression data set to capture differentiating features. Building such a graph requires 1) the definition of node features, which must be highly correlated with depression, and 2) the definition for edge metrics, which must also be highly correlated with depression. In …

Decision Science For Community Development And Social Change, Michael P. Johnson Jr.

Michael P. Johnson

Understanding The Impact Of Virtual-Mirroring Based Learning On Collaboration In A Data And Analytics Function: A Resilience Perspective, Nabil Raad

Wayne State University Dissertations

Large multinational organizations are struggling to adapt and innovate in the face of increasing turbulence, uncertainty, and complexity. The lack of adaptive capacity is one of the major risks facing such organizations as the rapid change in technology, urbanization, socio-economic trends, and regulations continues to accelerate and outpace their ability to adapt. This is a resilience problem that organizations are addressing by investing in Data and Analytics to improve their innovation and competitive capabilities. However, Data and Analytics projects are more likely to fail than to succeed. Competing on data and analytics is not only a technical challenge but also …

Diversity And Or/Ms/Analytics: Deepening The Impact Of Our Research, Broadening Access To The Profession, Michael P. Johnson Jr.

Michael P. Johnson

Socio-Economic Planning Sciences Special Issue: Indices For The Betterment Of The Public, Vincent Charles, Ali Emrouznejad, Michael P. Johnson Jr.

Michael P. Johnson

Emerging Trends And New Frontiers In Community Operational Research, Michael P. Johnson Jr., Gerald Midgley, George Chichirau

Michael P. Johnson

Utilizing Analytics In American Football To Improve Decision Making On Fourth Down, Daniel David Reid Ferguson

Graduate Theses - Engineering Management

The purpose of this paper was to investigate what advantages, if any, an analytical approach using historical data could have in guiding critical game decisions in order to maximize a team’s chances of winning. The analytical approach described in this paper involves using expected point values that correspond to an offensive team’s location on the field and historical first down conversion rates. From this information a decision is made that chooses the fourth-down option that yields the highest amount of expected points. Using historical, data a fourth-down Strategy Sheet was developed based upon expected point values. The Strategy Sheet was …

A Motion Capture System Framework For The Study Of Human Manufacturing Repetitive Motions, Francis Mendez, David Wierschem, Jesus Jimenez

15th IMHRC Proceedings (Savannah, Georgia. USA – 2018)

Our research proposes a framework to obtain and analyze real time data concerning the dynamic and natural motion of individuals in manufacturing-like processes that involve human labor. The framework that we propose consists of five main components: a tracking system, a system of sensors, a processor that collects time series data, data processing and discovery module, and an alert or reporting component. Using motion capture cameras, data is collected on a variety of human subjects performing simulated labor-intensive manufacturing operations. This data is analyzed for identification of actual and optimal activity motions. This project has significant potential impact for contribution …

Improving Decision-Making Skills Of Nonprofit Professionals, Michael P. Johnson Jr., George Chichirau, Jason Wright

Michael P. Johnson

Prediction Of Graduation Delay Based On Student Characterisitics And Performance, Tushar Ojha

Electrical and Computer Engineering ETDs

A college student's success depends on many factors including pre-university characteristics and university student support services. Student graduation rates are often used as an objective metric to measure institutional effectiveness. This work studies the impact of such factors on graduation rates, with a particular focus on delay in graduation. In this work, we used feature selection methods to identify a subset of the pre-institutional features with the highest discriminative power. In particular, Forward Selection with Linear Regression, Backward Elimination with Linear Regression, and Lasso Regression were applied. The feature sets were selected in a multivariate fashion. High school GPA, ACT …

Community-Engaged Operations Research: Trends, New Frontiers And Opportunities, Michael P. Johnson Jr.

Michael P. Johnson

Collaborative Data Analytics Towards Prediction On Pathogen-Host Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Jiangning Song

Faculty of Engineering and Information Sciences - Papers: Part B

Nowadays more and more data are being sequenced and accumulated in system biology, which bring the data analytics researchers to a brand new era, namely 'big data', to extract the inner relationship and knowledge from the huge amount of data.

Metamorphic Testing For Adobe Data Analytics Software, Darryl C. Jarman, Zhiquan Zhou, Tsong Yueh Chen

Faculty of Engineering and Information Sciences - Papers: Part B

It is challenging to test data analytics software because a test oracle might not be available. This study reports our experience of applying metamorphic testing to Adobe's data analytics software that is used for anomaly detection in a set of time series data. We make use of geometric transformations to build metamorphic relations and generate simple time series data as the source test cases. The results of this study show that metamorphic testing is highly effective for both verification and validation purposes. An investigation of the issues detected during metamorphic testing revealed three bugs in the software under test.

Barriers To Predictive Analytics Use For Policy Decision-Making Effectiveness In Turbulent Times: A Case Study Of Fukushima Nuclear Accident, Akemi T. Chatfield, Christopher Reddick

Faculty of Engineering and Information Sciences - Papers: Part A

No abstract provided.

An Agenda For Diversity And Inclusion-Related Research Within Or/Ms/Analytics, Michael P. Johnson Jr., George Chichirau

Michael P. Johnson

The Impact Of Analytics Utilization On Team Performance: Comparisons Within And Across The U.S. Professional Sports Leagues, Lee A. Freeman

Journal of International Technology and Information Management

Business analytics, defined as the use of data to make better, more relevant, evidence-based business decisions, has received a great deal of attention in practitioner circles. Organizations have adopted business analytics in an effort to improve revenue, product placement, and customer satisfaction. Professional sports teams are no different. While analytics has been used for over 30 years, the use of analytics by professional sports teams is a relatively new concept. However, it is unclear whether the teams that have adopted analytics are seeing any results. If not, then perhaps analytics is not the right solution. Analyses across the four, major …

Impact Of Poloxamer 188 Variability On Biologics Manufacturing: Mitigations And Causal Investigation, Salim Charaniya

Cell Culture Engineering XV

Poloxamer 188 (P188), a water-soluble, synthetic copolymer with hydrophilic as well as lipophilic properties, is widely used as a cell protectant for bubble-induced shear during cultivation of suspension-adapted mammalian cells for large-scale production of protein-based therapeutics. Poor cell growth and lower product yield has been recently observed at commercial scales in more than one Chinese hamster ovary-based manufacturing process within Roche network when specific lots of P188 were used. An investigation is being conducted to unearth the root cause of “poor-performing” P188 lots and to identify means to mitigate the product supply risks. P188 raw material is currently sourced from …

Renewable Energy Investment Planning And Policy Design, Alireza Ghalebani

USF Tampa Graduate Theses and Dissertations

In this dissertation, we leverage predictive and prescriptive analytics to develop decision support systems to promote the use of renewable energy in society. Since electricity from renewable energy sources is still relatively expensive, there are variety of financial incentive programs available in different regions. Our research focuses on financial incentive programs and tackles two main problem: 1) how to optimally design and control hybrid renewable energy systems for residential and commercial buildings given the capacity based and performance based incentives, and 2) how to develop a model-based system for policy makers for designing optimal financial incentive programs to promote investment …

Hpc Enabled Data Analytics For High-Throughput High-Content Cellular Analysis, Ross A. Smith, Rhonda J. Vickery, Jack Harris, Sara Gharabaghi, Thomas Wischgoll, David Short, Robert Trevino, Steven A. Kawamoto, Thomas J. Lamkin, Kevin Schoen, Eric E. Bardes, Scott C. Tabar, Bruce J. Aronow

Computer Science and Engineering Faculty Publications

Biologists doing high-throughput high-content cellular analysis are generally not computer scientists or high performance computing (HPC) experts, and they want their workflow to support their science without having to be. We describe a new HPC enabled data analytics workflow with a web interface, HPC pipeline for analysis, and both traditional and new analytics tools to help them transition from a single workstation mode of operation to power HPC users. This allows the processing of multiple plates over a short period of time to ensure timely query and analysis to match potential countermeasures to individual responses.

A Fuzzy Rough Sets-Based Multi-Agent Analytics Framework For Dynamic Supply Chain Configuration, Nagesh Shukla, Senevi Kiridena

SMART Infrastructure Facility - Papers

Considering the need for more effective decision support in the context of distributed manufacturing, this paper develops an advanced analytics framework for configuring supply chain networks. The proposed framework utilizes a distributed multi-agent system architecture to deploy fuzzy rough sets-based algorithms for knowledge elicitation and representation. A set of historical sales data, including network node-related information, is used together with the relevant details of product families to predict supply chain configurations capable of fulfilling desired customer orders. Multiple agents such as data retrieval agent, knowledge acquisition agent, knowledge representation agent, configuration predictor agent, evaluator agent and dispatching agent are used …

A Conceptual Model For The Application Of Business Analytics In The Horizontal Strategic Alliance, John Janosko, Tingru Cui, S K. Lau

Faculty of Engineering and Information Sciences - Papers: Part A

The formation of strategic alliances amongst organisations has grown in recent years as globalisation has opened new markets for firms to pursue. It is of ever-increasing importance that organisations have a thorough understanding of the performance of their alliance to achieve competitive advantage. However, much research on strategic alliance has focused on examining the organisations within the alliance rather than focusing on the alliance itself. Using the new discipline of business analytics, this paper proposes a hierarchical model blending the functional roles of business analytics with data standardisation and context mediation frameworks to allow business analytics to be applied to …

Towards Data Analytics Of Pathogen-Host Protein-Protein Interaction: A Survey, Huaming Chen, Jun Shen, Lei Wang, Jiangning Song

Faculty of Engineering and Information Sciences - Papers: Part A

"Big Data" is immersed in many disciplines, including computer vision, economics, online resources, bioinformatics and so on. Increasing researches are conducted on data mining and machine learning for uncovering and predicting related domain knowledge. Protein-protein interaction is one of the main areas in bioinformatics as it is the basis of the biological functions. However, most pathogen-host protein-protein interactions, which would be able to reveal much more infectious mechanisms between pathogen and host, are still up for further investigation. Considering a decent feature representation of pathogen-host protein-protein interactions (PHPPI), currently there is not a well structured database for research purposes, not …