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Articles 601 - 630 of 2514
Full-Text Articles in Computer Sciences
Technology Agency On Usage: Grounded Theory And Measurement Of Technology Induced Usage Behavior, Sandip Kumar Sarkar
Technology Agency On Usage: Grounded Theory And Measurement Of Technology Induced Usage Behavior, Sandip Kumar Sarkar
Graduate Theses and Dissertations
Most of today’s software applications involve a dyadic interplay between human and technology agency. The use of algorithms driven by user can alter users' interaction patterns by affording them novel and relevant technology action possibilities. I argue that algorithmic activities and features embedded in apps can keep users on IT applications (apps) for longer periods of time. I refer to the behavior of interacting with the apps for longer time than planned as technology-induced excessive use. While practitioners are beginning to recognize characteristics of technology-induced excessive use, research on this topic is very limited. I used a multimethod approach to …
Is Artificial Intelligence A Double-Edged Sword? Insights From Three Essays On Its Impacts, Ankur Arora
Is Artificial Intelligence A Double-Edged Sword? Insights From Three Essays On Its Impacts, Ankur Arora
Graduate Theses and Dissertations
"If we do it right, we might be able to evolve a form of work that taps into our uniquely human capabilities and restores our humanity. The ultimate paradox is that this technology may become a powerful catalyst that we need to reclaim our humanity." - John Hagel
Artificial intelligence (AI) is viewed as a disruptive technology that some executives believe will take over a lot of jobs. However, others believe that AI will bolster growth, improve business processes, and create new business opportunities. This dissertation focuses on the tension arising from such contrasting expected impacts of AI. Extant research …
Neural-Progressive Hedging: Enforcing Constraints In Reinforcement Learning With Stochastic Programming, Supriyo Ghosh, Laura Wynter, Shiau Hong Lim, Duc Thien Nguyen
Neural-Progressive Hedging: Enforcing Constraints In Reinforcement Learning With Stochastic Programming, Supriyo Ghosh, Laura Wynter, Shiau Hong Lim, Duc Thien Nguyen
Research Collection School Of Computing and Information Systems
We propose a framework, called neural-progressive hedging (NP), that leverages stochastic programming during the online phase of executing a reinforcement learning (RL) policy. The goal is to ensure feasibility with respect to constraints and risk-based objectives such as conditional value-at-risk (CVaR) during the execution of the policy, using probabilistic models of the state transitions to guide policy adjustments. The framework is particularly amenable to the class of sequential resource allocation problems since feasibility with respect to typical resource constraints cannot be enforced in a scalable manner. The NP framework provides an alternative that adds modest overhead during the online phase. …
Joint Chance-Constrained Staffing Optimization In Multi-Skill Call Centers, Tien Thanh Dam, Thuy Anh Ta, Tien Mai
Joint Chance-Constrained Staffing Optimization In Multi-Skill Call Centers, Tien Thanh Dam, Thuy Anh Ta, Tien Mai
Research Collection School Of Computing and Information Systems
This paper concerns the staffing optimization problem in multi-skill call centers. The objective is to find a minimal cost staffing solution while meeting a target level for the quality of service (QoS) to customers. We consider a staffing problem in which joint chance constraints are imposed on the QoS of the day. Our joint chance-constrained formulation is more rational capturing the correlation between different call types, as compared to separate chance-constrained versions considered in previous studies. We show that, in general, the probability functions in the joint-chance constraints display S-shaped curves, and the optimal solutions should belong to the concave …
Artificial Intelligence In Financial Technology, Keng Siau, Fiona Fui-Hoon Nah, Brenda L. Eschenbrenner, Langtao Chen
Artificial Intelligence In Financial Technology, Keng Siau, Fiona Fui-Hoon Nah, Brenda L. Eschenbrenner, Langtao Chen
Research Collection School Of Computing and Information Systems
AI applications in health care, communications, and arts have brought about rapid and dramatic advances in these fields. Nevertheless, the rapidly expanding potential of AI in the economy and society has raised a set of challenging issues. The fields of AI and financial technology are not spared. How can artificial intelligence (AI) be utilized in financial technology (fintech)? What will be the impact? What actionable objectives are needed to realize value from AI? This research uses a systematic qualitative research methodology, Value-Focused Thinking, to identify the actionable objectives for deriving value from AI in the fintech industry. The results of …
Predictors Of Email Response: Determinants Of The Intention Of Not Following Security Recommendations, Miguel Angel Toro-Jarrin
Predictors Of Email Response: Determinants Of The Intention Of Not Following Security Recommendations, Miguel Angel Toro-Jarrin
Engineering Management & Systems Engineering Theses & Dissertations
Organizations and government leaders are concerned about cyber incidents. For some time, researchers have studied what motivates people to act in ways that put the confidentiality, integrity, and availability of information in organizations at risk. Still, several areas remained unexplored, including the role of employees’ evaluation of the organizational systems and the role of value orientation at work as precursors of secure and insecure actions in relation to information technologies (information security [IS] action). The objective of this research project was to examine how the evaluations of formal and informal security norms are associated with the intention to follow them …
An Information-Theoretic Analysis Of Generative Adversarial Networks For Image Restoration In Physics-Based Vision, Xudong Kang
An Information-Theoretic Analysis Of Generative Adversarial Networks For Image Restoration In Physics-Based Vision, Xudong Kang
Lingnan Theses (MPhil & PhD)
Image restoration in physics-based vision (such as image denoising, dehazing, and deraining) are fundamental tasks in computer vision that attach great significance to the processing of visual data as well as subsequent applications in different fields. Existing methods mainly focus on exploring the physical properties and mechanisms of the imaging process, and tend to use a deconstructive idea in describing how the visual degradations (like noise, haze, and rain) are integrated with the background scenes. This idea, however, relies heavily on manually engineered features and handcrafted composition models, which can be theories only in ideal conditions or hypothetical models that …
Cybersecurity Educational Resources For K-12, Debra Bowen, James Jaurez, Nancy Jones, William Reid, Christopher Simpson
Cybersecurity Educational Resources For K-12, Debra Bowen, James Jaurez, Nancy Jones, William Reid, Christopher Simpson
Journal of Cybersecurity Education, Research and Practice
There are many resources to guide successful K-12 cybersecurity education. The objective of these resources is to prepare skilled and ethical cybersecurity students at the earliest level to meet the demands of higher-level programs. The goal of this article is to provide, as a starting point, a list of as many currently popular K-12 educational resources as possible. The resources provided are broken into five categories: 1) Career Information, 2) Curriculum, 3) Competitions, 4) CyberCamps, and 5) Labs and Gaming. Each resource listed has a link, the K-12 levels that are supported, whether the resource is free or has a …
Digital Contact Tracing And Privacy, Mahdi Nasereddin, Edward J. Glantz, Galen A. Grimes, Joanne Peca, Michelle Gordon, Mike Bartolacci
Digital Contact Tracing And Privacy, Mahdi Nasereddin, Edward J. Glantz, Galen A. Grimes, Joanne Peca, Michelle Gordon, Mike Bartolacci
Journal of Cybersecurity Education, Research and Practice
Digital contact tracing tools were developed to decrease the spread of COVID-19 by supplementing traditional manual methods. Although these tools have great potential, they were developed rather quickly resulting in tools with varying levels of success. The main issues with these tools are over privacy and who might have access to the information gathered. In general, their effectiveness varied globally, where users expressed privacy concerns associated with sharing identity, illness, and location information. This paper reviews these issues in deployments across Asia, Europe, and the United States. The goal is to begin a discussion that improves the design and development …
Security Simulations In Undergraduate Education: A Review, Joseph Simpson, Aaron Brantly
Security Simulations In Undergraduate Education: A Review, Joseph Simpson, Aaron Brantly
Journal of Cybersecurity Education, Research and Practice
Several decades of research in simulation and gamification in higher education shows that simulations are highly effective in improving a range of outcomes for students including declarative knowledge and interest in the topic being taught. While there appears to be a broad array of options to provide education in an undergraduate setting related to security, no previous reviews have explored computer-based simulations covering all facets of security. Given the increasing importance and adoption of interdisciplinary educational programs, it is important to take stock of simulations as a tool to broaden the range of problems, perspectives, and solutions presented to students. …
Assessing The Practical Cybersecurity Skills Gained Through Criminal Justice Academic Programs To Benefit Security Operations Centers (Socs), Lucy Tsado, Jung Seob "Scott" Kim
Assessing The Practical Cybersecurity Skills Gained Through Criminal Justice Academic Programs To Benefit Security Operations Centers (Socs), Lucy Tsado, Jung Seob "Scott" Kim
Journal of Cybersecurity Education, Research and Practice
Private-sector and public-sector organizations have increasingly built specific business units for securing company assets, reputation, and lives, known as security operations centers (SOCs). Depending on the organization, these centers may also be referred to as global security operations centers, cybersecurity operations centers, fusion centers, and corporate command centers, among many other names. The concept of centralized function within an organization to improve an organization’s security posture has attracted both the government and the private sectors to either build their own SOCs or hire third-party SOC companies.
In this article, the need for a multidisciplinary approach to cybersecurity education at colleges …
Learning To Ask Critical Questions For Assisting Product Search, Zixuan Li, Lizi Liao, Tat-Seng Chua
Learning To Ask Critical Questions For Assisting Product Search, Zixuan Li, Lizi Liao, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Product search plays an essential role in eCommerce. It was treated as a special type of information retrieval problem. Most existing works make use of historical data to improve the search performance, which do not take the opportunity to ask for user’s current interest directly. Some session-aware methods take the user’s clicks within the session as implicit feedback, but it is still just a guess on user’s preference. To address this problem, recent conversational or question-based search models interact with users directly for understanding the user’s interest explicitly. However, most users do not have a clear picture on what to …
Empirical Assessment Of Big Data Technology Adoption Factors For Organizations With Data Storage Systems, Ahmad B. Alnafoosi
Empirical Assessment Of Big Data Technology Adoption Factors For Organizations With Data Storage Systems, Ahmad B. Alnafoosi
College of Computing and Digital Media Dissertations
Many organizations have on-premises data storage systems. Data storage systems are evolving in multiple ways. One way is the adoption of Big Data. Big Data is a data storage system with the ability to analyze large volumes, velocity, and a variety of data. Per the Economist, data is now the most valuable resource (Parkins, 2017). Big Data holds the promise of unlocking a substantial value of data stored. Yet many organizations are not implementing Big Data. There is a need to identify key factors affecting adoption for such organizations. The literature review revealed multiple gaps in studied adoption factors (un-studied …
Theory About Factoring Service, Burhan Economy Rexhepi Ek
Theory About Factoring Service, Burhan Economy Rexhepi Ek
International Journal of Business and Technology
Factoring is one of the oldest and common methods of trade fi nance over the world with a long historical development. According to historians, Factoring is originated 4,000 years ago in the days of King Hammurabi of Mesopotamia whereby the fi rst literate societies were developed. Although Mesopotamia no longer exists, many of its great contributions to civilization have endured, including Factoring. The fi rst documented-use of factoring was widespread occurred in the American colonies before the revolution to serve for trade. With the abundance of the North American landscape, colonists cultivated and traded commodities like cott on, fur and …
Soft Wheat Quality Parameters Evaluation By Near Infrared Spectroscopy: From Field To Shelf Analysis, Kliton Bylykbashi
Soft Wheat Quality Parameters Evaluation By Near Infrared Spectroscopy: From Field To Shelf Analysis, Kliton Bylykbashi
International Journal of Business and Technology
Near InfraRed Spectroscopy (NIRS) is a powerful tool that is widely applied in agro-food science and technology research for qualitative as well as quantitative analysis. It is one analytical technique that is taking place in this sector due to its low costs, reliability, rapidity and not invasive / non-destructive nature. NIRS along with chemometric modelling can provide accurate assessment of various grain quality attributes and the chemical composition of grain. The present work investigates the ability of using NIRS for the evaluation of different wheat quality parameters by using a portable spectroradiometer working in Visible – Short Wave InfraRed (Vis-SWIR: …
Types Of Suturing Materials In Oral Surgery, Biljana Evrosimovska
Types Of Suturing Materials In Oral Surgery, Biljana Evrosimovska
International Journal of Business and Technology
Aim: In everyday surgical practice, different types of suturing materials are available. They play an important role in tissue healing, facilitate the process of hemostasis, enable the reconstruction and reunification of tissue whose integrity has been compromised during surgery or trauma. The aim of this study is to examine the reaction of the tissue to different suturing materials, as well as to determine the speed of wound healing and the incidence of complications after their use, in order to prove which of them is most suitable for oral surgery procedure. Material and methods: These researches were done based on analyzes …
Can Democratic Subjectivity Be A Way Out Of Recent Crisis Of Democracy? The Case Of Turkey, Erdem Damar
Can Democratic Subjectivity Be A Way Out Of Recent Crisis Of Democracy? The Case Of Turkey, Erdem Damar
International Journal of Business and Technology
Drawing from poststructuralist perspective with a specific emphasis on agonistic democracy, this paper emphasises on the notion of democratic subjectivity as a possible way out of the contemporary crisis of liberal democracy. The two faces of this crisis will be elaborated in the first part. While the crisis of democracy is largely produced by the implementations of conservative, technocratic and capitalist politics that embrace minimalist approaches to democracy by reducing it into a set of rules to govern politics, it also gains visibility to the emergence of a wide range of counter-mobilisations contesting these neoliberal variants. In that respect, post-structuralist …
Editorial, Michael E. Whitman, Herbert J. Mattord, Hossain Shahriar
Editorial, Michael E. Whitman, Herbert J. Mattord, Hossain Shahriar
Journal of Cybersecurity Education, Research and Practice
Since 2016, it has been the mission of the Journal of Cybersecurity Education, Research, and Practice (JCERP) to be a premier outlet for high-quality information security and cybersecurity-related articles of interest to teaching faculty and students. This is the 12th edition of the (JCERP) and, as ever, we are seeking authors who produce high-quality research and practice-oriented articles focused on the development and delivery of information security and cybersecurity curriculum, innovation in applied scholarship, and industry best practices in information security and cybersecurity in the enterprise for double-blind review and publication. The journal invites submissions on Information Security, Cybersecurity, …
Scenario Acceleration Through Automated Modelling: A Method And System For Creating Traceable Quantitative Future Scenarios Based On Fcm System Modeling And Natural Language Processing, Christopher W.H. Davis
Scenario Acceleration Through Automated Modelling: A Method And System For Creating Traceable Quantitative Future Scenarios Based On Fcm System Modeling And Natural Language Processing, Christopher W.H. Davis
Dissertations and Theses
Scenario planning is used extensively in strategic planning because it helps leaders broaden their perspectives and make better decisions by presenting possible futures in story form. Some of the benefits of using scenarios include breaking away from groupthink, creating better products, acceleration of organization learning and reducing bias. Product development teams, particularly for digital products, are gaining more autonomy in organizations and tend to manage risk by undergoing very short development iterations on their products while leaning on their consumers for feedback -- a process known as agile development. This method tends to limit the perspective of the team and …
Effect Of Monetary Policy Rate On Market Interest Rates In Nigeria: A Threshold And Nardl Approach, Oluwafemi E. Awopegba, Joseph O. Afolabi, Lydia T. Adeoye, Godwin O. Akpokodje
Effect Of Monetary Policy Rate On Market Interest Rates In Nigeria: A Threshold And Nardl Approach, Oluwafemi E. Awopegba, Joseph O. Afolabi, Lydia T. Adeoye, Godwin O. Akpokodje
CBN Journal of Applied Statistics (JAS)
This study examines the effect of monetary policy rate (MPR) on market interest rates in Nigeria. For parsimony, we develop two indexes called the short-term interest rate (SINT) and Lending interest rate (LINT) to represent deposit and lending rates respectively. The nonlinear autoregressive distributed lag (NARDL) and threshold regression models are adopted. The study uses monthly data from 2002:M1 to 2019:M12. The results of the threshold regression model indicate that the degree of the effect of MPR on SINT and LINT above the estimated threshold of 11 and 13 percent respectively is greater and significant than if MPR were to …
Social Dimension Of Inclusive Growth In Ecowas: Implication For Poverty Reduction, Toriola K. Anu, Goerge O. Emmanuel, Ajayi O. Felix
Social Dimension Of Inclusive Growth In Ecowas: Implication For Poverty Reduction, Toriola K. Anu, Goerge O. Emmanuel, Ajayi O. Felix
CBN Journal of Applied Statistics (JAS)
This study investigates the implication of the social dimension of inclusive growth on poverty reduction in Economic Community of West African States (ECOWAS) countries. It specifically examines how social indices of inclusive growth comprising of income inequality, education, and health outcomes affect poverty reduction. The study uses a panel dataset of the six (6) lower-middle income countries in ECOWAS which was analysed via panel Difference Generalised Method of Moment (D-GMM). The results show that GDP per capita exerts significant negative effect on poverty while inequality, education and health outcomes do not show significant effect on poverty. Although, the estimates of …
Effect Of Fdi Inflows On Employment Generation In Selected Ecowas Countries: Heterogeneous Panel Analysis, Timothy A. Aderemi, Olawunmi Omitogun, Bukonla G. Osisanwo
Effect Of Fdi Inflows On Employment Generation In Selected Ecowas Countries: Heterogeneous Panel Analysis, Timothy A. Aderemi, Olawunmi Omitogun, Bukonla G. Osisanwo
CBN Journal of Applied Statistics (JAS)
The aim of this study is to examine the effect of FDI on employment in ECOWAS sub region between 1990 and 2019. The study utilizes a panel autoregressive distributed lag model to analyse the short run and long run relationship between FDI and employment across ECOWAS sub region. In the short run, the impact of FDI on employment is negative and statistically not significant. Meanwhile, in the long run FDI has a positive and statistically significant impact on employment rate. This implies that FDI has the capacity to generate employment in countries in ECOWAS sub region. Therefore, this study recommends …
Impact Of Covid-19 Pandemic On The Nigeria Stock Market: A Sectoral Stock Prices Analysis, Peter A. Adekunle, Yakubu A. Bello, Udochukwu G. Nwachukwu
Impact Of Covid-19 Pandemic On The Nigeria Stock Market: A Sectoral Stock Prices Analysis, Peter A. Adekunle, Yakubu A. Bello, Udochukwu G. Nwachukwu
CBN Journal of Applied Statistics (JAS)
This study examines the impact of the COVID-19 pandemic on sectoral stock prices in Nigeria stock market using daily data covering from February 28, 2020 to June 26, 2020. Applying the autoregressive distributed lag (ARDL) bounds test, the study finds that COVID-19 pandemic had adverse impact on the stock market indices in the short run. Furthermore, the study documents negative response of sectoral stock prices to the pandemic while the stock prices of the banking sub-sector are the worst hit. Compared to the consumer goods, and industrial subsector indices, the speed of adjustment to long run equilibrium is faster for …
Representation Learning In Finance, Ajim Uddin
Representation Learning In Finance, Ajim Uddin
Dissertations
Finance studies often employ heterogeneous datasets from different sources with different structures and frequencies. Some data are noisy, sparse, and unbalanced with missing values; some are unstructured, containing text or networks. Traditional techniques often struggle to combine and effectively extract information from these datasets. This work explores representation learning as a proven machine learning technique in learning informative embedding from complex, noisy, and dynamic financial data. This dissertation proposes novel factorization algorithms and network modeling techniques to learn the local and global representation of data in two specific financial applications: analysts’ earnings forecasts and asset pricing.
Financial analysts’ earnings forecast …
Graph Enabled Cross-Domain Knowledge Transfer, Shibo Yao
Graph Enabled Cross-Domain Knowledge Transfer, Shibo Yao
Dissertations
The world has never been more connected, led by the information technology revolution in the past decades that has fundamentally changed the way people interact with each other using social networks. Consequently, enormous human activity data are collected from the business world and machine learning techniques are widely adopted to aid our decision processes. Despite of the success of machine learning in various application scenarios, there are still many questions that need to be well answered, such as optimizing machine learning outcomes when desired knowledge cannot be extracted from the available data. This naturally drives us to ponder if one …
The Significance Of Sonic Branding To Strategically Stimulate Consumer Behavior: Content Analysis Of Four Interviews From Jeanna Isham’S “Sound In Marketing” Podcast, Ina Beilina
Student Theses and Dissertations
Purpose:
Sonic branding is not just about composing jingles like McDonald’s “I’m Lovin’ It.” Sonic branding is an industry that strategically designs a cohesive auditory component of a brand’s corporate identity. This paper examines the psychological impact of music and sound on consumer behavior reviewing studies from the past 40 years and investigates the significance of stimulating auditory perception by infusing sound in consumer experience in the modern 2020s.
Design/methodology/approach:
Qualitative content analysis of audio media was used to test two hypotheses. Four archival oral interview recordings from Jeanna Isham’s podcast “Sound in Marketing” featuring the sonic branding experts …
Du Undergraduate Showcase: Research, Scholarship, And Creative Works: Abstracts, Emma Aggeler, Elena Arroway, Daisy T. Booker, Justin Bravo, Kyle Bucholtz, Megan Burnham, Nicole Choi, Spencer Cockerell, Rosie Contino, Jackson Garske, Kaitlyn Glover, Caroline Hamilton, Haley Hartmann, Madalyne Heiken, Colin Holter, Leah Huzjak, Alyssa Jeng, Cole Jernigan, Chad Kashiwa, Adelaide Kerenick, Emily King, Abigail Langeberg, Maddie Leake, Meredith Lemons, Alec Mackay, Greer Mckinley, Ori Miller, Guy Milliman, Katherine Miromonti, Audrey Mitchell, Lauren Moak, Megan Morrell, Gelella Nebiyu, Zdenek Otruba, Toni V. Panzera, Kassidy Patarino, Sneha Patil, Alexandra Penney, Kevin Persky, Caitlin Pham, Gabriela Recinos, Mary Ringgenberg, Chase Routt, Olivia Schneider, Roman Shrestha, Arlo Simmerman, Alec Smith, Tessa Smith, Nhi-Lac Thai, Kyle Thurmann, Casey Tindall, Amelia Trembath, Maria Trubetskaya, Zachary Vangelisti, Peter Vo, Abby Walker, David Winter, Grayden Wolfe, Leah York
Du Undergraduate Showcase: Research, Scholarship, And Creative Works: Abstracts, Emma Aggeler, Elena Arroway, Daisy T. Booker, Justin Bravo, Kyle Bucholtz, Megan Burnham, Nicole Choi, Spencer Cockerell, Rosie Contino, Jackson Garske, Kaitlyn Glover, Caroline Hamilton, Haley Hartmann, Madalyne Heiken, Colin Holter, Leah Huzjak, Alyssa Jeng, Cole Jernigan, Chad Kashiwa, Adelaide Kerenick, Emily King, Abigail Langeberg, Maddie Leake, Meredith Lemons, Alec Mackay, Greer Mckinley, Ori Miller, Guy Milliman, Katherine Miromonti, Audrey Mitchell, Lauren Moak, Megan Morrell, Gelella Nebiyu, Zdenek Otruba, Toni V. Panzera, Kassidy Patarino, Sneha Patil, Alexandra Penney, Kevin Persky, Caitlin Pham, Gabriela Recinos, Mary Ringgenberg, Chase Routt, Olivia Schneider, Roman Shrestha, Arlo Simmerman, Alec Smith, Tessa Smith, Nhi-Lac Thai, Kyle Thurmann, Casey Tindall, Amelia Trembath, Maria Trubetskaya, Zachary Vangelisti, Peter Vo, Abby Walker, David Winter, Grayden Wolfe, Leah York
DU Undergraduate Research Journal Archive
Abstracts from the DU Undergraduate Showcase.
Small Business Cybersecurity: A Loophole To Consumer Data, Matthew R. Espinosa
Small Business Cybersecurity: A Loophole To Consumer Data, Matthew R. Espinosa
The Scholar: St. Mary's Law Review on Race and Social Justice
Small businesses and small minority owned businesses are vital to our nation’s economy; therefore legislation, regulation, and policy has been created in order to assist them in overcoming their economic stability issues and ensure they continue to serve the communities that rely on them. However, there is not a focus on regulating nor assisting small businesses to ensure their cybersecurity standards are up to par despite them increasingly becoming a victim of cyberattacks that yield high consequences. The external oversight and assistance is necessary for small businesses due to their lack of knowledge in implementing effective cybersecurity policies, the fiscal …
Prospects For Legal Analytics: Some Approaches To Extracting More Meaning From Legal Texts, Kevin D. Ashley
Prospects For Legal Analytics: Some Approaches To Extracting More Meaning From Legal Texts, Kevin D. Ashley
University of Cincinnati Law Review
No abstract provided.
Active Learning With Cybersecurity, Carole Shook
Active Learning With Cybersecurity, Carole Shook
TFSC Publications and Presentations
A global campus grant was obtained in Spring 2020 to develop modules for Cybersecurity. This presentation encompasses the use of Cyberciege and case studies that require active learning of students.