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2019-04-11
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Information Technology
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- Type:
- Article
- Description/Abstract:
- Devices in the Internet of Things (IoT) have enhanced our ability to automate functions in smart homes and increased our ability to monitor day to day activities regardless of whether we are in our home. Despite these benefits of IoT devices, it is the case that notifications about threats to our home when we are away are typically only sent to one or two people within the home. We proposed enhanced monitoring of threats by allowing temporary access to IoT devices to extended networks of homeowners in situations where primary IoT device owners are not able to address a smartphone notification quickly.
- Creator/Author:
- Agrawal, Dev
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2019-04-11
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- As incessant cyber-attacks on organizations increase in complexity and destructiveness with the aim to disrupt services and steal information, proactive measures are critically needed to mitigate these attacks, cyber security risk assessment tops the list of measures. This study provides an overview of cybersecurity risk assessment, various types of frameworks, and the difference between qualitative and quantitative cybersecurity risk assessments. The aim of this early research is the creation of a hybrid system which integrates an existing cybersecurity risk assessment system based on the NIST framework into the Factor Analysis of Information Risk (FAIR) model, an analytic risk assessment model that enables true quantitative measurement. In this study, we propose a hybrid-assessment tool which will be used to describe and compare the impact of using NIST driven values as inputs for the resistance strength to determine the Loss Event Frequent (LEF) and Annual Loss Expectancy (ALE) of a risk scenario as opposed to using experts’ opinion as user inputs for determination of the LEF and ALE values.
- Creator/Author:
- Gilany, Yahya; Kunapareddy, Vivek; Bakare, Adeyinka, and Said, Hazem
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2019-04-11
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- A great deal of data is generated every day on social media, although this information is used for marketing purposes regularly, it has the potential to serve other purposes, such as in crisis management. This study focuses on collecting data from social media, specifically Twitter, in order to help 911 telecommunicators (floor supervisors, call takers, and dispatchers) to 1) identify Twitter users requesting assistance during a crisis, 2) identify information that may be useful to incidents that were called into 911, and 3) pass the information to the first responders (police, fire, and emergency medical services). Previous research in this area can be summarized into three stages. First, a set of information requirements has been developed that must be satisfied to dispatch first responders and meet their immediate awareness needs. Second, a coding schema has been presented to identify six types of actionable information. Finally, it proposed automated methods based on previous literature which can be used to implement these methods in the future (Kropczynski et al. 2018). This research concentration is on refining social media data by starting with finding local tweets that contain this information and recognize patterns of how it is used. Next, patterns will be used in the development of automated methods in the future. The contribution of this work is extending the coding schema of the 6Ws and put it on an action, develop an interface to view the data of social media separated by the 6Ws. It will begin with just on of the six Ws (Weapons).
- Creator/Author:
- Abdelhalim, Ammar Ahmed
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2019-04-11
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- Depression is a common illness that negatively affects feelings, thoughts and behaviors and can harm regular activities like sleeping. It is a leading cause of disability and many other diseases (Choudhury, et al 2013, Mathur et al, 2016, Watkins et al, 2013). According to WHO (World Health Organization) 1 statistics, more than 300 million people over the world are affected in depression and in each country at least 10% are provided treatment. Poor recognition and treatment of depression may aggravate heart failure symptoms, precipitate functional decline, disrupt social and occupational functioning, and lead to an increased risk of mortality (Cully, et al 2009). Early detection of depression is thus necessary. Unfortunately the rates of detecting and treating depression among those with medical illness are quite low (Egede, 2007). This research proposes a solution of using random forest classifier algorithm to detect and predict detection. A mobile application will be developed in order to collect user data and make prediction.
- Creator/Author:
- Halliday, Nnennaya
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2019-04-11
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- Cloud computing has been one of the major disruptive technology of this century changing the entire face of IT infrastructure across all spectrum. This has led to tremendous development, improvement and cost efficient means of securing IT infrastructures. Virtualization is the backbone driving the numerous cloud solutions and also making them marketable in the pay-as-you-use mechanism for all kind of deployment. This research is focus on improving the security and performance of cloud storage, backup and disaster recovery by evaluating the possibility of eliminating the Recovery Point Objective (RPO) and Recovery Time Objective (RTO). A live synchronization between production and Disaster Recovery (DR) sites is presented. We considered the mechanism behind Virtual Machines (VM) and hypervisor interaction with physical memory on host computers and evaluated the ability of VM to read/write directly to a unified multiple storage locations. Dependencies, requirements and guidelines for implementing this solution would also be analyzed.
- Creator/Author:
- Li, Chengcheng and Efosa, Ogbomo
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2019-04-11
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- Shooting crime is a serious public health problem in the US. The analysis of any historical crime data reveals that crime is non-randomly distributed in time and space. Based on this notion, hot spots policing has gained its momentum to effectively predict future crime locations. Recent studies; however, pointed out that traditional hot spots policing occasionally predict rare crimes such as homicides and shootings due to their less frequent recurring counts in a given place and time (specifically for shorter time periods such as weeks and months). Given this context, we developed a new shooting prediction system (SHOPS) to explore whether recent dynamic/mobility activity patterns of known violent individuals increase the prediction of short-term fatal and non-fatal shootings compared to the traditional hot spots policing. Findings suggest that SHOPS predicts fatal and non-fatal shooting locations more precisely by identifying fewer hotspot locations. Policy implications of the study were discussed in the conclusion section.
- Creator/Author:
- Varlioglu, M. Said and Ozer, Murat
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2019-04-11
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- The principles of minimalist design are evident in much of the technology we use today. This is especially the case with mobile applications. The most successful of which attempt to minimize the amount of user input needed to provide users with the information they are seeking. Although many mobile applications use data gathered by in-system activity such as a GPS to minimize input from users—some systems require user input, such is the case with roommate matching. This study utilizes the RoomUP mobile application as a testbed to define minimal criteria that can be used to gather user input and produce a compatible roommate match. Participatory design with prospective student users is used to reduce the number of variables and provide recommendations for a minimalistic user interface. The resulting prototype is then used to verify that it meets design goals and supports a satisfactory user experience.
- Creator/Author:
- Maddirala, Sumanth
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2019-04-11
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- Virtual Reality’s recent commercialization has created a potential for its implementation into classroom and training environments. Past adoptions of this technology and their efficacy are explored in the literature review. This paper outlines the possibility of combining current VR technology with custom hardware allowing the user to interact with physical and mechanical object within virtual worlds and its implication on the future of kinesthetic learning and training in hazardous or expensive scenarios.
- Creator/Author:
- Keller, Ian
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2019-04-11
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- The healthcare industry is thriving and the abundant amount of data involved raises call for help relating to managing and maintaining them. It becomes a hassle to keep the data in it’s required place and to pull and retrieve whenever necessary. The search for a proper data mining technique to enhance the process is always appreciated and encouraged. Our era is controlled by the upcoming technologies that are fast paced and yield great results. There is always a scope for improvement and optimization. Every individual from every generation has been an avid user of mobile phone and its applications. Healthcare facilities have slowly begun to depend on applications and technologies associated and supported by mobile phones and other networking platforms in order to have everyone within the facility and also the patients who have ties to the facility have access to the information that they are entitled to have.
- Creator/Author:
- Kaushik, Sanjana
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2019-04-11
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- With the prevalence of anxiety, depression, and stress among young adult populations, adaptive and innovative treatment options must be considered for the future. While there are various approaches to mental health treatment, art therapy is one traditional method that has been used to treat the symptoms of mental health disorders across various health contexts and populations. Some art therapists have even integrated information and communication technologies (ICTs) into their practices. With these factors in mind and considering the prominence of ICTs use among student populations, this study seeks to understand how the immersion and presence afforded by one such technology, virtual reality (VR), can impact the outcomes of art therapy practices. Through the use of an arts-based VR application, Tilt Brush, this study compares traditional art therapy methods as they are employed in and outside of VR. Through the comparison of self-reported measures, we can better understand the possibilities and effectiveness of art therapy practices delivered via Tilt Brush VR.
- Creator/Author:
- Schaaf, Andrea
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2019-04-11
- License:
- All rights reserved