Saudi Cultural Missions Theses & Dissertations
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Item Restricted DATA-DRIVEN EV CHARGING INFRASTRUCTURE PLANNING: ADAPTIVE SIMULATION AND STRATEGIC DEPLOYMENT IN VIRGINIA(Geroge Mason University, 2024-04-29) Zaylaee, Mohammed; Ji, WenyingAbstract The rapid adoption of electric vehicles (EVs) necessitates innovative approaches to manage and optimize the deployment of EV charging infrastructure. This scholarly paper integrates two complementary studies focusing on the dynamic modeling of EV charging behaviors and the strategic evaluation of charging station coverage in Virginia. The first part of the thesis employs advanced spatial analysis techniques to assess the current network of public EV charging stations in Virginia. Using a comprehensive dataset from Virginia Clean Cities, this analysis identifies regions with insufficient charging facilities, particularly in areas exhibiting high growth potential in the EV market. Techniques such as buffer and coverage analysis are utilized to map and visualize the distribution and capacity of existing infrastructure, thereby pinpointing areas where expansion is most needed. This spatial investigation highlights underserved areas by comparing infrastructure against critical benchmarks, facilitating targeted policy actions to bridge infrastructure gaps. The second part introduces a novel adaptive simulation framework that enhances traditional models by incorporating Bayesian inference with (MCMC). Together, these studies provide a comprehensive approach to understanding and improving the EV charging infrastructure. By combining detailed spatial analysis with adaptive simulation techniques, this scholarly paper offers actionable insights that can drive the sustainable growth of the EV market through more informed decision-making and strategic deployment of resources.191 0Item Open Access TOWARDS A TRANSDISCIPLINARY CYBER FORENSICS GEO-CONTEXTUALIZATION FRAMEWORK(Purdue University Graduate School, 2023-08-04) Mirza, Mohammad Meraj; Karabiyik, UmitTechnological advances have a profound impact on people and the world in which they live. People use a wide range of smart devices, such as the Internet of Things (IoT), smartphones, and wearable devices, on a regular basis, all of which store and use location data. With this explosion of technology, these devices have been playing an essential role in digital forensics and crime investigations. Digital forensic professionals have become more able to acquire and assess various types of data and locations; therefore, location data has become essential for responders, practitioners, and digital investigators dealing with digital forensic cases that rely heavily on digital devices that collect data about their users. It is very beneficial and critical when performing any digital/cyber forensic investigation to consider answering the six Ws questions (i.e., who, what, when, where, why, and how) by using location data recovered from digital devices, such as where the suspect was at the time of the crime or the deviant act. Therefore, they could convict a suspect or help prove their innocence. However, many digital forensic standards, guidelines, tools, and even the National Institute of Standards and Technology (NIST) Cyber Security Personnel Framework (NICE) lack full coverage of what location data can be, how to use such data effectively, and how to perform spatial analysis. Although current digital forensic frameworks recognize the importance of location data, only a limited number of data sources (e.g., GPS) are considered sources of location in these digital forensic frameworks. Moreover, most digital forensic frameworks and tools have yet to introduce geo-contextualization techniques and spatial analysis into the digital forensic process, which may aid digital forensic investigations and provide more information for decision-making. As a result, significant gaps in the digital forensics community are still influenced by a lack of understanding of how to properly curate geodata. Therefore, this research was conducted to develop a transdisciplinary framework to deal with the limitations of previous work and explore opportunities to deal with geodata recovered from digital evidence by improving the way of maintaining geodata and getting the best value from them using an iPhone case study. The findings of this study demonstrated the potential value of geodata in digital disciplinary investigations when using the created transdisciplinary framework. Moreover, the findings discuss the implications for digital spatial analytical techniques and multi-intelligence domains, including location intelligence and open-source intelligence, that aid investigators and generate an exceptional understanding of device users' spatial, temporal, and spatial-temporal patterns.44 0