An Analysis of open security issues of Android interfaces to cloud computing platforms

Smartphone usage is on the rise and some may argue that these devices are ubiquitous in today\u27s society, even among non-technical users. To remain competitive, mobile devices and applications need to quickly perform tasks with as minimal as possible impact on battery life. The emergence of cloud computing, open-source cloud platforms, and cloud-supported ventures such as Apple iCloud and Amazon Silk provide new and promising methods to improve device and application performance. However, little work has been done to examine the security of offloading processing from mobile devices to cloud services and the performance effects of implementing security features. This work aims to answer the questions that arise in securing mobile applications that communicate with the cloud. Via a proof-of-concept application that offloaded resource-intensive computations to an open-source cloud computing platform, the security of cloud computing and Android was studied. It was found that, by following recommended coding practices, the cloud-smartphone security landscape could be significantly improved. Further security enhancements were also recommended and summarized. Additionally, performance was analyzed, and it was found that mobile device applications benefit heavily from cloud support and that features such as secure authentication and encryption do not noticeably impact application performance

Cannabidiol tweet miner: a framework for identifying misinformation In CBD tweets.

As regulations surrounding cannabis continue to develop, the demand for cannabis-based products is on the rise. Despite not producing the psychoactive effects commonly associated with THC, products containing cannabidiol (CBD) have gained immense popularity in recent years as a potential treatment option for a range of conditions, particularly those associated with pain or sleep disorders. However, due to current federal policies, these products have yet to undergo comprehensive safety and efficacy testing. Fortunately, utilizing advanced natural language processing (NLP) techniques, data harvested from social networks have been employed to investigate various social trends within healthcare, such as disease tracking and drug surveillance. By leveraging Twitter data, NLP can offer invaluable insights into public perceptions around CBD, as well as the marketing tactics employed by those marketing such loosely-regulated substances to the general public. Given the lack of comprehensive clinical CBD testing, the various health claims made by CBD sellers regarding their products are highly dubious and potentially perilous, as is evident from the ongoing COVID-19 misinformation. It is therefore critically important to efficiently identify unsupportable claims to guide public health policy and action. To this end, we present our proposed framework, the Cannabidiol Tweet Miner (CBD-TM), which utilizes advanced natural language processing (NLP) techniques, including text mining and sentiment analysis, to analyze the similarities and differences between commercial and personal tweets that mention CBD. CBD-TM enables us to identify conditions typically associated with commercial CBD advertising, or conditions not associated with positive sentiment, that are also absent from personal conversations. Through our technical contributions, including NLP, text mining, and sentiment analysis, we can effectively uncover areas where the public may be misled by CBD sellers. Since the rise in popularity of CBD, advertisements making bold claims about its benefits have become increasingly prevalent. The COVID-19 pandemic created a new opportunity for sellers to promote and sell products that purportedly treat and/or prevent the virus, with CBD being one of them. Although the U.S. Food and Drug Administration issued multiple warnings to CBD sellers, this type of misinformation still persists. In response, we have extended the CBD-TM framework with an additional layer of tweet classification designed to identify tweets that make potentially misleading claims about CBD\u27s efficacy in treating and/or preventing COVID-19. Our approach harnesses modern NLP algorithms, utilizing a transformer-based language model to establish the semantic relationship between statements extracted from the FDA\u27s website that contain false information and tweets conveying similar false claims. Our technical contributions build upon the impressive performance of deep language models in various natural language processing and understanding tasks. Specifically, we employ transfer learning via pre-trained deep language models, enabling us to achieve improved misinformation identification in tweets, even with relatively small training sets. Furthermore, this extension of CBD-TM can be easily adapted to detect other forms of misinformation. Through our innovative use of NLP techniques and algorithms, we can more effectively identify and combat false and potentially harmful claims related to CBD and COVID-19, as well as other forms of misinformation. As the conversations surrounding CBD on Twitter evolve over time, concept drift can occur, leading to changes in the topics being discussed. We observed significant changes within the CBD Twitter data stream with the emergence of COVID-19, introducing a new medical condition associated with CBD that would not have been discussed in conversations prior to the pandemic. These shifts in conversation introduce concept drift into CBD-TM, which has the potential to negatively impact our tweet classification models. Therefore, it is crucial to identify when such concept drift occurs to maintain the accuracy of our models. To this end, we propose an innovative approach for identifying potential changes within social network streams, allowing us to determine how and when these conversations evolve over time. Our approach leverages a BERT-based topic model, which can effectively capture how conversations related to CBD change over time. By incorporating advanced NLP techniques and algorithms, we are able to better understand the changes in topic that occur within the CBD Twitter data stream, allowing us to more effectively manage concept drift in CBD-TM. Our technical contributions enable us to maintain the accuracy and effectiveness of our tweet classification models, ensuring that we can continue to identify and address potentially harmful misinformation related to CBD

Air Force Institute of Technology Research Report 2010

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physic

Biofuels and Food Security

Biofuels development has received increased attention in recent times as a means to mitigate climate change, alleviate global energy concerns and foster rural development. Its perceived importance in these three areas has seen biofuels feature prominently on the international agenda. Nevertheless, the rapid growth of biofuels production has raised many concerns among experts worldwide, in particular with regard to sustainability issues and the threat posed to food security. The UN Secretary General, in his opening remarks to the High-level Segment of the 16th session of the UN Commission on Sustainable Development, stated that: "We need to ensure that policies promoting biofuels are consistent with maintaining food security and achieving sustainable development goals." Aware of a lack of integrated scientific analysis, OFID has commissioned this study, Biofuels and Food Security, which has been prepared by the renowned International Institute for Applied Systems Analysis (IIASA). This seminal research work assesses the impact on developing countries of wide-scale production and use of biofuels, in terms of both sustainable agriculture and food security. The unique feature of this study is that its quantified findings are derived from a scenario approach based on a peer reviewed modelling framework, which has contributed to the work of many scientific fora such as the Intergovernmental Panel on Climate Change (IPCC), and the United Nations (Climate Change and Agricultural Vulnerability, World Summit on Sustainable Development, Johannesburg). One of the key conclusions of the study is that an accelerated growth of first-generation biofuels production is threatening the availability of adequate food supplies for humans, by diverting land, water and other resources away from food and feed crops. Meanwhile, the "green" contribution of biofuels is seen as deceptive, with mainly second-generation biofuels appearing to offer interesting prospects. Sustainability issues (social, economic and environmental), the impact on land use, as well as many risk aspects are amongst the key issues tackled in the research. With the publication of this study, OFID seeks to uphold its time-honored tradition of promoting debate on issues of special interest to developing countries, including the OFID/OPEC Member States

Book of abstracts, 4th World Congress on Agroforestry

International audienc

Water Security and Governance in Catchments

This book addresses several issues on water security and governance, helping readers to understand how the desire for water-secure basins can be accomplished through an interplay of water security, water resources management and water policies. The book contains a collection of 12 papers addressing specific as well as interlinked topics within the Special Issue scope. The editors are grateful to all contributors who made the book a reality