DNA Steganography

Cryptography and Steganography are the two popular methods available to provide security. The former distorts the message and the latter itself hides the existence of the message. Using cryptography, the data is transformed into some other gibberish form and then the encrypted data is transmitted. In steganography, the data is embedded in an image file and the image file is transmitted. In the present, DNA has been widely used in cryptography and steganography. DNA Cryptography can be defined as hiding data in terms of DNA Sequence. In this research endeavor, we will present a new technique for DNA Cryptography and DNA Steganography

A Comparative Study of Neural Networks and Logistic Regression for High Energy Physics

Neural networks are programs that run based on machine learning algorithms and resources to mirror the function of the brain in its roughest capacity. Neural networks are used primarily for the management and manipulation of large quantities data to form classifications, more efficient searches, and prediction of the data. Neural networks exist as part of the larger field of machine learning that exists. Linear regression in turn serves as the statistics based solution to the classification issue, an alternative to neural networks that are also a form of machine learning. The focus of this research was to observe whether neural networks or linear regression models are more effective for classification of a supersymmetry dataset. The supersymmetry dataset is made up of the results gathered particle collision events within a particle accelerator. Supersymmetry itself is a theory within particle physics that suggests the particles that are absent in the standard model are symmetric, or balancing, counterparts to the particles that have been already discovered

Machine learning evaluations using WEKA : Honors Thesis, Spring 2020

Computer science is a growing field and machine learning is a growing area withincomputer science. The development of various machine learning algorithms that have beencreated has been diverse. Using WEKA, the study used the mammography dataset to examinemachine learning algorithms to explain what components of the machine learning algorithmsmay affect performance. The logistic regression model classified the most instances of theprovided partitioned mammogram dataset. Results indicated an expansion in the assortment ofmachine learning algorithms would be employed generating a larger collection of models

River Report. State of the Lower St. Johns River Basin, Florida: Water Quality, Fisheries, Aquatic Life, Contaminants, 2022.

https://digitalcommons.unf.edu/sotr/1012/thumbnail.jp

Local Flood Risk Management Strategies in England: Patterns of Application

In England, the Flood and Water Management Act 2010 provides specific roles for Lead Local Flood Authorities in flood and coastal erosion risk management. Under Section 9 of the Act, authorities are responsible for preparing, applying and monitoring a local flood risk management strategy that balances community input into flood management with national policy objectives. Authorities are legally obliged to consider specified requirements in strategy production, including consultation with the public. Using an evaluative framework based on legal requirements and local government guidelines, this article assesses the extent to which these requirements have been met in a sample of 43 strategies. Our findings suggest that strategies generally meet minimal legal requirements, although variance exists in approaches adopted, particularly in respect of consultation and links to other environmental management aspects. Recommendations for enhancing future practice are provided

Ethical dimensions of user centric regulation

In this paper, we question the role of information technology (IT) designers in IT regulation. Through our concept of user centric regulation (UCR) we unpack what a closer alignment of IT design and regulation could mean. We also situate how they can respond to their ethical and legal duties to end users. Our concept asserts that human computer interaction (HCI) designers are now regulators and as designers are not traditionally involved in the practice of regulation hence the nature of their role is ill-defined. We believe designers need support in understanding what their new role entails, particularly managing ethical dimensions that go beyond law and compliance. We use conceptual analysis to consolidate perspectives from across Human Computer Interaction and Information Technology Law and Regulation, Computer Ethics, Philosophy of Technology, and beyond. We focus in this paper on the importance of mediation and responsibility and illustrate our argument by drawing on the emerging technological setting of smart cities

Universities and public libraries supporting student success: an exploratory study

As universities seek new ways to engage and support students in their learning, in Australia, students from regional and remote areas pose a challenge for universities given their geographical, social and technological isolation compared with their metropolitan counterparts. Much of the literature that address challenges associated with distance learning focus on teaching, course design and ways of accessing learning materials. Little is known about the provision of learning support services. Public libraries are well placed within their communities to assist university students with their learning needs. The aim of this research was to explore the idea of universities and public library services working together to support regional student success. The University of Southern Queensland, provided the context for this study. Semi-structured interviews with representatives from public library services in regional areas of Queensland were conducted to find out what service is currently being provided to students; challenges, opportunities and related issues. Thematic analysis was used to identify themes that told the ‘story’ within the data. Findings suggest there is an opportunity for universities and public libraries to work together to support regional student success, and that this opportunity is worthy of further discussion and exploration

An interdisciplinary system dynamics model for post-disaster housing recovery

Many previous disasters have demonstrated the need for extensive personal, public, and governmental expenditures for housing recovery highlighting the importance of studying housing recovery. Yet, much research is still needed to fully understand the multi-faceted and complex nature of housing recovery. The goal of this paper is to present a holistic model to further the understanding of the dynamic processes and interdependencies of housing recovery. The impetus for this work is that inequalities in housing recovery could be addressed more effectively if we better understood interconnected factors and dynamic processes that slow down recovery for some. Currently, there is a lack of understanding about such factors and processes. Literature from engineering and social sciences was reviewed to develop an integrated system dynamics model for post-disaster housing recovery. While it is beyond current capabilities to quantify such complexities, the presented model takes a major stride toward articulating the complex phenomenon that is housing recovery

Recommendations for improving public engagement with pre-incident information materials for initial response to a chemical, biological, radiological or nuclear (CBRN) incident: a systematic review

The risk of chemical, biological, radiological and nuclear (CBRN) incidents has increased in recent years, due to advances in technology, and increased willingness of terrorists to use unconventional weapons. There are basic actions which can reduce or prevent harm during such incidents. The speed with which these actions can be taken may be enhanced by providing pre-incident public information about how to undertake such actions. However, limited research has been carried out to identify potential benefits of providing pre-incident information in relation to preparing for and responding to terrorist attacks, including those involving CBRN agents. This paper presents findings from a systematic literature review which aimed to: examine potential efficacy of pre-incident information campaigns for improving public preparedness for CBRN incidents; identify what information should be included within public preparedness campaigns for CBRN incidents; and identify the best method(s) of providing pre-incident information for CBRN incidents. The review was carried out using Ovid, and selection and screening of papers followed a PRISMA framework. Findings showed that providing a pre-incident educational intervention generally resulted in an improvement in preparedness, compared to not providing any information. However, the majority of studies focused on improving preparedness behaviour in the immediate or short-term (<1 month). It is therefore unclear whether any improvement in preparedness is sustainable over the medium to longer-term. Further research is required to examine to what extent public information campaigns can improve public preparedness over the longer-term, and how best to enhance preparedness for CBRN incidents specifically