Thesis (M.S. in Computer Science)--Naval Postgraduate School, September 2009. / Thesis Advisor(s): Martell, Craig H. "September 2009." Description based on title screen as viewed on November 9, 2009. Includes bibliographical references (p. 77). Also available in print.

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Indiana University-Purdue University Indianapolis (IUPUI) / Tailoring messages is the process of customizing messages that are more relevant for the receiver, with the aim of improving the recipient’s engagement with and understanding about information in the message. Little research has been done to look at tailored messages in technical communication about healthcare technology, even though the use of technology in healthcare, and the complexity of that technology, continues to increase. Research was performed to investigate if students who plan to work in the healthcare technology field can demonstrate an understanding about tailoring messages and can tailor messages in their technical communication. A four-phase Action Research Cycle for inquiry into teaching and learning was used to modify course materials and analyze work for six assignments submitted by 14 students enrolled in Technical Communication for the Health Care Professions, TCM 38000, during the 2015 spring semester. Although TCM 38000 has always been open to students in other majors, the majority of students who take the course are in the Health Engineering Technology Management (HETM) program at Purdue’s School of Engineering and Technology on the campus of Indiana University Purdue University Indianapolis (IUPUI) in Indianapolis. Overall, the modifications made to TCM 38000 were successful in helping students begin to learn about tailoring messages and create messages tailored for a specific end-user in their technical communication developed for some course assignments. In their Reflections for a User Manual assignment, the majority of students explained that they used what they learned through course materials and discussions to reach beyond their learning and come up with techniques for tailoring messages on their own. Students used word choice, information content and role-play techniques to determine the end-user’s information needs and then to tailor messages in their manuals to address those needs. After reflecting on the results of the research, some course materials will be modified so that students can gain a deeper understanding about tailoring messages and can have more opportunities to practice writing tailored messages in course assignments. Research implications expand beyond the classroom into workplace training for organizations that have both technical and non-technical employees that must effectively communicate.

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

International Telemetering Conference Proceedings / October 13-16, 1986 / Riviera Hotel, Las Vegas, Nevada / Transaction messages are those which control action at a remote point. They are used in communication networks for such functions as surveillance of alarms, performance monitoring, administration of data bases and tests of leased circuits. Generic interface requirements permit full compatibility of a wide range of telecommunications equipment with common operations systems. The specifications cover all aspects of the interface, from connectors to messages. Existing commercial standards are used where appropriate, including those of the Open System Interconnection (OSI) model. This paper covers the methods used to define the requirements and reports on the status of work in various standards groups.

published_or_final_version / abstract / Linguistics / Master / Master of Philosophy

The dissertation examines the use of background appeals in campaign messages. I argue that background appeals allow campaigns to meet two seemingly conflicting incentives in the same message—the incentive to reduce voters’ uncertainty about their candidate, and the incentive to remain ambiguous in their issue positions. Background appeals allow voters to know more about a candidate and develop more certainty about what he will do in office. At the same times, campaigns can achieve this goal while avoiding specific policy commitments, which, on controversial issues, might repel a significant part of the electorate. I test my argument by examining how campaigns plan on using candidates’ backgrounds by interviewing a sample of political consultants. The consultants I interviewed make the candidate’s background a top priority in developing a message plan for their clients. They want to show voters “who their candidate is” as a means of developing likeability and credibility with voters. As expected, campaigns use background appeals frequently, in nearly 80% of advertisements aired by US Senate campaigns in 2000 and 2002. But in these appeals, campaigns avoid specifically connecting their candidate to particular policies. Also, the appeal of ambiguity is so great that campaigns only use more specific background appeals when discussing the opponent’s background. Background appeals can have a positive effect on perceptions of a candidate. Using an experimental design, I vary the background of a mock candidate for Congress while holding constant his issue position. Respondents regard the candidate more favorably when they learn about his occupation than when they receive no such information. / text

The United Colors of Benetton is a high-end clothing company that has been deemed as an iconic brand because of their non-traditional print advertisements. From the late 1980s to the early 1990s, the Benetton campaign used photographic images to symbolize social (and sometimes controversial) messages pertaining to race, gender, religion, sexuality and multiculturalism. Benetton claims that their advertising campaign sought to promote diversity, worldwide. However, others believed that their true motive was to gain revenue by placing sensitive social, political cultural issues and messages into an exchange system. The varieties in opinions about Benetton’s motives are highly dependent on how consumers interpret their advertisements. This paper will not only examine the ways in which consumers encode and decode social messages in Benetton’s print advertisements, but will also attempt to understand the process of attitudinal change through a theoretical approach by using discourse analysis. Further recommendations will be given that detail the importance of how consumers can become more active in their participation of encoding and decoding messages by the use of media literacy. / text

A dissertation submitted in partial ful llment of the requirements for the degree Master of Science. School of Computer Science and Applied Mathematics, Faculty of Science, University of the Witwatersrand, Johannesburg. November 2017 / In the cyberspace, spam emails are used as a way to divulge sensitive information of victims through social engineering. There are various classi cation systems that have been employed previously to identify spam emails. The primary objective of email spam classi cation systems is to classify incoming email as either legitimate (non-spam) or spam emails. The spam classi cation task can thus be regarded as a two-class classi cation problem. This kind of a problem involves the use of various classi ers such as Decision Trees (DTs) and Support Vector Machines (SVMs). DTs and SVMs have been shown to perform well on email spam classi cation tasks. Several studies have failed to mention how these classi ers were optimized in terms of their hyperparameters. As a result, poor performance was encountered with complex datasets. This is because SVM classi er is dependent on the selection of the kernel function and the optimization of kernel hyperparameters. Additionally, many studies on spam email ltering task use words and characters to compute Term-Frequency (TF) based feature space. However, TF based feature space leads to sparse representation due to the continuous vocabulary growth. This problem is linked with the curse of dimensionality. Overcoming dimensionality issues involves the use of feature reduction techniques. Traditional feature reduction techniques, for instance, Information Gain (IG) may cause feature representations to lose important features for identifying spam emails. This proposed study demonstrates the use of Distributed Memory (DM), Distributed Bag of Words (DBOW), Cosine Similarity (CS) and Autoencoder for feature representation to retain a better class separability. Generated features enable classi ers to identify spam emails in a lower dimension feature space. The use of the Autoencoder for feature reduction led to improved classi cation performance. Furthermore, a comparison of kernel functions and CS measure is taken into consideration to evaluate their impacts on classi ers when employed for feature transformation. The study further shows that removal of more frequent words, which have been regarded as noisy words and stemming process, may negatively a ect the performance of the classi ers when word order is taken into consideration. In addition, this study investigates the performance of DTs and SVM classi ers on the publicly available datasets. This study makes a further investigation on the selection of optimal kernel function and optimization of kernel hyperparameters for each feature representation. It is further investigated whether the use of Stacked Autoencoder as a pre-processing step for multilayer perceptron (MLP) will lead to improved classi cation results. / MT 2018