Protecting Your Search Privacy: A Lesson Plan

Each year search engines like Google, Bing and Yahoo, complete trillions of search queries online. Students are especially dependent on these search tools because of their popularity, convenience and accessibility. However, what students are unaware of, by choice or naiveté is the amount of personal information that is collected during each search session, how that data is used and who is interested in their online behavior profile. Privacy policies are frequently updated in favor of the search companies but are lengthy and often are perused briefly or ignored entirely with little thought about how personal web habits are being exploited for analytics and marketing. As an Information Literacy instructor, and a member of the Electronic Frontier Foundation, I believe in the importance of educating college students and web users in general that they have a right to privacy online. Class discussions on the topic of web privacy have yielded an interesting perspective on internet search usage. Students are unaware of how their online behavior is recorded and have consistently expressed their hesitancy to use tools that disguise or delete their IP address because of the stigma that it may imply they have something to hide or are engaging in illegal activity. Additionally, students fear they will have to surrender the convenience of uber connectivity in their applications to maintain their privacy. The purpose of this lightning presentation is to provide educators with a lesson plan highlighting and simplifying the privacy terms for the three major search engines, Google, Bing and Yahoo. This presentation focuses on what data these search engines collect about users, how that data is used and alternative search solutions, like DuckDuckGo, for increased privacy. Students will directly benefit from this lesson because informed internet users can protect their data, feel safer online and become more effective web searchers.

TR-2015001: A Survey and Critique of Facial Expression Synthesis in Sign Language Animation

Sign language animations can lead to better accessibility of information and services for people who are deaf and have low literacy skills in spoken/written languages. Due to the distinct word-order, syntax, and lexicon of the sign language from the spoken/written language, many deaf people find it difficult to comprehend the text on a computer screen or captions on a television. Animated characters performing sign language in a comprehensible way could make this information accessible. Facial expressions and other non-manual components play an important role in the naturalness and understandability of these animations. Their coordination to the manual signs is crucial for the interpretation of the signed message. Software to advance the support of facial expressions in generation of sign language animation could make this technology more acceptable for deaf people. In this survey, we discuss the challenges in facial expression synthesis and we compare and critique the state of the art projects on generating facial expressions in sign language animations. Beginning with an overview of facial expressions linguistics, sign language animation technologies, and some background on animating facial expressions, a discussion of the search strategy and criteria used to select the five projects that are the primary focus of this survey follows. This survey continues on to introduce the work from the five projects under consideration. Their contributions are compared in terms of support for specific sign language, categories of facial expressions investigated, focus range in the animation generation, use of annotated corpora, input data or hypothesis for their approach, and other factors. Strengths and drawbacks of individual projects are identified in the perspectives above. This survey concludes with our current research focus in this area and future prospects.