'Movie Recommendation Systems Using An Artificial Immune System'

We apply the Artificial Immune System (AIS)technology to the collaborative Filtering (CF)technology when we build the movie recommendation system. Two different affinity measure algorithms of AIS, Kendall tau and Weighted Kappa, are used to calculate the correlation coefficients for this movie recommendation system. From the testing we think that Weighted Kappa is more suitable than Kendall tau for movie problems.

Privacy in data publishing for tailored recommendation scenarios

Personal information is increasingly gathered and used for providing services tailored to user preferences, but the datasets used to provide such functionality can represent serious privacy threats if not appropriately protected. Work in privacy-preserving data publishing targeted privacy guarantees that protect against record re-identification, by making records indistinguishable, or sensitive attribute value disclosure, by introducing diversity or noise in the sensitive values. However, most approaches fail in the high-dimensional case, and the ones that don’t introduce a utility cost incompatible with tailored recommendation scenarios. This paper aims at a sensible trade-off between privacy and the benefits of tailored recommendations, in the context of privacy-preserving data publishing. We empirically demonstrate that significant privacy improvements can be achieved at a utility cost compatible with tailored recommendation scenarios, using a simple partition-based sanitization method.

Recomendr-entity recommendation based on ad-hoc dimensions

The growing availability and popularity of opinion rich resources on the online web resources, such as review sites and personal blogs, has made it convenient to find out about the opinions and experiences of layman people. But, simultaneously, this huge eruption of data has made it difficult to reach to a conclusion. In this thesis, I develop a novel recommendation system, Recomendr that can help users digest all the reviews about an entity and compare candidate entities based on ad-hoc dimensions specified by keywords. It expects keyword specified ad-hoc dimensions/features as input from the user and based on those features; it compares the selected range of entities using reviews provided on the related User Generated Contents (UGC) e.g. online reviews. It then rates the textual stream of data using a scoring function and returns the decision based on an aggregate opinion to the user. Evaluation of Recomendr using a data set in the laptop domain shows that it can effectively recommend the best laptop as per user-specified dimensions such as price. Recomendr is a general system that can potentially work for any entities on which online reviews or opinionated text is available.

'Movie Recommendation Systems Using An Artificial Immune System'

We apply the Artificial Immune System (AIS)technology to the collaborative Filtering (CF)technology when we build the movie recommendation system. Two different affinity measure algorithms of AIS, Kendall tau and Weighted Kappa, are used to calculate the correlation coefficients for this movie recommendation system. From the testing we think that Weighted Kappa is more suitable than Kendall tau for movie problems.

'On the Effects of Idiotypic Interactions for Recommendation Communities in Artificial Immune Systems'

It has previously been shown that a recommender based on immune system idiotypic principles can outperform one based on correlation alone. This paper reports the results of work in progress, where we undertake some investigations into the nature of this beneficial effect. The initial findings are that the immune system recommender tends to produce different neighbourhoods, and that the superior performance of this recommender is due partly to the different neighbourhoods, and partly to the way that the idiotypic effect is used to weight each neighbour's recommendations.

On The Effects of Idiotypic Interactions for Recommendation Communities in Artificial Immune Systems

It has previously been shown that a recommender based on immune system idiotypic principles can outperform one based on correlation alone. This paper reports the results of work in progress, where we undertake some investigations into the nature of this beneficial effect. The initial findings are that the immune system recommender tends to produce different neighbourhoods, and that the superior performance of this recommender is due partly to the different neighbourhoods, and partly to the way that the idiotypic effect is used to weight each neighbour’s recommendations.

The role of context in image annotation and recommendation

With the rise of smart phones, lifelogging devices (e.g. Google Glass) and popularity of image sharing websites (e.g. Flickr), users are capturing and sharing every aspect of their life online producing a wealth of visual content. Of these uploaded images, the majority are poorly annotated or exist in complete semantic isolation making the process of building retrieval systems difficult as one must firstly understand the meaning of an image in order to retrieve it. To alleviate this problem, many image sharing websites offer manual annotation tools which allow the user to “tag” their photos, however, these techniques are laborious and as a result have been poorly adopted; Sigurbjörnsson and van Zwol (2008) showed that 64% of images uploaded to Flickr are annotated with < 4 tags. Due to this, an entire body of research has focused on the automatic annotation of images (Hanbury, 2008; Smeulders et al., 2000; Zhang et al., 2012a) where one attempts to bridge the semantic gap between an image’s appearance and meaning e.g. the objects present. Despite two decades of research the semantic gap still largely exists and as a result automatic annotation models often offer unsatisfactory performance for industrial implementation. Further, these techniques can only annotate what they see, thus ignoring the “bigger picture” surrounding an image (e.g. its location, the event, the people present etc). Much work has therefore focused on building photo tag recommendation (PTR) methods which aid the user in the annotation process by suggesting tags related to those already present. These works have mainly focused on computing relationships between tags based on historical images e.g. that NY and timessquare co-exist in many images and are therefore highly correlated. However, tags are inherently noisy, sparse and ill-defined often resulting in poor PTR accuracy e.g. does NY refer to New York or New Year? This thesis proposes the exploitation of an image’s context which, unlike textual evidences, is always present, in order to alleviate this ambiguity in the tag recommendation process. Specifically we exploit the “what, who, where, when and how” of the image capture process in order to complement textual evidences in various photo tag recommendation and retrieval scenarios. In part II, we combine text, content-based (e.g. # of faces present) and contextual (e.g. day-of-the-week taken) signals for tag recommendation purposes, achieving up to a 75% improvement to precision@5 in comparison to a text-only TF-IDF baseline. We then consider external knowledge sources (i.e. Wikipedia & Twitter) as an alternative to (slower moving) Flickr in order to build recommendation models on, showing that similar accuracy could be achieved on these faster moving, yet entirely textual, datasets. In part II, we also highlight the merits of diversifying tag recommendation lists before discussing at length various problems with existing automatic image annotation and photo tag recommendation evaluation collections. In part III, we propose three new image retrieval scenarios, namely “visual event summarisation”, “image popularity prediction” and “lifelog summarisation”. In the first scenario, we attempt to produce a rank of relevant and diverse images for various news events by (i) removing irrelevant images such memes and visual duplicates (ii) before semantically clustering images based on the tweets in which they were originally posted. Using this approach, we were able to achieve over 50% precision for images in the top 5 ranks. In the second retrieval scenario, we show that by combining contextual and content-based features from images, we are able to predict if it will become “popular” (or not) with 74% accuracy, using an SVM classifier. Finally, in chapter 9 we employ blur detection and perceptual-hash clustering in order to remove noisy images from lifelogs, before combining visual and geo-temporal signals in order to capture a user’s “key moments” within their day. We believe that the results of this thesis show an important step towards building effective image retrieval models when there lacks sufficient textual content (i.e. a cold start).

Removing redundancy for attribute implications in data with grades

Reasoning with if-then rules –in particular, with those taking from of implications between conjunctions of attributes– is crucial in many disciplines ranging from theoretical computer science to applications. One of the most important problems regarding the rules is to remove redundancies in order to obtain equivalent implicational sets with lower size.

Factors influencing the recommendation of the Human Papillomavirus vaccine by South African doctors working in a tertiary hospital.

Background: In South Africa, HPV vaccination programme has been incorporated recently in the school health system. Since doctors are the most trusted people regarding health issues in general, their knowledge and attitudes regarding HPV infections and vaccination are very important for HPV vaccine program nationally. Objective: The objective of this study was to investigate factors contributing to recommendation of HPV vaccines to the patients. Methods: This was a quantitative cross-sectional study conducted among 320 doctors, using a self-administered anonymous questionnaire. Results: All the doctors were aware of HPV and knew that HPV is transmitted sexually. Their overall level of knowledge regarding HPV infections and HPV vaccine was poor. But the majority intended to prescribe the vaccine to their patients. It was found that doctors who knew that HPV 6 and 11 are responsible for >90% of anogenital warts, their patients would comply with the counselling regarding HPV vaccination, and received sufficient information about HPV vaccination were 5.68, 4.91 and 4.46 times respectively more likely to recommend HPV vaccination to their patients, compared to their counterparts (p<0.05). Conclusion: There was a knowledge gap regarding HPV infection and HPV vaccine among the doctors.

Governing the transition to higher levels of education and differences between achievement and school grades by gender

The author will explore the performance of boys and girls in external examinations in Slovenia at the beginning of upper secondary and tertiary education. These are critical points in students’ educational career at which he/she has to choose a school/university. Since both transitions are managed centrally by appropriate authorities, this is also a question of Educational Governance. Transitions between levels of education should, above all, assure fairness in selection procedures. At the point of transition to upper secondary schools we will explore differences between students’ achievements in various school subjects tested at the national assessment of knowledge (NA), and their school grades by gender. Since only school grades are used as admission criteria to upper secondary schools, this comparison of school grades with external and more objective measure of students’ achievement will show possible bias. In Slovenia admission to tertiary education usually consists of (externally assessed) Matura results and school grades in the last two years of upper secondary school. The author will compare the effects of both most commonly used measures of academic achievement on admission in view of gender differences. Study courses where selection procedure was actually applied will be of specific interest since they can show signs of (un)fairness. Results show signs of bias and build case for better Educational Governance. (DIPF/Orig.)

A NARRATIVE CASE STUDY EXAMINING THE EXPEREINCES OF MEN TEACHING SPECIAL EDUCATION IN THE ELEMENTARY GRADES

Over the past several decades, the landscape of the workplace has changed in many industrialized nations. In the United States this time period has seen the outright elimination or outsourcing of well-paying “blue collar” jobs. The workforce continues to evolve, change, and become more global, and men and women are making nontraditional occupational decisions, whether by choice or necessity. The traditional views of men and women have begun to shift. However, gender assumptions about masculinity have failed to keep pace with the shift. There are approximately 1.8 million elementary grade level teachers in United States public schools; of these, a mere 9% are male. The paucity of male teachers in the elementary grades has been a concern for many years. According to the Bureau of Labor Statistics, roughly 86% of all special education teachers are female. In 2012, 86.2% of all special education teachers were female, and by the following year, the number had dropped to 80.4%. The evidence indicates that more men are embarking on nontraditional career paths. Despite theses changes there is minimal research looking at the experiences of men working as special education teachers My goal in this study was to obtain a better understanding of the influences on and the process by which men make the decision to pursuing a career teaching special education in the elementary grades. The study utilized social role theory (Eagly, 1987), and Stead’s (2014) social constructionist theory as well as Williams’ (1992) glass escalator proposition The findings of this study confirm some of the factors related to career choice, experiences and barriers faced by men in nontraditional careers detailed in the literature. Three themes emerged for each research question: Experiences, advocacy, and benefits. Three themes emerged around the second research question exploring the experiences of men in a female-concentrated profession: The male body, communication, and perception. Three themes arose around the third research question: administration, My Masculinity, and pay. The findings run counter to Williams’ glass escalator proposition, which posits men working in female-concentrated professions are at an advantage. The findings advance support for Buschmeyer’s theory of (2013) alternative masculinity.

[Map of the city of Washington : showing the sub-divisions, grades, and the general configuration of the ground /

Cadastral map showing lot lines, lot numbers, and block numbers.

INVESTIGATING THE USE OF MAZE-CBM FOR HIGH SCHOOL STUDENTS

Recent legislation and initiatives set forth high academic expectations for all high school graduates in the area of reading (National Governors Association Center for Best Practices, 2010; Every Student Succeeds Act, 2015). To determine which students need additional support to meet these reading standards, teachers can conduct universal screening using formative assessments. Maze Curriculum-Based Measurement (Maze-CBM) is a commonly used screening and progress monitoring assessment that the National Center on Intensive Intervention (2013) and the Center on Instruction (Torgesen & Miller, 2009) recommend. Despite the recommendation to use Maze-CBM, little research has been conducted on the reliability and validity of Maze-CBM for measuring reading ability for students at the secondary level (Mitchell & Wexler, 2016). In the papers included in this dissertation, I present an initial investigation into the use of Maze-CBM for secondary students. In the first paper, I investigated prior studies of Maze-CBM for students in Grades 6 through 12. Next, in the second paper, I investigated the alternate-form reliability and validity for screening students in Grades 9 and 10 using signal detection theory methods. In the third paper, I examined the effect of genre on Maze-CBM scores with a sample of students in Grades 9 and 10 using multilevel modeling. When writing these three papers, I discovered several important findings related to Maze-CBM. First, there are few studies that have investigated the technical adequacy of Maze-CBM for screening and progress monitoring students in Grades 6 through 12. Additionally, only two studies (McMaster, Wayman, & Cao, 2006; Pierce, McMaster, & Deno, 2010) examined the technical adequacy of Maze-CBM for high school students. A second finding is that the reliability of Maze-CBM is often below acceptable levels for making screening decisions or progress monitoring decisions (.80 and above and .90 and above, respectively; Salvia, Ysseldyke, & Bolt, 2007) for secondary students. A third finding is that Maze-CBM scores show promise of being a valid screening tool for reading ability of secondary students. Finally, I found that the genre of the text used in the Maze-CBM assessment does impact scores on Maze-CBM for students in Grades 9 and 10.

SCOR WG 142: Quality Control Procedures for Oxygen and Other Biogeochemical Sensors on Floats and Gliders. Recommendation for oxygen measurements from Argo floats, implementation of in-air-measurement routine to assure highest long-term accuracy

Recommendation for Oxygen Measurements from Argo Floats: Implementation of In-Air-Measurement Routine to Assure Highest Long-term Accuracy As Argo has entered its second decade and chemical/biological sensor technology is improving constantly, the marine biogeochemistry community is starting to embrace the successful Argo float program. An augmentation of the global float observatory, however, has to follow rather stringent constraints regarding sensor characteristics as well as data processing and quality control routines. Owing to the fairly advanced state of oxygen sensor technology and the high scientific value of oceanic oxygen measurements (Gruber et al., 2010), an expansion of the Argo core mission to routine oxygen measurements is perhaps the most mature and promising candidate (Freeland et al., 2010). In this context, SCOR Working Group 142 “Quality Control Procedures for Oxygen and Other Biogeochemical Sensors on Floats and Gliders” (www.scor-int.org/SCOR_WGs_WG142.htm) set out in 2014 to assess the current status of biogeochemical sensor technology with particular emphasis on float-readiness, develop pre- and post-deployment quality control metrics and procedures for oxygen sensors, and to disseminate procedures widely to ensure rapid adoption in the community.

“To be or not to be retained… Thats' the question!” Retention, self-esteem, self-concept, achievement goals, and grades

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