How the Legal System Can Help Millions Retire: A Call for Improved Application of the Suitability Standard

An increased awareness in legal circles of the value of aggressive investments is necessary and the recommended solution should have two divergent effects on broker liability. On one hand, a broker who recommends growth investments should find his potential liability has decreased because the legal profession no longer solely focuses on financial loss. On the other hand, a broker who invests conservatively should discover his liability has potentially increased because his recommendations may not be in the client’s best interest. The value of both of these effects is that it causes brokers to have a substantially greater incentive to invest aggressively enough to help millions of Americans come closer to their goal of retirement

Structure Selection from Streaming Relational Data

Statistical relational learning techniques have been successfully applied in a wide range of relational domains. In most of these applications, the human designers capitalized on their background knowledge by following a trial-and-error trajectory, where relational features are manually defined by a human engineer, parameters are learned for those features on the training data, the resulting model is validated, and the cycle repeats as the engineer adjusts the set of features. This paper seeks to streamline application development in large relational domains by introducing a light-weight approach that efficiently evaluates relational features on pieces of the relational graph that are streamed to it one at a time. We evaluate our approach on two social media tasks and demonstrate that it leads to more accurate models that are learned faster

A COLLABORATIVE FILTERING APPROACH TO PREDICT WEB PAGES OF INTEREST FROMNAVIGATION PATTERNS OF PAST USERS WITHIN AN ACADEMIC WEBSITE

This dissertation is a simulation study of factors and techniques involved in designing hyperlink recommender systems that recommend to users, web pages that past users with similar navigation behaviors found interesting. The methodology involves identification of pertinent factors or techniques, and for each one, addresses the following questions: (a) room for improvement; (b) better approach, if any; and (c) performance characteristics of the technique in environments that hyperlink recommender systems operate in. The following four problems are addressed:Web Page Classification. A new metric (PageRank × Inverse Links-to-Word count ratio) is proposed for classifying web pages as content or navigation, to help in the discovery of user navigation behaviors from web user access logs. Results of a small user study suggest that this metric leads to desirable results.Data Mining. A new apriori algorithm for mining association rules from large databases is proposed. The new algorithm addresses the problem of scaling of the classical apriori algorithm by eliminating an expensive joinstep, and applying the apriori property to every row of the database. In this study, association rules show the correlation relationships between user navigation behaviors and web pages they find interesting. The new algorithm has better space complexity than the classical one, and better time efficiency under some conditionsand comparable time efficiency under other conditions.Prediction Models for User Interests. We demonstrate that association rules that show the correlation relationships between user navigation patterns and web pages they find interesting can be transformed intocollaborative filtering data. We investigate collaborative filtering prediction models based on two approaches for computing prediction scores: using simple averages and weighted averages. Our findings suggest that theweighted averages scheme more accurately computes predictions of user interests than the simple averages scheme does.Clustering. Clustering techniques are frequently applied in the design of personalization systems. We studied the performance of the CLARANS clustering algorithm in high dimensional space in relation to the PAM and CLARA clustering algorithms. While CLARA had the best time performance, CLARANS resulted in clusterswith the lowest intra-cluster dissimilarities, and so was most effective in this regard

The Humanitarian Monarchy Legislates: The International Committee of the Red Cross and Its 161 of Customary International Humanitarian Law

As the final course in the education “University Diploma Programme for Process Operators” there is a thesis in cooperation with a company required.This thesis is about operator maintenance and 5S made at Metsä Board in Husum.In this report you can read my opinions and conclusions based on literature studies and the interviews that have been made with the staff at PM6 (the paper machine).I chose to focus on the theory of lean, 5S and operator maintenance because it covers the area of this thesis.The operators shall do their rounds to make sure that the equipment works fine. They shall also write down things that they notice in a checklist. This is not done as it should be and the question is: can this be solved by using 5S?My conclusion of this thesis are:Better review of the task so that everyone is involved. The equipment should be clearly marked, and to digitize - for example, with an NFC tag the checklist is automatically filled in by the operator standing nearby the machine. The motivation of the operators will be increased if they are given feedback and clear objectives