Reciprocal Recommendation System for Online Dating

Online dating sites have become popular platforms for people to look for potential romantic partners. Different from traditional user-item recommendations where the goal is to match items (e.g., books, videos, etc) with a user's interests, a recommendation system for online dating aims to match people who are mutually interested in and likely to communicate with each other. We introduce similarity measures that capture the unique features and characteristics of the online dating network, for example, the interest similarity between two users if they send messages to same users, and attractiveness similarity if they receive messages from same users. A reciprocal score that measures the compatibility between a user and each potential dating candidate is computed and the recommendation list is generated to include users with top scores. The performance of our proposed recommendation system is evaluated on a real-world dataset from a major online dating site in China. The results show that our recommendation algorithms significantly outperform previously proposed approaches, and the collaborative filtering-based algorithms achieve much better performance than content-based algorithms in both precision and recall. Our results also reveal interesting behavioral difference between male and female users when it comes to looking for potential dates. In particular, males tend to be focused on their own interest and oblivious towards their attractiveness to potential dates, while females are more conscientious to their own attractiveness to the other side of the line

WEBWORK PROBLEMS FOR STAT

WeBWorK is an online homework system which is used mainly for mathematics and science. We developed a new package for WeBWorK and implemented it into WEBWorK with our new learning model. We also applied the model by designing homework problems for an introductory statistics course and conducted two experiments to test their effects

Q-Polynomial Association schemes with Irrational Eigenvalues

We work towards classifying the feasible parameter sets of irrational Q-polynomial association schemes with three classes. We aimed to provide a synopsis of the subject as well as provide some theorems and conjectures to understand these combinatorial objects

IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning

Current visual question answering (VQA) tasks mainly consider answering human-annotated questions for natural images. However, aside from natural images, abstract diagrams with semantic richness are still understudied in visual understanding and reasoning research. In this work, we introduce a new challenge of Icon Question Answering (IconQA) with the goal of answering a question in an icon image context. We release IconQA, a large-scale dataset that consists of 107,439 questions and three sub-tasks: multi-image-choice, multi-text-choice, and filling-in-the-blank. The IconQA dataset is inspired by real-world diagram word problems that highlight the importance of abstract diagram understanding and comprehensive cognitive reasoning. Thus, IconQA requires not only perception skills like object recognition and text understanding, but also diverse cognitive reasoning skills, such as geometric reasoning, commonsense reasoning, and arithmetic reasoning. To facilitate potential IconQA models to learn semantic representations for icon images, we further release an icon dataset Icon645 which contains 645,687 colored icons on 377 classes. We conduct extensive user studies and blind experiments and reproduce a wide range of advanced VQA methods to benchmark the IconQA task. Also, we develop a strong IconQA baseline Patch-TRM that applies a pyramid cross-modal Transformer with input diagram embeddings pre-trained on the icon dataset. IconQA and Icon645 are available at https://iconqa.github.io.Comment: Corrected typos. Accepted to NeurIPS 2021, 27 pages, 18 figures. Data and code are available at https://iconqa.github.i

Current-driven magnetization switching in a van der Waals ferromagnet Fe3GeTe2

The recent discovery of ferromagnetism in two-dimensional (2D) van der Waals (vdW) materials holds promises for novel spintronic devices with exceptional performances. However, in order to utilize 2D vdW magnets for building spintronic nanodevices such as magnetic memories, key challenges remain in terms of effectively switching the magnetization from one state to the other electrically. Here, we devise a bilayer structure of Fe3GeTe2/Pt, in which the magnetization of few-layered Fe3GeTe2 can be effectively switched by the spin-orbit torques (SOTs) originated from the current flowing in the Pt layer. The effective magnetic fields corresponding to the SOTs are further quantitatively characterized using harmonic measurements. Our demonstration of the SOT-driven magnetization switching in a 2D vdW magnet could pave the way for implementing low-dimensional materials in the next-generation spintronic applications

Can the use of a rapid nutrition screening tool facilitate timely dietetic referrals on the acute renal wards? : A validation study : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Nutrition and Dietetics at Massey University, Albany, New Zealand

Background: The percentage of malnourished patients in the acute renal hospital wards has been reported as 52.6% and associated with increased hospital stay and morbidity. There are currently no published nutrition screening tools that are sensitive enough to detect undernutrition risk in this patient group. Aim: To develop and validate a rapid nutrition screening tool that is sensitive and specific to recognise renal inpatients at undernutrition risk. Method: The renal nutrition screening tool (R-NST) was modified from the malnutrition screening tool (MST) that has been validated in the acute care setting. It includes the traditional risk variables such as involuntary weight loss and reduction in food intake, as well as biochemical measures to increase the effectiveness of recognising undernutrition risk. It was designed in three simple, accumulative steps. The new R-NST was validated using a prospective, blind comparison to a gold standard study design (N = 122). The undernutrition risk of each participant identified by the research assistants using the RNST was compared to the nutritional status independently assessed by the researchers using the 7-point subjective global assessment (SGA) as a gold standard and hand grip strength (HGS) as a functional indicator. The R-NST was autonomously undertaken by nursing staff to determine its feasibility as a routine screening on ward level. Results: The SGA and R-NST tools classified 63.9% and 68.0% of participants as malnourished or at undernutrition risk, respectively. The R-NST was valid to detect undernutrition risk (sensitivity = 97.3%, specificity = 74.4%, positive predictive value (PPV) = 88.0%, negative predictive value (NPV) = 93.6%) compared to the SGA. The HGS in malnourished participants were lower than those that are well nourished in either women (p = 0.001) or participants aged under 65 years (p = 0.009). The R-NST showed ability to recognise participants requiring dietetic intervention due to their renal conditions. The compliance rate in the R-NST screening by the nursing staff was low (22.6%). Conclusion: The R-NST is a good diagnostic tool for identifying acute renal patients at undernutrition risk and facilitating timely dietetic referral. Further research is warranted to explore innovative yet effective interventions to enhance nutrition screening compliance in ward practice