Consultation Experience in Public Health

Nowadays, students safe in violence area is becoming to a huge problems, from the survey- National Youth Risk Behavior Survey we find that the sexual and dating violence rate is increasing during the past few years.For the willing that we try to reduce the risk of dating and sexual violence, we are going to build some programs and publish them to the society especially the schools to protect our teenagers. As we know that the period for students from high school to the university is a very important time to build their right social norms, we start a program called Green Dot which aims to guide them following the right sexual and dating norms to let them away from these violence.This intervention trial is bystanding-based and randomized in 13 pairs of high schools in Kentucky. Lots of variables are added into this program such as race, gender these based information which may have high relating to the sexual and dating violence and they divide the degree of education of the Green Dot into five levels which is from zero intervention to full educating methods for the intervention. This project aims to find that if the Green Dot education in high school affects the students’ norms positively. We consider the Green Dot education as the exposure to do our survey. Then we choose the Project Time 1 as the unexposure part which the schools their have no Green Dot education forms. Moreover, we choose Project Time 5 as the exposure part which they have full of Green Dot education situation such as lecture form, speech form, post method, training form and etc. That means that the difference between the two parts are the exposure of Green Dot education situation. We hope to see that our program about Green Dot education and dating or sexual violence education can help our high school students build a great social norms and guide them to a right way to treat their partners. Besides, we choose six different variables as gender, race, sexual attractive, free meal plan situation, current relationship and past 12 months relationship (dating) to be our adjusted variables. On the other hand, we use the two scores in our questionnaire to be our predictions. DV_ACC score and IRMS score. These two scores will reflect the students’ opinions and attractions to dating violence and sexual violence. The lower this score, the higher they do not accept these two kinds of violence. Mainly, we try to figure out the relationship between the exposure variables ( The Green Dot education) and these two scores, by the way, we try to find that if these adjusted variables will affect the relationship. This project will help us know an important question: If our Green Dot education program is useful and meaningful to our students’ norm building. Can we reduce the rate of sexual violence by using this intervention as Education or Media way? Nowadays, not only US has so many sexual violence cases, but also in China, the sexual violence situation is so serious that we have to take action to stop that. In US, we have already built the Green Dot program to prevent this bad situation by intervening at school steps. Can our China follow this intervention if the program is effective? That is the meaning of what I do right now

An Exploration of Career-related Information Seeking Behavior on International Graduate Students at University of North Carolina, Chapel Hill

In this study, the researcher conducts semi-structured interviews with sixteen international graduate students at University of North Carolina, Chapel Hill to understand their information seeking behavior when choosing a career path. A detailed investigation of their information needs, information resources, and information barriers is done to understand international graduate students’ academic information use. The result of this study shows that the use of information resources by international graduate students varied between master students and doctoral students. In situations where they had difficulties in defining a career path from their chosen resources, many of them reported their expectation for the campus career consulting services.Master of Science in Information Scienc

POSGen: Personalized Opening Sentence Generation for Online Insurance Sales

The insurance industry is shifting their sales mode from offline to online, in expectation to reach massive potential customers in the digitization era. Due to the complexity and the nature of insurance products, a cost-effective online sales solution is to exploit chatbot AI to raise customers' attention and pass those with interests to human agents for further sales. For high response and conversion rates of customers, it is crucial for the chatbot to initiate a conversation with personalized opening sentences, which are generated with user-specific topic selection and ordering. Such personalized opening sentence generation is challenging because (i) there are limited historical samples for conversation topic recommendation in online insurance sales and (ii) existing text generation schemes often fail to support customized topic ordering based on user preferences. We design POSGen, a personalized opening sentence generation scheme dedicated for online insurance sales. It transfers user embeddings learned from auxiliary online user behaviours to enhance conversation topic recommendation, and exploits a context management unit to arrange the recommended topics in user-specific ordering for opening sentence generation. POSGen is deployed on a real-world online insurance platform. It achieves 2.33x total insurance premium improvement through a two-month global test.Comment: IEEE BigData 202

On the Super-exponential Quantum Speedup of Equivariant Quantum Machine Learning Algorithms with SU(dd) Symmetry

We introduce a framework of the equivariant convolutional algorithms which is tailored for a number of machine-learning tasks on physical systems with arbitrary SU($d$) symmetries. It allows us to enhance a natural model of quantum computation--permutational quantum computing (PQC) [Quantum Inf. Comput., 10, 470-497 (2010)] --and defines a more powerful model: PQC+. While PQC was shown to be effectively classically simulatable, we exhibit a problem which can be efficiently solved on PQC+ machine, whereas the best known classical algorithms runs in $O(n!n^2)$ time, thus providing strong evidence against PQC+ being classically simulatable. We further discuss practical quantum machine learning algorithms which can be carried out in the paradigm of PQC+.Comment: A shorter version established based on arXiv:2112.07611, presented in TQC 202

Some variational recipes for quantum field theories

Rapid developments of quantum information technology show promising opportunities for simulating quantum field theory in near-term quantum devices. In this work, we formulate the theory of (time-dependent) variational quantum simulation of the 1+1 dimensional $\lambda \phi^4$ quantum field theory including encoding, state preparation, and time evolution, with several numerical simulation results. These algorithms could be understood as near-term variational analogs of the Jordan-Lee-Preskill algorithm, the basic algorithm for simulating quantum field theory using universal quantum devices. Besides, we highlight the advantages of encoding with harmonic oscillator basis based on the LSZ reduction formula and several computational efficiency such as when implementing a bosonic version of the unitary coupled cluster ansatz to prepare initial states. We also discuss how to circumvent the "spectral crowding" problem in the quantum field theory simulation and appraise our algorithm by both state and subspace fidelities.Comment: 28 pages, many figures. v2: modified style, add references, clear typos. v3: significant change, authors adde