Modeling Individual Cyclic Variation in Human Behavior

Cycles are fundamental to human health and behavior. However, modeling cycles in time series data is challenging because in most cases the cycles are not labeled or directly observed and need to be inferred from multidimensional measurements taken over time. Here, we present CyHMMs, a cyclic hidden Markov model method for detecting and modeling cycles in a collection of multidimensional heterogeneous time series data. In contrast to previous cycle modeling methods, CyHMMs deal with a number of challenges encountered in modeling real-world cycles: they can model multivariate data with discrete and continuous dimensions; they explicitly model and are robust to missing data; and they can share information across individuals to model variation both within and between individual time series. Experiments on synthetic and real-world health-tracking data demonstrate that CyHMMs infer cycle lengths more accurately than existing methods, with 58% lower error on simulated data and 63% lower error on real-world data compared to the best-performing baseline. CyHMMs can also perform functions which baselines cannot: they can model the progression of individual features/symptoms over the course of the cycle, identify the most variable features, and cluster individual time series into groups with distinct characteristics. Applying CyHMMs to two real-world health-tracking datasets -- of menstrual cycle symptoms and physical activity tracking data -- yields important insights including which symptoms to expect at each point during the cycle. We also find that people fall into several groups with distinct cycle patterns, and that these groups differ along dimensions not provided to the model. For example, by modeling missing data in the menstrual cycles dataset, we are able to discover a medically relevant group of birth control users even though information on birth control is not given to the model.Comment: Accepted at WWW 201

Choosing the Right Weights: Balancing Value, Strategy, and Noise in Recommender Systems

Many recommender systems are based on optimizing a linear weighting of different user behaviors, such as clicks, likes, shares, etc. Though the choice of weights can have a significant impact, there is little formal study or guidance on how to choose them. We analyze the optimal choice of weights from the perspectives of both users and content producers who strategically respond to the weights. We consider three aspects of user behavior: value-faithfulness (how well a behavior indicates whether the user values the content), strategy-robustness (how hard it is for producers to manipulate the behavior), and noisiness (how much estimation error there is in predicting the behavior). Our theoretical results show that for users, upweighting more value-faithful and less noisy behaviors leads to higher utility, while for producers, upweighting more value-faithful and strategy-robust behaviors leads to higher welfare (and the impact of noise is non-monotonic). Finally, we discuss how our results can help system designers select weights in practice

Factors Affecting Air Traffic Controller’s Weather Dissemination to Pilots

As the number of flights in the United States continues to rise steadily, an equally amplified need for reliability and safety has come to the forefront of aviation research. One of the most alarming trends is the number of general aviation (GA) accidents during severe weather events that occur yearly, with fatalities occurring in more than half of these cases. This study focuses on identifying factors influencing weather dissemination of Air Traffic Controllers (ATC) to GA pilots. Ten factors affecting controllers’ performance during severe weather events were identified through an in-depth literature review including controller mental workload, situation awareness, weather information format and accuracy, weather information needs, weather tool limitations, inaccurate assumption and bias, controller training and expereince, regulatory factor, supervisory factors, and pilot-controller relationship. Recommendation can be developed to address each factors so that aviation safety could be enhanced in severe weather situations

Zipping Towards STEM: Simulation Wind Tunnel

The simulation wind tunnel was created to be integrated into a larger project funded by the National Science Foundation titled Zipping Towards STEM: Integrating Engineering Design into the Middle School Physical Science Curriculum. The goal of this project is to integrate the engineering design process of computer modeling, simulation, rapid prototyping, and testing into the 8th grade level curriculum by letting students design and test their own mini soap box derby cars. The simulation wind tunnel will be used to help the students understand the basics of aerodynamics so they can design an aerodynamic mini soap box derby car. The simulation wind tunnel code and graphics user interface (GUI) were created using MATLAB. This software was selected because the team had the most experience with Matlab and it has the capability of creating a standalone executable. This executable could then be downloaded onto the middle school computers for free without having to purchase MATLAB licenses.The simulation wind tunnel has 2D and 3D capabilities. The 2D functionality will be used to teach the students about aerodynamics by showing airflow around predetermined 2D figures. The 3D functionality will then be used for students to import their own 3D modeled soap box cars into the software to test their design so they can make improvements and then re-test their new and improved design. The software has many visual outputs that help students identify which objects are more aerodynamic than others. These visual outputs include streamlines, velocity field plot, pressure map, and most importantly drag. This software was able to have a balance of speed and accuracy so it can run in a short amount of time to keep the attention of the studentsbut also be accurate enough to be a reliable simulation tool that can be used in the design process. The Zipping Towards STEM curriculum will be tested during the 2016-2017 school year with a select number of Akron Public middle schools. The following year, the program will be spread to all Akron Public schools to help integrate engineering design education. If the program is a success it has the possibility to spread throughout the state and hopefully throughout the nation