Predicting mobile users’behaviors and locations using dynamic Bayesian networks

This paper studies the traveling location prediction problem for detecting whether mobile users will leave their living area and where they will go.We investigate the hidden connections between users’behaviors in different locations and online social interactions.We combine dynamic Bayesian networks with a majority voting model which is based on social interaction information to estimate the users’behaviors and predict the locations.By analyzing Instagram media records,spanning a period of 3 months,we explore rarely visited locations,which are often ignored as noise in previous research.In comparison,our model,using Instagram data with two existing location prediction models,shows that(1)our location prediction is more accurate and robust in both the general location and the location outside the living area;(2)social relations are instrumental in the location prediction as social interaction information can increase the accuracy of the prediction.

Analyzing the time buffer in the Theory of Constraints based lean operations

This paper uses quantitative methods to estimate the size of the time buffer in lean operations controlled by the Theory of Constraints(TOC).The main focus of the operations system of TOC is the identification and management of constraints.To protect the constraints,they should be buffered with time buffers,which protecting the system’s output from disruptions and fluctuations.Despite the importance of time buffers,the approaches to identifying the size of the time buffer in literature are very empirical.In this paper,a queuing-theory based method is applied to calculate the time buffer sizes.It provides a mathematically exact expression for the coefficient of variation of waiting time for Markov queues.It then applies the concept of isomorphism to approximate the variance of customer waiting time in a general queue.Simulation experiments are conducted to verify the accuracy of approximation.

Using a priority queuing approach to improve emergency department performance

Emergency department over-crowding has been a growing problem throughout the world.This paper presents a practical approach to estimate the waiting times for multi-class patients and apply the approach to reduce the waiting time for high priority patients.Patient flows with different levels of acuity are formulated based on the priority queue models.It derives explicit expressions of the wait time for the Markov queue and uses the concept of isomorphism to approximate the wait time in the general queue.Numerical results with simulation experiments are reported to display the accuracy of the approach.A case study from an emergency department indicates that the proposed approach can efficiently prioritize patient flows in decreasing waiting times.The queuing models have two features.First,the approximation applies to the general priority queues and reduces to the exact results of the Markov priority queue.Second,the models requires no iterative algorithm.

The impact of consistency between the emotional feature of advertising music and brand personality on brand experience

Music in advertising plays a crucial role in making the audience feel beyond the multi-level visual experience.The intrinsic link between brand publicity and advertising music has long been a puzzle.This paper discusses the impact of the consistency between the emotional characteristics of music and brand personality on brand experience and expands the discussion to brand experience under market competition.We use the examples of Canon and Apple for our study.The results shows that:(1)the higher the degree of consistency between the emotional experience from music and brand personality,the greater the positive effect on brand experience;(2)this positive effect is not as significant for functional brands as it is for representative brands;(3)the consistency between the emotional experience from music and brand personality has a greater impact on brand experience for representative brands than functional brands.The results provide practical guidance for branding campaigns.