A realtime lifelogging solution for iOS devices

Prior lifelogging work was done using specially developed devices such as the Microsoft Sensecam / Vicon Revue or using specially developed Android Phone apps, such as SenseSeer from DCU, FUNF from MIT or Deja-view from Univ. Southampton. In this work, we have developed a first prototype lifelogging tool for use with Apple iOS enabled devices. This tool gathers data using onboard sensors in a non-intrusive manner and sends the sampled life-activities to a server for storage and interaction using a WWW interface

PRE-PURCHASE AND POST-PURCHASE SALES PROMOTIONS ON E-COMMERCE PLATFORMS: THE EFFECTS OF PROMOTIONAL BENEFITS ON CUSTOMER-BASED BRAND EQUITY

This research examines the impacts of electronic commerce platforms\u27 sales promotions\u27 benefits on customer-based brand equity (platform brand awareness and platform brand association) and how these relationships are moderated by the promotion stage. Based on the two functions of sales promotions (stimulation vs. maintenance), we propose a five-benefit framework consisting of exploration, convenience, savings, social bonds and structural bonds. Our results reveal the two functions of sales promotions and the positive effects of the benefits on customer-based brand equity (CBBE). The differences between pre- and post-purchase sales promotions are also significant. We discuss the managerial and theoretical implications of these results at the end

A Variable Neighborhood MOEA/D for Multiobjective Test Task Scheduling Problem

Test task scheduling problem (TTSP) is a typical combinational optimization scheduling problem. This paper proposes a variable neighborhood MOEA/D (VNM) to solve the multiobjective TTSP. Two minimization objectives, the maximal completion time (makespan) and the mean workload, are considered together. In order to make solutions obtained more close to the real Pareto Front, variable neighborhood strategy is adopted. Variable neighborhood approach is proposed to render the crossover span reasonable. Additionally, because the search space of the TTSP is so large that many duplicate solutions and local optima will exist, the Starting Mutation is applied to prevent solutions from becoming trapped in local optima. It is proved that the solutions got by VNM can converge to the global optimum by using Markov Chain and Transition Matrix, respectively. The experiments of comparisons of VNM, MOEA/D, and CNSGA (chaotic nondominated sorting genetic algorithm) indicate that VNM performs better than the MOEA/D and the CNSGA in solving the TTSP. The results demonstrate that proposed algorithm VNM is an efficient approach to solve the multiobjective TTSP

Experiments and simulations of hollow cylinders falling through quiescent liquids

Acknowledgment This work was supported by the National Natural Science Foundation of China (grant numbers: 22078191, 21978165, 22081340412 and 92156020).Peer reviewe

Lattice Boltzmann Phase Field Simulations of Droplet Slicing

ACKNOWLEDGEMENT This research was sponsored by Shanghai Sailing Program (No. 20YF1416000) and SUES Distinguished Overseas Professor Program.Peer reviewedPostprin