The phase transition behaviors of the shocked water are investigated by employing an optical transmittance in-situ detection system. Based on the light scattering theory and phase transformation kinetics, the phase transition mechanism of the water under multiple shocks is discussed. The experimental data indicate that the evolution of the transmittance of the shocked water can be broadly divided into three stages: relaxation stage, decline stage, and recovery stage. In the early stage of the phase transition, the new phase particles began to form around the quartz/window interface. It should be mentioned that the water/ice phase boundary seems to move toward the liquid region in one experiment of this work. Due to the new phase core being much smaller than the wavelength of the incident light, the transmittance of the sample within the relaxation stage remains steady. The decline stage can be divided into the rapid descent stage and the slow descent stage in this work, which is considered as the different growth rates of the new phase particle under different shock loadings. The recovery stage is attributed to the emergence of the new phase particles which are bigger than the critical value. However, the influence of the size growth and the population growth of the new phase particles on the transmittance restrict each other, which may be responsible for the phenomenon that the transmittance curve does not return to the initial level.
Cell formation is one of the important problems in design of a cellular manufacturing system. In recent years,many works had been carried out in this active research field. Specially, similarity coe fficient methods had been studied widely to form part-machine cells so as to minimize intercellular part movements, but few of them had considered inŽuence of operation sequences and times on cell formation simultaneously. In this paper, we improve an existing similarity coefficients based on considering the factors of operation sequences and operation times. A feasible and effective operation sequences and times-based similarity coefficient method is presented to solve cell formation problems. The improved method is applied to several examples from literatures and a numerical example with some repeated production processes. The results demonstrate that it is necessary to consider the operation sequences and times into similarity measure between each pair of parts or machines, and the proposed method is valid and available for cell formation in cellular manufacturing system with some repeated operations.
Cross-trained worker assignment has become increasingly important for manufacturing efficiency and flexibility in cellular manufacturing system because of the recent increase in labor cost. Researchers mainly focused on assigning skilled workers to tasks for favorable capacity or cost. However, few of them have recognized the need for skill level enhancement through cross-training to avoid excessive training, especially for workload balance across multiple cells. This study presents a new mathematical programming model aimed at minimum training and maximum workload balance with economical labor utilization, to address the worker assignment problem with a cross-training plan spanning multiple cells. The model considers the trade-off between training expenditure and workload balance to achieve a more flexible solution based on decision-maker’s preference. Considering the computational complexity of the problem, the classical swarm intelligence optimizers, i.e., particle swarm optimization (PSO) and artificial bee colony (ABC), are implemented to search the problem landscape. To improve the optimization performance, a superior tracking ABC with an augmented information sharing strategy is designed to address the problem. Ten benchmark problems are employed for numerical experiments. The results indicate the efficiency and effectiveness of the proposed models as well as the developed algorithms.
Purpose Short-form health science videos have become an important medium for disseminating health knowledge and improving public health literacy. However, the factors that determine viewer engagement are not well understood. This study aims to address this research gap by investigating the association between doctor image features and viewer engagement behavior, building on the personal branding theory and information signaling theory. Design/methodology/approach A sample of 1245 health science short-form videos was collected, and key video features related to doctor images were extracted through manual labeling. Multi-variable regression analysis and SPSS process model were employed to test the hypotheses. Findings The results show that doctor image features are significantly associated with viewer engagement behavior. Videos featuring doctors in medical uniforms receive more viewer likes, comments and shares. Highlighting the doctor's title can increase viewer collections. Videos shot in a home, white wall, or study room setting receive more like, comments and sharing. The doctor's appearance demonstrates a positive nonlinear relationship with viewer likes and comments. Young doctors with title information tend to attract more video collections than older doctors with title information. The positive effect of the doctor's appearance and showing title information, become more significant among male doctors. Originality/value This research provides novel insights into the factors that determine viewer engagement behavior in short-form health science videos. Specific doctor image features can enhance viewer engagement by signaling doctor professionalism. The results also suggest that there may be age and gender biases in viewers' perceptions.
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