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Visualization is primarily utilized as a training method to enhance athletic movement quality, increase concentration power, and minimize competition stress on the player while building firm confidence. Physical literacy (PL) provides a valuable lens for analyzing physical activity (PA) movement in more significant social and affective learning processes. This paper presents an Interactive Visualization positioning in physical education (IVPPE) to deal with the signal fluctuations and positioning techniques in visualizing Deep Neural Network (DNN). To ensure the success of their game, athletes are always looking for new ways to improve their health and performance. Using sensors to keep tabs on training and recovery has become more popular among athletes. Currently, sports teams are using sensors to track both the players’ internal and external workloads. It illustrates the multilayer localizer (MLL) based on transfer learning to improve the positioning accuracy and physical literacy positioning model (PLPM) as a health determinant. A variety of data augmentation techniques are used to combat signal fluctuations. As a result, the combined effects of motivation-promoting physical activity-based visualization improve the accuracy ratio to 96.7%, prediction ratio to 96.2%, efficiency ratio to 96.8%, and reduce the error rate to 18.7%, stress level (52.8%) compared to other conventional models and have a positive impact on the localizer and positioning, making a difference in physical activity (PA) levels.

Animations of introductory physics material are now widely available on the World Wide Web. They are available in two forms: those that need a resident application to run them and those that are Java-based. Although the latter offer advantages over the former (superior graphics, no proprietory software etc.) they suffer from the drawback that they cannot be easily modified. This restriction may not be important to many educators but it can affect those who are trying to tailor their efforts to a specific audience. If this is the case, the disadvantage of Java-based simulations may be so important as to render them of minimal use.

Interactive Evolutionary Computation (IEC) is a kind of human–machine interaction calculation method derived from evolutionary computation. The main problem of interactive evolutionary computation is that fitness noise can make evolution direction to deviate from user’s preferences because user’s evaluation has cognitive fluctuations and fatigue. To improve these deficiencies, this paper recommends a fuzzy fitness prediction method based on fuzzy gray model FGM (1,1) with a precise number fitness. First of all, the relationship between fitness noise intensity and the fitness function is proposed. Then, it suggests a linear programming of fuzzy fitness set width under the restriction of minimum noise intensity, which can calculate the fuzzy fitness prediction parameters. Finally, the fuzzy gray model forecasts the fuzzy fitness. The proposed method uses new computation of individual’s dominance relation and crowding distance to realize NSGA–II. The experimental results verify that this method has advantages in improving optimization quality, alleviating user’s fatigue and improving efficiency in exploration.

This paper presents a two-phase interactive satisfying optimization method for fuzzy multiple objectives optimization with linguistic preference. This proposed approach utilizes the view that the more important objective has the higher desirable satisfying degree. The originally complex optimization problem is simplified and divided into two parts that are solved one by one. The decision maker can acquire satisfying solution of all the objectives under linguistic preference. Numerical example shows the efficiency, flexibility, and sensitivity of the proposed method.

Identifying the best solutions to large infrastructure decisions is a context-dependent multi-dimensional multi-stakeholder challenge in which competing objectives must be identified and trade-offs made. Our aim is to identify and explore features in an interactive visualization tool to help make group decision analysis more participatory, transparent, and comprehensible. We extended the interactive visualization tool ValueCharts to create Group ValueCharts. The new tool was introduced in two real-world scenarios in which stakeholders were in the midst of wrestling with decisions about infrastructure investment. We modeled the alternatives under consideration, for both scenarios, using prescribed criteria identified by domain experts. Participants in both groups were given instructions on how to use the tool to represent their preferences. Preferences for all participants were then displayed and discussed. The discussions were audio-recorded and the participants were surveyed to evaluate usability. The results indicate that participants felt the tool improved group interaction and information exchange and made the discussion more participatory. They expressed that visualizing individual preferences improved the ability to analyze decision outcomes based on everyone’s preferences. Additionally, the participants strongly concurred that the tool revealed disagreements and agreements and helped identify sticking points. These results suggest that a group decision tool that allows group members to input their individual preferences and then collectively probe into any differences makes the process of decision-making more participatory, transparent, and comprehensible and increases the quality and quantity of information exchange.

In view of the longtime interactive English–Chinese translation system, an interactive English–Chinese translation system based on Griffin–Lim algorithm (GLA) is proposed. The hardware design of the system is completed by the hardware structure design, the interactive English–Chinese translation memory design and the interactive English–Chinese translation retrieval system design. Through analysing the semantic characteristics of interactive English–Chinese translation, constructing interactive English–Chinese translation database and designing interactive English–Chinese translation process, the system software design is completed and interactive English–Chinese translation is realised. The results of the system test show that the interactive English–Chinese translation system based on the GLA algorithm cannot only shorten the time of interactive English–Chinese translation, but also accelerate the response speed of the translation system, and greatly improve the overall performance of the interactive English–Chinese translation system.

Changes such as expiring patents and shifting environments challenge a firm trying to reach long-lasting appropriation success of an innovation. To understand how appropriation can be continued over time, this study investigates and compares Bayer’s two innovations, Aspirin medicine and Roundup herbicide. Whereas for the first, appropriation success has been continued through decades, for the latter, such a continuum has not realised. Our findings suggest that long-lasting appropriation success lies in adjusting the appropriation strategy by identifying the most substantial appropriability premises for innovation (appropriability mechanisms and complementary assets) and the ways to use them in different situations, paying specific attention to the shifting appropriability conditions. For long-term success, it is critical for firms to recognise that isolating appropriability mechanisms and complementary assets can have varied and distinctive implications depending on the pertinent contextual factors at innovation level and to strategise accordingly.

The image segmentation of histopathological tissue images has always been a challenge due to the overlapping of tissue color distributions, the complexity of extracellular texture and the large image size. In this paper, we introduce a new region-merging algorithm, namely, the Regional Pattern Merging (RPM) for interactive color image segmentation and annotation, by efficiently retrieving and applying the user’s prior knowledge of stroke-based interaction. Low-level color/texture features of each region are used to compose a regional pattern adapted to differentiating a foreground object from the background scene. This iterative region-merging is based on a modified Region Adjacency Graph (RAG) model built from initial segmented results of the mean shift to speed up the merging process. The foreground region of interest (ROI) is segmented by the reduction of the background region and discrimination of uncertain regions. We then compare our method against state-of-the-art interactive image segmentation algorithms in both natural images and histological images. Taking into account the homogeneity of both color and texture, the resulting semi-supervised classification and interactive segmentation capture histological structures more completely than other intensity or color-based methods. Experimental results show that the merging of the RAG model runs in a linear time according to the number of graph edges, which is essentially faster than both traditional graph-based and region-based methods.

Based on a comparative study on the operation waiting area of Shanghai Children’s Medical Center before and after renovation, Post-Occupancy Evaluation (POE) toolkit for Built Environment was used to track the interactive mural of “beach rainbow” and “mini-submarine” parent-child reading space for a year. Fear is a common cause of children’s psychological stress before surgery, and the stress of children will be transmitted to family members and medical staff, which has a negative impact on the degree of preoperative cooperation and medical experience. The narrative space based on tangible interaction is more immersive and has a sense of storytelling compared with pure virtual interface interaction. It can effectively reduce the crying rate of preschool children and the anxiety of older children by positive distraction, and improve the degree of preoperative cooperation and user satisfaction with medical treatment. In the future, with the wider application of 5G and IoT, tangible interactive narrative space will become a more effective means to relieve stress used in children’s healing environment.