Transactions on Edutainment XVI

This study examined the effects of a motivational strategies-based edutainment intervention on college students’ motivation and engagement in College English as a Foreign Language (EFL) courses. The participants were junior students in the school of business who were divided into an experimental group and control group (N = 230). Independent samples t-tests, regressions, and correlations were used for data analysis. Activities such as the snowball activity and the gallery exhibition activity were used to stimulate students’ situational interests. The results indicated that students in the experimental group had significantly higher motivation and engagement than those in the control group. Also, students’ course perceptions predicted their engagement. Implications and limitations are discussed.

Emotional support in Online Learning (OL) has become a key factor in the success of self-regulated learning. Based on an elective course in the university, the dataset that includes cognitive, emotional and behavioral states of 35 students in daily self-regulated and single observed MOOC online learning are collected by means of investigation and experiment. The correlations between emotional engagement and achievement of online learning are analyzed via SPSS tool. The experimental data show that emotional engagement has the more significant impact on academic achievement than that of behavioral engagement, but less than that of cognitive engagement. The correlation between emotional engagement and cognitive engagement is extremely obvious, while the correlation between emotional engagement and behavioral engagement is extremely insignificant. Therefore, it is suggested that teachers could improve students’ positive emotions and execution ability by establishing appropriate evaluation of curriculum value and self-perception to guarantee learning effect.

In the process of orthodontics, accurate bracket positioning is a necessary condition to quickly obtain the ideal treatment result. We propose a virtual bracket-interaction method based on the Layered Depth-Normal Images (LDNI) and the point set matching. By means of mouse-interaction, the fast movement of the bracket on the tooth surface is realized. Specifically, LDNI is used to complete the sampling of the bottom point of the bracket in space coordinate system. Then the nearest-distance algorithm is used to find the corresponding point on the tooth surface. Finally, the position of the bracket on the tooth surface is determined by point set matching. In addition, in order to help the orthodontist to complete clinical correction, we design a virtual bracket interaction software to realize the positioning operation of the virtual bracket through mouse interaction. The results demonstrates that the software we developed is very helpful for orthodontists to complete bracket positioning.

Virtual reality technology plays an increasing important role in the study and implementation of pottery. This paper mainly summarizes the technologies, tools and application scenarios relating to virtual pottery, including modeling methods; interactive tools and their advantages/disadvantages; future trends in interactive methods; and, applications of virtual pottery in museums, teaching, archaeology and entertainment.

In most of the existing online search systems of museums, only the professional knowledge keywords are used to retrieve the artworks. It is a challenge for either professionals or non-professionals. In this paper, we divide the attributes of an artwork into two categories: subjective and objective, and propose a method of attribute annotation for artworks based on the visual perception of the searcher or audiences, which makes the retrieval simpler and more suitable for either professionals or non-professionals.

Road scene segmentation has always been regarded as a pixel-wise task in computer vision studies. In this paper, we introduce a practical and new features fusion structure named “Dual Path Network” for road semantic segmentation. This form aims to reduce the gap between low-level and high-level information, thereby improving features fusion. The Dual Path consists of two subpaths: Context Path and Spatial Path. In the Context Path, we select a pre-trained ResNet-101 model as the backbone and use multi-scale convolution blocks comprise the Spatial Path. Then, we create a fusion residual block and channel attention model to further optimize the network. The results of the experiment confirm a state-of-the-art mean intersection-over-union of 68.5% using the CamVid dataset.

In order to monitor the aging of transformers and ensure the operational safety in substations, a practical detection system for indoor substation transformers based on the analysis of audio signal is designed, which use computer technology instead of manpower to efficiently monitor the transformers working states in real-time. Our work consists of a small and low cost AI-STBOX and an intelligent AI Cloud Platform. AI-STBOX is installed directionally in each transformer room for continuously collecting, compressing and uploading the transformers audio data. The AI Cloud Platform receives audio data from AI-STBOX, analyses and organizes the data to low-dimensional speech features with STFT and Mel cepstrum analysis. Input the features into a powerful deep neural network, the system can quickly distinguish the working states of each substation transformer before is has serious faults. It can locate aging transformers, command the maintenance platform to quickly release the repair task, thus avoid unforeseeable outages and minimize planned downtimes. The approach has achieved excellent results in the substation aging transformers detection scene.

The shipping of the Yangtze River has been developing rapidly, the large scale and standardization of ship dimensions have also developed along with the development of China’s economy since entering the 21st century. As a main ship type of the Yangtze River shipping, the dry bulk carriers have changed greatly in the principal dimensions. The characteristics and regression formulas of the principal dimensions in the past are not applicable to the new ship type. On the basis of big data statistics of the dry bulk carrier over 1000 tons navigating on the Yangtze River, the distribution of the transport capacity and distribution of ship age are analyzed, and the linear formula between the gross ton and dead weight is summed up. Then the statistical characteristics of the important parameters of ships such as the ship length, the ship width, the design draft and the diameter of the propeller are analyzed. The research results can provide an important reference for ship design, ship form development, technical standard research and navigation management.

Foliage morphological features are important for plant recognition. However, the foliage shape generally presents big intra-class variations and small inter-class differences. This brings a great challenge to accurate plant foliage recognition. In this paper, we propose a deep residual squeeze-excitation network (R-SENet) for foliage recognition. Firstly, R-SENet learns and obtains the significance levels of each channel of the various convolutional layers in a residual block to recognition tasks via squeeze-excitation strategy. Then, the weights of each channel are rescaled by means of the significances to promote the relevant channels and inhibit non-important channels. Finally, we evaluate the proposed approach on the well-known Flavia dataset for foliage recognition. The experimental results indicate that our approach achieves more accurate average recognition rate (up to 97.86%) and more robustness to noise than other outstanding approaches.

In this paper, the greedy strategy is used to improve the density clustering algorithm, which can separate the noise points and deal with the uneven density distribution. In order to further improve the efficiency of density clustering algorithm based on greedy strategy, in this paper, it is applied to mining hot spots of taxi passengers. Firstly, large-scale data are processed, and large-scale data sets are sampled by reservoir, and effective hot data are obtained. Then, the data of 8,000 taxis in an urban area during December 4–8, 2018 are clustered to verify the validity of the proposed algorithm.

This research mainly explores the visualization of marine ranch in the tourism industry and provides a three-dimensional, dynamic, and visual model for the tourism development of coastal cities. The behavioral characteristics and environment of fish swarm are simulated in virtual marine ranch to shorten the distance between users and marine ecology. This research uses CINEMA 4D and Unity3D game engines to establish virtual scenes of marine fisheries and characteristic fisheries. The interaction between the user and the virtual scene is realized through C# programming and HTC VIVE head display device. Users can visually observe changes in fish swarm and surrounding environment.

As we can see in the real world, there are frequent public security accidents (earthquake, fire, virus, and flood) in the past years. When the ordinary people are facing the flood disaster, they often do not know how to avoid danger and save themselves. By using the most advanced VR technology, we can popularize public safety knowledge, and improve public security awareness. This paper first describes the related works in flood simulation modeling, VR training, and interacting techniques in VR systems. Then it discusses the implementation of a virtual training system for flood security education based on Unity3D engine which is widely used for the time being. The users can not only experience the horror of public safety disasters in the virtual world, but also learn how to save himself in the event of flood disasters in the virtual environment.

This paper presented a virtual reality experience system based on the theme of human body and cold virus struggle. In order to construct a realistic human cell scene, we applied physic-based rendering game production and Unreal® Engine. The proposed project used virtual reality, combining educational theory. Plentiful functionalities of virtual system were discussed in detail. As such, users could well participate in a war of cells to against virus from different perspectives. It is thought that users can become active learners, with they might well taking the initiative to acquire scientific knowledge and summing up their thinking in a lifelike experience, ultimately cultivating the ability of exploration and innovation.

Owing to the complexity of the anatomical structure of the pancreas, surgeons must perform long-term observations and strict training before performing operations. The application of AR technology provides an ideal surgical training platform and has important innovative significance for the surgical training of interns. Through the AR animation of pancreatojejunostomy, training efficiency can be improved. This article focuses on the feasibility and development of AR technology for application to pancreatic surgery, especially the role of AR technology in medical teaching and clinical practice. The study explores the development status, features, design methods, and applications of augmented reality animation as it relates to pancreatic surgery.

In this paper, we proposed a method of real-time human motion detection and skeleton control based on the depth image. For the human body part, we use Kinect to detect the original three-dimensional coordinates of the human joint; then smooth the joint movement; calculate the amount of rotation based on the smoothed data. Finally, the FBX file is used to drive the virtual mannequin. For the human face part, we use 3D modeling software to modify the FBX model and replace the head of the human model. With the help of the Kinect device, we combined the idea of linear blend skinning (LBS) to make the human body action effect more realistic. The experimental results show that the motion capture system can better recover the 3D skeleton motion of the captured real human body. Compared with other motion capture system, the motion control time of the human body is greatly reduced, and the 3D mesh and skeleton can be obtained immediately according to the detected human body motion. The modified FBX model can apply specific expression effects.

In view of the problems of high cost and many potential hazards in real middle school experiments, we construct a virtual experiment simulation situation with virtual human guidance in experiment operation, intelligent algorithm assistance in experiment failure, and systematic evaluation at the end of experiment. First of all, the experimental rule library is established, including: experimental process, trigger standard, coding standard and error content. Secondly, based on these libraries, the flow of system algorithm is designed. Finally, take the experiment of heating potassium permanganate to produce oxygen as an example. The flow design, scene design and virtual human design of the experiment are given. Realize intelligent assistance and interactive real-time guidance of the experimental process.

The driver’s distracted attention will cause a huge safety hazard to the traffic. In different types of distraction, it is illegal to make phone calls and smoke while driving, which will be fined in China. In order to solve this problem, a method of driver’s distracted behavior detection based on channel attention convolution neural network is proposed. SE module is added to the Xception network, which can distinguish the importance of different feature channels and enhance the expression ability of the network. SE module mainly assigns different weights to features to enhance more important features and suppress less influential features. The experiment uses Xception and SE-Xception for comparison. The experimental results show that the accuracy of SE-Xception is 92.60%, which has a good performance for the distracted driving behavior detection of drivers.

In recent years, motion capture devices have been widely used in 3D film special effects, animation generation, digital media and other virtual reality fields. The purpose of this paper is to achieve data acquisition, motion feature extraction and recognition of human motion by using motion capture device. First, we use the OptiTrack motion capture device and related data preprocessing methods to collect motion data, and realize the preview of joint point offset data. Then, a human motion feature representation method which combines the collected data with the key frame is designed. For the selection of key frames, we improve the frame subtraction algorithm by adding the second derivative calculation of reconstruction error to achieve the number of key frames automatic determination. In addition, in order to solve the problem of huge amount calculations and error existing in discretization of observation state, we use high-dimensional gaussian function to fit human motion data, and finally apply the method of Gaussian-Mixture Hidden Markov Model (GMM-HMM) for motion recognition. Experiments show that the method has achieved remarkable performances in human motion extraction and recognition.

At present, the display of marching roadmap in the revolutionary history memorial hall are mostly in the form of flat KT board. There are also a few ways of using animation or video, but the way KT board is not conducive to the understanding of the visitors, A certain cognitive burden, animation or video is also not conducive to the latter part of the maintenance, while the lack of interaction. The purpose of this paper is to research and design a marching roadmap system based on osgEarth, which is beneficial to the visitors to understand the revolutionary history more intuitively and to help the administrator to maintain the system content in the future. The system can customize the vector information, provide a highly customized route curve type, route dynamic setting and adjustment.

As we known, video game consoles are not only the carriers of games to global users, but also the communication and social platforms due to their embedded instant messenger software. In addition, the data structure and storage of game consoles enables them to provide facilitation to criminals who are willing to conceal potential evidence. As the eighth-generation of video game consoles, demand for play station 4 was strong, which means that it attracts numerous users. Nevertheless, seldom researchers conducted analysis towards this console. This paper provides a method for acquiring digital evidence on play station 4 and gives a detailed description of embedded instant messenger software.

Traditional public service advertisements mostly adopt one-way publicity, such as radio and television, which has limitations on them. With the rapid development of communication technology, public service advertising has a new mode of publicity, such as interactive advertising, incentive advertising. Based on the development status and problems of public service advertisements, this study takes care of the mental health of depressed patients as the starting point and expands the communication experience of public service advertisements from the perspectives of psychology and behavior. On the basis of analyzing the “inertia” of users’ subconscious behavior, a button model is designed to guide users’ subconscious behavior. By simulating the negative effects of users’ subconscious behaviors, such as bringing pain to depressed patients or the possibility of suicide, this study gives people a self-reflection and self-evaluation experience in a natural interactive way, so as to achieve the communication significance of public service advertisements.

National culture is the soul of Chinese animation. Chinese culture has a long history, which accumulates a wealth of material for the creation of animation scripts, and also provides inexhaustible role images for the shaping of Chinese animated characters. To revitalize the Chinese animation industry, it is necessary to inject the soul of Chinese national culture into Chinese animation, which requires China’s animators to improve their ideological understanding, strengthen the study of national culture, reform the current animation education system properly, have the courage to practice and explore, and then make Chinese animation a distinctive seal.

In order to build a large model database for fruit 3D printing and require (1) sampling data is as simple as possible; (2) data volume and data structure are unified; (3) modeling method has multi-resolution capabilities, this paper presents a fruit shape modeling method based on wavelet interpolation, trying to uniformly sample 2 to the power of m longitude lines of fruits with a upright axis, and uniformly sample 2 to the power of n points on each longitude line. Then, we use wavelet interpolation to obtain the longitude and latitude lines models that meet the required precision for 3D printing. Additionally, we discuss several special issues of fruit shape 3D printing and Gcode file generation. The experimental results show that the modeling method has the advantages of good model effect, short printing time, and saving of printing material, which can achieve simple and practical application requirements.

Since the first video game console called Pong was released in the 1970s, game consoles have grown continuously with the economic and technological development. There are some leading gaming manufacturers in current market, including Sony, Microsoft and Nintendo. As the eighth generation of video game console published by Microsoft, Xbox one is one of the most popular game consoles and thus attracts numerous customers. It is noticeable, however, Xbox one can no longer be treated as consoles but rather as computer-like machines. In this paper we are going to analyze partition, file system, relevant file and other data of Xbox One concretely.

Online learning monitoring is still on the urgent demand to track and analyze the learning engagement of the learners. To this end, the multimodal behavioral data of online learners are collected during the online learning process from the psychological, physiological and behavioral dimension which are respectively dependent on the techniques of expression recognition, physiological heart rate acquisition with Internet of Things and operation events listening. Based on the dataset with 25 experimental p, online learning engagement states are statistically analyzed and assessed by applying the schema including both prior rules and data fitting method which can quantitatively evaluate the learning engagement. Through the questionnaire survey and statistical validation, the assessment results show the schema can measure learning engagement in multiple dimensions and evaluate the whole state more comprehensively and automatically.

Failures (including hardware failures, software failures or unexpected shutdowns, sudden power failures, etc.) are unavoidable problems in large-scale distributed systems, so current distributed systems are required to support systematic fault tolerance. Aiming at the requirements of strong real-time application scenarios, this paper proposes a distributed cache and recovery method based on memory database. SQLite memory database is adopted and election-based multi-node data synchronization is introduced, which ensures the strong consistency of data on each node and eliminates the bottleneck and failure problems caused by the setting of the central node; at the same time, a dynamic load balancing mechanism is adopted to reduce the amount of synchronized data in the entire system and ensure the smooth operation of the system. Finally, the effectiveness of the proposed method is proved by experiments.

Culture is created during the process of human activities, and the development and prosperity of culture highly depend on the dissemination of media. In the context of international communication, Chinese culture is facing up with challenges both from cultural prejudice and media bias. With the breakthrough of Web 2.0, new media technologies have subverted the communication mechanism of the traditional media, and cultural communication also changed dramatically. Since the Strategy of Chinese Culture Going-out is launched, it is high time to adopt new technology and creative thinking to promote Chinese culture overseas. This paper explores the communication mechanism of social media, by analyzing the three core components of Platform, User and Content of social media. Based on the principle of Acculturation, it posits that the key points to break personal information cocoon should include the following methods: 1. Enriching cultural communication forms (utilizing the characteristic of social platform); 2. Customizing cultural communication scheme (by User Typology analysis); 3. Creating cultural communication contents (converging multiple new media technologies). This paper further points out that a Cross Cultural Hierarchy Phenomenon would occur if before-mentioned methods are adopted to raise cultural communication effect, and it is believed that the passive situation of Chinese cultural communication should be changed to promote Chinese culture overseas.