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This journal subline serves as a forum for stimulating and disseminating innovative research ideas, theories, emerging technologies, empirical investigations, state-of-the-art methods, and tools in all different genres of edutainment, such as game-based learning and serious games, interactive storytelling, virtual learning environments, VR-based education, and related fields. It covers aspects from educational and game theories, human-computer interaction, computer graphics, artificial intelligence, and systems design.

The 19 papers presented in the 15th issue were organized in the following topical sections: multimedia; simulation; cybersecurity; and e-learning.

Inhaltsverzeichnis

Frontmatter

Multimedia

Frontmatter

Wearable Sensors and Equipment in VR Games: A Review

Abstract
Virtual Reality (VR) has been developed dramatically in recent years due to its benefits of providing an engaging and immersive environment. The objective of this study was to collect and critically analyze wearable sensors and equipment used in VR games, aiming at classifying wearable sensors according to the player’s key needs and the characteristics of the VR game. The review is organized according to three perspectives: the player’s needs, the player mode and the functional sensor modularization in a VR game. Our review work is useful for both researchers and educators to develop/integrate wearable sensors and equipment for improving a VR game player’s performance.
Mingliang Cao, Tianhua Xie, Zebin Chen

A Style Image Confrontation Generation Network Based on Markov Random Field

Abstract
A style-transfer generates against network based on Markov random field is proposed in this paper. Based on the original image, a new image is generated by generate network, and then the error between the original image and the style image is calculated using the discriminant network and backward propagation to the generate network, high-quality style transfer images are generated through the continuous confrontation of the two networks. In the quantification of style loss and content loss, we have introduced Markov random field, which uses its limitation on the spatial layout to reduce the distorted distortion of the generated image and improve the quality of the generated image. Experiments show that the network can quickly generate high-quality style transition images in a short time.
Guopeng Qiu, Jianwen Song, Lilong Chen

A Point Cloud Registration Algorithm Based on 3D-SIFT

Abstract
Point cloud registration is a key technology in reverse engineering. The registration process of point cloud is divided into coarse registration and fine registration. For fine registration process, ICP (Iterative Close Point) is a classic algorithm. The traditional ICP algorithm is inefficient and incorrect if the correct initial point set is not obtained. In this paper, a point cloud registration algorithm based on 3D-SIFT features is proposed. In this method, the 3D-SIFT algorithm is used to extract key points. At the same time, the 3D-feature descriptor is used as a constraint on the initial set of points in the ICP algorithm. The results show that the method improves the efficiency and precision of the ICP algorithm, and achieves better results of point cloud registration.
Zehua Jiao, Rui Liu, Pengfei Yi, Dongsheng Zhou

Lip-Reading Based on Deep Learning Model

Abstract
With the rapid development of computer computing power, deep learning plays a more and more important role in the fields of automatic driving, medical research, industrial automation and so on. In order to improve the accuracy of lip-reading recognition, an algorithm based on the model of lip deep learning was proposed in this paper. Binary image of the lip contour motion sequence was projected to the spatio-temporal energy, lip dynamic grayscale was used to reduce noise interference in the recognition process and then lip-reading recognition result was improved by using the excellent characteristics of deep learning ability. The experimental results show that deep learning can obtain the effective characteristics of lip dynamic change from the lip dynamic gray scale and get better recognition results.
Mei-li Zhu, Qing-qing Wang, Jiang-lin Luo

Simulation

Frontmatter

Parameter Estimation of Decaying DC Component via Improved Levenberg-Marquardt Algorithm

Abstract
Fault current usually contain a decaying DC component and some kinds of noise. This DC component and noise decrease the accuracy and speed of the operation of digital relay protection. In order to remove the decaying DC component and noise in current signals for power system, parameters of decaying DC component should be estimated firstly. To solve this parameter estimation problem, a specific neural network is proposed, and then an adaptive learning algorithm based on improved Levenberg-Marquardt algorithm is derived to iteratively resolve its weights by optimizing the pre-defined objective function. From weights of the trained neural network, all parameters of decaying DC components can be well calculated. Profiting from good nature in fault tolerance of neural network, the proposed algorithm possess a good performance in resistance to noise. Simulation experimental results indicate that our algorithm can achieve a high accuracy with acceptable time consumption for parameters estimating in noise.
Xiuchun Xiao, Baitao Chen, Jingwen Yan

Cybersecurity

Frontmatter

Typing Technology of Virtual Character of Animation Based on Enneagram Personality

Abstract
Facial expression inevitably leads to facial deformation. In this paper, the advantages and disadvantages of feature extraction and recognition method are considered. A facial expression recognition method based on mixed feature fusion of nine types of personality is proposed. The texture features are extracted by discrete wavelet transform and standard orthogonal non negative matrix decomposition for a person’s facial expression image sequence, and AAM square is used. The method calculates the coordinate difference between the expression key points of the expression frame and the neutral frame in the image sequence, and extracts the geometric deformation characteristics. Then use the canonical correlation analysis (CCA) to fuse the two features, and finally use discrete HMM to classify faces.
Jiang-lin Luo, Mei-li Zhu, Qing-qing Wang

E-learning

Frontmatter

The Style-Based Automatic Generation System for Xinjiang Carpet Patterns

Abstract
Xinjiang carpet patterns have flowery color, strong contrast, and the overall harmony, how to design a carpet patterns with Xinjiang style feature is a challenging problem. This paper puts forward a method based on interactive choice mechanism and establishment color constraint rules in order to create Xinjiang carpet patterns. First, we can establish pattern design model through the medallion pattern, corner pattern and brink pattern; then according to the user’s choice, we can get sample pattern, and establish respectively dominant color matrix of samples and generated patterns; finally, through the color similarity to generate design constraints, the simulation experiment shows that method of the paper can innovatively design more inherited color style of Xinjiang carpet designs, and enrich the research methods of Xinjiang carpet style design.
Xiao Gang Hou, Hai Ying Zhao

Research on Teaching Experiment of Color and Digital Color

Abstract
Color is one of the most familiar physical phenomena and common sense in daily life. However, to understand color is a very complicated learning processing, which takes a long period of time with great effort in professional color application and design practice to mastering the basic laws of color application. Therefore, how to develop a visual teaching system for learning basic law of color and how to make this system more acceptable by students becomes an urgently issue among all art colleges. In this paper, we start with the color digitization issue, establishing the basic relations and orders of color by using color cube and virtual reality technology. Moreover, within this system, it offers an easy way to extract The Color Family System from any image and build a harmonious color relationship. This paper provides a new and high level of color teaching standard, also, solves the key problems between teaching and learning effectively.
JianWen Song, ZheFeng Ma, Peng Song, ZhiGeng Pan

Cybersecurity Curriculum Design: A Survey

Abstract
The threat of cyber attacks continue to grow with the increasing number of sophisticated and successful targeted cyber attacks throughout the globe. To address this issue, there is a dire need for cybersecurity professionals with adequate motivation and skills to prevent, detect, respond, or even mitigate the effect of such threats. To this end, several cybersecurity educational programs and concentrations have been established over the past years both at the graduate and undergraduate levels. Moreover, a number of initiatives taken by the government standard bodies in the cybersecurity domain have emerged to help in framing cybersecurity education. Due to the interdisciplinary (and sometimes multidisciplinary) nature of cybersecurity, educational institutions face many issues when designing a cybersecurity curriculum. In this context, we believe that there is a desideratum to provide a big picture of the overall efforts done so far in the direction of cybersecurity curriculum design. In this paper, we present an overview and comparison of existing curriculum design approaches for cybersecurity education. This survey will help the researchers and educators to have an overview of the existing approaches for the purpose of developing a suitable and more effective cybersecurity curriculum in their future endeavour.
Djedjiga Mouheb, Sohail Abbas, Madjid Merabti

Teaching as a Collaborative Practice: Reframing Security Practitioners as Navigators

Abstract
The need is growing for a workforce with both technical skills and the ability to navigate existing and emerging information security challenges. Practitioners can no longer depend upon process-driven approaches to people, processes and IT systems to manage information security. They need to be navigators of the entire environment to effectively integrate controls to protect information and technology. The research presented in this paper trialed an innovative tactile learning activity developed through the European Technology-supported Risk Estimation by Predictive Assessment of Socio-technical Security (TREsPASS) project with tertiary education students, designed to provide students with experience in real-world modelling of complex information security scenarios. The outcomes demonstrate that constructing such models in an educational setting are a means of encouraging exploration of the multiple dimensions of security. Such teaching may be a means of teaching social, organization and technical navigation skills necessary to integrate security controls in complex settings.
Patricia A. H. Williams, Lizzie Coles-Kemp

Pedagogical Approach to Effective Cybersecurity Teaching

Abstract
Initial research ruled out many factors that were thought may correlate to student academic performance. Finally, a strong correlation was found between their academic performance and their motivation. Following on from this research teaching practice was restructured to improve student motivation, engagement, and interest in cybersecurity by contextualizing teaching material with current real-world scenarios. This restructuring led to a very significant improvement in student academic performance, engagement and interest in cybersecurity. Students were found to attend more of their lectures and practical sessions and that this had a strong positive correlation with their academic performance.
Abdullahi Arabo, Martin Serpell

Choose Your Pwn Adventure: Adding Competition and Storytelling to an Introductory Cybersecurity Course

Abstract
Narrative is an important element of gamification. In this article, we describe the development of a framework that adds a narrative to an 11-week cybersecurity course. The students play the part of a new IT security employee at a company and are asked to complete a number of security tasks, for which they receive flags. As well as being used to assess their performance throughout the course, students can send the flags they find to a number of different characters to progress the storyline in different ways. As the story unfolds they find deceit, corruption and ultimately murder, and their choices lead them to one of three different endings. Our framework for running the story and the exercises is completely self-contained in a single virtual machine, which the students each download at the start of the course; this means that no resource-consuming backend or cloud support is required. We report on the results of qualitative and quantitative evaluations of the course that provide evidence that both the VM and the story contained within it increased student engagement and improved their course results.
Tom Chothia, Chris Novakovic, Andreea-Ina Radu, Richard J. Thomas

A Virtual Classroom for Cybersecurity Education

Abstract
Education in general and cybersecurity education in particular can be made more attractive by adding hands-on experience to classrooms. This requires new technology, such as virtualisation, to be developed fully geared towards the needs of educational purposes. Over the years, several techniques have been developed by the authors. In this paper, the authors first give a full account of their earlier work on a distributed virtual computer lab for cybersecurity education. Then, this virtual lab is extended with educational enhancements, such as an intelligent tutoring system, which resulted in a prototype for a virtual classroom for cybersecurity education.
Jens Haag, Harald Vranken, Marko van Eekelen

The Cyber Security Knowledge Exchange: Working with Employers to Produce Authentic PBL Scenarios and Enhance Employability

Abstract
The shortage of professionals to combat the growth of cyber-attacks demands a response from universities to equip students with relevant skills and knowledge. Furthermore, the small and medium enterprise (SME) sector in the UK particularly lacks information security expertise. This paper explains and critically evaluates innovative approaches which address both problems. Our innovations include open-access adaptable Problem-based learning (PBL) scenarios, developed with industry partners to ensure authenticity. Full resources are available at https://​www.​cyberedge.​uk/​cske/​index.​php. PBL was found to be well-aligned with the multi-disciplinary challenge of information security - it develops essential professional skills and can model the consultancy process. To address the SME skills issues, teams of students, conducted consultancy-based work-placements to address SME-identified problems. Evaluation showed PBL scenarios and consultancy work placements received strongly positive responses from participants. The educational design, processes of development and engagement with partners, and the evaluation methods are readily transferable to other subject domains.
Chris Beaumont, Peter Hartley

Virtual Training and Experience System for Public Security Education

Abstract
Public security is a major problem facing our country at present. Frequent public security accidents have become a great hidden danger affecting social stability. The public security consciousness of our people is generally scarce. When facing such disasters as earthquake and fire, we often do not know how to avoid danger and save ourselves. With the most advanced virtual simulation technology, to popularize public safety knowledge to the whole people, improve public security awareness, has become an urgent task of today’s society. This paper designs and implements a virtual simulation system for public security education based on Unity3D engine and virtual reality technology. The system combines earthquake escape and fire fighting. The experiencer can not only experience the horror and ruthlessness of public safety disasters in the virtual world, but also learn how to save himself in the event of disasters without risk. It is an effective scheme to popularize safety knowledge to citizens.
Zhigeng Pan, Yi Zong

Intelligent Coach Avatar Based Virtual Driving Training

Abstract
This paper presents an intelligent coach avatar based training system for one-to-one automatic guidance in virtual driving training. Compared with previous training methods, the intelligent coach avatar embodies a combination of more interest and knowledge, and provides a reference for exploring the deep integration of the intelligent behavior mode.
Mingliang Cao, Lvjie She

Multi-channel Scene Synchronization Strategy in Real Time Rendering

Abstract
This paper introduces a new synchronization method in real-time multichannel scene rendering, which is based on global time stamps, and collects and updates sync data in an adaptive way. Our method can reduce the times of sending acknowledge data between network server and each client node, thus keeps enough network bandwidth for use. It also handles slow or invalid network nodes and avoids the entire system to wait inefficiently, and can be used widely in interactive projects and researches.
Xiaofen Li

On the Characteristics of Mise-en-scène in Animated Audio-Visual Language

Abstract
Animation mise-en-scène is in the system of animated audio-visual language, but it has its own characteristics in the process of expressing meanings and information. Though the form of animation mise-en-scène is pictorial, it also has its own features on the mind of constructing film space and scene. All these characteristics mentioned above are the key points of this paper. Whether it is the motility, subjectivity, description, spatiality, symbolism, contrast or economy, it reflects the unique charm of animation mise-en-scène. This paper focuses on concluding the characteristics of animation mise-en-scène, the thinking way that animations are different from other film, and the unique rule of animated audio-visual language in order to create more fantastic domestic animation films.
Lingling Cui

Human Eye Tracking Based on CNN and Kalman Filtering

Abstract
The driver fatigue detection method based on human eye feature information has the advantages, such as non-invasion, low cost, natural interaction and so on, which has been widely favored. However, in the actual detection process, the driver’s face will be shaken due to various factors, and there will be motion blur, which will cause misjudgment and missed judgment on the fatigue driving detection. Therefore, this paper designs a method based on CNN convolutional neural network to detect human key points, then uses Kalman filter to track human eyes, eliminates jitter interference, and greatly improves the accuracy of fatigue detection. The experimental results show that the proposed method can track the human eyes in real time and has high accuracy and robustness.
Zhigeng Pan, Rongfei Liu, Mingmin Zhang

Backmatter

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