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The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings, and solutions, and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods.

This, the 28th issue of the Transactions on Computational Science journal, is comprised of extended versions of selected papers from the International Conference on Cyberworlds, CyberWorlds 2015, held in Gotland, Sweden, in October 2015. The first paper is a position paper, presenting open problems and identifying future directions within the domain. The remaining 8 papers focus on a range of topics, including virtual reality, games, haptic modeling, cybersecurity, brain wave analysis, shape parameterization, projects, and data mining.



Problems of Human-Computer Interaction in Cyberworlds

Created intentionally or spontaneously, cyberworlds are information spaces and communities that immensely augment the way we interact, participate in business and receive information throughout the world. This paper reports position statements presented at the plenary panel of the 2015th International Conference on Cyberworlds. First, the problems of enhancing creativity in cyberworlds using new interfaces are considered. It follows by the discussions on using biometric interfaces in on-line services. Finally, the challenges of using brain-computer interfaces and emotion recognition using electroencephalograms are considered.
Alexei Sourin, Rae Earnshaw, Marina Gavrilova, Olga Sourina

Mark Projection on Real World with Precise Measurement of Angular Velocity for Helping Picking Works

There are varieties of methods for realizing augmented reality. A projection type augmented reality proposes augmented information in the real world. Every person can share the experience within the environment. However, the method needs many preparation works and enormous energy for freely projecting images. It can work on only limited conditions, such as indoors or outdoors at night. Our research solves these problems. We propose a method that works in a head-worn type equipment using the method of projection type augmented reality. It recognizes an object from camera images. It projects a mark that carries a little information onto a recognized object. There is an error on the position where the mark projected when the equipment moves. We decrease this error using precise measurements of angular velocity. We propose the method, the implementation and the experiments for evaluating the performance in vitro and in vivo.
Kyota Aoki, Naoki Aoyagi

Application for Real-Time Generation of Mathematically Defined 3D Worlds

This paper presents an application developed as a research platform for the real-time generation of 3D L-system structures, including rudimentary game physics and a freely scalable depth buffer that enables the user to interact with the L-system geometries, and in addition to render a mathematically defined world that is virtually unlimited in scope.
Mikael Fridenfalk

Generating Chinese Calligraphy on Freeform Shapes

To adequately reveal aesthetic value of Chinese calligraphy, the way to precisely generate characters on freeform shapes is a critical issue. In this paper, we present a novel method to solve the problem. Firstly, to avoid the disadvantage of pictures and obtain an excellent visual effect, we vectorize Chinese calligraphy characters by disk B-spline curve (DBSC). Secondly, instead of the traditional texture mapping method, we innovatively employ geodesic computation and exponential map method to calculate accurate texture coordinates. The geodesic computation is to calculate the geodesic distance between every two vertexes of the character mapped region. And the exponential map is to obtain every vertex’s geodesic coordinates. Thirdly, 3D points coordinates on surfaces that correspond to vectored character in tangent plane are acquired, therefore the vectored character is able to be mapped onto surfaces. At last, some experiments are accomplished to test and verify the accuracy and efficiency of our method.
Qian Fu, Zhongke Wu, Xiang Ying, Mengdi Wang, Xia Zheng, Mingquan Zhou

How the Perceived Identity of a NPC Companion Influences Player Behavior

This paper explores how the perceived identity of a Non-Player Character (NPC) effects a players behaviour in computer games. We explore whether the players will change their behaviour towards a synthetic in-game companion if it assumes different identities. Specifically, will the players change their behaviour if they interact with an identical artificial intelligence, assuming a guise of a human or robot companion. To investigate this question we developed a top-down, 2D on-line game where the player is given the objective of surviving successive waves of hostile opponents. As a secondary objective the player is asked to protect a unarmed male, female or robot companion. The intention is to explore whether the player is more protective over a known NPC assuming either a human or non-human identity. The results of our study indicate that superficially changing the identity of an AI companion can have a dramatic influence over the players behaviour. The players in this study are shown to be significantly more protective to human rather than robot companions, despite the underlying AI being identical. Moreover, our results highlight further differences between the male and female companions.
Christopher J. Headleand, James Jackson, Ben Williams, Lee Priday, William J. Teahan, LLyr Ap Cenydd

CogniMeter: EEG-Based Brain States Monitoring

Electroencephalogram (EEG) techniques are traditionally used in the medical field. Recent research work focuses on applying these techniques to daily life with wireless and relatively low-price EEG devices available in the market. As a result, applications such as neurofeedback training, neuromarketing, emotion, stress, mental workload recognition, etc. using EEG techniques on healthy adults have been developed. Since the EEG measures and records electrical activity in the brain, it is possible for it to reflect a person’s brain states. In this paper, we describe a novel brain computer interface called CogniMeter integrated with proposed real-time emotion, mental workload, and stress recognition algorithms. With this system, we can assess human emotions, mental workload, and stress in real time. This work can be applied as a human study tool in many fields. For example, the wellbeing of users within a system or workers in industry can be monitored to improve their protection from overly stressful workload conditions. In research, brain state monitoring can be applied in simulation scenarios during human factor study experiments. In marketing, a person’s emotional response toward products or advertisements can be studied using EEG-based brain states monitoring.
Xiyuan Hou, Yisi Liu, Wei Lun Lim, Zirui Lan, Olga Sourina, Wolfgang Mueller-Wittig, Lipo Wang

Four Adaptive Memetic Bat Algorithm Schemes for Bézier Curve Parameterization

This paper is an extension of a previous one presented at the conference Cyberworlds 2015. In that work we addressed the problem to fit a given set of data points in the least-square sense by using a polynomial Bézier curve. This problem arises in many scientific and industrial domains, such as numerical analysis, statistical regression, computer-aided design and manufacturing, computer graphics, virtual reality, etc. A critical issue to address this least-squares minimization problem is that of curve parameterization. In our previous work we solve it by applying a powerful nature-inspired optimization method called the bat algorithm. Although we obtained pretty good results on a number of examples, the method can still be further improved by considering a memetic approach, in which the global search bat algorithm is hybridized with a local search procedure to enhance the exploitation phase of the minimization process. In this paper we extend our previous method through two local search strategies: Luus-Jaakola and ASSRS. In both cases, the adaptive and self-adaptive versions are considered, leading to four memetic schemes. A comparative analysis of our results on the previous benchmark for these four memetic schemes and our previous method has been carried out. It shows that the memetic approaches improve the efficiency of the previous method at different extent for all instances in our benchmark.
Andrés Iglesias, Akemi Gálvez, Marta Collantes

Auto-Parameterized Shape Grammar for Constructing Islamic Geometric Motif-Based Structures

The complex formation of Islamic Geometric Patterns (IGP) is one of the distinctive features in Islamic art and architecture. Many have attempted to reproduce these patterns in digital form, using various pattern generation techniques, in 2D. Shape grammars are an effective pattern generation method, providing good aesthetic results. In this paper we describe a novel approach in generating 3D IGP using the shape grammar method. The particular emphasis here is to generate the motifs (repeated units with the pattern) in 3D using parameterization. These can then be manipulated within the 3D space to construct architectural structures. In this work we have developed two distinctive Shape Grammars in 3D namely Parameterized Shape Grammar (PSG) and Auto-Parameterized Shape Grammar (APSG). Here the PSG generates the motifs and the APSG enables construction of the structures using the generated motifs. Both grammars are practically implemented as a 3D modelling tool within Autodesk Maya. The parameterization within each grammar is the key to generate both Islamic geometric motifs and Islamic geometric motif-based structures.
Zahra Sayed, Hassan Ugail, Ian Palmer, Jon Purdy, Carlton Reeve

Data Mining via Association Rules for Power Ramps Detected by Clustering or Optimization

Power ramp estimation has wide ranging implications for wind power plants and power systems which will be the focus of this paper. Power ramps are large swings in power generation within a short time window. This is an important problem in the power system that needs to maintain the load and generation at balance at all times. Any unbalance in the power system leads to price volatility, grid security issues that can create power stability problems that leads to financial losses. In addition, power ramps decrease the lifetime of turbine and increase the operation and maintenance expenses. In this study, power ramps are detected by data mining and optimization. For detection and prediction of power ramps, data mining K means clustering approach and optimisation scoring function approach are implemented [1]. Finally association rules of data mining algorithm is employed to analyze temporal ramp occurrences between wind turbines for both clustering and optimization approaches. Each turbine impact on the other turbines are analyzed as different transactions at each time step. Operational rules based on these transactions are discovered by an Apriori association rule algorithm for operation room decision making. Discovery of association rules from an Apriori algorithm will serve the power system operator for decision making.
Nurseda Yıldırım, Bahri Uzunoğlu


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