Previous works have shown the potential of immersive technologies to make physical activities a more engaging experience. With encountered-type haptic feedback, users can perceive a more realistic sensation for exertion interaction in substitutions reality. Although substitutional reality has utilized physical environments, props, and devices to provide encountered-type haptic feedback, these cannot withstand the fierce force of humans and do not give feedback when users move around simultaneously, such as in combat sports. In this work, we present Hit Around, a substitutional moving robot for immersive and exertion interaction, in which the user can move and punch the virtual opponent and perceive encountered-type haptic feedback anywhere. We gathered insight into immersive exertion interaction from three exhibitions with iterative prototypes, then designed and implemented the hardware system and application. To understand the ability of mobility and weight loading, we conducted two technical evaluations and a laboratory experiment to validate the feasibility. Finally, a field deployment study explored the limitations and challenges of developing immersive exertion interaction with encountered-type haptics.

Utilizing haptic devices to enhance the immersive experience is a direct approach in virtual reality (VR) applications. Various studies develop haptic feedback using force, wind, and thermal mechanisms. However, most haptic devices simulate feedback in dry environments such as the living room, prairie, or city. Water-related environments are thus less explored, for example, rivers, beaches, and swimming pools. In this paper we present GroundFlow, a liquid-based haptic floor system for simulating fluid on the ground in VR. We discuss design considerations and propose a system architecture and interaction design. We conduct two user studies to assist in the design of a multiple-flow feedback mechanism, develop three applications to explore the potential uses of the mechanism, and consider the limitations and challenges thereof to inform VR developers and haptic practitioners.

Taiwanese opera is the important culture inheritance in Taiwan, however, this culture inheritance is dying in recently years. Although the Taiwan government and various Taiwanese opera troupes have worked hard for many years to promote this culture to campuses, and held several interest courses; this culture inheritance is still losing and dying. For elder people, Taiwanese opera and Taiwanese cultures are both precious culture treasures and parts of their childhood memories. Nowadays, young people in Taiwan are no longer familiar to Taiwanese, neither to Taiwanese opera singings. It is hard for young people to learn how appreciating this traditional culture. In this study, we refer to the current promotion methods of drama troupes which learn the singing method and posture of Taiwanese opera, we combine artificial intelligence techniques into traditional Taiwanese opera on singing and posture. The proposed system could analyzes students’ voice and postures, and then assists teachers to improve the learning performance of students. Students could compare their singing skill or postures with professional actors and adjust their singing and posture. Students of Taiwanese opera interest class can practice independently without professional teacher's guidance at home. In campus promotion, this game-like promotion method brings young people more acceptance of Taiwanese opera.

In this paper, we present Haptic Around, a hybrid-haptic feedback system, which utilizes fan, hot air blower, mist creator and heat light to recreate multiple tactile sensations in virtual reality for enhancing the immersive environment and interaction. This system consists of a steerable haptic device rigged on the top of the user head and a handheld device also with haptics feedbacks to simultaneously provide tactile sensations to the users in a 2m x 2m space. The steerable haptic device can enhance the immersive environment for providing full body experience, such as heat in the desert or cold in the snow mountain. Additionally, the handheld device can enhance the immersive interaction for providing partial body experience, such as heating the iron or quenching the hot iron. With our system, the users can perceive visual, auditory and haptic when they are moving around in virtual space and interacting with virtual object. In our study, the result has shown the potential of the hybrid-haptic feedback system, which the participants rated the enjoyment, realism, quality, immersion higher than the other.

In this study, an interactive block-building system named as e-Block system is developed for children to learn the concepts of geometric structures and space. First, the system displays a picture (e.g., car or house) of the target object intended for the child to assemble. The child then follows the instructions provided by the system and uses various blocks to build the object. After the child has completed the task, the system employs a pattern recognition algorithm to automatically compare the assembled object with the picture and determine whether the shape is identical. The experimental results show that the proposed system achieves high accuracy rate, and children in testing are enjoy this system and have more motivation to play with building blocks.

In this study, a Mandarin-phonetic-symbol communication aid named as zhuyin communication board is developed for children with high-functioning autism. The zhuyin communication board can execute on Tablet PC to assists autistic children to express their thought to other people. When an autistic child wants to express his thought, he can press the corresponding phonetic symbols by using the developed zhuyin communication board. To motivate the interesting of autistic children, the developed app provides a picture-based testing for learning Mandarin phonetic symbols of variety objects. Compared with the traditional paper keyboard, the developed aid could show the typing phonetic symbol immediately on the screen, and provides the voice of zhuyin pronunciation to improve autistic children's language perception skill.

The attractiveness of human faces can be predicted with a high degree of accuracy if we represent the faces as feature vectors and compute their relative distances from two prototypes: the average of attractive faces and the average of unattractive faces. Moreover, the degree of attractiveness, defined in terms of the relative distance, exhibits a high degree of correlation with the average rating scores given by human assessors. These findings motivate a bi-prototype theory that relates facial attractiveness to the averages of attractive and unattractive faces rather than the average of all faces, as previously hypothesized by some researchers.

In this paper, a gain-adjusted fuzzy PI/PD (GFPIPD) adaptive controller is proposed. The proposed controller first constructs fuzzy rules for fuzzy PD/PI controller with the fixed weighting. Then the fuzzy rules, which self-learning their parameters for a desired condition, are learned through the accumulated GA. Finally, fuzzy gain-adjusted mechanism is further learned through the accumulated GA for the variations of a measured system dynamics. The proposed GFPIPD controller is tested by the high order systems with time delay and variable system dynamics. The experimental results illustrate the performance of the proposed method

In this article, we propose a special type of decision tree, called a decision cascade, for binarizing document images. Such images are produced by cameras, resulting in varying degrees of brightness over different parts of the images. Our method decides what action to take on each part of the input image in order to obtain a satisfactory binary result. The advantage of this approach lies in its ability to learn decision rules from training data that may be labeled with multiple identities. Tests on images produced under improperly illuminated conditions show that our method yields much better visual quality and OCR performance than using a global threshold for binarization.

This paper presents a new approach to an on-line learning neuro-fuzzy system based on artificial immune systems. Via the proposed on-line learning algorithm, a neuro-fuzzy system can be incrementally constructed. Several data sets were tested to illustrate the effectiveness of the proposed on-line learning neuro-fuzzy system.

We propose a modified version of the K-means algorithm to cluster data. The proposed algorithm adopts a novel nonmetric distance measure based on the idea of "point symmetry". This kind of "point symmetry distance" can be applied in data clustering and human face detection. Several data sets are used to illustrate its effectiveness.

It is often reported in the technique literature that the success of the self-organizing feature map (SOM) formation is critically dependent on the initial weights and the selection of main parameters of the algorithm, namely, the learning-rate parameter and the neighborhood set. In this paper, we propose a healing mechanism to repair feature maps that are not well topologically ordered. The healed map is then further fine-tuned by the SOM algorithm so as to improve the accuracy of the map. Two data sets are tested to illustrate the performance of the proposed method.

In this paper we present an associative-memory-based face detection system. First, the symmetry of human faces is used to quickly locate all the candidates of human faces with all possible sizes and locations. Then two associative memories are used to decide whether or not a human face exists at the locations. Some experimental results are given.