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Through three elements of thinking style, learning portfolio, and learning outcome, this study analyzes the correlation and explores the learning results of students based on different thinking styles and learning experiences. Thinking styles are based on “Function”, “Form”, “Level”, “Scope”, and “Leaning” five orientations to distinguish between different styles, from which to identify the individual characteristics of students, and through the student’s learning experience on the Learning Management System (LMS), to understand the different personal characteristics of students’ learning styles and learning preferences. Consequently, the teacher can adaptively teach students with different thinking styles according to their characteristics and adjust the teaching strategy interacting with the students in time.

The digital learning has been an important subject for improvement and research in education, especially the development of the Internet and the advancement of computer multimedia tools. This study involves the design of teaching materials and how the role of the teacher acts in digital teaching videos. Thus, two teaching methods are concerned to capture the teaching videos, one is only to capture teaching screen (PPT) without teacher's body language, and the other is to capture teacher's presentation in front of an interactive whiteboard such that the teacher can reveal the situation of problem-solving and logical thinking. Contributions of this research are clearly to state "Teaching Material Favorability" and "Learning Motivation" which will really allow students to cause accompanied effect and reflection in their learning interest from situated impacts.

The paper proposes an interactive virtual reality (VR) 360-degree panorama application system which can be applied in education for soil and water conservation. In the development of the system, the interactive VR 360-degree panoramic videos are produced first. The contents of videos come from introductions of facilities built in soil and water conservation outdoor classrooms. The design of video contents and interactions between video contents and users is on the basis of the cognitive theory of multimedia learning. Additionally, the system offers an android app developed using VR technology to offer users with interactions between users and videos. Learners first download the app into a smart phone and then insert the phone into a cheap VR helmet. Subsequently, they play the app with wearing the VR helmet to watch VR 360-degree panoramic videos so as to achieve immersion on watching video in a 3D VR environment. Moreover, learners can move the interaction sign, a single-circle shape, by shaking their VR helmets on the specific marks on screen to trigger corresponding interactive actions such as selecting a video, exiting viewing video, answering questions of true-false items, etc. Experimental results show the way participants received the system has better interaction than that without the system. Furthermore, the interaction portfolios are also collected in the cloud space for future analysis. Finally, the system can be also applied in learning activities of performing flipped classroom strategy when people will visit soil and water conservation outdoor classrooms.

The paper proposes an interactive virtual reality (VR) application in education for soil and water conservation. Here an android app was developed using VR technology, which can be used for reading a picture book for learning concepts in soil and water conservation. A story is presented by the picture book. Learners play the app with VR in a smart phone and then inserting the smart phone into cheap VR helmets. Learners can watch the VR application by wearing the VR helmet so as to achieve immersive reading in a 3D VR environment. Hereafter, watching the VR application is called watching the 3D VR picture book or 3D VR video. Moreover, learners first wear the VR helmet to read the 3D VR video and then they can use the interaction sign, a double-circle shape, to trigger interactive actions such as playing sound for speaking story, going to next page, going to previous page, showing text annotations, displaying questions for getting responses to the questions, etc. Experimental results show the way learners read the 3D VR picture book has better learning effect, interaction. Furthermore, the interactive portfolios are also collected in the cloud space immediately while triggering actions by the app using the interaction sign. Each record is constructed by experience API. Therefore, interactive portfolios can be analyzed in the future for realizing the behaviors while reading 3D VR picture book.

An e-Learning video having more than one screen enables users to compare the various sources with 360-degree video streaming situation learning environment. Moreover, learners can use 360-degree multiple illustrations to develop their interrelated concept and knowledge. This proposed solution could provide learners during self-learning by addressing and enhancing their physical and psychological factors including attention and cognitive load. However, attention is a mental phenomenon that humans cannot always focus on simultaneous presentations of information. Cognitive load may become profoundly heavy while processing rich information from multiple sources simultaneously. Therefore, the aim of this study is to investigate the split-attention effect, worked example effect, and learning achievement of using multiple screens in learning environments for a Discrete Mathematics course. The results of this study showed significant differences of two learning effects and learning achievement of learners between two learning environments. To conclude, this study may provide evidence toward explaining the influences of split attention of learners and their learning with worked examples and the effects of learning in a 360-degree multiple-screen video streaming environment, as well as in providing users with another suggestion for using the multiple - screen environment in e-Learning.

This paper develops a multi-user streaming feedback system for cooperative learning in classroom learning. The system offers Android Apps to perform mobile interactive learning. Therefore, the system can be applied for interactive teaching. It also provides a game-based approach to improve students' cooperative learning. On the cognitive development of the game-based learning, the students use mobile devices camera and record their screen activity to play from streaming server and broadcast the contest on the streaming video wall such that the whole class can be able to see the contest. Moreover, the teacher can observe students' learning status and problems in real-time. That students have more willing to concentrate on their learning in the lecture. In other words, the streaming feedback system for cooperative learning in game-based theory classroom learning increases interactive between the teacher and students. Therefore, it improves learners' interest and efficiency in learning.

This article presents a Color Image Retrieval method based on Combined Color Descriptions and Features, which is called the CIRCCODF method hereafter. A main contribution of the article is that the method first devises a modified-color-feature-extraction algorithm, called Image Vector (IV). Then, another color features, Color Layout Descriptor (CLD), which is used in the MPEG-7, is selected. Subsequently, CLD and IV are effectively combined to represent each color image. Experimental results shows that the CIRCCODF method possesses better retrieval performance than that of the other existing schemes under considerations here.

The paper presents a teaching model using an ebook tool with lecturing function and a game-based student response system in flipped classroom for a seminar course for graduate students. The ebook tool with lecturing function helps presenters (students) to easily display their multimedia materials by dual-codes mode and to interact their presentation with students (audience) by handwriting, a screen including video and powerpoint slides, two-pages swapping, etc. The Game-based Student Response System is utilized in the teaching model to increase more interactions among presenter and audience by answering questions using mobile devices in a game-like fashion.

This paper presents an Image Filter with noise detector using Fuzzy Logic and Particle Swarm Optimization (PSO), which is called the IFFLPSO filter, for removal and restoration of impulse noises. In IFFLPSO filter, the fuzzy logic is employed to efficiently design the noise detector. The proposed filter effectively judges the input pixel vector whether it is corrupted or not. Meanwhile, the particle swarm optimization algorithm (PSO) is utilized so as to optimize the noise detectors to enhance the noise detection performance. Subsequently, in order to enhance the restoration performance of proposed filter, the color ratio of spot's region in the restored image is employed to determine the spot's color. Also, the pixel vectors with different color ratios in the spot region are detected. Finally, the vector median filter is utilized to restore the corrupted pixels. Experimental results demonstrate that the proposed image filter outperforms the existing other well-known filters in restoration performance. And the system can be widely applied in microarray image processing.

This paper presents a novel facial emotion recognition (FER) technique, based on support vector machine (SVM), to recognize the facial emotion expression. Here it is called the FERS technique. First, a face detection method, which combines the Haar-like features (HFs) method with the self quotient image (SQI) filter, is used in the FERS technique to accurately locate the face region of an image. It can improve the detection rate due to the use of the SQI filter to overcome the insufficient light and shade light. Subsequently, angular radial transform (ART), discrete cosine transform (DCT) and Gabor filter (GF) are employed in the procedure of facial expression feature extraction. An SVM is trained and then utilized to recognize the facial expression for a queried face image. Finally, experimental results show that the recognition performance of the FERS technique can be better than that of other existing methods.

The paper proposes an Image Filter with a hybrid impulse detector based on Decision Tree (DT) and Particle Swarm Optimization (PSO), which is called the IFDTPSO filter, for the recovery of the corrupted image by impulse noises. The Several impulse noise detectors are combined in the design of the IFDTPSO filter to form an impulse noise detector (IND) which is designed by DT and PSO to effectively detect corrupted pixels of noisy images. The IND can correctly classify pixels as either noise-free or noise-corrupted, and then, restoring process utilizes the median filter to powerfully recover corrupted pixels from noisy images. Experimental results demonstrate that the IFDTPSO filter outperforms the existing well-known methods.

This paper presents a robust lossless watermarking technique using alpha-trimmed mean and support vector machine (SVM), which is called the RLW method hereafter. It does not damage the contents of original images during watermark embedding, because it uses trained SVMs to memorize the watermark or owner signature and then exploits the trained SVMs to estimate the watermark. Meanwhile, its robustness can be enhanced using alpha-trimmed mean operator against attacks. Experimental results demonstrate that the RLW method not only possesses the robust ability to resist on image-manipulation attacks under consideration but also, in average, is superior to other existing methods being considered in the paper.

A novel character recognition method, called character recognition based on neural network and Dempster-Shafer theory (CRNNDS), is proposed in this paper. The CRNNDS integrates a recurrent neural network (RNN) and Dempster-Shafer (D-S) theory to recognize handwritten characters. It employs an RNN to effectively extract oriented features of a handwritten character and then these features are applied to Dempster-Shafer theory which can powerfully estimate the similarity ratings between a recognized character and sampling characters in the character database. Experimental results demonstrate that the CRNNDS system achieves a satisfying recognition performance.

Phonetic awareness is a critical and often neglected component in the learning of the English language. It is submitted that good pronunciation can improve upon spelling and reading abilities of children. This paper describes a multimedia (ML) learning system that is directed at children with the aim of enhancing their English pronunciation. The system uses hidden Markov models (HMMs) to analyze phonetic structures, identify and capture pronunciation errors. It provides children with targeted advice in pronunciation, intonation, rhythm and volume that is equivalent to four years of instruction. The system was tested in an informal experiment that involved thirty two elementary students that were divided into two groups: sixteen high and sixteen low achievers. It helped the low achieving group to significantly improve not only their English pronunciation but their spelling and reading abilities.

A robust watermarking (ROW) technique is proposed to protect image authorization. The ROW technique explores features which are the distances among rank orders of the coefficients in subbands of a wavelet-domain image. The features are then utilized to divide wavelet blocks of the image into three categories. A set of thresholds, which corresponds with the three categories, is exploited to develop the embedding and the extraction algorithms. The ROW technique retrieves watermarks without original images. The GROW technique, which employs a genetic algorithm to optimize the ROW technique, to enhance the robustness of the ROW technique. Experimental results illustrate that the performances of the ROW and the GROW techniques are acceptable.

Summary form only given. This paper presents a GA-based adaptive image watermarking technique with just-noticeable distortion (JND) profile and fuzzy inference system (FIS) which is referred to as the GAIWJF technique. During watermark embedding, the GAIWJF technique embeds a watermark into an image by referring to the JND profile of an image so that the technique makes the watermark more imperceptible. The GAIWJF technique employs image features and local statistics to create an FIS containing three fuzzy input variables, eight fuzzy inference rules, and a single fuzzy output variable. During watermark extraction, the GAIWJF technique does not require the information of original images because it employs the FIS to extract watermarks. Also, the FIS is further optimized by a GA so that the performance of watermark extraction can be improved. From experimental results, the GAIWJF technique not only makes the embedded watermark more imperceptible but also possesses adaptive and robust capabilities to resist image manipulations.

Summary form only given, as follows. Image detail preservation and impulse noise attenuation are not easy to simultaneously achieve in image restoration design. This study proposes a novel adaptive type-2 fuzzy median (type-2 FM) filter to accomplish these objects. The novel filter is mainly based on the uncertainty handling ability of the type-2 fuzzy sets to use the filtering behavior merits of two filters: the fuzzy median (FM) filter and the type-1 FM filter. On the design of a type-2 FM filter, the proposed method adopts a powerful scheme to extend the restriction on the derivation of membership functions by the FM filter, and a flexibility inference mechanism to improve the performance in the limited memory usage by the type-1 FM filter. Extensive simulation results illustrate that the type-2 FM filter not only possesses desirable robustness in suppressing noises but also outperforms other proposed filtering approaches.