Average-consensus protocol is one of the ways to develop distributed time-synchronization algorithms in Internet of Things (IoT) networks. However, the large number of iteration leads to a common time notion issue in nodes. This poses a critical challenge in the convergence of the time-synchronization algorithm and resulting asymptotic convergence in the average consensus protocol. In this article, a parameter-sharing-based average-consensus time-synchronization (PACTS) algorithm is proposed. For fast convergence, the proposed PACTS quickly forwards the time information to multihop nodes and employs multihop average-consensus instead of single-hop average consensus. Specifically, a node asynchronously and periodically broadcasts the relative clock offset estimation of neighbors with its local time information. Meanwhile, the relative clock offset estimation of the multihop node is calculated and used to estimate the average value. Consequently, an average consensus among local multihop nodes is obtained. As a result, the iteration number and convergence time are significantly reduced over the network. Finally, the experimental results indicate that the proposed PACTS algorithm has low complexity, high accuracy, and quick convergence.

This study proposes to design a mobile robot to assist language learning. This should motivate learners to practice speaking and listening in order to improve their English skill. This project provides a low-cost robot for all students who are willing to spend time learning English inside and outside the classroom. This research proposes to deliver a robot with wheels, cameras, microphones and speakers. Raspberry Pi 3 and Arduino provide the computation power to interact with and control the robot. The robot converses with English learners to accomplish specific tasks. In one task, a learner asks the robot to travel on a street map with simple roads and locations such as a library, a park, and an elementary school. The utterances of the learner are recognized with a Google cloud service, and the voice response of the robot is generated with text-to-speech technology. When the robot walks on a street map, it does image processing to follow lanes and recognize intersections and a number of prescribed locations. An empirical experiment was run to study the learning process of learners. Some interesting results were found.

Ecological education is important to let the young generation to learn that the flora and fauna in the environment are fragile and sensitive to pollution. The Taijian National Park of Taiwan is a beautiful and winter shelter for black-faced spoonbills migrated from Korea and China. In this study, an Android app was developed with a picture book to educate the public about spoonbills. A technology of augmented reality was used in the app in order to help users focus their attention on the critical elements in the environment. The app and the picture book were used by 54 elementary school students in an empirical study. Preliminary results showed that the app and the picture book was a positive educational experience for the students. Future work would focus on the use of more advanced machine learning technology and the exploration of more ecological issues in public education.

This study presents a fast intra‐prediction algorithm for a high‐profile H.264 encoder. First, a pre‐decision algorithm is proposed to reject the impossible block size based on image variance. Then a fast 4 × 4 block prediction algorithm is proposed to select four possible modes from nine predicted modes based on the edge‐filtering detection. With a hierarchical approach, the 8 × 8 block prediction is based on the result of the chosen 4 × 4 block mode. This approach selects only one to five modes of H.264 coding from nine prediction modes. Following the prediction of the 16 × 16 luminance block and 8 × 8 chrominance block is mapped by the result of the 8 × 8 luminance block by checking only one to two modes. The pre‐decision algorithm, the fast 4 × 4, 8 × 8 and 16 × 16 block prediction algorithms can be combined to improve the coding speed. Simulations demonstrate that the proposed algorithm can save about 70% coding time at most for intra‐frame coding in the H.264 system while increasing only about 1% bit‐rate with a negligible peak signal‐to‐noise ratio drop.

Traditional physics labs in high school ask students to follow step-by-step procedure to collect data in order to confirm given physical laws. This study proposes to let students take up the role of scientist in physics labs. Modern physics labs can make use of powerful mobile technologies of smartphones and Lego Mindstorms NXT. These devices can be used to act as moving objects as well as data acquisition devices. Moreover, students are asked to find the functional relation between physical variables, e.g., pendulum length and pendulum period, by detecting patterns in experimental data. An empirical study was done in a real high school setting and some interesting preliminary results were found.

Inductive reasoning is an important domain-general skill for learning science and math, etc. Unfortunately, previous studies have pointed out that students still have many weaknesses, when they do the tasks of inductive reasoning. A web-based environment is designed to train their skills of inductive reasoning. The pedagogy of self-directed experimentation is adopted in the learning environment, in which learners are asked to express one variable as a function of another variable. Two input interfaces are used for the users to input expressions. The control group uses a traditional tool of expressing a dependent variable as a function of an independent variable. The experimental group uses a tool that can generate a new term by addition, subtraction or multiplication of two existing terms of expressions. Some interesting results are reported.

The learners of English as a second language generally need many practices on writing English, identification of the mistakes in their English, and feedback hints on how to correct their mistakes. A computer-assisted online system is designed to address these issues in a context of learning from a corpus of parallel English-Chinese corpus of New York Times news articles. In the system, students match chunks of English words to chunks of Chinese strings and order chunks of English to produce the original English sentences. Results from an empirical experiment indicated that the students found the tasks challenging and felt that the learning activities were meaningful in improving their knowledge of English. Their score improvement increased when they practiced more.

This paper presents a tool for drawing dynamic geometry figures by understanding the texts of geometry problems from common textbooks. With the tool, teachers and students can construct dynamic geometry figures on a webpage by inputting a geometry problem in natural language. First a knowledge base for understanding geometry problems is built. With the help of a knowledge engineering tool InfoMap, geometric concepts are extracted from an input text. The concepts are then used to output a multi-step JavaSketchpad script that constructs a dynamic geometry figure step by step. Finally, the system outputs the script as a HTML document that can be read and visualized with an internet browser.

In this paper, a diagnosis system for problem posing is developed. The domain of this system is restricted to area word problems. The student poses the problems through the system with phrase combination approach. Then the system diagnoses the problem and provides the information for students to revise the posed problem, if needed. The system uses an ontology-based knowledge engineering tool, InfoMap, to represent the concept knowledge for diagnosing area word problems posed by students.

Many students of geometry theorem proving do not perform satisfactorily even when asked to prove simple theorems. Their problems might arise from their poor understanding of the involved geometric concepts, or from their ignorance of intermediate geometric propositions that are needed to derive the final conclusion. To address these issues, we propose a dynamic geometry environment for theorem proving that integrates the elements of exploration and theorem proving.