This paper concerns health rumors that emerged during the outbreak of novel coronavirus. A serious game was designed as an experimental program for the prevention and control of health rumors. This covers two parts that include the TCP model for the games and cognitive questionnaires. The relevant variables of the experimental study are defined and the hypothesis is proposed. Two hundred experimental subjects are selected to participate in the experiments. Through the collection of relevant data in the experiments, statistical observations and comparative analysis are conducted to test whether the experimental hypothesis can be established. In addition, influence factors for the judgment and recognition of health rumors are considered in the comparison and analysis.
Visual speech-lip reading, making the computer understands what do speakers want to express through observing the lip direction of them. The most simply method of lip reading in early stage is to compare between characters from the frozen pictures and templates being stored. It neglects the character is changing with time. This method is very simply, but it only can classify the simple elements not the words, so it couldn't render great serves to speech recognition. Afterwards the adoption of behavioral characteristics is becoming more widespread. Because of the superior of Hidden Markov model (HMM), it can be applied in speech recognition widely. In recent years, it is also used in the research of lip-reading recognition. The classical HMM model makes two hypotheses: hidden expropriation hypothesis: the state at t+1 is only conditioned by the state at t, not the state before; the expropriation hypothesis from hidden state to visible state: the visible state at t only conditioned by the hidden state at t, not the state before. Such kind of hypothesis is not very reasonable in some practical application (such as lip-reading). In some kind condition, the state at t is not only conditioned by t-1, but also t-2. Therefore this thesis revises the assumed condition classical HMM to derive a new HMM model and algorithm, and applying it into lip-reading recognition to increase the discrimination.
In the decommissioning of the Fukushima Daiichi Nuclear Power Plant (FDNPP), the Japanese government has drawn mid- and long-term roadmap towards 1F decommissioning. However, the decommissioning work of the three reactors has faced difficulties due to the lack of realistic information about the damaged cores such as distribution of fuel debris. Since the radiation levels inside the reactor buildings have been too high for human access, remote detection, which combines robot and measurement technique, is required. In this study, we proposed a remote controlling method. The experiment has been conducted remotely controlling the ultrasonic measurement. Finally, the experiment data and results are successfully obtained through remote control.
Gomoku (also called "Five in a row") is one of the earliest popular checkerboard games invented by humans. In computing research, a tree-based data structure and its branching factor is the common technique of analyzing such board game. While eye-tracking techniques have been used for decades in interpreting human behaviors and improving human-computer interaction, it had rarely been utilized in analyzing engagement in game playing. Utilizing a game refinement theory alongside eye-tracking technique, the objective of this paper is to propose a new algorithm to measure the branching factor and quantify personalized challenge in playing a game. In addition, investigating the eye-tracking parameters may also provide means of measuring the players ability, further supporting the main objective of this paper. The findings showed that the proposed algorithm is a promising approach in order to help the game developer to design a game with a personalized challenge that changes according to the players ability; thus, possibly improving the players engagement and entertainment in games as well as other domains in the future.
In the process of decommissioning the Fukushima Daiichi Nuclear Power Plant (FDNPP). It is crucial the investigation of the internal conditions of the reactor. Nuclear fuel debris was formed in the reactor and need to be taken out first. Up to now, the main investigation is on the investigation of the vessel’s internal structure, and nuclear fuel debris distribution inside the reactor. However, to cut and store nuclear fuel debris, it is equally important to analyze the elemental composition of them.
As an important component of the future HumanComputer Interface, Automatic Speech Recognition is designed for the purpose of realizing identification recognition and natural language comprehension by means of human voice. Speech recognition technology has acquired significant achievements with some successful popularity and applications. IBM's ViaVoice system, for instance, has good performances when the vocabulary pool is small and when the noise is low. But its performance will be greatly degraded when used in real application environments. In future applications of the humancomputer interaction, such as in a car, at airport, or live interviews, higher requirements for robust systems will be needed, therefore we need to explore new ways. Proved highly effective by most researchers, the combination of visual features of lip motion with vocal features can raise the recognition rate of the automatic speech system, and make it more robust and more adaptable to real environments. This focuses on the recognition methods and speech and visual fusion algorithm, which aims to attract more researchers to be interested and concerned in this area of research.
Unlike traditional remote sensing inversion, this study proposes a new distribution–distribution scheme, which uses statistical inferences to estimate the probability distribution of in-water components based on the probability distribution of the observed spectra. The distribution–distribution scheme has the advantages that it rapidly gives the statistical information of the water of interest, assists the traditional scheme in improving models, and provides more valuable information for water classification and aquatic environment analysis. In this study, based on Landsat-8 images, we analyzed the spectral probability distributions of 688 global waters and found that many of them were normal, log normal, and exponential distributions with diverse patterns in distribution parameters such as the mean, standard deviation, skewness, and kurtosis. Using simulated and field-measured data, we propose a bootstrap-based distribution–distribution scheme and develop some simple remote sensing statistical inference models to estimate the distribution parameters of yellow substance in water.
Background Health rumors arbitrarily spread in mainstream social media on the internet. Health rumors emerged in China during the outbreak of COVID-19 in early 2020. Many midelders/elders (age over 40 years) who lived in Wuhan believed these rumors. Objective This study focused on designing a serious game as an experimental program to prevent and control health rumors. The focus of the study was explicitly on the context of the social networking service for midelders/elders. Methods This research involved 2 major parts: adopting the Transmission Control Protocol model for games and then, based on the model, designing a game named “Fight With Virus” as an experimental platform and developing a cognitive questionnaire with a 5-point Likert scale. The relevant variables for this experimental study were defined, and 10 hypotheses were proposed and tested with an empirical study. In total, 200 participants were selected for the experiments. By collecting relevant data in the experiments, we conducted statistical observations and comparative analysis to test whether the experimental hypotheses could be proved. Results We noted that compared to traditional media, serious games are more capable of inspiring interest in research participants toward their understanding of the knowledge and learning of health commonsense. In judging and recognizing the COVID-19 health rumor, the test group that used game education had a stronger ability regarding identification of the rumor and a higher accuracy rate of identification. Results showed that the more educated midelders/elders are, the more effective they are at using serious games. Conclusions Compared to traditional media, serious games can effectively improve midelders’/elders’ cognitive abilities while they face a health rumor. The gameplay effect is related to the individual’s age and educational background, while income and gender have no impact.
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