Real faces and robot faces: The effects of representation on computer-mediated communication

While there is much research regarding audio, video and text based communication, there has been little work concerning how users communicate via avatars—that is graphical embodiments of remote users. The aim of this study was to explore the effects of different forms of representation, by examining how users communicate via high quality video images and basic graphical representations in different communicative contexts. Communication analysis revealed that video images facilitate turn-taking, although they are not necessarily perceived very differently from basic avatars in terms of questionnaire responses. Using eye-tracking techniques, we found that while participants generally gaze more often at video images, this is dependent on the communicative context and is not necessarily an advantage in a problem-solving situation. This study has demonstrated the value of employing various measures and tasks in order to evaluate computer-mediated interactions. The results have implications for the use of video and graphical representations in computer mediated communication and suggest that the benefits of video must be considered in relation to the user's requirements (e.g. communication process versus outcome) and context in which the system is to be applied (e.g. problem-solving or social).     

A novel waterborne polyurethane coating modified by highly dispersed nano-boron carbide particles

In this study, waterborne polyurethane (WPU) coatings were modified by adding various compositions of nano-boron carbide (nano-B₄C) particles. In order to achieve proper dispersion of nano-B₄C in WPU and increasing chemical interactions between them, the nano-B₄C particles were treated with polyethylene glycol (PEG) or polypropylene glycol (PPG). The modified surface and microstructure of nano-B₄C were characterized by Fourier transform infrared, scanning electron microscopy and transmission electron microscopy. The deposition experiment was designed to evaluate the dispersion effect of nano-B₄C in PEG or PPG aqueous solution. The physical performance of nano-B₄C modified WPU coatings was measured following the national standards of paints and vanishes. The results revealed that the PEG6000 not only enhanced the interaction between nano-B₄C and WPU but also exhibited a remarkable ability to improve the physical performance of WPU coating. The coating with 15 wt% of nano-B₄C addition exhibited the best performance in terms of abrasion and hardness, which could be attributed to the best uniform dispersion of nano-B₄C particles in PEG6000 aqueous solution.     

Style synthesis and analysis of car designs for style quantification based on product appearance similarities

Understanding how similar design appears is a key element to understanding companies’ design strategies. However, it is difficult to evaluate companies’ design strategies with conventional style measurement methods since they only taxonomically measure whether a specific characteristic is included in a specific style. This study numerically measured car design similarities to synthesize and analyze car brand styles, thereupon discovering the design trends among car brands for strategic design positioning. This paper aims to find methods for quantifying style differences and identifying unique design elements of car designs among 23 automobile manufacturers based on design similarities of a large quantity of car designs (N = 119). To achieve this goal, a hybrid style quantification methodology – a mixture of Fourier decomposition, eye tracker, and shape grammar – was created to evaluate similarities, visual significance, and combinations of 19 car design elements. Fourier decomposition was incorporated to find the quantifiable values of design similarities of car design elements. Visual significance analysis was also conducted for each car design element through eye tracker to measure the importance of certain design elements for weighting factors. Then, each combination of design elements was compared with car design elements of other cars for similarity calculations. Finally, car design alternatives were synthesized, and transitions of design positioning were analyzed based on the similarity values weighed by the visual significance results. Using the suggested methods, alternate designs can be synthesized while preserving brands’ design styles, and design trends can be analyzed for strategic evaluation.     

基于SVM的P2P流量识别

根据P2P应用从最初的采用固定的端口号,发展到动态端口,再发展到伪装端口,甚至发展到现在的一些采用加密技术的具有反侦察意识的新型的P2P应用这样一个变化快的特点,再利用支持向量机分类的本质,提出一种基于SVM的P2P流量识别方法.通过实验证明,该方法具有较高的识别率,对未知协议的F2P识别精度也很高,说明采用支持向量机技术进行P2P流量识别的有效性.     

Establishment-level occupational safety analytics: Challenges and opportunities

In occupational safety and health, big data and analytics show promise for the prediction and prevention of workplace injuries. Advances in computing power and analytical methods have allowed companies to reveal insights from the “big” data that previously would have gone undetected. Despite the promise, occupational safety has lagged behind other industries, such as supply chain management and healthcare, in terms of exploiting the potential of analytics and much of the data collected by organizations goes unanalyzed. The purpose of the present paper is to argue for the broader application of establishment-level safety analytics. This is accomplished by defining the terms, describing previous research, outlining the necessary components required, and describing knowledge gaps and future directions. The knowledge gaps and future directions for research in establishment-level analytics are categorized into readiness for analytics, analytics methods, technology integration, data culture, and impact of analytics.     

Round-trip driving effects on driving performances and mental workload under different traffic rules

This study investigates the effect of switching between different traffic rules (left-versus right-hand traffic) on driving performance and mental workload. A driving simulation environment was developed according to the real environment. Two urban roads with different traffic systems were simulated. Twenty participants executed intersection turns and continuous car-following behavior in four simulated driving stages, including driving with familiar, unfamiliar, second time unfamiliar, and back to familiar traffic rules. The mean and standard deviations for speed, distance headway, and the standard deviation of lateral position were recorded as driving performance. Mental workload was determined using the NASA-TLX and Rating Scale Mental Effort questionnaires. One-way analysis of variance was used to evaluate the differences between the four driving stages using subjective and objective measures. The results showed that significant differences were obtained in all measures when driving in the four driving situations, except for the speed standard deviation. The car-following behavior was the most unsafe (significantly larger standard deviations for distance headway and mental workload) when driving in unfamiliar road traffic compared with the other stages. When driving under unfamiliar traffic rules for the second time, the mental workload was significantly relieved and the lane-keeping ability significantly improved. The results indicated that providing an adaptive runway for drivers to familiarize themselves with different traffic rules is necessary to improve driving performance and safety. These findings provide useful information for designing bridges linking two places with different traffic rules to increase traffic safety.     

A quick identification model for assessing human anxiety and thermal comfort based on physiological signals in a hot and humid working environment

We propose a simple and quick method for quantifying workers' anxiety and thermal comfort levels using physiological signals. Nine subjects enrolled in a series of controlled laboratory experiments involving varying temperature, relative humidity, and labor intensities. A total of 40 experiments were conducted, and 1592 groups of anxiety data and 1624 groups of thermal comfort data were obtained, respectively. During 2-h-working trials, Electroencephalogram (EEG), photoplethysmography (PPG), and pupil diameter of each subject were collected synchronously, and the State-Trait Anxiety Inventory (STAI) and thermal comfort vote (TCV) were completed in stages. Random Forest was adopted to screen out the appropriate sensitivity feature indicators of anxiety levels and thermal comfort levels from the 70 features of the 10 EEG channels. Finally, Random Forest, Gradient Boosting Decision Tree, K-nearest Neighbor Algorithm, and Support Vector Machine were used to determine relevant physiological data combinations and modeling algorithms. The Precision of the anxiety level and thermal comfort level quick identification model based on Random Forest Algorithm can reach 81.04% and 84.79%, respectively. This suggests that the proposed quick identification method for assessing workers' anxiety and thermal comfort levels holds promise. Physiological data need to be obtained by monitoring only PPG, pupil diameter, and 5 EEG channels. By processing these data, the workers' anxiety and thermal comfort level could be judged realistically to ensure their safety. It is suggested that PPG, pupil diameter, and EEG should be considered all together in the future study of anxiety and thermal comfort.     

Turk-2, a multi-modal chess player

In this paper we present Turk-2, a hybrid multi-modal chess player with a robot arm and a screen-based talking head. Turk-2 can not only play chess, but can see and hear the opponent, can talk to him and display emotions. We were interested to find out if a simple embodiment with human-like communication capabilities enhances the experience of playing chess against a computer. First, give an overview of the development road to multi-modal communication with computers. Then we motivate our research with a hybrid system, we introduce the architecture of Turk-2, we describe the human experiments and its evaluation. The results justify that multi-modal interaction makes game playing more engaging, enjoyable – and even more effective. These findings for a specific game situation provide yet another evidence of the power of human-like interaction in turning computer systems more attractive and easier to use.