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The demand for flexible and wearable electronic devices with excellent stretchability and sensitivity is increasing, especially for human motion detection. In this work, a simple, low-cost and convenient strategy has been employed to fabricate flexible strain sensor with a composite of carbon black and silver nanoparticles as sensing materials and thermoplastic polyurethane as matrix. The strain sensors thus prepared possesses high stretchability and good sensitivity (gauge factor of 21.12 at 100% tensile strain), excellent static (almost constant resistance variation under 50% strain for 600 s) and dynamic (100 cycles) stability. Compared with bare carbon black-based strain sensor, carbon black/silver nanoparticles composite-based strain sensor shows ~18 times improvement in sensitivity at 100% strain. In addition, we discuss the sensing mechanisms using the disconnection mechanism and tunneling effect which results in high sensitivity of the strain sensor. Due to its good strain-sensing performance, the developed strain sensor is promising in detecting various degrees of human motions such as finger bending, wrist rotation and elbow flexion.

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Oil spills bring great damage to the environment and, in particular, to coastal ecosystems. The ability of identifying them accurately is important to prompt oil spill response. We propose a semi-automatic oil spill detection method, where texture analysis, machine learning, and adaptive thresholding are used to process X-band marine radar images. Coordinate transformation and noise reduction are first applied to the sampled radar images, coarse measurements of oil spills are then subjected to texture analysis and machine learning. To identify the loci of oil spills, a texture index calculated by four textural features of a grey level co-occurrence matrix is proposed. Machine learning methods, namely support vector machine, k-nearest neighbor, linear discriminant analysis, and ensemble learning are adopted to extract the coarse oil spill areas indicated by the texture index. Finally, fine measurements can be obtained by using adaptive thresholding on coarsely extracted oil spill areas. Fine measurements are insensitive to the results of coarse measurement. The proposed oil spill detection method was used on radar images that were sampled after an oil spill accident that occurred in the coastal region of Dalian, China on 21 July 2010. Using our processing method, thresholds do not have to be set manually and oil spills can be extracted semi-automatically. The extracted oil spills are accurate and consistent with visual interpretation.

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Humanism has never been able to establish a firm place in technical education, which remains predominantly pragmatist in response to industry needs, certification requirements and educational standardisation. However, after a period of decline, humanism has made somewhat of a comeback as part of the movement toward student-centred education. Research conducted at a technical college showed that although . This research indicated that including humanistic elements in educational practice will enable instructors to be more effective in helping students to develop skills in relation to team work, problem-solving, systems improvement, lifelong learning and other areas that are becoming increasingly necessary for success in the workplace. The include a constructivist approach with a focus on contextual teaching and learning using situated cognition, cognitive apprenticeships, anchored instruction and authentic assessment. At the same time, some suggestions for improving professional development for teachers by using a Gestalt approach along with self-study in the context of learning communities have been discussed.

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