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Quadriplegia is an extremely serious disease. Due to the impaired function of patients' limbs, it is difficult for them to move freely by a wheelchair. This dilemma has become a huge obstacle to the rehabilitation of the disabled, and meanwhile added extra burden to society. To improve the quality of their lives, our team designs a vision-controlled automatic wheelchair based on the pupil center and cornea reflection (PCCR) technique. By constructing a multi-sensor real-time intelligent control system, the wheelchair realizes eye-controlled movements and other auxiliary functions such as emergency communication and rollover alarm. Through continuous optimization of multiple versions, a more intelligent, highly reliable, and low-cost wheelchair is manufactured.

Multiple-shot human re-identification is an important issue in both academia and industry. It addresses the problem of building correspondences among object instances appearing in a camera network using biometric cues. Among all possible cues, face is a typical one that has long been investigated, while the whole body has become a recent trend. This problem is challenging because of small intra-class similarities and inter-class dissimilarities caused by the variations of human appearance in real scenarios. Existing methods mainly involve designing a representation and/or devising a measure to explore the within-class compactness and between-class separation. Although encouraging progress has been made, the results are still far from satisfactory. In this paper, we propose a novel set-based matching model, "Locality Based Discriminative Measure", to re-identify the human body when a set of test samples for each person are available. A new set-to-set dissimilarity is crafted considering both majorities and minorities of samples from each pair of sets. The discriminability of this dissimilarity is then further exploited by the local metric field; it can thereby serve as a more capable low-level measure to support the high-level measure for the final matching. Extensive experiments on widely used benchmarks demonstrate that our proposal remarkably outperforms state-of-the-arts.

SUMMARY Re-identifying the same person in different images is a distinct challenge for visual surveillance systems. Building an accurate correspondence between highly variable images requires a suitable dissimilarity measure. To date, most existing measures have used adapted distance based on a learned metric. Unfortunately, real-world human image data, which tends to show large intra-class variations and small inter-class differences, continues to prevent these measures from achieving satisfactory re-identification performance. Recognizing neighboring distribution can provide additional useful information to help tackle the deviation of the to-be-measured samples, we propose a novel dissimilarity measure from the neighborhood-wise relative information perspective, which can deliver the effectiveness of those well-distributed samples to the badly-distributed samples to make intra-class dissimilarities smaller than inter-class dissimilarities, in a learned discriminative space. The effectiveness of this method is demonstrated by explanation and experimentation.

What are the experiences of Chinese students taking engineering courses taught in English by American professors using active learning techniques? Case studies of three such courses are explored in this work. Specifically, two American professors taught courses in English to about 100 students whose native language was Chinese. These courses included a required Electronics course for electrical engineering sophomores, a seminar on Medical Device New Product Development within a required Biomedical Instrumentation course for juniors in biomedical engineering, and a lecture series on New Product Development for first year honors students. All courses included homework teams and active learning techniques in the classroom. Focus groups were conducted near the end of the courses to examine students' experiences. Results and analyses of this qualitative data are presented here. Themes which emerged include the importance of teamwork, challenges with and comfort gained using English, conflicting attitudes toward teaching style, and exposure to practical applications.

In China, innovations in laboratories or lectures for fundamental required courses are rare. However, the Electric and Electronic Experiment Center of Southeast University has designed an innovative comprehensive laboratory to develop active autonomous learners and integrate three fundamental laboratory courses: Circuits, Logic Design, and Electronics. This innovative laboratory has been used since 2009 with second-year honors students in the Class for Advanced Science and Technology. The experimental plan including laboratories and projects and student assessment are discussed. Instructor response is considered. This course could serve as a model for other institutions.

Faculty development (FD) is a relatively young and under-developed field of study in China. However, faculty development is essential to higher engineering education development. Faculty's pedagogy have a strong impact on shaping the way students looking at the world. This study endeavors to explore the humanities characteristics of faculty development in its current context in engineering colleges in China. The pedagogical tradition and moral background and faculty evaluation system have been discussed in order to give a humanities explanation of the situation of faculty development in China.