Browsing by Author "Zhang, Xin"

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Analyzing Students' Attention in Class Using Wearable Devices
(2017-01-01)
Zhang, Xin
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Wu, Cheng-Wei
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Fournier-Viger, Philippe
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Van, Lan-Da
;
Tseng, Yu-Chee
Detecting students' attention in class provides key information to teachers to capture and retain students' attention. Traditionally, such information is collected manually by human observers. Wearable devices, which have received a lot of attention recently, are rarely discussed in this field. In view of this, we propose a multimodal system which integrates a head-motion module, a pen-motion module, and a visual-focus module to accurately analyze students' attention levels in class. These modules collect information via cameras, accelerometers, and gyroscopes integrated in wearable devices to recognize students' behaviors. From these behaviors, attention levels are inferred for various time periods using a rule-based approach and a data-driven approach. The former infers a student's attention states using user-defined rules, while the latter relies on hidden relationships in the data. Extensive experimental results show that the proposed system has excellent performance and high accuracy. To the best of our knowledge, this is the first study on attention level inference in class using wearable devices. The outcome of this research has the potential of greatly increasing teaching and learning efficiency in class.
Energy Harvesting Techniques: Energy Sources, Power Management and Conversion
(2015)
Fan, Philex Ming-Yan
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Wong, Oi-Ying
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Chung, Ming-Jie
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Su, Tze-Yun
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Zhang, Xin
Energy harvesting techniques have been developed more than a decade and received much attention in realizing long-term energy autonomous microsystems. Many converter topologies and circuit techniques have been reported to effectively convert the harvested energy to usable outputs. In this paper, major green energy sources as well as the equivalent circuits are reviewed. In addition, maximum power point tracking (MPPT) technique and power conversion topologies are also included.
Smart Surveillance with Context and Location Sensitivity and Quality Control
(2016-01-01)
Wu, Kun-Ru
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Liang, Jia-Ming
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Zhang, Xin
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Li, Kuan-Yi
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Lin, Yi-Ting
Smart video surveillance systems are essentials in modern environments to ensure safety and security for lives and property. In order to capture critical clues of reconnaissance, it is important to automatically and dynamically control the surveillance sensitivity and quality for detecting abnormal/suspicious events to perform high quality monitoring. In this work, we design a smart video surveillance system, which fully utilizes pan tilt-zoom (PTZ) cameras and well integrates with environment sensors (such as fire/motion/door sensors) while cooperating with wearable devices that can adaptively monitor events and ensure the surveillance quality in terms of pixel-per-foot (PPF), viewing angles, timeliness, and accuracy. In addition, this system also supports to define the special monitoring tasks and surveillance requirements, such as the surveillance timeliness and duty cycle for particular moving objects to be tracked per time unit. Then, a smart camera dispatch algorithm will calculate and determine the best cameras set with the corresponding configurations to accomplish the surveillance tasks effectively and precisely. We will show how our system realizes smart detecting and monitoring in this demonstration by leveraging PTZ cameras, environmental sensors and wearable devices.