This study summarizes and reports first-time users' satisfaction of a Blackboard Learn user interface that had been adopted as an online/blended teaching-learning management tool. Users' satisfaction was measured in terms of the overall consistency, ease of use, universability, positive aspects, and problems/limitations of the Blackboard Learn user interface. Data were collected through a number of 5-point Likert scale type items using an online survey. The survey also gathered participants' gender and major area of study to determine if there exists any significant difference in their satisfaction, among the possible groups in these measures. Results revealed that first-time Blackboard Learn users are most likely overall satisfied in using it without any
Video shot boundary detection, which segments a video by detecting boundaries between camera shots, is usually the first and important step for content-based video retrieval. This paper investigates methods which are effective in detecting abrupt transitions and gradual transitions, respectively, and proposes an integration scheme to combine their results, aiming to detect both types of transitions.
This paper presents some projects in the area of network security suitable for online and/or in-class delivery in relevant courses. The developed projects consider the E-Learning environment and provide support to allow distance learning without requiring the students and professor to be in the same physical location.
Captcha (Completely Automated Public Turing test to tell Computers and Humans Apart) is a widely used online security tool that ensures that a computer program is not posing as a human user. While smart programs with advanced image processing capability have already cracked picture based captcha systems there is a need for making the test harder. This paper presents a design prototype of a simplified type of labeled-image captcha where a picture of a common animal or household item is marked with a number of different labels and the users will be asked to provide the correct label for specific parts of the picture. Due to human’s familiarity with body shapes and part names of such common pictures, they will easily identify a specific organ/parts of the picture. Such labeled-image captcha tests are expected to be very easy for human users regardless of their culture, age, gender, educational background and other discriminations but tough for the bots and automated computer programs.
Captcha (Completely Automated Public Turing test to tell Computers and Humans Apart) is a widely used online security tool that ensures that a computer program is not posing as a human user. While smart programs with advanced image processing capability have already cracked picture based captcha systems there is a need for making the test harder. This paper presents a design prototype of a simplified type of labeled-image captcha where a picture of a common animal or household item is marked with a number of different labels and the users will be asked to provide the correct label for specific parts of the picture. Due to human's familiarity with body shapes and part names of such common pictures, they will easily identify a specific organ/parts of the picture. Such labeled-image captcha tests are expected to be very easy for human users regardless of their culture, age, gender, educational background and other discriminations but tough for the bots and automated computer programs.
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