Cultivating Contemplative Mind in the Classroom

In Fall 2019, we showed video interviews of successful (i.e., graduated) alumni to first-year seminar students in the hope that incoming students would be inspired to adopt similar success strategies leading to increased retention and completion of their UNLV degree. The Academic Success Center filmed interviews with ten UNLV graduates who took our first-year seminar, COLA 100E. These COLA 100E Success Stories were then edited into three videos, each focusing on a particular theme, such as the first-year transition, the major selection process, and the key tips for graduation. The goal was that these successfully-graduated students would serve as motivational role models for UNLV’s diverse first-year student population. Though the alumni echoed concepts taught in the class, we imagined these peers would be more relatable than the instructor alone, encouraging students to identify with and potentially adopt new approaches to and perspectives of success early in their college careers.https://digitalscholarship.unlv.edu/btp_expo/1090/thumbnail.jp

Cost-Sensitive Decision Tree with Multiple Resource Constraints

Resource constraints are commonly found in classification tasks. For example, there could be a budget limit on implementation and a deadline for finishing the classification task. Applying the top-down approach for tree induction in this situation may have significant drawbacks. In particular, it is difficult, especially in an early stage of tree induction, to assess an attribute’s contribution to improving the total implementation cost and its impact on attribute selection in later stages because of the deadline constraint. To address this problem, we propose an innovative algorithm, namely, the Cost-Sensitive Associative Tree (CAT) algorithm. Essentially, the algorithm first extracts and retains association classification rules from the training data which satisfy resource constraints, and then uses the rules to construct the final decision tree. The approach has advantages over the traditional top-down approach, first because only feasible classification rules are considered in the tree induction and, second, because their costs and resource use are known. In contrast, in the top-down approach, the information is not available for selecting splitting attributes. The experiment results show that the CAT algorithm significantly outperforms the top-down approach and adapts very well to available resources.Cost-sensitive learning, mining methods and algorithms, decision trees

Determining absolute orientation of a phone by imaging celestial bodies

The absolute orientation of a phone is of importance in a variety of applications, e.g., navigation, augmented reality, photography, etc. Phone sensors, e.g., gyroscope, etc. can determine relative changes in orientation, but absolute orientation is generally poorly known or unknown. Absolute orientation is not factory-set, and if it is set, requires periodic recalibration. This disclosure provides techniques to determine absolute orientation of a phone by imaging celestial bodies, e.g., sun, moon, etc. Once the absolute orientation is determined, phone sensors measure relative changes in orientation and thereby keep track of absolute orientation

geometrical vision measurement in mechanical engineering

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Development of a compact DFB laser interferometer for high-speed inline displacement measurement

A compact fiber laser interferometer, capable of precise displacement measurements, was devised using a 1550 nm DFB laser for frequency modulation up to 300 kHz. The system comprises a fiber laser, a fiber-optic interferometer, and a wavelength modulation system. The presented method offers nanometer-scale precision and incorporates a hydrogen cyanide (HCN) gas cell for monitoring the laser's central wavelength. A technique to compensate for modulation depth has been developed to maintain a consistent modulation depth over extensive measurement ranges. Preliminary trials reveal a measurement bias of less than 40 nm achieved over a 300 mm range at a speed of 100 mm/s compared to a calibrated interferometer. This approach proves beneficial for high-precision measurements for inline semiconductor manufacturing processes

Always Open, Seven-Eleven: Education Targeting Healthier Food Choices in a High Convenience Store Density Area in Taipei

To enhance children's health, the promotion of nutrition literacy in school is vital as it helps prevent the development of health conditions and diseases and maintain healthy lifestyles. Taiwan features the top highest ratio of convenience stores per population density. Convenience stores, an increasingly popular dining place, were linked to the development of eating behavior and body weight issues in children. An eight-week classroom-based nutrition intervention, employing the Traffic Light Diet as a framework, targeting children's perception of and intention to visit the convenience store was implemented. The study conducted a quasi-experimental pretest-posttest research design with a comparison group. A total of 49 students participated in the study, with 25 in the intervention and 24 in the comparison group. Data were collected by utilizing surveys, interviews, and observations. The study's findings demonstrated the positive trajectory of the impact of this intervention on increasing food-and-nutrition-related knowledge and improving healthier diet choices at convenience stores among children. One main theme was identified in coding interviews: parent involvement in meal preparation may reduce convenience store use and increase consumption of vegetables among children. Assessing the influence of parental support for healthy dietary choices, eating nutritious foods at home, and involving the family in meal preparation is an area for future research