The purpose of the present study was to explore the usefulness of an objectively scored self-rating sentence completion test in the development of objective prognostic statements regarding marital counseling.

<p>Sensors are being used in many industrial applications for equipment health mon-itoring and anomaly detection. However, sometimes operation and maintenanceof these sensors are costly. Thus companies are interested in reducing the num-ber of required sensors as much as possible. The straightforward solution is tocheck the prediction power of sensors and eliminate those sensors with limitedprediction capabilities. However, this is not an optimal solution because if we dis-card the identified sensors. Their historical data also will not be utilized anymore.However, typically such historical data can help improve the remaining sensors’signal power, and abolishing them does not seem the right solution. Therefore, wepropose the first data-driven approach based on tensor completion for re-utilizingdata of removed sensors, in addition to remaining sensors to create virtual sensors.We applied the proposed method on vibration sensors of high-speed separators,operating with five sensors. The producer company was interested in reducing thesensors to two. But with the aid of tensor completion-based virtual sensors, weshow that we can safely keep only one sensor and use four virtual sensors thatgive almost equal detection power compared to when we keep only two physicalsensors.</p>

Increasing student on-time completion is a challenge for many higher education institutions. In the community college chosen for this study, only 5.2% of its first-time-in-college, full-time students graduated within 3 years with a 2-year degree. The purpose of this study was to explore the relationship between participation in the college's academic advising program and students' time-to-degree completion, based on the pre- and post-entry attributes outlined in Tinto's institutional departure theory. A non-experimental, correlational, quantitative research method with multiple regression analysis was applied, using a convenience sample of 190 graduating students from the institution's 2011 Integrated Postsecondary Education Data System (IPEDS) cohort. Specifically, the quantitative design employed bivariate correlation analysis to select applicable pre- and post-entry characteristics and then regression analysis to determine the degree to which academic advising predicted time-to-degree completion based on characteristics. The regression analysis indicated that the variables of first-generation, intent to transfer, use of services, club participation, and financial aid eligibility significantly impacted student time to degree completion. The data analysis also indicated that students who did not see an academic advisor graduated faster than those who did. These findings led to a white paper recommending implementation of a tiered academic advising approach, development of specific advising outcomes, and increased data collection to improve the advising structure at the institution. By working to increase the IPEDS graduation rate, the institution can provide opportunities for students to increase their employment and earnings potential, improving the overall quality of life for students, their families, and the community, thus promoting positive social change.

High attrition of nursing students in the United States may contribute to a shortage of registered nurses and inefficient use of scarce resources. The purpose of this study was to explore the relationship between nursing student grades in 3 science prerequisites and length of time to program completion on each of the study college's 4 campuses. Ausubel's theory of subsumption, wherein a learner's ability to meaningfully learn new data depends on the existing cognitive structure within which the new material is assimilated, was used as a theoretical framework. Prerequisite science course grades for 575 nursing students attending a Midwestern technical and community college with 4 campuses were obtained along with data on program completion. Grade data from 2005-2015 were analyzed using a 1-way or Welch ANOVA and Pearson product-moment correlation. Significant differences were found among campuses in both mean science grades and time to completion. Most science course grades did not demonstrate a significant correlation with time to completion. Based on these findings, it is possible that student preparation in general science courses is not equivalent among campuses and may not provide the cognitive structure necessary for meaningful learning in nursing courses. To enable faculty from both disciplines to collaboratively document, examine, and align content in science and nursing courses, a curriculum mapping project was designed. Registered nurse graduates contribute to the economic and social well-being of their communities. By providing more insight about science and nursing courses and degree completion, this study is intended to promote positive social change.

AI-supported programming has arrived, as shown by the introduction and successes of large language models for code, such as Copilot/Codex (Github/OpenAI) and AlphaCode (DeepMind). Above-average human performance on programming challenges is now possible. However, software development is much more than solving programming contests. Moving beyond code completion to AI-supported software development will require an AI system that can, among other things, understand how to avoid code smells, follow language idioms, and eventually (maybe!) propose rational software designs. In this study, we explore the current limitations of Copilot and offer a simple taxonomy for understanding the classification of AI-supported code completion tools in this space. We first perform an exploratory study on Copilot’s code suggestions for language idioms and code smells. Copilot does not follow language idioms and avoid code smells in most of our test scenarios. We then conduct additional investigation to determine the current boundaries of Copilot by introducing a taxonomy of software abstraction hierarchies where ‘basic programming functionality’ such as code compilation and syntax checking is at the least abstract level, software architecture analysis and design are at the most abstract level. We conclude by providing a discussion on challenges for future development of AI-supported code completion tools to reach the design level of abstraction in our taxonomy. / Graduate

This thesis presents a method for completing target regions ("hole filling") in RGB stereo pairs. It builds upon the state of the art for completing single images by matching to and then blending source patches drawn from the rest of the image. A method is introduced for first completing the respective disparity maps using a coupled partial differential equation based on that of Bertalmio, et al. extended to create mutual disparity consistency. Estimated disparities are then used to guide completion of the missing color image texture. An extension to the coherence-based objective function introduced by Wexler, et al. is then introduced, which not only encourages coherence of the respective images with respect to source images but also stereoscopic consistency between the two. The PatchMatch algorithm of Barnes, et al. is extended to cross-image searching and matching. This matching is capable of automatically copying from corresponding unoccluded portions of the other image without requiring an explicit preliminary warping step. Stereoscopic consistency is produced by giving preference to matches with cross-image consistency when blending source patches. Additionally, the PatchMatch algorithm is extended to draw from scaled texture in a directed fashion based on the 3D structure of the scene estimated from the stereo image pairs. Results demonstrate that this method produces better completion than either single-image completion or previous methods for stereo completion.

Code completion systems act both as a way to decrease typing and as a way to easily access documentation, both implicit and explicit. The former is typically done by completing known variable or function names, while the latter is done by providing a list of possible completions or by providing convenient views of or access to documentation. Because static type information makes these goals possible and feasible for qualifying languages, many improvements to completion systems are focused on improving the order of results or trimming less-valuable results. It follows that almost all validation techniques for this work have focused on proving how well a completion system can put a desired result at the top of the list. However, because of the lack of static type information in dynamically-typed languages, achieving the aforementioned goals is much harder, and many of the completion suggestions may even result in compile-time or runtime crashes. Unfortunately, of the work done on creating completers for these languages, little validation work has been done, making it hard to determine what improvements can be made. This thesis provides two validation techniques that provide information both on how well completion suggestions are ordered and also which completion suggestions result in errors. This information will be used to guide the development and evolution of a completion system for the Racket programming language.

<p>Three main theories have been proposed to account for the completion of occluded objects, namely local theories (e.g., Kellman & Shipley, 1991), global theories (e.g., Boselie & Leeuwenberg, 1986), and integrative models of completion (e.g., Sekuler, 1994; van Lier et al., 1994). Here, we investigated age-related changes in the completion of a complex partially occluded object using a prime-matching task. Subjects were shown a prime (global, local, occluded, or no prime) that was followed immediately by two shapes that were judged as being the same or different. In Experiment 1, we tested adults (n = 36/group) at various prime durations (150 - 700 msec) to tap into earlier and later representations of the occluded object. Although the occluded object primed both the global and local shapes at 150 and 500 msec (<em>p</em>s<0.05), only the global shapes were primed at 300 and 700 msec (<em>p</em>s<0.05). Overall, our results are most consistent with integrative models of completion. In Experiment 2, we tested 8-year-olds (n = 20) at a prime duration of 700 msec and 11-year-olds (n = 30/group) at a prime duration of 300 or 700 msec. For 11-year-olds, unlike adults, the occluded object did not significantly prime either the global or local shapes at 300 msec (<em>p</em>>0.50). For both 8- and 11-year-olds, the global, local, and occluded primes did not significantly prime either shape at 700 msec (<em>p</em>s>0.50). Based on the current testing conditions, we found that the perceptual completion process may not be adult-like even at 11 years of age.</p> / Master of Science (MSc)

This study investigated the relationship between selected adolescent characteristics and treatment completion in a large, national sample of adolescents receiving substance misuse treatment in 2011. Participants were de-identified adolescent entries between the ages of 12 and 17 in the Treatment Episode Dataset- Discharges (TEDS-D), which is a national census data system including persons discharged from public and private substance abuse treatment programs that received public funding. Chi-square tests of independence and logistic regressions were used to examine the relationships between adolescent characteristics and treatment completion. The results showed significant relationships between selected variables (sex, gender, primary substance problem, principal source of referral, frequency of use) and treatment completion, but with small to medium effect sizes. Implications, limitations and directions for future research are discussed. / School Psychology

This study investigated the influence of computer-generated reminders on the rate in which distance learners submitted assignments and completed courses. The computer-generated reminders, sent via email, served as a time management support strategy. Participants were randomly divided into two groups: control and treatment. Both groups received a list of target due dates for course assignments. The control group did not receive reminders. The treatment group received reminders when they failed to submit an assignment by a target due date. The results indicated no significant difference between the control and treatment groups in terms of assignment submission rates and course completion rates. However, results of this study did reveal that the number of assignments in a distance course influences the timeliness of assignment completion and the likelihood of course completion. / Ph. D.