The random-like filling strategy pursuing high compression for scan test introduces large test power. To pursue high compression in conjunction with reducing test power for multiple scan chain designs is even harder and very few works were dedicated to solve this problem. This paper proposes and demonstrates a Multilayer Data Copy (MDC) scheme for test compression as well as test power reduction for multiple scan designs. The scheme utilizes a buffer, which supports fast load using previous loaded data, to achieve test data compression and test power reduction at the same time. The scheme can be applied ATPG-independently or to be incorporated in an ATPG to generate highly compressible and power efficient test sets. Experiment results on benchmarks show that test sets generated by the scheme had large compression and power saving with little area design overhead.

Objective Huddles are short, regular debriefings that are designed to provide frontline staff and bedside caregivers environments to share problems and identify solutions. Daily huddle implementation could improve medical safety work, problem identification and improvement, situation awareness and teamwork enhancement, the collaboration and communication between professionals and departments, and patient safety. This study aimed evaluated the effectiveness of a hospital-based huddle at a general medical ward in Taiwan. Methods A Continuous Integration team was conducted by combining multidisciplinary frontline staff to huddle at a 74-bed general medical ward. Team Huddles started twice a week. A physical huddle run board was created, which contained four parts, including idea submitted, idea approved, working on an idea and standardizing. Problems were submitted to the board to be identified, and the solutions were evaluated through huddle discussion. We divided the problems into two groups: quick hits (resolved within 24–48hrs) and complex issues (resolved >48hrs). An anonymous questionnaire was designed to evaluate the huddle response. Results A total of 44 huddles occurred from September 9th, 2020, to September 30th, 2021, and 81 issues were identified and resolved. The majority issues were policy documentation (n=23; 28.4%). Sixty-seven (82.7%) issues were defined as quick hits, and the other fourteen (17.3%) issues were complex. The mean hours to the resolution of quick hits was 5.17 hours, median 3.5 hours, and range from 0.01–15.4 hours. The mean days to resolve completion issues were 19.73 days, median 7.5 days, and range 3.57–26.14 days. An overwhelming 92.9% of staff responded that huddles help to expedite the process to reach treatment goals, reduce clinical mistakes, near misses, reduce patient incidences, and help teamwork enhancement, with rating of 4.52 (on a 5-point Likert scale). Conclusion Implementing of multidisciplinary team huddle improved the accountability of issue identification, problem-solving and teamwork enhancement.

Scan test for SoC has now suffered large data volume and test application time. In this paper, we propose and demonstrate an Adaptive Encoding scheme to reduce the test volume and test time for SoC scan test. The scheme, instead of handling test data themselves, encodes them in "packets" according to difference bits of two consecutive test patterns. A decoder machine is designed to decode the compressed data and a repeat filling mechanism from the ATE is adopted to eliminate the synchronization problem. It supports variable block size and is flexible in encoding multi-core test patterns; therefore, the proposed method is effective in SoC scan test. Experimental results show that on average the scheme achieves 73% reduction in test data and more than 16 times of speedup in test application time.

The paper programs motion paths using laser detection system for the mobile robot. The laser detection system contains a laser range finder and a laser positioning system. The mobile robot is constructed using aluminum frame, and has the shape of cylinder and its diameter, height and weight is 40 cm, 80cm and 40kg respectively. In the driver system and avoidance obstacle driver system, we use NI motion control card and MAXON drivers to control two DC servomotors, and detect obstacle using a laser range finder and sixteen reflective IR sensors. The mobile robot locates the position of the detected obstacles using a laser positioning system. The mobile robot can program the motion path using A* searching algorithm and avoids the detected obstacles to follow the programmed trajectory. We develop the user interface to display the positions of the detected obstacles. Finally, we implement the experimental results using the proposed method. The mobile robot moves to the target position from the start position autonomously. The mobile robot detects environment status using the laser detection system and avoids the detected obstacles to finish the assigned tasks.

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