134 research outputs found
Improving SAASI’s Knowledge Management Practices
Binghamton University’s Student Affairs Assessment and Strategic Initiatives (SAASI) is facing a variety of problems related to knowledge management (KM). Regarding explicit knowledge, SAASI has no universal format for documenting the analysis process and professional staff and student workers have different skill sets. Meanwhile it receives documents from other departments within Student Affairs Division and those data require a significant amount of time for SAASI to spend on reformatting to make it useable. Regarding tacit knowledge, since many of the student positions are on year appointments, there is a great deal of turnover in the department. The turnover influences the continuity of ongoing projects and transition of knowledge
Incorporating Complexity Theory in Collaborative Educational Programs
The field of education has witnessed an increasing trend of inter-organizational and inter-departmental collaborations and forming of networks. Collaborative educational programs have been implemented in a variety of ways. This paper proposes to understand and study collaborative educational programs through the lens of complexity theory and to utilize nonlinear research methods. This paper also proposes to connect the dots in the literature among complexity theory, collaborative educational programs, program evaluation, and alternative nonlinear research methods
Professionalisierung der Berufsschullehrer in China durch Dualisierung
Im Bereich der Bildung rückte ab den 1990er Jahren in China die Diskussion um die Professionalisierung der Berufschullehrer in den Vordergrund. Ein wichtiges Thema der Diskussionen um die Professionalisierung der Berufsschullehrer in China ist der „Dual-Lehrer“. Diese Dissertation knüpft an diese Professionalisierungsdebatte an und befasst sich insbesondere mit der Professionalisierung der „Dual-Lehrer“. Auf der Grundlage von wichtigen Theorien der Professionalisierung der Lehrkräfte, insbesondere im deutschsprachigen Raum, wurde eine ganzheitliche Reflexion der Professionalisierung der Berufsschullehrer Chinas durchgeführt.
Basierend auf die Inspirationen der Professionstheorien wurde zunächst durch die Auswertung der offiziellen Statistiken der aktuelle Stand der Berufsschullehrkräfte vorgestellt. Anschließend wurden durch die Analyse wissenschaftlicher Dokumente der Bedeutungsinhalt des Begriffs der „Dual-Lehrer“ sowie dessen Entwicklungsprozess dargestellt. Weiterhin wurde die Provinz Guangxi als Untersuchungsort ausgewählt und dort empirische Untersuchungen (Interview und Befragung) von „Dual-Lehrern“ und Verwaltern in Berufsschulen durchgeführt. Die Analyse der empirischen Untersuchungen zeigt auf, dass momentan vor allem das Ausbildungssystem sowie das Managementsystem die größten Schwachstellen für den Ausbau der „Dual-Lehrkräfte“ darstellen.
Auf den Ergebnissen der eigenen empirischen Untersuchungen und des Dokuments „Erlass der Berufsstandards der Berufsschullehrer (Probeversion)“ (Erziehungsministerium, 20. September 2013) stützend wird vorgeschlagen, zusätzlich „Berufsstandards der Berufsschullehrer der verschiedenen Unterrichtsfächer“ sowie „Ausbildungsstandards der Berufsschullehrer der verschiedenen Unterrichtsfächer“ zu entwickeln und entsprechende Ausbildungsmodelle für Lehramtsstudenten mit unterschiedlichen Berufserfahrungen und Bildungsabschlüssen zu entwickeln, um qualifizierte „Dual-Lehrer“ auszubilden.
Hinsichtlich des Managementsystems sollten die bestehenden Systeme wie Arbeitsplätzeplanungssystem, Qualifikationssystem, Titelsystem sowie das Fort- und Weiterbildungssystem optimiert, und auf diesen basierend zusätzlich ein Motivationssystem und ein Ausstiegssystem erstellt werden. Mithilfe dieser Teilsysteme werden drei miteinander verknüpfte Systeme konzipiert, das Zugangssystem, das Entwicklungssystem sowie das Ausstiegssystem. Damit wird ein zusammenhängendes Managementsystem aufgebaut, welches die nachhaltige Entwicklung der „Dual-Lehrkräfte“ vorantreibt
SRoUDA: Meta Self-training for Robust Unsupervised Domain Adaptation
As acquiring manual labels on data could be costly, unsupervised domain
adaptation (UDA), which transfers knowledge learned from a rich-label dataset
to the unlabeled target dataset, is gaining increasing popularity. While
extensive studies have been devoted to improving the model accuracy on target
domain, an important issue of model robustness is neglected. To make things
worse, conventional adversarial training (AT) methods for improving model
robustness are inapplicable under UDA scenario since they train models on
adversarial examples that are generated by supervised loss function. In this
paper, we present a new meta self-training pipeline, named SRoUDA, for
improving adversarial robustness of UDA models. Based on self-training
paradigm, SRoUDA starts with pre-training a source model by applying UDA
baseline on source labeled data and taraget unlabeled data with a developed
random masked augmentation (RMA), and then alternates between adversarial
target model training on pseudo-labeled target data and finetuning source model
by a meta step. While self-training allows the direct incorporation of AT in
UDA, the meta step in SRoUDA further helps in mitigating error propagation from
noisy pseudo labels. Extensive experiments on various benchmark datasets
demonstrate the state-of-the-art performance of SRoUDA where it achieves
significant model robustness improvement without harming clean accuracy. Code
is available at https://github.com/Vision.Comment: This paper has been accepted for presentation at the AAAI202
SoK: Fully Homomorphic Encryption Accelerators
Fully Homomorphic Encryption~(FHE) is a key technology enabling
privacy-preserving computing. However, the fundamental challenge of FHE is its
inefficiency, due primarily to the underlying polynomial computations with high
computation complexity and extremely time-consuming ciphertext maintenance
operations. To tackle this challenge, various FHE accelerators have recently
been proposed by both research and industrial communities. This paper takes the
first initiative to conduct a systematic study on the 14 FHE accelerators --
cuHE/cuFHE, nuFHE, HEAT, HEAX, HEXL, HEXL-FPGA, 100, F1, CraterLake,
BTS, ARK, Poseidon, FAB and TensorFHE. We first make our observations on the
evolution trajectory of these existing FHE accelerators to establish a
qualitative connection between them. Then, we perform testbed evaluations of
representative open-source FHE accelerators to provide a quantitative
comparison on them. Finally, with the insights learned from both qualitative
and quantitative studies, we discuss potential directions to inform the future
design and implementation for FHE accelerators
Formalization of Robot Collision Detection Method based on Conformal Geometric Algebra
Cooperative robots can significantly assist people in their productive
activities, improving the quality of their works. Collision detection is vital
to ensure the safe and stable operation of cooperative robots in productive
activities. As an advanced geometric language, conformal geometric algebra can
simplify the construction of the robot collision model and the calculation of
collision distance. Compared with the formal method based on conformal
geometric algebra, the traditional method may have some defects which are
difficult to find in the modelling and calculation. We use the formal method
based on conformal geometric algebra to study the collision detection problem
of cooperative robots. This paper builds formal models of geometric primitives
and the robot body based on the conformal geometric algebra library in HOL
Light. We analyse the shortest distance between geometric primitives and prove
their collision determination conditions. Based on the above contents, we
construct a formal verification framework for the robot collision detection
method. By the end of this paper, we apply the proposed framework to collision
detection between two single-arm industrial cooperative robots. The flexibility
and reliability of the proposed framework are verified by constructing a
general collision model and a special collision model for two single-arm
industrial cooperative robots
Study of Highly Pixelated CdZnTe Detector for PET Applications
AbstractWe are investigating the feasibility of a high-resolution PET insert device based on a Cadmium Zinc Telluride (CdZnTe) detector with 350μm anode pixel pitch to be integrated into a conventional animal PET scanner to improve its image resolution to sub-500 micrometer range. In this work, we have used a simplified version of the future 2048-pixel CdZnTe planar detector with 250μm anode pixel size and 100μm gap. This simplified 9 anode pixel structure makes it possible to conduct experiments without a complete ASIC readout system (with 2048 channels) that is still under development. We characterized this CdZnTe detector by investigating it charge sharing, spatial resolution, and energy resolution. We imaged a Na-22 point source using the coincidence events between this 350μm pixelated CdZnTe detector and a lutetium oxyorthosilicate (LSO) based Siemens Inveon PET detector. The reconstructed PET image shows a resolution of 590μm full width at half maximum (FWHM) by using single-pixel events. When we included double-pixel charge sharing events in the image reconstruction, the image resolution was degraded to 655μm, but the sensitivity of the coincidence system increased 2.5 to 3 times
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