Crises trigger both learning and unlearning at intra-organizational inter-organizational levels. This article stresses the need to facilitate for effective crisis management shows how we could use mindfulness practice enhance transformative in a crisis. study proposes conceptualization of mindful with different mechanisms foster three stages (pre-crisis, during-crisis, post-crisis). These inclu...

Personalized Internet of Things (IoT) services prediction based on Quality-of-Service (QoS) is an indispensable technique for selecting appropriate each user. However, existing collaborative models do not take into account the user’s authority to manage their own generated data. From standpoint users, expectation eliminate impact sensitive data greatest extent possible. Meanwhile, IoT service p...

Indigenous trans-systemic approach is a lifelong unlearning and relearning process, with no endpoint. peoples have long called for decolonizing minds so as to support self-determination, challenge colonial practices, value cultural identity pride in being peoples. also political standpoint toward valuing revitalizing knowledge methodologies while weeding out colonizer biases or assumptions that...

Nourished by my research's theoretical and ethnographic resources, this article explores the act of drawing its potential. I introduce a concept gaze that call “the gradual gaze.” suggest drawing, which can transform into gaze, is creative heuristic way attentive thinking process involving both unlearning learning. The mimetic quality strengthens fieldworker’s eye entails search for connectedne...

As one of the STEM disciplines with lowest percentages minoritized students and professionals, faculty administrators in geosciences have an opportunity to address racism within context their classrooms campuses. In response, a group community college geoscience from disparate institutions across U.S. came together participate Unlearning Racism Geoscience (URGE) program. This chapter describes ...

Real-world online learning applications often face data coming from changing target functions or distributions. Such changes, called the concept drift, degrade the performance of traditional online learning algorithms. Thus, many existing works focus on detecting concept drift based on statistical evidence. Other works use sliding window or similar mechanisms to select the data that closely ref...