Power-Aware Real-Time Scheduling: Models, Open Problems, and Practical Considerations

Power-related issues have received considerable research attention from the real-time community in the past decade. In our talk, we introduce a recent model and set of assumptions made in the recent real-time literature on energy and thermal issues; suggest two high-level open problems for power-aware real-time scheduling: {em peak-temperature minimization} and {em energy-minimization with temperature as a constraint}; and discuss practical considerations that should be considered in proposed solutions

Dark Nights and Nonlinear Paths in Western Abrahamic Contemplative Traditions

Recent research has documented meditation-related experiences in contemporary Buddhist traditions and the appraisal processes involved with either normalizing or pathologizing such experiences. These studies have complicated the frameworks that even clinicians and psychologists use to make such differential diagnoses but to date there has been almost no comparable work examining how such appraisal processes are navigated in other religious and spiritual communities. This thesis makes a contribution in this area by investigating some of the textual sources and themes that contemporary teachers and students in Western Abrahamic contemplative traditions draw upon to interpret distressing and challenging meditation-related experiences. When appraising difficult experiences as ‘part of the path’ in contemporary Christian traditions, teachers and practitioners invoked both Teresa of Avila and John of the Cross, particularly the latter’s discussion of the “dark nights,” and the contemplative path structure utilized by both of purgation-illumination-union. Purgation or purification was often translated into a psychological key and Thomas Keating’s conception of “divine therapy” and “the unloading of the unconscious” in the Centering prayer tradition was found to be influential in this formulation. In Western Sufi traditions, challenging or distressing experiences were understood as normative in relation to Classical Sufi psychological literature describing different states (hal) and stations (maqamat) of the Sufi path (tariqa), particularly those related to a process of purification or “polishing the mirror of the heart.” Other key ideas referenced in normalizing interpretations were the valley of bewilderment (hayrat) in Farid ad-Din Attar’s The Conference of the Birds, descriptions of painful experiences in the poetry of Jallal al-din Rumi, and the dual concept of annihilation (fana) and subsistence (baqa) that is ubiquitous in classical Sufi literature. Jewish teachers and practitioners referenced a constellation of several key texts, figures, and ideas in appraising challenging experiences as ‘part of the path’ as well: mystical interpretations of the Song of Songs, “descent for the sake of ascent” (yeridah tzorech aliyah) and purification, the doctrine of “expanded and constricted consciousness” (mochin d’gadlut, mochin d’katnut), the Hasidic practice and doctrine of elevating sparks and “foreign thoughts” (machshavot zerot), and finally, liminality and “the breaking of the vessels” (shevirat ha-keilim). In introducing the conception of ‘non-linear paths’ to describe these trajectories of contemplative practice invoked by contemporary teachers and practitioners, this thesis seeks to highlight the ways in which certain negatively valenced meditation- related experiences are normalized even as individual variability and unpredictability has been acknowledged for centuries in these traditions

ARTIFICIAL SENSOR FOR ELECTRIC POWER SYSTEM USING MACHINE LEARNING

The demand for sustainable, reliable, and efficient electric power systems continues to increase as new methods of power generation are introduced and power systems expand to meet consumer needs. Reliable sensor and data collection is critical to accurately monitor and assess the state of an electric power system. The purpose of this study is to develop a method for predicting missing or erroneous data entries for a Phasor Measurement Unit (PMU) in the event of a malfunctioning sensor or dropped communication packet, even during unexpected periods of abnormal oscillations. To do this, we propose using machine learning to build a neural network to accurately and efficiently predict missing or erroneous observations from real world PMU data. The trained neural network is capable of predicting missing PMU data entries for six different abnormal oscillation events, with less than 5% error. Power system observers can utilize this method to maintain an accurate system state estimation, even while undergoing sensor malfunctions or dropping communication packets.Distribution Statement A. Approved for public release: Distribution is unlimited.Captain, United States Arm

NPM-BUNDLE: Non-Preemptive Multitask Scheduling for Jobs with BUNDLE-Based Thread-Level Scheduling (Artifact)

The BUNDLE and BUNDLEP scheduling algorithms are cache-cognizant thread-level scheduling algorithms and associated worst case execution time and cache overhead (WCETO) techniques for hard real-time multi-threaded tasks. The BUNDLE-based approaches utilize the inter-thread cache benefit to reduce WCETO values for jobs. Currently, the BUNDLE-based approaches are limited to scheduling a single task. This work aims to expand the applicability of BUNDLE-based scheduling to multiple task multi-threaded task sets. BUNDLE-based scheduling leverages knowledge of potential cache conflicts to selectively preempt one thread in favor of another from the same job. This thread-level preemption is a requirement for the run-time behavior and WCETO calculation to receive the benefit of BUNDLE-based approaches. This work proposes scheduling BUNDLE-based jobs non-preemptively according to the earliest deadline first (EDF) policy. Jobs are forbidden from preempting one another, while threads within a job are allowed to preempt other threads. An accompanying schedulability test is provided, named Threads Per Job (TPJ). TPJ is a novel schedulability test, input is a task set specification which may be transformed (under certain restrictions); dividing threads among tasks in an effort to find a feasible task set. Enhanced by the flexibility to transform task sets and taking advantage of the inter-thread cache benefit, the evaluation shows TPJ scheduling task sets fully preemptive EDF cannot

Measuring Length of Electron Bunches with Optics in LCLS-II

Since the launch of the LINAC Coherent Light Source (LCLS) in 2009, there have been over 1,000 publications enabling pioneering research across multiple fields. Advances include: harnessing the sun’s light, revealing life’s secrets and aiding drug development, developing future electronics, designing new materials and exploring fusion, customizing chemical reactions, and many more. These discoveries gathered worldwide attention, and now work has begun on a new revolutionary tool, LCLS-II. The LCLS-II will pulse at a million times a second, compared to the 120 pulses from the LCLS. Within the LCLS-II, there are two chicanes, serpentine curves. As the electron beam passes through each bend, radiation is fragmented off. After each chicane, the radiation is reflected up to a box where pyro-detectors are set up to receive diagnostic information to accurately maintain the electron beams

NPM-BUNDLE: Non-Preemptive Multitask Scheduling for Jobs with BUNDLE-Based Thread-Level Scheduling

The BUNDLE and BUNDLEP scheduling algorithms are cache-cognizant thread-level scheduling algorithms and associated worst case execution time and cache overhead (WCETO) techniques for hard real-time multi-threaded tasks. The BUNDLE-based approaches utilize the inter-thread cache benefit to reduce WCETO values for jobs. Currently, the BUNDLE-based approaches are limited to scheduling a single task. This work aims to expand the applicability of BUNDLE-based scheduling to multiple task multi-threaded task sets. BUNDLE-based scheduling leverages knowledge of potential cache conflicts to selectively preempt one thread in favor of another from the same job. This thread-level preemption is a requirement for the run-time behavior and WCETO calculation to receive the benefit of BUNDLE-based approaches. This work proposes scheduling BUNDLE-based jobs non-preemptively according to the earliest deadline first (EDF) policy. Jobs are forbidden from preempting one another, while threads within a job are allowed to preempt other threads. An accompanying schedulability test is provided, named Threads Per Job (TPJ). TPJ is a novel schedulability test, input is a task set specification which may be transformed (under certain restrictions); dividing threads among tasks in an effort to find a feasible task set. Enhanced by the flexibility to transform task sets and taking advantage of the inter-thread cache benefit, the evaluation shows TPJ scheduling task sets fully preemptive EDF cannot

Expert and Lay Mental Models of Ecosystems: Inferences for Risk Communication

The authors evaluate a mental modeling approach to studying differences between lay and expert comprehension of ecosystems