Response Time Bounds for DAG Tasks with Arbitrary Intra-Task Priority Assignment

Most parallel real-time applications can be modeled as directed acyclic graph (DAG) tasks. Intra-task priority assignment can reduce the nondeterminism of runtime behavior of DAG tasks, possibly resulting in a smaller worst-case response time. However, intra-task priority assignment incurs dependencies between different parts of the graph, making it a challenging problem to compute the response time bound. Existing work on intra-task task priority assignment for DAG tasks is subject to the constraint that priority assignment must comply with the topological order of the graph, so that the response time bound can be computed in polynomial time. In this paper, we relax this constraint and propose a new method to compute response time bound of DAG tasks with arbitrary priority assignment. With the benefit of our new method, we present a simple but effective priority assignment policy, leading to smaller response time bounds. Comprehensive evaluation with both single-DAG systems and multi-DAG systems demonstrates that our method outperforms the state-of-the-art method with a considerable margin

Cyclotron Dynamics of a Kondo Singlet in a Spin-Orbit-Coupled Alkaline-Earth Atomic Gas

We propose a scheme to investigate the interplay between Kondo-exchange interaction and quantum spin Hall effect with ultracold fermionic alkaline-earth atoms trapped in two-dimensional optical lattices using ultracold collision and laser-assisted tunneling. In the strong Kondo-coupling regime, though the loop trajectory of the mobile atom disappears, collective dynamics of an atom pair in two clock states can exhibit an unexpected spin-dependent cyclotron orbit in a plaquette, realizing the quantum spin Hall effect of the Kondo singlet. We demonstrate that the collective cyclotron dynamics of the spin-zero Kondo singlet is governed by an effective Harper-Hofstadter model in addition to second-order diagonal tunneling

Multi-Path Bound for DAG Tasks

This paper studies the response time bound of a DAG (directed acyclic graph) task. Recently, the idea of using multiple paths to bound the response time of a DAG task, instead of using a single longest path in previous results, was proposed and leads to the so-called multi-path bound. Multi-path bounds can greatly reduce the response time bound and significantly improve the schedulability of DAG tasks. This paper derives a new multi-path bound and proposes an optimal algorithm to compute this bound. We further present a systematic analysis on the dominance and the sustainability of three existing multi-path bounds and the proposed multi-path bound. Our bound theoretically dominates and empirically outperforms all existing multi-path bounds. What's more, the proposed bound is the only multi-path bound that is proved to be self-sustainable

Influence of green technology, tourism, and inclusive financial development on ecological sustainability: exploring the path toward green revolution

This study demonstrates the linkages between green technological innovations, sustainable tourism, financial development, economic growth, and ecological sustainability using China’s regional data from 2000 to 2019. The study applies the novel estimation technique, Quantile Autoregressive Distributive Lag (QARDL) approach to examine long-run and short-run relationships between the stated variables. The initial findings confirm non-linearity in the data verified through J-B test statistics. It approves the implication of QARDL estimation for exploring ecological sustainability trends over the study period. The study outcomes confirm that tourism and green technology innovation assists in reducing ecological footprints in China in the long run. Moreover, financial development and economic growth reflect a direct role towards more ecological footprints; therefore, the sustainability dimension has been missing both in financial development and growth. Furthermore, the results in the short run cover the same phenomenon and confirm that ecological innovations and tourism would help in sustaining the natural environment. The study outcomes demonstrate that government officials in China should specifically implement long-term policies to support the natural environment from adverse shocks of more financial development and economic growth

Nutrition Mission--A Multimedia Educational Tool for Youth Grades 4 - 6

Nutrition Mission is a multimedia educational CD-ROM with an accompanying Web site designed to teach 4th - 6th grade students about making healthy food and activity choices. The CD-ROM incorporates a rich learning environment using graphics, audio, video, and interactive animations to excite students and make learning about nutrition fun. The CD includes lessons about the food guide pyramid, food labels, nutrient density, fast foods, snacking, physical activity, and food science experiments. Preliminary data indicates that the majority of youth acquire knowledge and skills related to foods, nutrition, and physical activity

Physical layer security enhancement in multi-user multi-full-duplex-relay networks

We propose a novel joint user and full-duplex (FD) relay selection (JUFDRS) scheme to enhance physical layer security in a multi-user multi-relay network. In this scheme, the user and the FD decode-and-forward relay are selected such that the capacity of the end-to-end channel (i.e., the user-relaydestination channel) is maximized to ensure the highest quality of cooperative transmission. In order to fully examine the benefits of the JUFDRS scheme, we derive a new closed-form expression for the secrecy outage probability. We show that the JUFDRS scheme significantly outperforms the joint user and half-duplex relay selection (JUHDRS) scheme when the self-interference at the FD relay can be reasonably suppressed. This result indicates that adopting the FD technique at relays can effectively enhance the physical layer secrecy performance in the multi-user multirelay network.ARC Discovery Projects Grant DP150103905

Particle Swarm Algorithm to Optimize LSTM Short-Term Load Forecasting

Accurate load forecasting is of great significance for national and grid planning and management. In order to improve the accuracy of short-term load forecasting, an LSTM prediction model based on particle swarm optimization (PSO)algorithm is proposed. LSTM has the characteristics of avoiding gradient disappearance and gradient explosion, but there is a problem that parameters are difficult to select. Therefore, particle swarm optimization algorithm is used to help it select parameters. The experimental results show that the optimized LSTM has higher prediction accuracy