Performance optimization for energy-aware adaptive checkpointing in embedded real-time systems

Using additional store-checkpoinsts (SCPs) and compare-checkpoints (CCPs), we present an adaptive checkpointing for double modular redundancy (DMR) in this paper. The proposed approach can dynamically adjust the checkpoint intervals. We also design methods to calculate the optimal numbers of checkpoints, which can minimize the average execution time of tasks. Further, the adaptive checkpointing is combined with the DVS (dynamic voltage scaling) scheme to achieve energy reduction. Simulation results show that, compared with the previous methods, the proposed approach significantly increases the likelihood of timely task completion and reduces energy consumption in the presence of faults.<br /

The Synthesis Lab: Empowering Collaborative Learning in Higher Education through Knowledge Synthesis

The ability to synthesize information has emerged as a critical skill for success across various fields. However, within the field of education, there is a lack of systematic understanding and well-defined design infrastructures that address the mechanisms and processes of knowledge synthesis in collaborative learning settings. In this poster, we introduce a design innovation - The Synthesis Lab, which aims to support students in synthesizing ideas from their online discussions in higher education classrooms. The tool offers structured work-spaces for students to decompose the synthesis process into intermediate synthesis products and features two key iterative processes of knowledge synthesis in collaborative settings: categorizing peers' ideas into conceptual building blocks and developing a synthesis of the discussions. Future implementation and evaluation of the design will make significant contributions to both research and practice

Note on a non-critical holographic model with a magnetic field

We consider a noncritical holographic model constructed from an intersecting brane configuration D4/$\bar{\rm{D4}}$-D4 with an external magnetic field. We investigate the influences of this magnetic field on strongly coupled dynamics by the gauge/gravity correspondence.Comment: 18 pages, references added and typos revise

Holographic phase transition in a non-critical holographic model

We consider a holographic model constructed from the intersecting brane configuration D4-$\bar{\rm{D4}}$/D4 in noncritical string theory. We study the chiral phase diagram of this holographic QCD-like model with a finite baryon chemical potential through the supergravity dual approximation.Comment: 14 pages, reference adde

Stability and convergence of the two parameter cubic spline collocation method for delay differential equations

AbstractIn this paper, we propose the cubic spline collocation method with two parameters for solving delay differential equations (DDEs). Some results of the local truncation error and the convergence of the spline collocation method are given. We also obtain some results of the linear stability and the nonlinear stability of the method for DDEs. In particular, we design an algorithm to obtain the ranges of the two parameters α,β which are necessary for the P-stability of the collocation method. Some illustrative examples successfully verify our theoretical results

A Note on Chiral Symmetry Breaking from Intersecting Branes

In this paper, we will consider the chiral symmetry breaking in the holographic model constructed from the intersecting brane configuration, and investigate the Nambu-Goldstone bosons associated with this symmetry breaking.Comment: 16 pp, minor changes, to appear PR

The Era of Radiogenomics in Precision Medicine: An Emerging Approach to Support Diagnosis, Treatment Decisions, and Prognostication in Oncology

With the rapid development of new technologies, including artificial intelligence and genome sequencing, radiogenomics has emerged as a state-of-the-art science in the field of individualized medicine. Radiogenomics combines a large volume of quantitative data extracted from medical images with individual genomic phenotypes and constructs a prediction model through deep learning to stratify patients, guide therapeutic strategies, and evaluate clinical outcomes. Recent studies of various types of tumors demonstrate the predictive value of radiogenomics. And some of the issues in the radiogenomic analysis and the solutions from prior works are presented. Although the workflow criteria and international agreed guidelines for statistical methods need to be confirmed, radiogenomics represents a repeatable and cost-effective approach for the detection of continuous changes and is a promising surrogate for invasive interventions. Therefore, radiogenomics could facilitate computer-aided diagnosis, treatment, and prediction of the prognosis in patients with tumors in the routine clinical setting. Here, we summarize the integrated process of radiogenomics and introduce the crucial strategies and statistical algorithms involved in current studies