Federated learning model complexity vs robustness to non-IID data and selective federated learning

Federated learning trains a global model using data distributed across local nodes, and differs from centralized machine learning by moving the computation to the data in order to address the challenges of data ownership, privacy, computational power, and data storage. Previous federated learning research has addressed the effect of non independent and identically distributed data on federated learning [6]. Meanwhile, local models may have better performance if the test set is also non-IID [7]. However, there may be insufficient data on a node to train a local model for every node; hence the purpose of federated learning. This research is the first, to our knowledge, to consider model performance on both a global test set and non-IID test set. Our experiments provide a original finding in that federated learning is only robust to non-IID data with constraints on the width and depth of a neural network. There is a tradeoff, however, between model complexity and feasibility of training the model on edge devices. Thus, we propose selective federated learning algorithm which greatly allows simpler models that fit on edge devices to be robust to highly non-IID data. For non-IID test sets, we prove that a converged federated model may converge to weights which do not provide the optimal local loss for an arbitrary chosen number of training samples on each node. Additionally, this thesis discusses the experiments that were conducted to examine the effects of model complexity, percentage of unbalanced data, and the current modes of model aggregation on model accuracy. For the experiments, we deployed federated learning library for multiple devices, Jetson Nano, Raspberry Pi, Macbook Pro, and Linux server and provide hardware benchmarks.Electrical and Computer Engineerin

Research Progress on the Effects of Different Treatments on the Microstructure and Properties of Egg Yolk and Its Components

Egg yolk is rich in nutrition and complex in structure. Its major components are egg yolk granules (EYGs) and egg yolk plasma (EYP). The physicochemical properties and microstructures of egg yolk and its components are greatly affected by different treatments during processing, and in turn affect their functional properties. Therefore, this paper reviews the effects of different treatments including salting, alkali treatment, heat treatment and enzymatic treatment on the physicochemical properties (surface hydrophobicity, oil exudation, and protein solubility) and microstructure of egg yolk as well as EYGs and EYP. In addition, this paper discusses the functional changes of egg yolk and its components after different treatments. We expect this review to provide theoretical support for future research on the physicochemical properties and microstructure of egg yolk components and on their effects on the functional properties of egg yolk components

Emotions and global warming action

Prior researches have found that emotions and subsequent behaviours are closely bonded. Following that, in the context of global warming, this study examines how approach-oriented emotions (e.g. happiness) and avoidant emotions (e.g. sadness) influence the preference of energy, choice of diet and willingness to recycle. Thus, we have two conditions (i.e. happy and sad) in the study and each condition is asked to complete a survey regarding the pro-environmental behaviors. The result reveals that happiness makes people more likely to recycle and sadness has the opposite effect. However, no results are found in the willingness to use green energy and plant-based diet. This result contributes to the previous finding and give a dimensional perspective on how to analysis the effect of emotions on global warming actions. Limitations and implication are also discussed. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”Arts, Faculty ofScience, Faculty ofPsychology, Department ofResources, Environment and Sustainability (IRES), Institute forUnreviewedUndergraduat

Composite Interpolation-Based Multiscale Fuzzy Entropy and Its Application to Fault Diagnosis of Rolling Bearing

Multiscale fuzzy entropy (MFE), as an enhanced multiscale sample entropy (MSE) method, is an effective nonlinear method for measuring the complexity of time series. In this paper, an improved MFE algorithm termed composite interpolation-based multiscale fuzzy entropy (CIMFE) is proposed by using cubic spline interpolation of the time series over different scales to overcome the drawbacks of the coarse-grained MFE process. The proposed CIMFE method is compared with MSE and MFE by analyzing simulation signals and the result indicates that CIMFE is more robust than MSE and MFE in analyzing short time series. Taking this into account, a new fault diagnosis method for rolling bearing is presented by combining CIMFE for feature extraction with Laplacian support vector machine for fault feature classification. Finally, the proposed fault diagnosis method is applied to the experiment data of rolling bearing by comparing with the MSE, MFE and other existing methods, and the recognition rate of the proposed method is 98.71%, 98.71%, 98.71%, 98.71% and 100% under different training samples (5, 10, 15, 20 and 25), which is higher than that of the existing methods

Boron/nitrogen co-doped diamond electrode for highly efficient electrochemistry detection of aniline

Aniline is a mutagenic and carcinogenic material for human health, and it is desirable to construct high-performance detecting system for the trace detection of aniline. In this work, the boron (B)/nitrogen (N)-doped diamond (BND) films prepared by chemical vapor deposition are proposed as electrochemical electrodes to detect aniline in a wide concentration scale. The BND electrodes have a high sensitivity (detect limitation of 0.29 μmol L−1) and a wide linear detection range (0.5 − 500 μmol L−1). Both the detection limitation and linear range are significantly improved with respect to that from traditional electrodes of boron-doped diamond and various carbonaceous materials, which can be attributed to the synergistic effect of increased electrochemistry reduction and density of reaction sites on the BND electrode surfaces. This work develops a kind of electrochemical electrodes of B/N-doped diamond films with high performances for quantitative detections of aniline in practical applications. Supplemental data for this article is available online at http://dx.doi.org/10.1080/26941112.2021.193917

The complete chloroplast genome sequence of Dictamnus albus L.

Dictamnus albus L. refers to a perennial herb with both ornamental and medicinal value. In the present study, we obtained the complete chloroplast genome sequence of D. albus through high-throughput sequencing. The length of the chloroplast genome was 157,139 bp, while the large single-copy and small single-copy regions were 84,478 bp and 18,587 bp, respectively. The pair of inverted repeat sequences was 27,037 bp, and the GC content was 38.5%. A total of 132 genes were annotated, including 87 protein-coding genes (PCGs), eight ribosomal RNA (rRNA) genes, and 37 transfer RNA (tRNA) genes. The chloroplast genomes of D. albus and eight species of Rutaceae were subjected to maximum-likelihood phylogenetic tree analysis. D. albus was found to be most closely related to Orixa japonica

Isotopic Disorder: The Prevailing Mechanism in Limiting the Phonon Lifetime in Hexagonal BN

The phonon linewidth of isotopically controlled hexagonal boron nitride (h-BN) single crystals has been determined by Raman scattering. The scattering by isotopic mass disorder induces a phonon broadening that is largest for boron 11 fractions around 0.65. Lowest-order perturbation theory does not suffice to explain the dependence of the isotopic broadening on isotopic composition. A multiple-scattering theory based on the coherent potential approximation provides a good quantitative account of the phonon shift and broadening with isotopic composition observed in the experiments. Isotopic-disorder scattering is shown to have a prominent role in limiting the optical-phonon lifetime in h-BN © 2020 American Physical SocietyThis work has been supported by the Spanish MINECO/FEDER under Contract No. MAT2015-71035-R. Support for the h-BN crystal growth from the Materials Engineering and Processing programof the National Science Foundation, Grant No. CMMI 1538127, is greatly appreciated.Peer reviewe