朱舜水の「拜官不就」と「明徴君」の称号

世界の中の日本研究 : 批判的提言を求めて, 国際日本文化研究センター, 2018年5月19日-21

Distributed Adaptive Gradient Algorithm with Gradient Tracking for Stochastic Non-Convex Optimization

This paper considers a distributed stochastic non-convex optimization problem, where the nodes in a network cooperatively minimize a sum of $L$-smooth local cost functions with sparse gradients. By adaptively adjusting the stepsizes according to the historical (possibly sparse) gradients, a distributed adaptive gradient algorithm is proposed, in which a gradient tracking estimator is used to handle the heterogeneity between different local cost functions. We establish an upper bound on the optimality gap, which indicates that our proposed algorithm can reach a first-order stationary solution dependent on the upper bound on the variance of the stochastic gradients. Finally, numerical examples are presented to illustrate the effectiveness of the algorithm.Comment: 14 pages, 8 figure

Public Restroom Access and Mental Health Among Gender-Minoritized Individuals in China

open access articleThis cross-sectional study assesses the adequacy of gender-neutral public restrooms and examines the association of public restroom–related stress with mental health among gender-diverse individuals in China

Analysis of the correlation between cervical HPV infection, cervical lesions and vaginal microecology

BackgroundVaginal microbiota is involved in human papillomavirus (HPV) infection and cervical cancer (CC) progression, and the specific changes in vaginal microbial composition during this process remains uncertain.ObjectiveThis study aimed to observe the changes in the specific composition of vaginal microorganisms in different cervical lesions and identify biomarkers at different stages of lesions.MethodsIn this study we used the illumina high-throughput gene sequencing technology to determine the V4 region of 16SrRNA and observed the vaginal microbial composition in different cervical lesions.ResultsThe vaginal microbiota of patients with high-risk HPV infection and cervical lesions is significantly different from that of the normal population, but there is no significant difference in the richness of vaginal microbes. The diversity of vaginal species in CC patients is higher than that in high-risk HPV infection or CIN patients. The main manifestation is an increase in the diversity of vaginal microbes, a decrease in the relative abundance of cyanobacteria and Lactobacillus, and an increase in the relative abundance of dialister, peptonephila and other miscellaneous bacteria. There are characteristic vaginal biomarker in normal women, high risk HPV patients and CC patients. In detail, the biomarker in the normal group was varibaculum, the biomarker in the high-risk HPV group was saccharopolyspora, the biomarker of the CC group was the Proteobacteria, Corynebacterium, Coprococcus, Peptococcus and Ruminococcus.ConclusionsThe study indicated that the compositions of vaginal microbes in different cervical lesions is different. The vaginal microbial composition has a certain diagnostic effect on healthy women, patients with high-risk HPV infection and cervical lesions. These microbes may serve as potential biomarkers for CC. It also provided an effective way for the treatment of HPV infections and cervical lesions

Event-Based Dissipative Control of Interval Type-2 Fuzzy Markov Jump Systems under Sensor Saturation and Actuator Nonlinearity

This paper proposes a new design of an event-based dissipative asynchronous controller for the interval type2 (IT2) fuzzy Markov jump systems (MJSs) subject to sensor saturation and actuator nonlinearity. By resorting to a generalized performance index, the &lt;formula&gt;&lt;tex&gt;$H_{\infty}$&lt;/tex&gt;&lt;/formula&gt;, passive, and dissipative fuzzy control problems are solved in a unified framework. The event-based scheme is developed for the IT2 fuzzy MJSs subject to sensor saturation and actuator nonlinearity, and the energy consumption of communication can be reduced. Moreover, the system and controller modes are asynchronous, and a hidden Markov model (HMM) is employed to observe the modes of the original system. The Membership-Function-Dependent (MFD) approach is applied to analyze the stability of the closed-loop system. Finally, two examples are given to demonstrate the effectiveness of the proposed algorithms.</p

Research and Application of Image Enhancement and Correction Algorithm of Handwritten Steel Plate Numbering Based on Machine Vision

Correct identification and inspection of steel plate numbers are major conditions for achieving automated production in production lines. In recent years, many production lines have been equipped with inkjet printers at the material preparation positions for automatically marking material numbers. Spray-printed handwriting is clear and heat-resistant, and the use of steel plate number recognition equipment can achieve a recognition rate of nearly 100% without application. However, due to equipment failures or limited funding and space, installing printing equipment and relying only on manual handwriting to mark numbers on the surfaces of steel plates are sometimes impossible. Compared with spray-printed numbers, handwritten numbers involve complex features, such as arbitrary writing, continuous strokes, and distorted handwriting, which limit the accuracy of the recognition system. Due to poor recognition performance, relying on manual visual inspection to assist in recognition is often necessary, which affects the implementation of material-tracking automation. To improve the recognition of handwritten steel plate numbers, this study introduces improvements to the traditional machine learning Optical Character Recognition (OCR) text-region detection algorithm. An algorithm for image enhancement and distortion correction is also proposed based on the characteristics of handwritten steel plate numbers. These algorithms are designed to improve the image quality and shapes of handwritten steel plate numbers, thereby increasing recognition accuracy. Overall, the study aims to improve the recognition of handwritten steel plate numbers to solve the difficulties associated with automated production. Through image enhancement and correction, the recognition system can process handwritten steel plate numbers more effectively, further promoting the automated implementation of material tracking