An inspection technology of inner surface of the fine hole based on machine vision

Fine holes are an important structural component of industrial components, and their inner surface quality is closely related to their function.In order to detect the quality of the inner surface of the fine hole,a special optical measurement system was investigated in this paper. A sight pipe is employed to guide the external illumination light into the fine hole and output the relevant images simultaneously. A flexible light array is introduced to suit the narrow space, and the effective field of view is analyzed. Besides, the arc surface projection error and manufacturing assembly error of the device are analyzed, then compensated or ignored if small enough. In the test of prefabricated circular defects with the diameter {\phi}0.1mm, {\phi}0.2mm, 0.4mm distance distribution and the fissure defects with the width 0.3mm, the maximum measurement error standard deviation are all about 10{\mu}m. The minimum diameter of the measured fine hole is 4mm and the depth can reach 47mm

Internal Language Model Estimation Through Explicit Context Vector Learning for Attention-based Encoder-decoder ASR

An end-to-end (E2E) ASR model implicitly learns a prior Internal Language Model (ILM) from the training transcripts. To fuse an external LM using Bayes posterior theory, the log likelihood produced by the ILM has to be accurately estimated and subtracted. In this paper we propose two novel approaches to estimate the ILM based on Listen-Attend-Spell (LAS) framework. The first method is to replace the context vector of the LAS decoder at every time step with a vector that is learned with training transcripts. Furthermore, we propose another method that uses a lightweight feed-forward network to directly map query vector to context vector in a dynamic sense. Since the context vectors are learned by minimizing the perplexities on training transcripts, and their estimation is independent of encoder output, hence the ILMs are accurately learned for both methods. Experiments show that the ILMs achieve the lowest perplexity, indicating the efficacy of the proposed methods. In addition, they also significantly outperform the shallow fusion method, as well as two previously proposed ILM Estimation (ILME) approaches on several datasets.Comment: Proceedings of INTERSPEEC

Validating Multimedia Content Moderation Software via Semantic Fusion

The exponential growth of social media platforms, such as Facebook and TikTok, has revolutionized communication and content publication in human society. Users on these platforms can publish multimedia content that delivers information via the combination of text, audio, images, and video. Meanwhile, the multimedia content release facility has been increasingly exploited to propagate toxic content, such as hate speech, malicious advertisements, and pornography. To this end, content moderation software has been widely deployed on these platforms to detect and blocks toxic content. However, due to the complexity of content moderation models and the difficulty of understanding information across multiple modalities, existing content moderation software can fail to detect toxic content, which often leads to extremely negative impacts. We introduce Semantic Fusion, a general, effective methodology for validating multimedia content moderation software. Our key idea is to fuse two or more existing single-modal inputs (e.g., a textual sentence and an image) into a new input that combines the semantics of its ancestors in a novel manner and has toxic nature by construction. This fused input is then used for validating multimedia content moderation software. We realized Semantic Fusion as DUO, a practical content moderation software testing tool. In our evaluation, we employ DUO to test five commercial content moderation software and two state-of-the-art models against three kinds of toxic content. The results show that DUO achieves up to 100% error finding rate (EFR) when testing moderation software. In addition, we leverage the test cases generated by DUO to retrain the two models we explored, which largely improves model robustness while maintaining the accuracy on the original test set.Comment: Accepted by ISSTA 202

Superradiance-induced multistability in one-dimensional driven Rydberg lattice gases

We study steady-state phases of a one-dimensional array of Rydberg atoms coupled by a microwave (MW) field where the higher-energy Rydberg state decays to the lower-energy one via single-body and collective (superradiant) decay. Using mean-field approaches, we examine the interplay among the MW coupling, intrastate van der Waals (vdW) interaction, and single-body and collective dissipation between Rydberg states. A linear stability analysis reveals that a series of phases, including uniform, antiferromagnetic, oscillatory, and bistable and multistable phases can be obtained. Without the vdW interaction, only uniform phases are found. In the presence of the vdW interaction, multistable solutions are enhanced when increasing the strength of the superradiant decay rate. Our numerical simulations show that the bistable and multistable phases are stabilized by superradiance in a long chain. The critical point between the uniform and multistable phases and its scaling with the atom number is obtained. Through numerically solving the master equation of a finite chain, we show that the mean-field multistable phase could be characterized by expectation values of Rydberg populations and two-body correlations between Rydberg atoms in different sites

MRI signal intensity differentiation of brainstem encephalitis induced by Enterovirus 71: a classification approach for acute and convalescence stages

Additional file 3. After tick the segment region, Medflovan show the segmentation region of lesion

New Findings, Classification and Long-Term Follow-Up Study Based on MRI Characterization of Brainstem Encephalitis Induced by Enterovirus 71

Background To report the diversity of MRI features of brainstem encephalitis (BE) induced by Enterovirus 71. This is supported by implementation and testing of our new classification scheme in order to improve the diagnostic level on this specific disease. Methods Neuroimaging of 91 pediatric patients who got EV71 related BE were hospitalized between March, 2010 to October, 2012, were analyzed retrospectively. All patients underwent pre- and post-contrast MRI scan. Thereafter, 31 patients were randomly called back for follow-up MRI study during December 2013 to August 2014. The MRI signal patterns of BE primary lesion were analyzed and classified according to MR signal alteration at various disease stages. Findings in fatal and non-fatal cases were compared, and according to the MRI scan time point during the course of this disease, the patients’ conditions were classified as 1) acute stage, 2) convalescence stage, 3) post mortem stage, and 4) long term follow-up study. Results 103 patients were identified. 11 patients did not undergo MRI, as they died within 48 hours. One patient died on 14th day without MR imaging. 2 patients had postmortem MRI. Medical records and imaging were reviewed in the 91 patients, aged 4 months to 12 years, and two cadavers who have had MRI scan. At acute stage: the most frequent pattern (40 patients) was foci of prolonged T1 and T2 signal, with (15) or without (25) contrast enhancement. We observed a novel pattern in 4 patients having foci of low signal intensity on T2WI, with contrast enhancement. Another pattern in 10 patients having foci of contrast enhancement without abnormalities in T1WI or T2WI weighted images. Based on 2 cases, the entire medulla and pons had prolonged T1 and T2 signal, and 2 of our postmortem cases demonstrated the same pattern. At convalescence stage, the pattern observed in 4 patients was foci of prolonged T1 and T2 signal without contrast enhancement. Follow-up MR study of 31 cases showed normal in 26 cases, and demonstrated foci of prolonged T1 and T2 signal with hyper-intensity on FLAIR in 3 cases, or of prolonged T1 and T2 signal with hypo-intensity on FLAIR in 2 cases. Most importantly, MR findings of each case were thoroughly investigated and classified according to phases and MRI signal alteration. Conclusions This study has provided enhanced and useful information for the MRI features of BE induced by EV71, apart from common practice established by previous reports. In addition, a classification scheme that summarizes all types of features based on the MRI signal at the four different stages of the disease would be helpful to improve the diagnostic level

An optically pumped atomic clock based on a continuous slow cesium beam

Herein, we report the scheme of an optically pumped atomic clock based on a cold cesium atomic beam source. We propose the laser system and physical mechanism of this atomic clock, wherein the atomic beam travels in an upper parabolic trajectory, thereby eliminating the light shift effect. In the experiments, when the length of the free evolution region was 167 mm, the line width of the Ramsey fringe was 37 Hz. When the expected signal-to-noise ratio of the Ramsey fringe that can be achieved is 36,000, the expected short-term frequency stability is about 3.6 × 10–14/√τ, which is significantly higher than that of a conventional optically pumped cesium clock of similar volume