Review on Machine Learning-based Defect Detection of Shield Tunnel Lining

At present, machine learning methods are widely used in various industries for their high adaptability, optimization function, and self-learning reserve function. Besides, the world-famous cities have almost built and formed subway networks that promote economic development. This paper presents the art states of Defect detection of Shield Tunnel lining based on Machine learning (DSTM). In addition, the processing method of image data from the shield tunnel is being explored to adapt to its complex environment. Comparison and analysis are used to show the performance of the algorithms in terms of the effects of data set establishment, algorithm selection, and detection devices. Based on the analysis results, Convolutional Neural Network methods show high recognition accuracy and better adaptability to the complexity of the environment in the shield tunnel compared to traditional machine learning methods. The Support Vector Machine algorithms show high recognition performance only for small data sets. To improve detection models and increase detection accuracy, measures such as optimizing features, fusing algorithms, creating a high-quality data set, increasing the sample size, and using devices with high detection accuracy can be recommended. Finally, we analyze the challenges in the field of coupling DSTM, meanwhile, the possible development direction of DSTM is prospected

Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models

AI Safety is a major concern in many deep learning applications such as autonomous driving. Given a trained deep learning model, an important natural problem is how to reliably verify the model's prediction. In this paper, we propose a novel framework -- deep verifier networks (DVN) to verify the inputs and outputs of deep discriminative models with deep generative models. Our proposed model is based on conditional variational auto-encoders with disentanglement constraints. We give both intuitive and theoretical justifications of the model. Our verifier network is trained independently with the prediction model, which eliminates the need of retraining the verifier network for a new model. We test the verifier network on out-of-distribution detection and adversarial example detection problems, as well as anomaly detection problems in structured prediction tasks such as image caption generation. We achieve state-of-the-art results in all of these problems.Comment: Accepted to AAAI 202

Permutation-invariant Feature Restructuring for Correlation-aware Image Set-based Recognition

We consider the problem of comparing the similarity of image sets with variable-quantity, quality and un-ordered heterogeneous images. We use feature restructuring to exploit the correlations of both inner$\&$inter-set images. Specifically, the residual self-attention can effectively restructure the features using the other features within a set to emphasize the discriminative images and eliminate the redundancy. Then, a sparse/collaborative learning-based dependency-guided representation scheme reconstructs the probe features conditional to the gallery features in order to adaptively align the two sets. This enables our framework to be compatible with both verification and open-set identification. We show that the parametric self-attention network and non-parametric dictionary learning can be trained end-to-end by a unified alternative optimization scheme, and that the full framework is permutation-invariant. In the numerical experiments we conducted, our method achieves top performance on competitive image set/video-based face recognition and person re-identification benchmarks.Comment: Accepted to ICCV 201

5IDER: Unified Query Rewriting for Steering, Intent Carryover, Disfluencies, Entity Carryover and Repair

Providing voice assistants the ability to navigate multi-turn conversations is a challenging problem. Handling multi-turn interactions requires the system to understand various conversational use-cases, such as steering, intent carryover, disfluencies, entity carryover, and repair. The complexity of this problem is compounded by the fact that these use-cases mix with each other, often appearing simultaneously in natural language. This work proposes a non-autoregressive query rewriting architecture that can handle not only the five aforementioned tasks, but also complex compositions of these use-cases. We show that our proposed model has competitive single task performance compared to the baseline approach, and even outperforms a fine-tuned T5 model in use-case compositions, despite being 15 times smaller in parameters and 25 times faster in latency.Comment: Interspeech 202

A three-dimensional macroscopic fundamental diagram for mixed bi-modal urban networks

Recent research has studied the existence and the properties of a macroscopic fundamental diagram (MFD) for large urban networks. The MFD should not be universally expected as high scatter or hysteresis might appear for some type of networks, like heterogeneous networks or freeways. In this paper, we investigate if aggregated relationships can describe the performance of urban bi-modal networks with buses and cars sharing the same road infrastructure and identify how this performance is influenced by the interactions between modes and the effect of bus stops. Based on simulation data, we develop a three-dimensional vehicle MFD (3D-vMFD) relating the accumulation of cars and buses, and the total circulating vehicle flow in the network. This relation experiences low scatter and can be approximated by an exponential-family function. We also propose a parsimonious model to estimate a three-dimensional passenger MFD (3D-pMFD), which provides a different perspective of the flow characteristics in bi-modal networks, by considering that buses carry more passengers. We also show that a constant Bus-Car Unit (BCU) equivalent value cannot describe the influence of buses in the system as congestion develops. We then integrate a partitioning algorithm to cluster the network into a small number of regions with similar mode composition and level of congestion. Our results show that partitioning unveils important traffic properties of flow heterogeneity in the studied network. Interactions between buses and cars are different in the partitioned regions due to higher density of buses. Building on these results, various traffic management strategies in bi-modal multi-region urban networks can then be integrated, such as redistribution of urban space among different modes, perimeter signal control with preferential treatment of buses and bus priority

Children's International Polyposis (CHIP) study : a randomized, double-blind, placebo-controlled study of celecoxib in children with familial adenomatous polyposis

Objective: To evaluate the efficacy and safety of celecoxib versus placebo in the prevention and treatment of colorectal polyposis in children with familial adenomatous polyposis (FAP). Methods: In this Phase III, double-blind, randomized, placebo-controlled, multicenter trial patients aged 10-17 years with FAP were randomized to celecoxib (16 mg/kg/day) or placebo for up to 5 years. Patients underwent annual assessments, including colonoscopies, to detect the time from randomization to the earliest occurrence of >= 20 polyps (> 2 mm in size) or colorectal malignancy. The study was terminated early due to low rate of observed endpoints combined with a lower than expected enrollment rate. Descriptive results are provided. Results: Of 106 randomized patients, 55 were treated with celecoxib (mean age 12.6 years; 52.7% female) and 51 were given placebo (mean age 12.2 years; 54.9% female). Disease progression (>= 20 polyps, > 2 mm in size) was observed in seven (12.7%) and 13 (25.5%) patients, respectively. The median time to disease progression was 2.1 years in the celecoxib group and 1.1 years for placebo. No patient developed colorectal cancer. The rate of adverse events (AEs) was similar in both groups (75.5% and 72.9%, respectively). Three patients in the celecoxib group (none in the placebo group) experienced serious AEs. Conclusion: In children with FAP, celecoxib was a well-tolerated treatment that was associated with a lower rate of colorectal polyposis and a longer time to disease progression compared with placebo. Due to the low rate of observed endpoints, the long-term impact of these results could not be ascertained

Production operation of small petroleum enterprises in Tomsk region

Implementing resource-innovative strategy to develop Russian fuel-and-energy sector implies the promotion of small oil production enterprises developing fields with the reserves of less than 5 mln. tons. However, the efficiency of such enterprises, investigated on the example of Tomsk region (considering the indexes of oil extraction, growth of reserves, amount of capital expenditures and geological surveys), signifies the presence of definite tendencies. Consequently, management decisions concerning economic, organizational, financial and fiscal character should be taken in order to eliminate detrimental factors

A reference time scale for Site U1385 (Shackleton Site) on the SW Iberian Margin

We produced a composite depth scale and chronology for Site U1385 on the SW Iberian Margin. Using log(Ca/Ti) measured by core scanning XRF at 1-cm resolution in all holes, a composite section was constructed to 166.5 meters composite depth (mcd) that corrects for stretching and squeezing in each core. Oxygen isotopes of benthic foraminifera were correlated to a stacked δ^18O reference signal (LR04) to produce an oxygen isotope stratigraphy and age model. Variations in sediment color contain very strong precession signals at Site U1385, and the amplitude modulation of these cycles provides a powerful tool for developing an orbitally-tuned age model. We tuned the U1385 record by correlating peaks in L* to the local summer insolation maxima at 37^oN. The benthic δ^18O record of Site U1385, when placed on the tuned age model, generally agrees with other time scales within their respective chronologic uncertainties. The age model is transferred to down-core data to produce a continuous time series of log(Ca/Ti) that reflect relative changes of biogenic carbonate and detrital sediment. Biogenic carbonate increases during interglacial and interstadial climate states and decreases during glacial and stadial periods. Much of the variance in the log(Ca/Ti) is explained by a linear combination of orbital frequencies (precession, tilt and eccentricity), whereas the residual signal reflects suborbital climate variability. The strong correlation between suborbital log(Ca/Ti) variability and Greenland temperature over the last glacial cycle at Site U1385 suggests that this signal can be used as a proxy for millennial-scale climate variability over the past 1.5 Ma. Millennial climate variability, as expressed by log(Ca/Ti) at Site U1385, was a persistent feature of glacial climates over the past 1.5 Ma, including glacial periods of the early Pleistocene (‘41-kyr world’) when boundary conditions differed significantly from those of the late Pleistocene (‘100-kyr world’). Suborbital variability was suppressed during interglacial stages and enhanced during glacial periods, especially when benthic δ^18O surpassed ~ 3.3-3.5‰. Each glacial inception was marked by appearance of strong millennial variability and each deglaciation was preceded by a terminal stadial event. Suborbital variability may be a symptomatic feature of glacial climate or, alternatively, may play a more active role in the inception and/or termination of glacial cycles.This research was supported by the Natural Environmental Research Council Grant NE/K005804/1 to DH and LS and NE/J017922/1 to DH.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.gloplacha.2015.07.00