Prototypical Residual Networks for Anomaly Detection and Localization

Anomaly detection and localization are widely used in industrial manufacturing for its efficiency and effectiveness. Anomalies are rare and hard to collect and supervised models easily over-fit to these seen anomalies with a handful of abnormal samples, producing unsatisfactory performance. On the other hand, anomalies are typically subtle, hard to discern, and of various appearance, making it difficult to detect anomalies and let alone locate anomalous regions. To address these issues, we propose a framework called Prototypical Residual Network (PRN), which learns feature residuals of varying scales and sizes between anomalous and normal patterns to accurately reconstruct the segmentation maps of anomalous regions. PRN mainly consists of two parts: multi-scale prototypes that explicitly represent the residual features of anomalies to normal patterns; a multisize self-attention mechanism that enables variable-sized anomalous feature learning. Besides, we present a variety of anomaly generation strategies that consider both seen and unseen appearance variance to enlarge and diversify anomalies. Extensive experiments on the challenging and widely used MVTec AD benchmark show that PRN outperforms current state-of-the-art unsupervised and supervised methods. We further report SOTA results on three additional datasets to demonstrate the effectiveness and generalizability of PRN.Comment: Accepted by CVPR 202

MRN: Multiplexed Routing Network for Incremental Multilingual Text Recognition

Multilingual text recognition (MLTR) systems typically focus on a fixed set of languages, which makes it difficult to handle newly added languages or adapt to ever-changing data distribution. In this paper, we propose the Incremental MLTR (IMLTR) task in the context of incremental learning (IL), where different languages are introduced in batches. IMLTR is particularly challenging due to rehearsal-imbalance, which refers to the uneven distribution of sample characters in the rehearsal set, used to retain a small amount of old data as past memories. To address this issue, we propose a Multiplexed Routing Network (MRN). MRN trains a recognizer for each language that is currently seen. Subsequently, a language domain predictor is learned based on the rehearsal set to weigh the recognizers. Since the recognizers are derived from the original data, MRN effectively reduces the reliance on older data and better fights against catastrophic forgetting, the core issue in IL. We extensively evaluate MRN on MLT17 and MLT19 datasets. It outperforms existing general-purpose IL methods by large margins, with average accuracy improvements ranging from 10.3% to 35.8% under different settings. Code is available at https://github.com/simplify23/MRN.Comment: Accepted by ICCV 202

A novel method for building air conditioning energy saving potential pre-estimation based on thermodynamic perfection index for space cooling

The construction energy consumption (CEC) is about 35% of entire energy consumption (EC), of which 50% is for cooler air-conditioner. The practical cooling EC is relevant to the dynamic thermal performance of cooler air-conditioner. Analyzing the difference in cooling efficiency and energy-saving potential (ESP) of the same equipment is significant to cutting down building EC. Using the concept of thermodynamic perfectness, a thermal model of refrigeration equipment is established to analyze the deviation from the ideal refrigeration cycle. At the same time, to explore the internal connection between its energy conservation and climate adaptability, five typical cities in different thermal climate zones were selected. Dynamic load model of an office building is established and the cooling EC throughout the year of each city is simulated separately. Preliminary research results show that the thermodynamic perfectness does not have a single-valued function relationship with their cooling efficiency; Guangzhou has the highest cooling demand, with a total cooling load 14.3% higher than Wuhan, and its cooling EC is lower than Wuhan. Through the establishment of a thermodynamic model and preliminary application, the calculation of the cooling ESP in different climatic regions in Chinese summer is greatly important to the usage of air conditioner

Poverty Reduction Effect of New-Type Agricultural Cooperatives: An Empirical Analysis Using Propensity Score Matching and Endogenous Switching Regression Models

Agricultural cooperatives have been found to effectively alleviate poverty in developing countries because of their specific socioeconomic functions that allow poor households to overcome marketing and production constraints. However, cooperative evaluations are inevitably influenced by other poverty alleviation measures and rarely consider the characteristics of specific ethnic groups. Using cross-sectional surveys in Southwest China and employing propensity score matching (PSM) and endogenous switching regression (ESR) models, this paper analyzed the participation of poor households in New-type Agricultural Cooperatives (NACs) in ethnic areas and assessed the income impacts of NAC membership by eliminating unobserved biases and group heterogeneity. This study detected heterogeneous policy perceptions and behavioral differences between the member and nonmember groups, and the PSM and ESR model results indicated that, overall, participation in the NACs had a positive effect on household income. The ESR model was found to be more plausible as it was able to reveal the significant income gaps under a counterfactual inference framework. Local policymakers need to focus on the policy perception and behavioral and earning capability differences between groups and increase the balanced policy implementation

Study on the Effect of Radiant Insulation Panel in Cavity on the Thermal Performance of Broken-Bridge Aluminum Window Frame

Windows have a great impact on building energy consumption, and the thermal performance of window frames directly affects its energy-saving potential. In this paper, a novel method is proposed to optimize the thermal performance of commercially available broken-bridge aluminum window frames, by incorporating radiant insulation panels (RIPs) into the window frame cavity. A typical aluminum alloy window frame heat transfer model is theoretically analyzed and validated, and the effects of key design parameters on the equivalent thermal conductivity (ETC) of the cavity radiation heat transfer and the heat transfer coefficient (U-factor) of window frames are quantitatively analyzed by a finite element simulation method using the THERM software. Moreover, the RIP, the insulation material filling, and low surface emissivity on the thermal performance of the window frame are compared and analyzed. The results show that the RIP is better placed in the middle, the width and quantity of RIPs are negatively correlated with the U-factor, while the surface emissivity of RIPs is positively correlated with the U-factor. Adding RIPs in the cavity can reduce the U-factor of the window frame by more than 7.43%, slightly lower than 8.97% for the filling type, but significantly higher than 0.81% for the low-emissivity type. Inserting RIPs is a simple and effective way to reduce the U-factor of the window frame and have a great potential of use

SVTR: Scene Text Recognition with a Single Visual Model

Dominant scene text recognition models commonly contain two building blocks, a visual model for feature extraction and a sequence model for text transcription. This hybrid architecture, although accurate, is complex and less efficient. In this study, we propose a Single Visual model for Scene Text recognition within the patch-wise image tokenization framework, which dispenses with the sequential modeling entirely. The method, termed SVTR, firstly decomposes an image text into small patches named character components. Afterward, hierarchical stages are recurrently carried out by component-level mixing, merging and/or combining. Global and local mixing blocks are devised to perceive the inter-character and intra-character patterns, leading to a multi-grained character component perception. Thus, characters are recognized by a simple linear prediction. Experimental results on both English and Chinese scene text recognition tasks demonstrate the effectiveness of SVTR. SVTR-L (Large) achieves highly competitive accuracy in English and outperforms existing methods by a large margin in Chinese, while running faster. In addition, SVTR-T (Tiny) is an effective and much smaller model, which shows appealing speed at inference. The code is publicly available at https://github.com/PaddlePaddle/PaddleOCR.Comment: Accepted by IJCAI 202

Indoor thermal nonuniformity of atrium-centered public building: Monitoring and diagnosis for energy saving

Heating ventilation and air conditioning system accounts for over one third of building energy usage, especially for public buildings due to large indoor heat source and high ventilation and thermal comfort requirement compared to residential buildings. Natural ventilation shows high application potentials in public buildings because of its high-efficient ventilation effect and energy saving potential for indoor heat dissipation. In this paper, the building design is conducted for a science museum and library with atrium-centered natural ventilation consideration. The floor layout, building orientation and internal structure are optimized to make full use of natural ventilation for space cooling under local climatic conditions. A natural ventilation model is established through building field tests to evaluate the air flow and thermal environment under indoor and outdoor pressure differences. The preliminary results show that Building A's courtyard exhibited overheating issues, likely attributed to outdoor solar radiation, whereas Building B's courtyard experienced localized cooling, possibly due to indoor air conditioning system controls. Addressing these concerns necessitates modifications in courtyard design and structure. Moreover, both courtyards displayed vertical temperature gradients, emphasizing the need for effective management of outdoor heat influx and enhancements in indoor ventilation and shading strategies. To mitigate these issues, the study proposed three distinct roof design models and more refined indoor air conditioning system control strategies. The optimization of architectural design can achieve a maximum energy-saving rate of 46.54 %. Furthermore, aligning functional zones with thermal comfort areas was recommended to enhance overall building thermal comfort. The findings and proposed solutions from this study are anticipated to contribute to the enhancement of thermal comfort, energy efficiency, and vertical temperature distribution in large public buildings, catering to user requirements while reducing energy consumption. This research holds significant implications for advancing sustainability and environmental preservation in the realm of architecture

The Effectiveness of Exfiltration Technology to Support Sponge City Objectives

Urban stormwater management is essential to improve the management of floodwaters in municipalities in urban areas. However, relying on sponge city options for site planning in an attempt to decrease the impacts of flooding is challenging due to the magnitude of flooding in urban China. The merits of exfiltration technology being used in Canada are described as having significant potential; this technology encourages passage from the stormwater pipe down to a second, lower pipe, to facilitate exfiltration to the vadose zone and, ultimately, to replenish groundwater. For example, for a small urban catchment, stormwater runoff from a 2-h long, 5-yearly storm, is demonstrated as being able to exfiltrate approximately 53% of the stormwater. Overall, the potential exists to exfiltrate stormwater from the lower pipe and it is estimated that 71% of the water entering the storm sewer is exfiltrated to the vadose zone, for a small catchment. The exfiltration pipe technology increases groundwater recharge which provides an opportunity to help manage subsidence in China. However, attention must be paid to the quality of the infiltrating water since, as true for any sponge city initiative, poor quality infiltrating water may deteriorate the quality of the groundwater

Occurrence and risks of antibiotics in the coastal aquatic environment of the Yellow Sea, North China

Eleven antibiotics in three different categories were investigated in two types of coastal bays (a semi-enclosed bay and an open bay) of the Yellow Sea and in fresh water (rivers and sewage treatment plants [STP] effluents) that discharged into the bays. The results revealed the presence of three predominant antibiotics: dehydration erythromycin, sulfamethoxazole and trimethoprim. These antibiotics were detected in the seawater and fresh water with concentrations of 1) risks to the most sensitive aquatic microorganisms, such as Synechococcus leopoliensis and Pseudokirchneriella subcapitata, whilst in the Yantai Bays, the compounds could pose medium risks (1 >= RQ > 0.1) to the same aquatic microorganisms. (C) 2013 Elsevier B.V. All rights reserved.Eleven antibiotics in three different categories were investigated in two types of coastal bays (a semi-enclosed bay and an open bay) of the Yellow Sea and in fresh water (rivers and sewage treatment plants [STP] effluents) that discharged into the bays. The results revealed the presence of three predominant antibiotics: dehydration erythromycin, sulfamethoxazole and trimethoprim. These antibiotics were detected in the seawater and fresh water with concentrations of 1) risks to the most sensitive aquatic microorganisms, such as Synechococcus leopoliensis and Pseudokirchneriella subcapitata, whilst in the Yantai Bays, the compounds could pose medium risks (1 >= RQ > 0.1) to the same aquatic microorganisms. (C) 2013 Elsevier B.V. All rights reserved