An Ensemble Model for Distorted Images in Real Scenarios

Image acquisition conditions and environments can significantly affect high-level tasks in computer vision, and the performance of most computer vision algorithms will be limited when trained on distortion-free datasets. Even with updates in hardware such as sensors and deep learning methods, it will still not work in the face of variable conditions in real-world applications. In this paper, we apply the object detector YOLOv7 to detect distorted images from the dataset CDCOCO. Through carefully designed optimizations including data enhancement, detection box ensemble, denoiser ensemble, super-resolution models, and transfer learning, our model achieves excellent performance on the CDCOCO test set. Our denoising detection model can denoise and repair distorted images, making the model useful in a variety of real-world scenarios and environments

Performance analysis of plate heat exchangers used as refrigerant evaporators

PhD, Faculty of Engineering and the Built Environment, University of the WitwatersrandIn this study the heat transfer and frictional pressure drop performance characteristics of plate heat exchangers (PHE’s) used as refrigerant liquid overfeed evaporators were investigated. PHE’s have been gaining new applications in the refrigeration industry, especially as evaporators, during the last few decades, but the available information in the open literature for operation in this mode is rather limited. This study aims to extend the knowledge of PHE evaporator performance and to develop a model for use in evaluating heat transfer and pressure drop over as wide a range of operating conditions as possible. A laboratory experimental facility was constructed and the thermal-hydraulic characteristics of three middle-size industrial PHE’s were measured. The exchangers all had 24 plates of the same size but with different chevron angle combinations of 28°/28°, 28°/60°, and 60°/60°. Two sets of tests were carried out with the three units: single-phase performance tests with water, and evaporator performance tests with R134a and R507A, for which the exchangers operated as refrigerant liquid over-feed evaporators. The tests with water served to provide accurate water-side heat transfer information for the evaporator performance analysis which is the primary purpose of this study. In the evaporator performance tests, refrigerant flow boiling heat transfer and two-phase pressure drop data were obtained under steady conditions, over a range of heat flux from 1.9 to 6.9 kW/m2, refrigerant mass flux from 5.6 to 31.4 kg/(m2s), outlet vapour quality from 0.2 to 0/95, and saturation temperatures from 5.9 to 13.0 °C. Additional field data of thermal performance were collected on an ammonia and a R12 PHE water chiller, operating as thermo-siphon evaporators at their design working conditions. All experimental data were reduced and analyzed to obtain the refrigerant-side heat transfer coefficients and frictional pressure drops in the PHE evaporators. The heat transfer results showed a strong dependence on heat flux and a weak dependence on mass flux, vapour fraction and the chevron angle. Along with the ii observations from the ammonia and R12 evaporators, it is concluded that the dominating heat transfer mechanism in this type of evaporator is nucleate boiling rather than forced convection. In contrast to the heat transfer characteristics, the refrigerant two-phase frictional pressure drop was found to be strongly influenced by mass flow rate, vapour fraction and also the chevron angle. An almost linear increase of the frictional pressure drop with the homogeneous two-phase kinetic energy per unit volume was observed for both refrigerants. Based on the experimental data, correlations were developed for predicting the refrigerant boiling heat transfer coefficient and two-phase frictional pressure drop in PHE liquid over-feed evaporators. Two correlations were developed for boiling heat transfer, one of these reflecting the h-q relationship in pool boiling, the other with all constants and exponents determined by regression analysis. The mean absolute errors are respectively 7.3% and 6.8% for these correlations. For two-phase frictional pressure drop, data were correlated using two established methods, namely the homogeneous and the Lockhart-Martinelli methods, with means absolute errors of 6.7% and 4.2%, respectively. The homogeneous model showed a slightly higher discrepancy with the experimental data but is likely to be more physically sound for PHE evaporators, and is much simpler to apply. Validation of these correlations with other data has been difficult due to the shortage of published information. For other refrigerants operating at comparable conditions, these correlations should serve as a guide, while more accurate design or evaluation may need to be based on further testing. The performance analysis carried out in this study was based on systematic experimental investigations and field tests on industrial PHE units. Correlations were developed covering a rather extensive range of flow parameters, plate geometry and various refrigerants. Such correlations have not been reported previously for PHE liquid over-feed evaporators. The results simplify the performance analysis of PHE evaporators and provide a reliable thermalhydraulic model of PHE liquid over-feed evaporators, which can be used for system modeling of water-chilling machines employing this type of evaporator

Towards the Desirable Decision Boundary by Moderate-Margin Adversarial Training

Adversarial training, as one of the most effective defense methods against adversarial attacks, tends to learn an inclusive decision boundary to increase the robustness of deep learning models. However, due to the large and unnecessary increase in the margin along adversarial directions, adversarial training causes heavy cross-over between natural examples and adversarial examples, which is not conducive to balancing the trade-off between robustness and natural accuracy. In this paper, we propose a novel adversarial training scheme to achieve a better trade-off between robustness and natural accuracy. It aims to learn a moderate-inclusive decision boundary, which means that the margins of natural examples under the decision boundary are moderate. We call this scheme Moderate-Margin Adversarial Training (MMAT), which generates finer-grained adversarial examples to mitigate the cross-over problem. We also take advantage of logits from a teacher model that has been well-trained to guide the learning of our model. Finally, MMAT achieves high natural accuracy and robustness under both black-box and white-box attacks. On SVHN, for example, state-of-the-art robustness and natural accuracy are achieved

Far from just a poke : Common painful needle procedures and the development of needle fear

Background: Vaccine injections are the most common painful needle procedure experienced throughout the lifespan. Many strategies are available to mitigate this pain; however, they are uncommonly utilized, leading to unnecessary pain and suffering. Some individuals develop a high level of fear and subsequent needle procedures are associated with significant distress. Objective: The present work is part of an update and expansion of a 2009 knowledge synthesis to include the management of vaccinerelated pain across the lifespan and the treatment of individuals with high levels of needle fear. This article will provide a conceptual foundation for understanding: (a) painful procedures and their role in the development and maintenance of high levels of fear; (b) treatment strategies for preventing or reducing the experience of pain and the development of fear; and (c) interventions for mitigating high levels of fear once they are established. Results: First, the general definitions, lifespan development and functionality, needle procedure-related considerations, and assessment of the following constructs are provided: pain, fear, anxiety, phobia, distress, and vasovagal syncope. Second, the importance of unmitigated pain from needle procedures is highlighted from a developmental perspective. Third, the prevalence, course, etiology, and consequences of high levels of needle fear are described. Finally, the management of needle-related pain and fear are outlined to provide an introduction to the series of systematic reviews in this issue. Discussion: Through the body of work in this supplement, the authors aim to provide guidance in how to treat vaccination-related pain and its sequelae, including high levels of needle fear

Impact of epicardial adipose tissue volume on hemodynamically significant coronary artery disease in Chinese patients with known or suspected coronary artery disease

BackgroundEpicardial adipose tissue (EAT) is directly related to coronary artery disease (CAD), but little is known about its role in hemodynamically significant CAD. Therefore, our goal is to explore the impact of EAT volume on hemodynamically significant CAD.MethodsPatients who underwent coronary computed tomography angiography (CCTA) and received coronary angiography within 30 days were retrospectively included. Measurements of EAT volume and coronary artery calcium score (CACs) were performed on a semi-automatic software based on CCTA images, while quantitative flow ratio (QFR) was automatically calculated by the AngioPlus system according to coronary angiographic images.ResultsThis study included 277 patients, 112 of whom had hemodynamically significant CAD and showed higher EAT volume. In multivariate analysis, EAT volume was independently and positively correlated with hemodynamically significant CAD [per standard deviation (SD) cm3; odds ratio (OR), 2.78; 95% confidence interval (CI), 1.86–4.15; P < 0.001], but negatively associated with QFRmin (per SD cm3; β coefficient, −0.068; 95% CI, −0.109 to −0.027; P = 0.001) after adjustment for traditional risk factors and CACs. Receiver operating characteristics curve analysis demonstrated a significant improvement in predictive value for hemodynamically significant CAD with the addition of EAT volume to obstructive CAD alone (area under the curve, 0.950 vs. 0.891; P < 0.001).ConclusionIn this study, we found that EAT volume correlated substantially and positively with the existence and severity of hemodynamically significant CAD in Chinese patients with known or suspected CAD, which was independent of traditional risk factors and CACs. In combination with obstructive CAD, EAT volume significantly improved diagnostic performance for hemodynamically significant CAD, suggesting that EAT could be a reliable noninvasive indicator of hemodynamically significant CAD

An efficient hierarchical identity-based encryption based on SM9

Hierarchical identity-based encryption can efficiently reduce the workload of private key generation and key distribution of the private key generator in the identity-based cryptography. SM9 is an identity-based cryptosystem and has become a Chinese cryptographic standard and national standard. It plays a significant role in many applications, such as finance and government affairs. However, SM9 encryption algorithm does not support hierarchical encryption, which is undesirable for the large network and becomes a bottleneck for its deployments. In this paper, we proposed an efficient hierarchical identity-based encryption scheme SM9-HIBE based on SM9. Compared to SM9 encryption algorithm, the ciphertext in SM9-HIBE only requires an additional group element and the decryption overhead increases one pairing operation only, which is independent of the length of receiver’s identity. We prove that if the DBDHI assumption holds, our scheme is proved to be IND-sCPA secure in the random oracle model. Finally, we theoretically analyze our scheme and make a comparison. The result shows that the SM9-HIBE is comparable to the existing HIBE schemes in terms of computational cost and communication overhead

Characterization of the complete chloroplast genome of sugar maple (Acer saccharum)

Acer saccharum is one ecologically and economically important tree species cultivated widely across the world. In this study we generated the complete chloroplast (cp) genome of A. saccharum via genome-skimming method. The assembled genome is 155,684 base-pairs (bp) in size, with one large single copy region of 85,393 bp and one small single copy region of 18,033 bp separated by two inverted repeats of 26,129 bp. The genome contains a total of 133 genes, including 85 protein-coding genes, 8 rRNAs and 40 tRNAs. Furthermore, phylogenomic estimation strongly supported A. saccharum as a distinct lineage within the monophyletic Acer

An R

An R2 indicator based selection method is a major ingredient in the formulation of indicator based evolutionary multiobjective optimization algorithms. The existing classical indicator based selection methodologies have demonstrated an excellent performance to solve low-dimensional optimization problems. However, the R2 indicator based evolutionary multiobjective optimization algorithms encounter enormous challenges in high-dimensional objective space. Our main purpose is to explore how to extend the R2 indicator to handle many-objective optimization problems. After analyzing the R2 indicator, the objective space partition strategy, and the decomposition method, we propose a steady-state evolutionary algorithm based on the R2 indicator and the decomposition method, named, R2-MOEA/D, to obtain well-converged and well-distributed Pareto front. The main contribution of this paper contains two aspects. (1) The convergence and diversity for the R2 indicator based selection are analyzed. Two improper selection situations will be properly solved via applying the decomposition method. (2) According to the position of a new individual in the steady-state evolutionary algorithm, two different objective space partition strategies and the corresponding selection methods are proposed. Extensive experiments are conducted on a variety of benchmark test problems, and the experimental results demonstrate that the proposed algorithm has competitive performance in comparison with several tailored algorithms for many-objective optimization

Crystal structure of bis((3-chlorosalicylidene)-ethylenediaminato-κ4N,N′,O,O′)nickel (II), C16H12Cl2NiN2O2

C16H12Cl2NiN2O2, orthorhombic, Pbca (no. 61), a = 12.5166(12) Å, b = 12.5881(14) Å, c = 19.0086(19) Å, V = 2995.0(5) Å3, Z = 8, Rgt(F) = 0.0435, wR2 = 0.0826, T = 296.15