Image Data Augmentation for Deep Learning: A Survey

Deep learning has achieved remarkable results in many computer vision tasks. Deep neural networks typically rely on large amounts of training data to avoid overfitting. However, labeled data for real-world applications may be limited. By improving the quantity and diversity of training data, data augmentation has become an inevitable part of deep learning model training with image data. As an effective way to improve the sufficiency and diversity of training data, data augmentation has become a necessary part of successful application of deep learning models on image data. In this paper, we systematically review different image data augmentation methods. We propose a taxonomy of reviewed methods and present the strengths and limitations of these methods. We also conduct extensive experiments with various data augmentation methods on three typical computer vision tasks, including semantic segmentation, image classification and object detection. Finally, we discuss current challenges faced by data augmentation and future research directions to put forward some useful research guidance

Aggregate Model of District Heating Network for Integrated Energy Dispatch: A Physically Informed Data-Driven Approach

The district heating network (DHN) is essential in enhancing the operational flexibility of integrated energy systems (IES). Yet, it is hard to obtain an accurate and concise DHN model for the operation owing to complicated network features and imperfect measurement. Considering this, this paper proposes a physically informed data-driven aggregate model (AGM) for DHN, providing a concise description of the source-load relationship of DHN without exposing network details. First, we derive the analytical relationship between the state variables of the source and load nodes of DHN, offering a physical fundament for the AGM. Second, we propose a physics-informed estimator for AGM that is robust to low-quality measurement, in which the physical constraints associated with the parameter normalization and sparsity are embedded to improve the accuracy and robustness. Finally, we propose a physics-enhanced algorithm to solve the nonlinear estimator with non-closed constraints efficiently. Simulation results verify the effectiveness of the proposed method

Trap-Assisted Charge Injection into Large Bandgap Polymer Semiconductors.

The trap-assisted charge injection in polyfluorene-poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT:PSS) model systems with an Al or Al/LiF cathode is investigated. We find that inserting 1.3 nm LiF increases electron and hole injections simultaneously and the increase of holes is greater than electrons. The evolution of internal interfaces within polymer light-emitting diodes is observed by transmission electron microscopy, which reveals that the introduction of LiF improves the interface stability at both the cathode (cathode/polymer) and the anode (indium tin oxide (ITO)/PEDOT:PSS). Above-mentioned experimental results have been compared to the numerical simulations with a revised Davids model and potential physical mechanisms for the trap-assisted charge injection are discussed

Strongly adhesive dry transfer technique for van der Waals heterostructure

That one can stack van der Waals materials with atomically sharp interfaces has provided a new material platform of constructing heterostructures. The technical challenge of mechanical stacking is picking up the exfoliated atomically thin materials after mechanical exfoliation without chemical and mechanical degradation. Chemically inert hexagonal boron nitride (hBN) has been widely used for encapsulating and picking up vdW materials. However, due to the relatively weak adhesion of hBN, assembling vdW heterostructures based on hBN has been limited. We report a new dry transfer technique. We used two vdW semiconductors (ZnPS3 and CrPS4) to pick up and encapsulate layers for vdW heterostructures, which otherwise are known to be hard to fabricate. By combining with optimized polycaprolactone (PCL) providing strong adhesion, we demonstrated various vertical heterostructure devices, including quasi-2D superconducting NbSe2 Josephson junctions with atomically clean interface. The versatility of the PCL-based vdW stacking method provides a new route for assembling complex 2D vdW materials without interfacial degradation.Comment: Accepted for publication in 2D Material

Distributed Joint Source-Channel Coding in Wireless Sensor Networks

Considering the fact that sensors are energy-limited and the wireless channel conditions in wireless sensor networks, there is an urgent need for a low-complexity coding method with high compression ratio and noise-resisted features. This paper reviews the progress made in distributed joint source-channel coding which can address this issue. The main existing deployments, from the theory to practice, of distributed joint source-channel coding over the independent channels, the multiple access channels and the broadcast channels are introduced, respectively. To this end, we also present a practical scheme for compressing multiple correlated sources over the independent channels. The simulation results demonstrate the desired efficiency

Pharmaceutical Supply Chain in China: Pricing and Production Decisions with Price-Sensitive and Uncertain Demand

In this paper, we apply game theory to study the price competition between drugstores and hospitals in China’s pharmaceutical supply chain. Motivated by drug shortages and price disparity problems, we build a simplified model with one supplier, one hospital, and one drugstore in which the sellers sell one kind of drug and compete on price. The hospital receives a discount from the government when ordering the drug and both sellers face a price-sensitive and uncertain demand. The existence and uniqueness of a Nash equilibrium are proved and closed-form solutions are found for linear demand cases. We characterize the pricing and ordering decisions of the hospital and drugstore. The analysis shows that high ex-factory price, high price sensitivity, and a small discount are three factors contributing to drug shortages. We consider two special kinds of linear demand to obtain insights into the drug price disparity problem

Dynamic security control in heat and electricity integrated energy system with an equivalent heating network model

Intensified interaction between electric power system (EPS) and district heating network (DHN) has raised an urgent requirement of security control to ensure the regular operation of the heat and electricity integrated energy system (HE-IES). However, the implicit expressions of thermal dynamics remain an obstacle to building the quantitative relationships between the EPS and the DHN. To solve this, this paper proposes a novel dynamic model of the district heating network, which contains the equivalent pipe model and the analytical thermal source-load function (TSLF). Then, the interaction between EPS and DHN is divided into the energy flow calculation at the control points and the dynamic simulation during the control intervals to investigate the coupling effect. On this basis, the dynamic characteristics in HE-IES are employed to quantitatively establish the security control strategy using the combined sensitivity analysis. Case studies verify the accuracy and efficiency of the proposed method

Perioperative outcomes of zero ischemia radiofrequency ablation-assisted tumor enucleation for renal cell carcinoma: results of 182 patients

Abstract Background To evaluate the perioperative outcomes of zero ischemia radiofrequency ablation-assisted tumor enucleation. Methods Patients undergoing zero ischemia radiofrequency ablation-assisted tumor enucleation were retrospectively identified from July 2008 to March 2013. The tumor was enucleated after RFA treatment. R.E.N.A.L., PADUA and centrality index (C-index) score systems were used to assess each tumor case. We analyzed the correlation of perioperative outcomes with these scores. Postoperative complications were graded with Clavien-Dindo system. Multivariate logistic regression analyses were used to assess risk of complications. Results Among 182 patients assessed, median tumor size, estimated blood loss, hospital stay and operative time were 3.2 cm (IQR 2.8–3.4), 80 ml (IQR 50–120), 7 days (IQR 6–8) and 100 min (IQR 90–120), respectively. All three scoring systems were strongly correlated with estimated blood loss, hospital stay and operative time. We found 3 (1.6%) intraoperative and 23 (12.6%, 13 [7.1%] Grade 1 and 10 [5.5%] Grade 2 & 3a) postoperative complications. The median follow-up was 55.5 months (IQR 45–70). Additionally, the complexities of R.E.N.A.L., PADUA and C-index scores were significantly correlated with complication grades (P < 0.001; P < 0.001; P < 0.001; respectively). As the representative, R.E.N.A.L. score was an independent predictive factor for postoperative complications and patients with a high complexity had an over 24-fold higher risk compared to those with a low complexity (OR 24.360, 95% CI 4.412–134.493, P < 0.001). Conclusions Zero ischemia radiofrequency ablation-assisted tumor enucleation is considered an effective nephron-sparing treatment. Scoring systems could be useful for predicting perioperative outcomes of radiofrequency ablation-assisted tumor enucleation