Adversarial Attacks and Defenses in Images,Graphs and Text: A Review

Machine Intelligence Research - Deep neural networks (DNN) have achieved unprecedented success in numerous machine learning tasks in various domains. However, the existence of adversarial examples...     

Visible-light Catalysed Trifluoromethylthiolation and Related Dearomative Spirocyclizations

We conceptualized a radical cyclization approach for the synthesis of SCF₃, SAr, SO₂Ar and COAr featured spirocyclic [4.5] and [5.5] trienone between biaryls and ArSO₂H or ArCOCO₂H in presence of RFTA as a photocatalyst whereas the insertion of ArSSAr or AgSCF₃ devoid of photocatalyst via an energetically demanding dearomative transformation under visible-light catalysis. The photo-excited charge transfer complex with biaryl tethered ynones provides a way to promote S-centered radical generation followed by its insertion to enable a wide range of biologically important molecules.     

Different diode models comparison using Lambert W function for extracting maximum power from BIPV modules

Perfect modeling of the building‐integrated photovoltaic (BIPV) module circuit equivalent is required for examining the operation of a BIPV system. Before designing the power electronic converters of an overall BIPV system, a perfect diode modeling is required that usually resembles the I‐V and P‐V characteristics of the BIPV modules. In this research article, different types of diode modeling of BIPV systems along with their comparative analysis based on the Lambert W function in MATLAB/Simulink environment is presented. The main aim of this research article is to analyze Mprime transparent M 115‐130P‐FI BIPV modules (115 Wp and 130 Wp) and compare the existing diode models in terms of accuracy and extraction of unknown parameters for the same. Simulation results for Lambert W function based comparison of the five‐parameter model (FPM), seven‐parameter model (SPM) and nine‐parameter model (NPM) power of 115 Wp and 130 Wp BIPV modules along with their percentage errors are well presented. Lambert W function based comparison of FPM, SPM, and NPM is further made at different values of irradiations and temperatures respectively.     

搅拌摩擦对接焊6061铝合金的高周疲劳行为（英文）

对6061铝合金进行搅拌摩擦对接焊,其焊接工艺参数为:旋转速度600、800、1000、1200 r/min,前进速度80、100 mm/min,探针插入深度1.85 mm。基于搅拌摩擦焊参数计算得到的能量输入结果表明,在输入能量为196~405 kJ的情况下,接头在297~354 kJ的输入能量范围内有最大的抗拉强度。在不同的应力比(R=0.5,0.3,0.1,-0.3,-0.5)下,将高强度、低强度2种焊接头进行疲劳测试。结果表明,对于这2种焊接头,显微组织特征明显影响其疲劳性能,比如搅拌区、热力影响区(TMAZ)和热影响区。从接头的显微组织、裂纹扩展路径和断裂表面观察等方面对其疲劳强度进行讨论。     

搅拌摩擦对接焊6061铝合金的高周疲劳行为

对6061铝合金进行搅拌摩擦对接焊,其焊接工艺参数为：旋转速度600、800、1000、1200 r/min,前进速度80、100 mm/min,探针插入深度1.85 mm。基于搅拌摩擦焊参数计算得到的能量输入结果表明,在输入能量为196～405 kJ的情况下,接头在297～354 kJ的输入能量范围内有最大的抗拉强度。在不同的应力比（R=0.5,0.3,0.1,-0.3,-0.5）下,将高强度、低强度2种焊接头进行疲劳测试。结果表明,对于这2种焊接头,显微组织特征明显影响其疲劳性能,比如搅拌区、热力影响区（TMAZ）和热影响区。从接头的显微组织、裂纹扩展路径和断裂表面观察等方面对其疲劳强度进行讨论。     

Squeeze and multi-context attention for polyp segmentation

Artificial Intelligence-based Computer Aided Diagnostics (AI-CADx) have been proposed to help physicians in reducing misdetection of polyps in colonoscopy examination. The heterogeneity of a polyp's appearance makes detection challenging for physicians and AI-CADx. Towards building better AI-CADx, we propose an attention module called Squeeze and Multi-Context Attention (SMCA) that re-calibrates a feature map by providing channel and spatial attention by taking into consideration highly activated features and context of the features at multiple receptive fields simultaneously. We test the effectiveness of SMCA by incorporating it into the encoder of five popular segmentation models. We use five public datasets and construct intra-dataset and inter-dataset test sets to evaluate the generalizing capability of models with SMCA. Our intra-dataset evaluation shows that U-Net with SMCA and without SMCA has a precision of 0.86 ± 0.01 and 0.76 ± 0.02 respectively on CVC-ClinicDB. Our inter-dataset evaluation reveals that U-Net with SMCA and without SMCA has a precision of 0.62 ± 0.01 and 0.55 ± 0.09 respectively when trained on Kvasir-SEG and tested on CVC-ColonDB. Similar results are observed using other segmentation models and other public datasets. In conclusion, we demonstrate that incorporating SMCA into the segmentation models leads to an increase in generalizing capability of the segmentation models.