IEEE

Deep Learning for Unsupervised Anomaly Localization in Industrial Images: A Survey

Abstract: Currently, deep learning-based visual inspection has been highly successful with the help of supervised learning methods. However, in real industrial ...
IEEE

DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data

Abstract: Despite over two decades of progress, imbalanced data is still considered a significant challenge for contemporary machine learning models. Modern advances in deep learning have further ...
IEEE

A Strategy for Short-Term Load Forecasting by Support Vector Regression Machines

Abstract: This paper presents a generic strategy for short-term load forecasting (STLF) based on the support vector regression machines (SVR). Two important improvements to the SVR based load ...
IEEE

Moving Beyond Optimism Bias and Strategic Misrepresentation: An Explanation for Social Infrastructure Project Cost Overruns

Abstract: Infrastructure projects regularly experience cost and schedule overruns. Research led by Flyvbjerg has suggested that misrepresentation and optimism bias are primary causes for overruns.
IEEE

Modeling and Control of

Abstract: Designing adequate control laws for grid-connected inverters with LCL filters is complicated. The power quality standards and the system resonances burden the task. In order to deal with ...
IEEE

Extending Amdahl’s Law for Heterogeneous Multicore Processor with Consideration of the Overhead of Data Preparation

Abstract: We extend Amdahl’s law by considering the overhead of data preparation (ODP) for multicore systems, and apply it to three “traditional” multicore system scenarios (homogeneous symmetric ...
IEEE

Transient Damping Method for Improving the Synchronization Stability of Virtual Synchronous Generators

Abstract: The virtual synchronous generator (VSG) was proposed to emulate a synchronous machine's dynamics when integrating power electronic converter-based distributed energy resources to the power ...
IEEE

Probabilistic Selection Approaches in Decomposition-Based Evolutionary Algorithms for Offline Data-Driven Multiobjective Optimization

Abstract: In offline data-driven multiobjective optimization, no new data are available during the optimization process. Approximation models, also known as surrogates, are built using the provided ...
IEEE

Towards an Analysis of Security Issues, Challenges, and Open Problems in the Internet of Things

Abstract: The Internet of Things (IoT) devices have become popular in diverse domains such as e-Health, e-Home, e-Commerce, and e-Trafficking, etc. With increased deployment of IoT devices in the real ...
IEEE

A Simple Adaptive Overcurrent Protection of Distribution Systems With Distributed Generation

Abstract: A significant increase in the penetration of distributed generation has resulted in a possibility of operating distribution systems with distributed generation in islanded mode. However, ...
IEEE

Dermatologist-Level Classification of Skin Cancer Using Cascaded Ensembling of Convolutional Neural Network and Handcrafted Features Based Deep Neural Network

Abstract: Skin cancer is caused due to unusual development of skin cells and deadly type cancer. Early diagnosis is very significant and can avoid some categories of skin cancers, such as melanoma and ...
IEEE

Understanding and Learning Discriminant Features based on Multiattention 1DCNN for Wheelset Bearing Fault Diagnosis

Abstract: Recently, deep-learning-based fault diagnosis methods have been widely studied for rolling bearings. However, these neural networks are lack of interpretability for fault diagnosis tasks.