Engineering Data‐ & Model‐Driven Applications: EDMA ‐2017 special issue editorial

EDMA-2017, the first International Workshop on Engineering Data- & Model-driven Applications, was held in conjunction with 10th IEEE Conference Cyber, Physical and Social Computing (IEEE CPSCom-2017). EDMA-2017 provided authors a forum for presentations, discussions sharing of current challenges, knowledge, expertise solutions regarding trends technologies use data computational models dealing complexity industrial, engineering, cyber-physical related domains. Contributions to included relevant studies from across computer science researchers (knowledge discovery, machine learning, big analytics) model-based methods (e.g. engineering hybrid systems reliability, degradation vehicle health management) delivering effective efficient challenges associated handling real-world industrial applications. Selected extended contributions are this special issue, authored by multidisciplinary international teams focussing cutting edge environment image segmentation, application neural networks high-speed train wheel wear classification, manufacturing job shop planning learning. The list selected papers includes: An ordered sparse subspace clustering algorithm based p-Norm: Liping Chen, Gongde Guo Hui Wang extend initial work noise-resilient sequences propose new approach sequential under heavy noise conditions, characteristic industry environments, requiring video scene segmentation. wavelet-histogram oriented gradient transform kernel view extract source images global features using wavelet processes, local an optimized weighted form coefficient matrix, denoising component techniques Laplacian constraints. Analysis prediction SIMPACK backpropagation networks: Shuwen Wang, Hao Yan, Caixia Liu, Ning Fan, Xiaoming Liu Chengguo combination dynamic simulation measurements deliver predictive important aspects safe operation trains. Wheel is studied carriages network classifiers measurement data. By investigating normal lateral contact forces wheels, wheel-rail interfaces, integrating simulations learning classifiers, contributors provide insights useful maintenance Job scheduling manufacturers manual operations, authors: Longzhi Yang, Jie Li, Fei Chao, Phil Hackney, Mark Flanagan study collate pack area completion time estimation Point Sale Purchase Manufacturing Scheduling optimisation industry. build searching most cost-effective permutation operations cost each compatible relations between operations. include algorithms genetic that integrates fuzzy inferences expert loop initialisation adaptive processes. chairs issue editors thank authors, organisers readers passion apply research Dr Daniel Neagu Professor successful AI/ML/big analytics scientist 20+ years project leadership funded national, programmes, also national leads Bradford's AI Research (AIRe) Group has Explainable AI, Machine Learning algorithms, responsible model governance, their applications healthcare, toxicology engineering. chaired number conferences (eg DSS 2018, UKCI 2014), founder series Applications (EDMA 2017-2021). Felician Campean, PhD, FRSS, Reliability Director Automotive Centre at University Bradford, UK. He internationally recognised established extensive track record knowledge transfer automotive industry, spanning over 24 years. His interests development novel data-driven approaches enhance reliability resilience complex multi-disciplinary systems, throughout lifecycle. co-founded Advanced Analytics laboratory 2016, currently leading significant portfolio projects driving ML real world problems. Marian Gheorghe Computational Models Software Bradford. Gheorghe's software interest classes unconventional models, especially membrane connections other (unconventional) - Petri nets, process algebras, L-systems, reactive etc. interested formally verifying such checking approaches. testing formal verification. been working large scale simulations, contributed building adequate platforms specifications verification tools synthetic biology, but autonomous systems. served as Chair Steering Committee Membrane 2010 2014, main computing community, editing proceedings these events Springer, Lecture Notes Computer Science Series. active collaborations many prestigious Universities groups world. EPSRC, EU, Royal Academy Engineering, British Council some abroad scientific advisor collaborator.