Journal Information
Computers & Electrical Engineering
Impact Factor:

Call For Papers
The impact of computers has nowhere been more revolutionary than in electrical engineering. The design, analysis, and operation of electrical and electronic systems are now dominated by computers, a transformation that has been motivated by the natural ease of interface between computers and electrical systems, and the promise of spectacular improvements in speed and efficiency.

Published since 1973, Computers & Electrical Engineering provides rapid publication of topical research into the integration of computer technology and computational techniques with electrical and electronic systems. The journal publishes papers featuring novel implementations of computers and computational techniques in areas like signal and image processing, high-performance computing, parallel processing, and communications. Special attention will be paid to papers describing innovative architectures, algorithms, and software tools.

Specific topics of interest include:

    Applications of high-performance computing and novel computing systems

    Internet-based, multimedia, and wireless networks and applications

    Communications, especially wireless

    Signal processing architectures, algorithms, and applications

    Green technologies in information, computing, and communication systems

    Multi-disciplinary areas, including robotics, embedded systems, and security
Last updated by Xin Yao in 2017-08-21
Special Issues
Special Issue on Computational Intelligence and Smart Power Systems
Submission Date: 2017-09-30

Computational Intelligence (CI) emerges as a significant computing field to facilitate the operation, maintenance and control of power systems. CI can transform the traditional power grid to a smart power grid by effective conditioning and control of the production and distribution of electric power. For the power industry to evolve due to deregulation, engineers require CI tools for appropriate planning, operation and control of the power system. The CI tools can be broadly categorized as optimization methods and decision making methods. They can offer power utilities with novel solutions for efficient analysis, optimal operation and control, and intelligent decision making. The objective of this special issue is to address and disseminate the latest CI applied to generation and distribution of alternate energy, and to manage smart power systems. It plans to cover various aspects of power quality in smart grids and the perspectives of addressing them by researchers of both academia and industry. Authors are invited to submit original and unpublished submissions that exploit CI approaches such as artificial intelligence, soft computing, bio-inspired computing, fuzzy set, etc, for power quality analysis, distributed generation of alternative energy, unbalanced distribution of electrical energy, controlling and maintenance of nonlinear loads and enhancement in smart grids. Topics of interest are limited to: - Power quality issues in smart power grid - Power quality conditioners in smart grids - Coordinated control in inter-area inter-connected power systems and smart distribution network - Power quality issues in multi-micro-grid systems, mini-grids and remote areas - Techno-economic effects of power quality problems in smart grids - ICT and communication requirements for smart power quality assessment and improvement - Micro-grids and distributed generators (DGs) with power quality ancillary services such as voltage support, reactive power flow control, low voltage ride-through, unbalance and harmonics compensation - Active damping control methods for DGs, micro-grids, and smart grids - Islanding detection and synchronization regarding power quality issues of DGs and micro-grids - Protections during faults and severe power quality issues in smart grids and micro-grids
Last updated by Dou Sun in 2017-09-16
Submission Date: 2017-09-30

Artificial intelligence has grown widely for various applications. The current trends of Artificial Intelligence focus on hybridization to improve the performance of system. Despite the immense growth of various AI techniques, there are many challenges and threats which limits the performance these techniques. This special issue invites researchers to provide new directions in addressing the current challenges in identifying various hybrid AI methodologies to combat the current research problems. It will focus very specifically on bringing the current edge opinions on the hybrid artificial intelligence techniques. Authors are invited to submit original unpublished research manuscripts focused on the latest developments in hybrid artificial intelligence or machine learning methodologies. The topic of interest are: - Hybrid machine learning methods or Artificial neural networks - Cognitive frame work using ANN - Clustering process using the artificial neural networks - Fast stable learning in the hybrid neural network - Neural Network based power management systems - Information storage and quality prediction using ANN - FPGA implementation process in ANN - Distance recognition in wireless sensor network using ANN - Analyzing different hybrid activation function using the supervised learning algorithm - Self learning, adaptability, deployment process in the neural networks and machine learning methods - Hybridization of machine learning tools
Last updated by Dou Sun in 2017-09-16
Special Issue on Artifical Neural Network-Based Wireless Sensor Communication
Submission Date: 2017-09-30

Wireless sensor network is one of the most effective communication mechanisms in the present world. The current research is combating in crossing over the limiting boundaries. Despite the immense growth of wireless sensor communication, there are many challenges such as conflicts, middle-man attack, loss of energy, optimized path, etc. This special issue invites researchers to provide new directions in addressing the current challenges in identifying different routing algorithms with energy efficient protocols to make the most effective transfer of information. It will focus very specifically on bringing the current edge opinions on the artificial neural network- based wireless communication systems. Authors are invited to submit original unpublished research manuscripts focused on the latest developments in machine learning or artificial neural network-based wireless sensor communication. The topic of interest are: - Quality of the services using the machine learning methods or Artificial neural networks - Cognitive frame work using ANN in wireless network - Reliable data transmission in the wireless network - Clustering process using the artificial networks - Management of energy efficiency - Fast stable learning in the wireless sensor network - Neural Network based power management systems - Information storage and quality prediction using ANN - Localization of node in WSN - FPGA implementation process in ANN - Distance recognition in wireless sensor network using ANN - Analyzing different activation function using the supervised learning algorithm - Self learning, adaptability, deployment process in the wireless sensor networks - Optimization techniques to improve inter and intra clustering process in the wireless sensor network.
Last updated by Dou Sun in 2017-05-22
Special Issue on Artificial Intelligence and Computer Vision
Submission Date: 2017-10-01

The integration of artificial intelligence and computer vision technologies has become a topic of increasing interest for both researchers and developers from academic fields and industries worldwide. It is foreseeable that artificial intelligence will be the main approach of the next generation of computer vision research. The explosive number of artificial intelligence algorithms and increasing computational power of computers has significantly extended the number of potential applications for computer vision. It has also brought new challenges to the vision community. This is the second special issue on artificial intelligence and computer vision: the first special issues on the same topic will be published in July 2017. We expect to have more special issues on artificial intelligence and computer vision as the area is open to new developments with many innovative and highly productive research. Authors are invited to submit outstanding and original unpublished research manuscripts focused on the latest findings in artificial intelligence and computer vision. The topics of interest are strictly limited to: Theoretical Foundations of Artificial Intelligence 3D Scene Reconstruction RGB-D Vision Pattern Recognition and Machine Vision Computational Imaging Object Tracking Deep Learning for Computer Vision Deep Learning for Mobile Computing Multimedia Big Data Analysis Big Data Analysis for Robotic Vision Big Data Analysis for Medical Imaging Computer Vision for Ocean Observing User Experience for Big Multimedia Systems Artificial Intelligence Hardware Design Smart Vision-based Robotic Manipulation Submission of manuscripts: Research articles must not have been published or submitted for publication elsewhere. All articles will be peer reviewed and accepted based on quality, originality, novelty, and relevance to the special issue theme. Before submission authors should carefully read over the journal's Author Guidelines, which is available at Manuscripts must be submitted through Elsevier Editorial System ( using the Article Type “SI-aicv2”.
Last updated by Dou Sun in 2017-01-15
Special Issue on Intelligent Computing and Smart Systems, Big Data, and Signal Processing
Submission Date: 2017-10-01

This special issue is based on the 6th International Multi-Conference on Engineering and Technology Innovation 2017 (IMETI2017), which will be held during Oct. 28 - Nov. 01, 2017 in Hualien, Taiwan ( It will include the extended versions of the selected best papers of IMETI2017 after going through the CAEE review process. The scope of the special issue is to provide a forum for exchange of ideas among interested researchers, students, developers, and practitioners in the areas of intelligent computing and smart systems, big data, and signal processing (electrical, video, audio, optical). The topics of the special issue include - Architecture, algorithm for intelligent computing - Artificial intelligence and its novel application - Soft computing, fuzzy logic and artificial neural networks - Multimedia information processing and retrieval - Algorithms and systems for big data - Big data analytics and social media - Value of digital convergence for big data - Data collection and storage for digital convergence - Data mining and analysis for digital convergence - Models and tools of digital convergence - Digital convergence for services and composition - Bioinformatics, biometry and medical Imaging - Novel multimedia and compression technology - Intelligence signal processing approaches - Signal processing and control challenges for smart system - Technologies for industry 4.0
Last updated by Dou Sun in 2017-08-05
Special Issue on Image and Video Processing
Submission Date: 2017-10-30

Image and Video processing research have undergone enormous changes and development in recent decades. The main goal is to treat and handle an image or video frame in order to improve its quality. Image processing is the basis of modern technology as computer graphics and computer vision, and it is quite useful for the creation, transfer, and storage of high-quality images and videos using mobile devices and social networks. The remarkable number of new algorithms that emerge day by day and the increasing computational power of computers and mobile devices have created more challenges to the research community in these areas. Therefore, researchers are invited to submit outstanding and original unpublished research manuscripts focused on the latest achievements in Image and Video processing. This will be the 9th special issue in this series; special issues have been published so far in September 2011, September 2012, April 2013, April 2014, November 2014, August 2015, August 2016, and August 2017. The topics of interest are aimed to show the continuing efforts to provide novel Image and Video processing techniques for application on potential topics that include: - Compression. - De-noising - Face Recognition. - Image Retrieval. - Image Enhancement - Image Segmentation. - Pattern Recognition. - Reconstruction and Recovery. - Security - Tracking
Last updated by Dou Sun in 2017-08-05
Special Issue on Advanced Signal Processing in Biomedical Imaging
Submission Date: 2017-11-01

With advancement in biomedical imaging, the amount of data generated by multimodality image techniques, e.g., ranging from Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, Single Photon Emission Computed Tomography (SPECT), and Positron Emission Tomography (PET), Magnetic Particle Imaging, EE/MEG, Optical Microscopy and Tomography, Photoacoustic Tomography, Electron Tomography, and Atomic Force Microscopy, has grown exponentially and the nature of such data has increasingly become more complex. This poses a great challenge on how to develop new advanced imaging methods and computational models for efficient data processing, analysis and modelling in clinical applications and in understanding the underlying biological process. The purpose of this special issue is to provide a diverse, but complementary, set of contributions to demonstrate new developments and applications of advanced imaging analysis in the multimodal biomedical imaging area. The ultimate goal is to promote research and development of advanced imaging analysis for multimodal biomedical images by publishing high-quality research articles and reviews in this rapidly growing interdisciplinary field. The topics of interest include: - New algorithms, models and applications of advanced imaging methods - Multimodal imaging techniques: data acquisition, reconstruction; 2D, 3D, 4D imaging, etc.) - Translational multimodality imaging and biomedical applications (e.g., detection, diagnostic analysis, quantitative measurements, image guidance of ultrasonography) - Variational and combinatorial optimizations for biomedical imaging and image analysis - Advanced Biomedical image analysis ( image processing, Statistical and probabilistic methods for biomedical imaging and image analysis, Machine learning in biomedical imaging and image analysis) - Deep learning methods (convolutional neural network, autoencoder, deep belief network, etc.) - Visualization
Last updated by Dou Sun in 2017-08-05
Special Issue on Emerging Technologies for Connected Vehicles and ITS Networks
Submission Date: 2017-12-01

Over the past decade advances in vehicular communications, also referred as Connected Vehicles and intelligent transportation systems (ITS), have intended to trim down the fuel expenditure by avoiding congested traffic and enhancement of traffic safety, while initiating a new application perspective, i.e., mobile infotainment. To address the individual requirements of both safety and non-safety applications in the Connected Vehicles, there is a need to build a new communication technology for the integrated solutions of vehicular communications and ITS. Connected Vehicles can be of various types, such as Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Everything (V2E). Due to the rapid growth in Connected Vehicles, many research issues need to be addressed, e.g., reliability and latency, appropriate scalable design of MAC and routing protocols, performance and adaptability to the changes in environment (node density and oscillation in network topology), and evaluation/validation of Connected Vehicles’ protocols under the umbrella of coherent assumptions using simulation methodologies. This special issue aims to emphasize the latest achievements to identify those aspects of Connected Vehicles and ITS networks that are identical to a traditional communication network in the broader spectrum. Papers that exploit connectionism and emergence of networking systems in various problem-solving methods in the Connected Vehicles and ITS are invited. Also, papers that outline essential challenges, proof of the concept studies with a direct and simulated comparison to the technical solutions, and mathematical models of the communication principles are welcome. Topics of interest include: - Intra-vehicle communication (vehicle-to-pedestrians, vehicle-to-portable, vehicle-to-sign, etc.) - Network and system architecture for Connected Vehicles - MAC protocols and channel management - Physical layer and routing protocols - Delay tolerant vehicular networks - Real-time optimization system - Modeling and theory - Internet-of-Vehicles, smart sensors (infrastructure and vehicle based) - Mobility management (Traffic models) - Energy efficient vehicular communication - Quality-of-Service for vehicular communication - Future Internet in ITS and Networking Systems - Information and Content Centric Networking in Connected Vehicles Networks
Last updated by Dou Sun in 2017-09-15
Special Issue on Edge-of-Things Computing for Smart Healthcare Systems: Opportunities and Challenges
Submission Date: 2017-12-30

Recently, the Internet of Things (IoT) technologies have made their entrance into the healthcare domain. It is now providing many opportunities to develop Smart healthcare solutions with more intelligent and prediction capabilities both for daily life (home/office) and in-hospitals. In most of such Smart healthcare IoT systems, numerous IoT devices and sensors are being used to monitor users’ healthcare status and transmit the data directly to remote cloud data centers. Such combination of cloud computing and IoT (Cloud-IoT) enables the resource-constrained IoT devices to get the benefit from Cloud’s high-performance computing and massive storage infrastructure for real-time processing, storing, visualization, and analysis of IoT data. However, currently such Cloud-IoT system is facing increasing difficulty to handle the healthcare Big data that IoT generates from various healthcare applications and services. It has become challenging to ensure low latency and network bandwidth consumption, scalability, reliability, mobility, and energy efficiency of healthcare IoT devices while moving all data to the cloud. To cope with these challenges, a recent trend is to deploy an edge computing infrastructure between IoT healthcare system and cloud computing. This new paradigm termed as Edge-of-Things (EoT) computing, operates closer to the IoT data source and allows computing, storage and service supply to be moved from Cloud to the local edge devices such as Smart phones, Smart gateways or routers and local PCs. These edge devices can offer computing, intelligence and storage capabilities on a smaller scale in real-time. Thus, EoT paradigm enables accurate healthcare service delivery with low response time. It helps to avoid delays and network failures that may interrupt or delay the decision process and healthcare service delivery. However, the successful utilization of edge-of–things computing in a Smart healthcare system is still challenging. There exist several issues that need to be addressed such as novel network architecture and middleware platform for Edge-of-Things in healthcare system considering emerging technologies such as 5G wireless networks, software defined network and semantic computing; edge analytics for healthcare Big data; novel security and privacy methods; social intelligence into the edge node to host healthcare applications; and context-aware service management on the edge with effective quality of service (QoS) support and other issues. This special issue targets a mixed audience of researchers, and practionars from both academia and healthcare industry to share and exchange new ideas, approaches, theories and practice to resolve the challenging issues of utilizing the Edge-of-Things technology for improving the efficiency, sustainability and reliability of smart healthcare systems. Therefore, the suggested topics of interest for this special issue include: - Novel Edgecomputing architecture for Smart healthcare monitoring system - Distributed Deep Learning on Edge devices for Smart healthcare data analysis - Energy-efficient data offloading and computing over Edge for Smart mobile healthcare - Techniques, algorithms and methods of processing smart healthcare data over Edge devices - Cognitive Edge computing for Smart healthcare system - New communications and networking protocols for Edge computing in Smart healthcare system - Programming models and toolkits for supporting Edge Computing for Smart healthcare system - Trust, privacy and security issues in Edge computing for Smart healthcare - Simulation, emulation and testbed support of Smart healthcare systems over Edge computing - Autonomic resource management on Edge devices for Smart healthcare - Mobility and context-aware information processing in edge computing for healthcare applications - Emerging Smart healthcare services and applications over Edge computing
Last updated by Dou Sun in 2017-08-05
Special Issue on Soft Computing Approaches for Sustainable Systems
Submission Date: 2018-03-05

To deal with uncertain and imprecise problems of real world, Sustainable Systems with Soft Computing approaches proved to be successful in multi-criteria control strategies ranging from urban infrastructure ecology to renewable electricity and corporate environmental strategy. Soft computing techniques offer an effective solution for studying and modelling the stochastic behaviour of sustainable systems and their ability to handle imprecise information has been a key factor for their increasing demand. Modern environmental challenges like Depletion of fossil fuels, Global warming, Water scarcity, and Loss of biodiversity can be dealt with intelligently using soft computing techniques with sustainable systems. Integration of soft computing approaches via Artificial Neural Networks, Genetic Algorithms, Cluster Analysis, Fuzzy Logic, Evolutionary Computation, Swarm Intelligence and their applications in sustainable systems helps to solve lots of social concerns. This special issue aims to gather latest research and development achievements in this area and to promote their applications in all important fields with society needs. Topics of interest are: - Multilayer perceptron neural networks (MLP) in sustainable systems - Algorithms for analysis, modelling, simulation and optimization of sustainable systems - Renewable generation technologies - Sustainable design and models for disaster management - Smart grid-connected renewable energy systems - Sustainable systems with Artificial Intelligence (AI) - Human-centred sustainable systems - Adaptive neuro-fuzzy interference systems (ANFIS) - Measurement and instrumentation techniques - Sustainable smart city approaches - Sustainable wireless networks - Geographical load balancing with sustainable systems - Information-intensive sustainable systems - Sustainable transportation technologies - Photo-voltaic (PV) systems and grid-connected PV plants - Sustainable systems for health-care informatics - Soft computing models for sustainable systems
Last updated by Dou Sun in 2017-08-05
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