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Computers & Electrical Engineering
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Solicitud de Artículos
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
Última Actualización Por Dou Sun en 2019-11-24
Special Issues
Special Issue on Sensors and Wearable-based Intelligent Systems
Día de Entrega: 2019-12-24

Overview Sensor-based IoT (Internet of Things) systems and wearable systems have become popular recently due to their portability, effectiveness, easy-of-use interface, and accurate measurements. Modern smart and intelligent environments need advancements in such sensor and wearable-based applications that can not only thrive on the power of sensor-based systems, but also solve daily life problems in the domains of health, education, governance, security, tourism, etc. Thus, it is important to develop intelligent methods and techniques that can use artificial intelligent algorithms to maximize the use of sensors and wearable devices and produce intelligent and smart IoT systems that are beneficial for humans. In the past few decades, automated and intelligent Smart Systems have emerged, opening new research directions that are still evolving due to new challenges and technological advances in the field. The aim of this special section is to bring together academics and industrial practitioners to exchange and discuss the latest innovations and applications of IoT and wearable devices in the domain of artificial intelligent-based systems. The International Conference on Intelligent Technologies and Applications (Bahawalpur – Pakistan Oct, 2019, INTAP-2019, is being organized by Artificial Intelligence Research Group with cooperation of Sir Sadiq Association of Computing and the Islamia University of Bahawalpur, Pakistan. INTAP-2019 focuses mainly on techniques and applications for IoT and wearable-based smart environments. This special section will include a few invited extended versions of the best papers presented at INTAP-2019. Topics The scope of this special sectin is the application of artificial intelligence techniques and algorithms using IoT and wearable devices to designing and solving problems of smart systems in the domain of education, health, agriculture, business, etc. These techniques might include: Wearable IoT systems Implantable IoT systems IoT-based Connected Vehicles IoT-based Smart Supply Chain and Retail Energy Efficient IoT Systems Wireless Positioning and IoT Smart Environments and IoT RFID and Smart Technologies for IoT Machine Learning for IoT
Última Actualización Por Dou Sun en 2019-03-31
Special Issue on Smart City Oriented Cyber-Physical Systems
Día de Entrega: 2019-12-30

With the popularization of information technology and the continuous progress of big data technology, it has been urgent to generate various types of network intelligence and dynamic information collection systems. The Internet of Things (IoT) and computers with powerful functions can simulate urban operation by operating under reasonable safety regulation. However, a series of practical problems should be solved to make breakthroughs and realize sustainable development of a new urban generation. Information technology is widely used for multi-dimensional aggregation in smart cities. By using technologies, such as networking, intelligent sensor placement can be applied in cities for the creation of object-linked information integration. Moreover, the collected information can be integrated with the Internet and other networks based on intelligent analyses. Such systems can implement analyses according to the requirements for intelligent decision support and communication. Practical systems can be established through information technology for public service, public industry, and public management. Also, the service efficiency of the government and the life quality of the public can be improved. A smart city emphasizes high-efficiency information processing ability, information resource integration ability, and management ability to coordinate various activities. Interdisciplinary, multi-level, cross-sectional, and cross-regional cooperation can realize the interconnection and mutual understanding among people, objects, networks and industries. Consequently, new models and new forms of urban development can be realized, which reflect the wisdom of smart cities. As a complex multi-dimensional system, Cyber-Physical System (CPS) is a comprehensive computing, network and physical environment. The information world can be closely integrated with the physical world through the combination of control technology, communication technology and computing technology. With close relation to human life and social progress, IoT has been widely used in various fields such as industrial control, environmental monitoring, intelligent medical, intelligent transportation, intelligence grid, military reconnaissance and aerospace. As a typical application of IoT, intelligent medical systems can provide reliable, safe and real-time medical services in a wired or wireless way. The key information in intelligent transportation system, such as traffic signals, can be monitored in real time. The system analyzes, computes, and publishes a great deal of information, so that real-time road information can be shared by vehicles. By observing and real-time monitoring the system, road managers can release information and guide vehicles to improve urban traffic conditions. High quality and up-to-date technology of CPS and IoT are the target of this special issue. It can be taken as a forum for researchers from different countries to discuss their works and progresses. Particularly, the issue aims to show the latest progress and development in the discovery and exploration of IoT. Both state-of-the-art practical applications and theoretical studies can be submitted. The submitted papers will be peer-reviewed and selected according to their quality and relevance to the special issue. Topics: Topics of interest include the following: - Integration of provenance into Cyber-Physical Systems(CPS) and Internet-of-Things - Internet of Vehicles and Internet of Things - Real-time meanings in different application spaces: energy, transportation, medical and aeronautics - Pervasive and Ubiquitous Technology in IoT - Mining of spatial data in IoT - Multimedia Communications and Visual Signal Processing in IoT - Physical/virtual testbeds for real-time closed-loop control - Robot navigation in IoT - Knowledge reasoning in physical systems - Machine learning and other approaches for real time data analytics - Data-driven urban transportation management
Última Actualización Por Dou Sun en 2019-05-09
Special Issue on Image Processing in Security Applications
Día de Entrega: 2019-12-30

Signal processing research plays an important role in industrial and scientific applications, which has boosted important changes and developments in recent decades. The increased use of Internet, social networks and wireless communication technologies with high quality image streaming, necessitate to secure and protect the transmitted information. One of the main goals of the researcher community is to handle and analyze media data (images or videos) in order to embed or retrieve meaningful information. The necessity to conceal or recover relevant information in images and video have led technological advancements in many domains, such as: face recognition for video surveillance, pattern recognition for monitoring, cryptography to improve information protection, forensics for data verification integrity, people and vehicle tracking, intruder detection and target recognition, among many others. These applications have proven the importance of performing research in this area for continuous innovation. The remarkable number of new emerged methods and the increasing computational power of integrated circuits and personal computers have increased the necessity for more efficient and powerful Image Processing methods for Security, bringing greater challenges to the scientific community. Therefore, researchers are invited to submit outstanding and original unpublished research manuscripts focused on the latest achievements of Image Processing in Security Applications. Topics: The topics of interest are aimed to show continuing efforts provided in the domain of Image Processing for Security applications. The topics of interest include the following: Image/Video Coding and Compression Image/Video Cryptography Watermarking and Steganography Biometric recognition/forensics Tracking systems Security metrics and models Information Forensics and Security Surveillance Image/Video Communications and Networks Image/Video Storage and Retrieval Cybersecurity
Última Actualización Por Dou Sun en 2019-05-18
Special Issue on Internet of Energy - designing and planning energy-efficient smart control systems
Día de Entrega: 2019-12-31

The extensive attention drawn towards development of Internet and shift towards green energy, pioneered the novel concept of Internet of Energy (IoE) by converging the two notions with the aid of Internet of Things (IoT). IoT enables innovative ways to share data, leverage devices, and facilitates remote access. However, problems arise because the infrastructure has not been modernized for implementation. To capitalize on the notion of IoE, physical grids must evolve. The upgrading and automation of electricity infrastructures allow clean energy production with minimal waste. Millions of small renewable energy- generating units are added to the main energy system, in order to achieve maximum efficacy. Increasing demand for a clean energy intensifies the need of transforming the conventional grids. Even though the solution is renewable energy, the radical shift from existing grids leaves us with tremendous technical challenges that require an entirely new way of managing energy systems. In similar fashion, IoE benefits its stakeholders by increasing efficiency, wireless charging, saving money, and reducing waste production. Further, IoE uses sensors to gather data from various equipment to improve the operational performance, subsequently followed by analysis through domain-specific software. The beauty of IoE is that its benefits are not limited to the large manufacturers, but utility providers, domestic producers, and solar-based companies can also benefit from it. Furthermore, IoE also enables the grid infrastructure to improve energy generation and distribution, while facilitating the integration of renewable energy generators. Simultaneously, IoE ensures grid data collection from the beginning to the very last end of the grid. Such aggregated data will empower utility decision making regarding load balancing, forecasting, and pricing. For this special section we are soliciting high quality unpublished manuscripts that present original results. The aim is to bring novel research ideas, highlight the open issues, and indicate current research advancements and future directions in the field of IoE-based smart control systems and energy grids, their architectures and various applications in IoT. Potential topics include: Next generations of IoE-based smart electronic/embedded devices architectures New algorithms and architectures for IoE in the context of IoT New security and privacy models for protecting IoE based infrastructures Semi and full autonomous architectures of embedded devices based on IoE The applications and designing of sustainable environments and smart grids based on IoE IoE and the global demand for clean energy The applications of Artificial Intelligence and Quantum computing in IoE Industrial practices and benchmark suites for IoE Wireless powering of devices over several meters using IoE Migration from traditional electronics to IoE based electronics Designing energy harvesting techniques based on IoE
Última Actualización Por Dou Sun en 2019-07-27
Special Issue on Recent Advancements in Biomedical Engineering
Día de Entrega: 2020-01-15

Computers (hardware and software) play a critical role in different fields of biomedical engineering nowadays. There are many modalities of the data that are obtained through different biomedical systems. These systems normally provide the data in types of signals and images etc. that can be used for diagnosis, evaluation of treatment, surgical planning and so on. With the development of technologies for biomedical systems and advancement of the power of hardware systems, generation and storage of huge medical data has been facilitated. It is evident that processing such data manually is not possible or very time consuming and erroneous. The challenge is now to develop solutions to analyze the data automatically. Another perspective is to use the power of computers in simulation. There are a wide range of applications in the domain of biomedical engineering including bioelectrics, biomechanics and biomaterials for computer simulations of experimental data, or computer modelling of biological events. In order to deal with these challenges, the data analysis paradigms need to be continuously updated by means of new methods and architectures that make it possible to maintain its high degree of applicability in different domains. The aim of this special section is to disseminate the latest advances in different fields of biomedical engineering regarding the new methods, architectures and applications that emerge from the scientific community. It is intended to contain mainly the extended versions of the best papers presented at the 4thInternational Iranian Conference on Biomedical Engineering 2019 (ICBME19, Tehran, Iran, Nov. 2019, Topics: Suggested topics include: - Assistive Technology - Assistive Robotics - Biological Information Processing - Biomedical Signal and Image Processing - Medical Imaging - Medical Data Mining - Body sensor networking - Biological System Modelling - Biomedical Measurement - Bioinformatics - Telemedicine - Neuroengineering - Rehabilitative assessment - Computational Methods for Medical Data Fusion - Biomechanics of Sport - Tissue Engineering - Nanomaterials - Other related topics of bioelectrics, biomechanics and biomaterials that include the application of computers (hardware and software) in biomedical engineering
Última Actualización Por Dou Sun en 2019-10-20
Special Issue on Mobile Intelligence for Sustainable Enterprise Management
Día de Entrega: 2020-01-25

Mobile Intelligence Research focuses on applications of elements of intelligence to different areas, including automatic control, pattern recognition, electronic and mobile commerce, e-finance, e-payment, telecommunications, vision, forecasting, learning, data communication, and wireless optimization. Future e-commerce industry as a whole is experiencing a huge increase in the use of data driven intelligent computing that goes way beyond what we imagined ten years ago. Mobile intelligence is manifested in many different ways, including our abilities to modeling, analysis, integration, monitoring, and management interact with business environment. Mobile data is being collected in different formats, at unprecedented speeds, and from many different sources. There are increasingly complex challenges, with a need to leverage large amounts of heterogeneous data to develop computational intelligence solutions for process optimizations, monitoring, and control applications. Design of the tools imitating human abilities is important task of Mobile Intelligence. such as healthcare and neuroscience, design and art, Internet of Things, computer vision and speech processing, imaging and 3D data, education and learning, climate, economy and finance. This special section focuses on high quality research papers that address significant and Future Mobile Intelligence application and related system development issues in the emerging sustainable wireless applications. It invites high quality research contributions from a wide range of professions, including scholars, researchers, academicians and industry people. Original research papers and state of the art reviews will be accepted. We anticipate that the special section will open new entrance for further research and technology improvements in this important area. Suggested topics include: Mobile enterprise modeling: supervised, unsupervised and reinforcement learning Evolutionary computation, wireless modeling and simulation Development of new technologies for mobile intelligence and large-scale wireless analysis. Uncertainty modeling in big data analytics for mobile intelligence Providing solutions to pressing problems across areas including connected and autonomous vehicles, automation, healthcare, and enterprise security. Bridge developments in Artificial Intelligence to real mobile applications in collaboration with industry partners. New generation of scientists to address the skills shortage in these areas and increase competitiveness Complex systems, multi-agent systems, game theory and statistics
Última Actualización Por Dou Sun en 2019-07-27
Special Issue on Recent Advancements in Big Data Fusion
Día de Entrega: 2020-02-15

Overview The term Data Fusion refers to the process of combining data coming from different sources with the goal of producing a more complete, improved and precise information than that provided by each source separatedly. The Data Fusion paradigm has been growing recently due to factors such as sustained increase in systems connectivity, the advent of the Internet of Things (IoT), and the need for dealing with Big Data. In the current distributed environment, where it is possible to find heterogeneous data sources that generate big amounts of data, the use of Data Fusion techniques has demonstrated to be useful to address diffent tasks in various application domains. Big Data Fusion is strongly linked to current trends such as big data analytics, sensor networks, and the IoT. These are constantly evolving disciplines where new challenges related to data management and explotation arise continuously. In order to deal with these challenges, the Data Fusion paradigm also needs to be continuously updated by means of new methods and architectures that make it possible to mantain its high degree of applicability in different domains. The aim of this special section is to disseminate the latest advances in Big Data Fusion regarding the new methods, architectures and applications that emerge from the scientific community. It is intended to contain mainly the extended versions of the best papers presented at the International Conference on Data Science, E-learning and Information Systems 2019 (Data'19, Dubai, Arab Emirates, Dec. 2019, Topics: Suggested topics include: Big Data Fusion Big Image Fusion Data Fusion in Incomplete or Imprecise Environments Data Fusion in Distributed Environments Data Fusion Algorithms Data Fusion Architectures Data Fusion for Time Series Analysis Data Fusion in the Internet of Things Data Fusion in Data Mining Tasks Data Fusion in Sensors Networks Image Data Fusion Bio-inspired Data Fusion Data Fusion in Environments with Limited Resources Multi-agent Data Fusion Systems Data Fusion Applications: Medicine, Education, Transportation, Economics, Robotics, etc. Mining Big Data Fusion Multimedia Big Data Fusion
Última Actualización Por Dou Sun en 2019-03-31
Special Issue on Application of Artificial Intelligence in Security of Cyber Physical Systems
Día de Entrega: 2020-03-01

The deployment of smart technologies in the communication layer brings new challenges for online monitoring and control of Cyber-Physical Systems (CPS). In addition to the failure of physical infrastructure, CPS is sensitive to cyber attacks on its communication layer. There are many discussions about the role of security-aware design and analysis in the development of modern CPS, such as the smart grid using advanced Artificial Intelligence(AI), and machine learning techniques. Rapid advancement in AI technology enhances the scale, speed, and accuracy of the security in CPS. AI has the potential to be leveraged in different aspects of cyber security, cyber threat detection, and cyber threat intelligence. This special section will focus on the cutting edge, from both academia and industry, with a particular emphasis on novel practical and theoretical solutions for securing critical infrastructure and CPS using AI-based tools, techniques and procedures. The goal is to provide a sampling of recent advances and ideas on progress of research and the practical usage of AI technologies in addressing security of the CPS. Topics of interest include: Applications of intelligent data analytics in CPS Cyber investigation and threat intelligence utilizing AI solutions Applications of blockchain and smart contracts in securing CPS Threat intelligence techniques for cyber-attack detection, and reaction in CPS Application of AI in vulnerability and risk analysis for CPS AI-based security tools, techniques and procedures for the Internet of Things (IoT) Intelligent analysis of different types of data collected from different layers of CPS Intelligent access control and key management for CPS Application of AI in CPS system security and privacy modeling and simulation Intelligent AI-based control strategies to improve CPS performance Design, optimization and data-driven modeling of CPS Novel sensor placement methodologies for CPS AI-assisted digital investigation in CPS Cyber threat hunting and anomaly detection in CPS
Última Actualización Por Dou Sun en 2019-11-12
Special Issue on Artificial Intelligence and Computer Vision
Día de Entrega: 2020-04-15

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 have significantly extended the number of potential applications for computer vision. It has also brought new challenges to the vision community. This is the third special section of Computers and Electrical Engineering on artificial intelligence and computer vision: the first two were published in July 2017 and July 2018, and the next one will be published in January 2020. We expect to have more special sections on this topic 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: Theoretical Foundations of Artificial Intelligence 3D Scene Reconstruction Explainable Deep Learning Pattern Recognition and Machine Vision Computational Imaging Object Tracking Computer Vision Soft Computing Internet of Visual Networks Robotic Vision Intelligent Medical Imaging and Processing Extreme Optical Vision User Experience for Big Multimedia Systems Vision-based Robotic Manipulation Mixed Reality/Augmented Reality for Computer Vision
Última Actualización Por Dou Sun en 2019-10-20
Special Issue on Data Preprocessing for Big Biomedical Data in Deep Learning Models
Día de Entrega: 2020-04-15

Overview Due to numerous biomedical information sensing devices, such as, Photoacoustic Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, Single Photon Emission Computed Tomography (SPECT), Magnetic Resonance (MR) Imaging, Ultrasound, and Positron Emission Tomography (PET), Magnetic Particle Imaging, EE/MEG, Electron Tomography and Atomic Force Microscopy, etc. Large amounts of biomedical information were gathered these years. Many advanced methods are proposed like deep learning due to its excellent performance. However, a lot of issues appear in obtaining and preprocessing such big biomedical data, such as data heterogeneity, data missing, data imbalance and high dimensionality of data etc. Moreover, many biomedical data set simultaneously contain multiple issues. However, most of the current techniques can only deal with homogeneous, complete, and moderate sized-dimensional data, which makes the learning of big biomedical data difficult. Therefore, data processing including data representation learning, dimensionality reduction, missing value imputation should be developed to solve the big gap to make the deep learning methods used for the practical applications. The purpose of this special issue aims to provide a diverse, but complementary, set of contributions to demonstrate new developments and applications that cover existing above issues in data processing of big biomedical data. We would also like to accept successful applications of the new methods, including but not limited to data processing, analysis, and knowledge discovery of big biomedical data. Topics: Suggested topics include: Feature extraction by deep learning or sparse codes for biomedical data Data representation of biomedical data Dimensionality reduction techniques (subspace learning, feature selection, sparse screening, feature screening, feature merging, etc) for biomedical data Information retrieval for biomedical data Kernel-based learning for multi-source biomedical data Incremental learning or online learning for biomedical data. Data fusion for multi-source biomedical data Missing data imputation for multi-source biomedical data Data management and mining in biomedical data Web search and meta-search for biomedical data Web information retrieval for biomedical data Biomedical data quality assessment Transfer learning of biomedical data.
Última Actualización Por Dou Sun en 2019-11-24
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