Author Archive

Advances in Deep and Shallow Machine Learning Approaches for Handling Data Irregularities

1. Summary and Scope Performance of most of the well-known learning systems can considerably degrade if the data to be handled (e.g. the training examples for supervised learning) contain irregularities of various types. By data irregularity, we point to those situations where the distribution of data points, the sampling of data space ...Read More

Deep Learning for Human Activity Recognition

Aims & Scope: Human activity recognition (HAR) can benefit various applications, such as health-care services and smart home applications. Many sensors have been utilized for human activity recognition, such as wearable sensors, smartphones, radio frequency (RF) sensors (WiFi, RFID), LED light sensors, cameras, etc. Owing to the rapid development of wireless sensor ...Read More

Human Visual Saliency and Artificial Neural Attention in Deep Learning

1) Aim and Scope Human visual system can process large amounts of visual information (108-109 bits per second) in parallel. Such astonishing ability is based on the visual attention mechanism which allows human beings to selectively attend to the most informative and characteristic parts of a visual stimulus rather than the whole scene. Modeling ...Read More

Neural-Network-based Optimization and Analysis for Nonlinear Stochastic Systems

Neural networks are widely used learning machines with strong learning ability and adaptability, which have been extensively applied in intelligent control field on parameter optimization, anti-disturbance of random factors, etc., and neural network- based stochastic optimization and control have applications in a broad range of areas. As one of the most important ...Read More

Advanced Methods in Optimization and Machine Learning for Heterogeneous Data Analytics

1. Summary and Scope Recent advances in storage, hardware, information technology, communication, and networking have resulted in a large amount of heterogeneous data. This has powered the demand to extract useful and actionable insights from such data in an automatic, reliable and scalable way. Machine learning, which aims to construct algorithms that ...Read More

Call-for-papers Computational Biostatistics and Biometrics in Internet-of-Medical-Things

In recent decades, there have been increasing utility of computational bio-statistical methods to clinical and health examination. This new generation of research is also known as biometrics or biometry in the Internet-of-Medical-Things (IoMT), and extends to applications such as medical research, epidemiology, clinical and public health science. Biostatistics involves the utility of ...Read More

Machine Learning and Big Data Analytics for IoT Security

The \”Internet of things\” heralds the connections of a nearly countless number of devices to the internet thus promising accessibility, boundless scalability, amplified productivity and a surplus of additional paybacks. The hype surrounding the IoT and its applications is already forcing companies to quickly upgrade their current processes, tools, and technology to ...Read More

New, Modern and Advanced Digital Forensic Techniques

Future Generation Computer Systems The International Journal of eScience, Editor-in-Chief: Peter Sloot Special Issue on New, Modern and Advanced Digital Forensic Techniques A digital forensic operation is a technological inspection, acquisition, and examination of digital media and their contents using forensic equipment and special software tools. The objective is to locate, identify, collect ...Read More

“Internet of People: Human-driven Artificial Intelligence and Internet for Smarter Hyper-Connected Societies”

The rise of wearable/embodied technologies and personal/body area networks has successfully bridged our personal physical and cyber worlds in recent years. Interactions between human users and their personal mobile devices push toward an Internet where the human user becomes more central than ever (evolving from consumers of information to prosumers), and where ...Read More

“Advances in Self Protecting Systems”

Call for paper Effectively protecting computer systems from cyber-attacks is a challenging task due to their large scale and the heterogeneity of the underlying hardware and software components. Furthermore, when trying to defend from an attack, the time factor is critical, and any non-guided human resolution attempt could introduce a significant stress ...Read More