# A Simple Sum of Products Formula to Compute the Reliability of the KooN System

Reliability block diagram (RBD) is a well-known, high-level abstract modeling method for calculating systems reliability. Increasing redundancy is the most important way for increasing Fault-tolerance and reliability of dependable systems. K-out-of-N (KooN) is one of the known redundancy models. The redundancy causes repeated events and increases the complexity of the computing system’s reliability, and researchers use techniques like factorization to overcome it. Current methods lead to the cumbersome formula that needs a lot of simplification to change in the form of Sum of the Products (SoP) in terms of reliabilities of its constituting components. In This paper, a technique for extracting simple formula for calculating the KooN system’s reliability in SoP form using the Venn diagram is presented. Then, the shortcoming of using the Venn diagram that is masking some joints events in the case of a large number of independent components is explained. We proposed the replacement of Lattice instead of Venn diagrams to overcome this weakness. Then, the Lattice of reliabilities that is dual of power set Lattice of components is introduced. Using the basic properties of Lattice of reliabilities and their inclusion relationships, we propose an algorithm for driving a general formula of the KooN system’s reliability in SoP form. The proposed algorithm gives the SoP formula coefficients by computing elements of the main diagonal and elements below it in a squared matrix. The computational and space complexity of the proposed algorithm is θ ((n – k) 2 /2) that n is the number of different components and k denotes the number of functioning components. A lemma and a theorem are defined and proved as a basis of the proposed general formula for computing coefficients of the SoP formula of the KooN system. Computational and space complexity of computing all of the coefficients of reliability formula of KooN system using this formula reduced to $\theta (n-k)$ . The proposed formula is simple and is in the form of SoP, and its computation is less error-prone.

# Reliability in Sensor-Cloud Systems and Applications (SCSA)

IEEE Access invites manuscript submissions in the area of Reliability in Sensor-Cloud Systems and Applications (SCSA).

The sensor-cloud system (SCS) integrates sensors, sensor networks, and cloud for managing sensors, collecting data, and decision-making. The integration provides flexible, low-cost, and reconfigurable platforms for monitoring and controlling the applications, including emerging applications of the Internet of things (IoT), machine to machine, and cyber-physical systems. Though the SCS has received tremendous attention from both academia and industry because of its numerous exciting applications, it suffers from issues with reliability.

The reliability of the SCS is the ability to perform required functions at or below a given failure rate for a given period of time. The required functions are identified as correctly providing measurement results. Sensor data can be faulty due to system faults or security attacks during the sensor data acquisition and collection, and data processing/decision-making on the cloud. There is also the possibility of not receiving the data at all or received data is compromised. Sensor data is also susceptible to errors and interference such as noise. Furthermore, to save sensor resources, end-users are becoming more dependent on cloud processing and decision-making. This enables significant interactions between sensors and between sensors and the cloud. As a result, the required functions can be extended to cover more concerns, including system design and integration, system continuity, real-time responsiveness, data security, and prevention of privacy intrusions, etc. This is why practitioners and engineers must also be able to measure imprecision and true reliability for both the data and the system that deals with the data.  When designing and developing the SCS for real applications, the reliability verification at any level is required.

This Special Section aims to collect and publish state-of-art research results to solve the reliability concerns of sensor-cloud systems.

The topics of interest include, but are not limited to:

• Reliability theory, standardization, modeling, and architecture for SCSA
• Reliability in sensor design and integration in SCSA
• Reliability in communication and networking in SCSA
• Reliability in sensor data privacy processing, computing, and control in SCSA
• Reliability in applying machine learning models and methods for SCSA
• Reliability through data security, privacy, and trust for SCSA
• Reliability concerns in monitoring diverse applications of SCSA
• Reliability through QoS in application monitoring in SCSA
• Reliability issues (e.g., cloud storage, computing, decision-making) in SCSA
• Reliability in fog and edge computing in SCSA
• Reliability assessment, measures, and testbeds for SCSA
• Reliability levels and relations, metrics, and measures for SCSA
• Data quality assurance and quality control in SCSA
• Effective network design and development of SCSA
• Smartphone-based and heterogeneous design of SCSA
• Reliability through fault-tolerance and reliability in SCSA

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.

Associate Editor:  Md Zakirul Alam Bhuiyan, Fordham University, USA

Guest Editors:

1. Arafatur Rahman, University Malaysia Pahang, Malaysia
2. Liu Qin, Hunan University, China
3. Xuyun Zhang, Macquarie University, Australia
4. Taufiq Asyhari, Coventry University, UK

Relevant IEEE Access Special Sections:

IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

# Uncertainty Quantification in Robotic Applications

IEEE Access invites manuscript submissions in the area of Uncertainty Quantification in Robotic Applications.

Uncertainty in engineering systems comes from a variety of sources such as manufacturing imprecision, assembly errors, model variation and stochastic operating conditions. Hence the actual performance of an engineering system may deviate from the design target, resulting in a quality loss, customer dissatisfaction, or even catastrophic failures. To ensure robust and reliable system operations, it is imperative to quantify and reduce the uncertainty effects during the system design, manufacturing and field operation.

For the robotic systems, the dynamic and highly nonlinear performance is significantly affected by operating conditions, time-varying load, and other random stresses. This creates new challenges in measuring and characterizing the performance uncertainty with dynamic performance. Uncertainty quantification methods, such as reliability modeling, reliability analysis, reliability-based design optimization, model validation, sensitivity analysis, and robust design are deemed essential in improving the reliability of robotic systems.

This Special Section in IEEE Access invites academic scholars and industry practitioners to submit full-length articles that report the recent advances in theoretical, numerical, and experimental development in uncertainty quantification. The articles are expected to describe original findings or innovative concepts that address different aspects of uncertainty quantification challenges arising for robotic systems. New uncertainty quantification methods are anticipated to address the safety, reliability and quality issues of emerging robotic technologies, and thus move the robotic industry forward.

The topics of interest include, but are not limited to:

• Reliability modeling, analysis and design optimization of robotic systems
• Model verification and validation of robotic systems
• Sensitivity analysis of robotic systems
• Robust design of robotic systems
• Performance reconstruction under uncertainty of robotic systems
• Big data and machine learning in robotic systems
• Internet of Things for robotic systems under uncertainty

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor:  Zhonglai Wang, University of Electronic Science and Technology of China, China

Guest Editors:

1. Tongdan Jin, Texas State University, USA
2. Om Prakash Yadav, North Dakota State University, USA
3. Ningcong Xiao, University of Electronic Science and Technology of China, China
4. Yi (Leo) Chen, Glasgow Caledonian University, UK

Relevant IEEE Access Special Sections:

IEEE Access Editor-in-Chief:
Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

# Security and Privacy in Emerging Decentralized Communication Environments

IEEE Access invites manuscript submissions in the area of Security and Privacy in Emerging Decentralized Communication Environments.

Modern, decentralized digital communication environments are changing with the availability of new technologies, and the development of new, real-world applications, which lead to novel challenges in security, such as: 5G/6G mobile applications, smart Internet of Things (IoT) devices, big data applications, and cloud systems. Mobile – cloud architecture is emerging as 5G /6G mobile IoT devices are generating large volumes of data, which need cloud infrastructure to process. Many IoT systems and cloud systems are decentralized and Blockchain is emerging in decentralized networks. The increasing interdependence of IT solutions accepted by society has led to a sharp increase in data. As a result, chances of data leakage or privacy infringement also increase, along with the need for new solutions for digital security and privacy protection.

This Special Section in IEEE Access aims to report highlighted security and privacy research in modern, decentralized digital communication environments. The Special Section invites experts and scholars in the fields of digital security, so that readers can keep abreast of the latest developments in the industry, and master the latest security technologies. The Special Section will support industry researchers working with emerging decentralized communication environments to solve real-world security problems. This Special Section will focus on relevant emerging digital security and privacy protection solutions.

The topics of interest include, but are not limited to:

• Security and privacy in 5G /6G mobile / wireless networks
• Security and privacy in the smart mobile Internet of Things
• Security and privacy in Blockchain based decentralized networks
• Security and privacy in 5G vehicular network
• Security and privacy in 5G device to device communications
• Security and privacy for big data in cloud applications

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor:   Xiaochun Cheng, Middlesex University, UK

Guest Editors:

1.   Zheli Liu, Nankai University, China
2.   James Xiaojiang Du, Temple University, USA
3.   Shui Yu,   University of Technology Sydney, Australia
4.  Leonardo Mostarda, Università di Camerino, Italy

Relevant IEEE Access Special Sections:

IEEE Access Editor-in-Chief:
Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

# Artificial Intelligence in CyberSecurity

IEEE Access invites manuscript submissions in the area of Artificial Intelligence in CyberSecurity.

Recent studies show that Artificial Intelligence (AI) has resulted in advances in many scientific and technological fields, i.e., AI-based medicine, AI-based transportation, and AI-based finance. It can be imagined that the era of AI will be coming to us soon. The Internet has become the largest man-made system in human history, which has a great impact on people’s daily life and work. Security is one of the most significant concerns in the development of a sustainable, resilient and prosperous Internet ecosystem. Cyber security faces many challenging issues, such as intrusion detection, privacy protection, proactive defense, anomalous behaviors, advanced threat detection and so on. What’s more, many threat variations emerge and spread continuously. Therefore, AI-assisted, self-adaptable approaches are expected to deal with these security issues. Joint consideration of the interweaving nature between AI and cyber security is a key factor for driving future secure Internet.

The use of AI in cybersecurity creates new frontiers for security research. Specifically, the AI analytic tools, i.e., reinforcement learning, big data, machine learning and game theory, make learning increasingly important for real-time analysis and decision making for quick reactions to security attacks. On the other hand, AI technology itself also brings some security issues that need to be solved. For example, data mining and machine learning create a wealth of privacy issues due to the abundance and accessibility of data. AI-based cyber security has a great impact on different industrial applications if applied in appropriate ways, such as self-driving security, secure vehicular networks, industrial control security, smart grid security, etc. This Special Section in IEEE Access will focus on AI technologies in cybersecurity and related issues. We also welcome research on AI-related theory analysis for security and privacy.

The topics of interest include, but are not limited to:

• Reinforcement learning for cybersecurity
• Machine learning for proactive defense
• Big data analytics for security
• Big data anonymization
• Big data-based hacking incident forecasting
• Big data analytics for secure network management
• AI-based intrusion detection and prevention
• AI approaches to trust and reputation
• AI-based anomalous behavior detection
• AI-based privacy protection
• AI for self-driving security
• AI for IoT security
• AI for industrial control security
• AI for smart grid security
• AI for security in innovative networking
• AI security applications

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor:   Chi-Yuan Chen, National Ilan University, Taiwan

Guest Editors:

1. Wei Quan, Beijing Jiaotong University, China
2. Nan Cheng, University of Toronto, Canada
3. Shui Yu, Deakin University, Australia
4. Jong-Hyouk Lee, Sangmyung University, Republic of Korea
5. Gregorio Martinez Perez, University of Murcia (UMU), Spain
6. Hongke Zhang, Beijing Jiaotong University, China
7. Shiuhpyng Shieh, National Chiao Tung University, Taiwan

Relevant IEEE Access Special Sections:

IEEE Access Editor-in-Chief:
Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

IEEE Access invites manuscript submissions in the area of Additive Manufacturing Security.

Additive Manufacturing (AM), a.k.a. 3D Printing, is a rapidly growing multi-billion dollar industry. This technology is being used to manufacture 3D objects for a broad range of application scenarios such as prototypes in R&D and functional parts in safety critical systems. The benefits of this technology include shorter design-to-product time, just-in-time and on-demand production, and close proximity to assembly lines. Furthermore, AM can produce functional parts with complex internal structures and optimized physical properties with less material waste than subtractive manufacturing.

Due to the numerous technical and economic advantages that this technology promises, AM is expected to become a dominant manufacturing technology in both industrial and home settings. The need to secure physical and cyber-physical systems gives rise to a corresponding need to understand potential attacks via AM systems, and to develop countermeasures that will enable attack prevention, detection, and digital investigation. So far, three major security threat categories have been identified for AM: theft of technical data (or violation of intellectual property, IP), sabotage of AM, and manufacturing of illegal objects. AM Security is a fairly new and highly multi-disciplinary field of research that addresses these threats.

The aim of this Special Section in IEEE Access is to discuss recent advances in AM Security, addressing both offensive and defensive approaches.

The topics of interest include, but are not limited to:

• Compromise of AM systems and environment
• Security threats and attacks in AM context: Theft of technical data (or violation of intellectual property), sabotage of AM, manufacturing of illegal objects
• Technical approaches to detect attacks on/with AM
• Technical approaches to prevent attacks on/with AM
• Digital Investigation and [digital] forensics in the AM context
• Legal aspects of attacks on/with AM
• Economic incentives for AM Security
• Socioeconomic implications of attacks on/with AM
• Comparative analysis of AM vs. CPS/IoT/Industry 4.0/… Securities

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Mark Yampolskiy, Auburn University, USA

Guest Editors:

1. Mohammad Al Faruque, University of California Irvine, USA
2. Raheem Beyah, Georgia Tech, USA
3. William Frazier, Naval Air Systems, USA
4. Wayne King, The Barnes Group Advisors, USA
5. Yuval Elovici, Ben-Gurion University of the Negev, Israel
6. Anthony Skjellum, University of Tennessee at Chattanooga, USA
7. Joshua Lubell, National Institute of Standards and Technology (NIST), USA
8. Celia Paulsen, National Institute of Standards and Technology (NIST), USA

Relevant IEEE Access Special Sections:

IEEE Access Editor-in-Chief:
Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

# Advances in Prognostics and System Health Management

IEEE Access invites manuscript submissions in the area of Advances in Prognostics and System Health Management.

There is a growing interest from industry, government, and academia for prognostics and health management of engineering systems and critical components. Prognostics aim to predict the time when an engineering system or a critical component will no longer perform its intended functionality. Health management is to take a measure to respond to the anticipation of failures and minimize economic loss, and then prevent any unexpected accidents. Thanks to advances of sensor systems, a large amount of direct and indirect health monitoring data may be available. Direct health monitoring data mean that data can be directly used as health indicators to assess the current health condition of engineering systems and critical components. Indirect health monitoring data indicate that some transformations of data should be conducted to construct health indicators for condition assessment of engineering systems and critical components. Thus, signal processing and data mining algorithms are required to preprocess indirect health monitoring data prior to the use of any prognostic algorithms. After preprocessing is conducted, a health indicator is constructed to describe how far the current health condition of engineering systems and critical components deviate from their expected normal health conditions. Once a health indicator is available, prognostic algorithms are developed to extrapolate the current health condition to future health conditions and then predict the remaining useful life.

The goal of this Special Section in IEEE Access is to provide a forum for the latest advances in the area of prognostics and system health management.

The topics of interest include, but are not limited to:

• Smart senor designs for emitting excitations and receiving degradation data
• Signal processing algorithms for reprocessing degradation data
• Extraction of health indicators from engineering systems and critical components
• Abnormal health detection algorithms and statistical control charts
• Data fusion for degradation data
• Deep learning based diagnostic and prognostic algorithms
• Statistical modelling for degradation data
• State space modeling for degradation data
• Uncertainty interpretation, uncertainty quantification, uncertainty propagation and uncertainty management
• Performance evaluation
• Decision Making for degradation data
• Industrial applications and their success in prognostics and health management

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor:

1. Dong Wang, Shanghai Jiao Tong University, China
2. Chuan Li, Chongqing Technology and Business University, China

Guest Editors:

1. Enrico Zio, Foundation Electricite’ de France (EDF) at CentraleSupélec, France
2. José Valente de Oliveira, Universidade do Algarve, Portugal
3. Nishchal K. Verma, Indian Institute of Technology Kanpur, India
5. Michael Pecht, University of Maryland, USA
6. Abhinav Saxena, GE Global Research, USA
7. Chetan S. Kulkarni, NASA Ames Research Center, USA

Relevant IEEE Access Special Sections:

IEEE Access Editor-in-Chief:
Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

# New Developments on Reliable Control and Filtering of Complex Nonlinear Systems

IEEE Access invites manuscript submissions in the area of New Developments on Reliable Control and Filtering of Complex Nonlinear Systems.

During the past three decades, the problems of reliable control and filtering have attracted considerable attention due to the growing demands for system safety, reliability, maintainability, and survivability. The main aim of reliable control and filtering is to design a suitable controller and filter with guaranteed stability and performance, respectively, not only when all the system components are in operation, but also in the situation when some component failures occur. To guarantee a higher reliability level and better control performance, reliable control systems depending on various control strategies have been concerned to achieve these critical requirements, i.e., the pole region assignment method, coprime factorization method, the algebraic Riccati equation (ARE)-based method, the Hamilton-Jacobi inequality (HJI)-based method, and linear matrix inequality (LMI)-based method, for example. Although many researchers have investigated the reliable control/state estimation problems for linear systems with different scenarios for many years, the topic of reliable control/filtering in complex nonlinear systems is still in the early stage of development and many critical issues remain to be further investigated.

The primary objective of this Special Section in IEEE Access is to provide up-to-date research on technical innovations and theoretical advancement in system analysis and reliable controller/filter design of complex nonlinear systems. Of particular interest, the articles in this Special Section are devoted to the modeling of complex nonlinear systems, the development of advanced communication technology used in nonlinear systems, distributed reliable control/state estimation, fault detection and isolation, fault-tolerant control of nonlinear systems, and their applications in industrial process systems. The contributions to this Special Section are expected to provide the latest results in advanced analysis, optimization, reliable control/filtering and real applications for nonlinear dynamical systems.

The topics of interest include, but are not limited to:

• Mathematical modeling of complex nonlinear systems
• The characterizations of the system failures/faults
• Co-design of reliable control systems
• Reliable control/state estimation schemes of nonlinear systems with guaranteed performance
• Distributed reliable control/state estimation for networked nonlinear systems
• Advanced fault detection and diagnosis and fault-tolerant control schemes for nonlinear systems
• Resiliency, robustness and reliability analysis in practical engineering systems
• Reliable control/state estimation of stochastic nonlinear systems and their industrial applications

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Jianbin Qiu, Harbin Institute of  Technology, China

Guest Editors:

1.  Yanling Wei, Technical University of Berlin, Germany
2. Ye-Hwa Chen, Georgia Institute of Technology, USA
3. Hak-Keung Lam, King’s College London, UK
4. Hamid Reza Karimi, Politecnico di Milano, Italy

Relevant IEEE Access Special Sections:

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access