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RESILIENCE ENGINEERING FOR SMART ENERGY SYSTEMS
CFP - A special issue of Sensors Journal
Over the last few decades, the planning and operation of energy production and energy consumption have been a growing concern globally. Smart energy management is the systematic coordination of the procurement, conversion, transmission, distribution, and use of energy to meet user, environmental, and economic requirements. In this context, the key drivers include resource conservation, climate protection, and cost savings, while the users have permanent and affordable access to the energy they need. Traditionally, smart energy management has been tackled separately in different sectors (e.g., transportation, electricity generation, built environment, industry, agriculture), each with its own specific constraints, requirements, and design solutions. In contrast to these single-sector solutions, smart energy systems adopt a holistic, systemic approach that aims to include, integrate, and coordinate technologies and stakeholders from/within multiple sectors to provide a feasible solution for each sector, as well as for the overall energy system. Smart energy systems are playing an increasingly broad and critical role in many countries to support sustainable development. One requirement of these smart energy systems is that they are resilient to any imposed damage or irregularities and continue to function at the required performance level. Resilience engineering is a holistic systems engineering approach that provides the models and methods to design and analyze systems for resilience.
The aim of this Special Issue is to bring together innovative developments and applications of resilience engineering for smart energy systems. We welcome both research papers addressing new insights and experience papers discussing the lessons learned in practice. Articles may include, but are not limited to, the following topics:
  • Modelling approaches for the resilience of smart energy systems;
  • System architecture design for resilience engineering of smart energy systems;
  • Application of system of systems for resilient smart energy systems;
  • Tools for resilient smart energy systems;
  • Obstacles to resilience of smart energy systems;
  • Methods and process models for resilience engineering of smart energy systems;
  • Empirical evaluation approaches for resilience engineering of smart energy systems;
  • Resilient engineering of smart grids and microgrids;
  • Critical infrastructures and smart energy systems;
  • Cross-sectoral integration of smart energy systems;
  • Workflow patterns for resilient smart energy systems;
  • Business modelling approaches for resilient smart energy systems;
  • Metrics for resilient smart energy systems.
Prof. Dr. Bedir Tekinerdogan Dr. Tarek AlSkaif Dr. William Hurst Prof. Dr. Cagatay Catal Guest Editors
See for submission details:
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Thanks Prof. Bedir Tekinerdoğan for the informative explanations.
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CALL FOR CONTRIBUTIONS
Cyber-Physical Systems in Pandemic Monitoring and Management
Special Issue for the Cyber-Physical Systems Journal
Cyber-Physical Systems in Pandemic Monitoring and Management
This special issue addresses the timely theme of tackling challenges associated with managing infectious diseases.  As witnessed in the outbreaks of many infectious diseases such as SARS and swine flu over the past couple of decades, and more recently another wave of global pandemic, the substantial volume of human traffic from country to country has posed substantial challenges to public health systems.
Utilizing integrated solutions of computation, networked sensors, and physical processes; cyber-physical systems are well-suited as monitoring systems for effective disease-spread simulation analysis that enables health resource management in tackling the current global epidemic as well as any infectious disease outbreaks that may happen in the future.
Given the urgent need for modeling disease transmission behavior in highly infectious risk areas and mitigation strategies under different outbreak circumstances, this special issue invites manuscript submissions in the following topics, but not limited to:
  • Physical processes in air quality control for ventilation enhancement
  • Disease transmission and spread modelling
  • Pandemic data protection and management system architecture
  • Social impact and socio-technology development of CPS in healthcare
  • Data mining and analytics for analyzing public health data
  • Model-based design, validation and implementation of CPS
  • Model driven disease transmission simulation
  • Transportation scenarios in confined spaces (e.g. trains, ships, airplanes)
  • Sensor networks
  • Data Fusion of epidemiological knowledge
  • Ethical and regulatory issues concerning CPS deployment in fighting pandemic
For details please visit:
Important Dates
Paper submission due: October 15, 2020
Notification of decision: December 23, 2020
Revision due: January 15, 2021
Acceptance notification: February 28, 2021
Approximate publication date: Spring 2021, subject to journal publication schedules
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Thank you for this post
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How to analyze the root system architecture of harvested plants? Please discuss the free software and resources and also the most basic methods which can count the lateral branches, root hair etc.
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Please guide me regarding te best free software to analyze root system architecture?
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What is the best software to analyze Root System Architecture (2D) ?
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AMAP Studio will be the right software for you.
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Are there comparisons of the technical capabilities of the different radio technologies and system architectures for Cellular Internet of Things (CIoT) as described in 3GPP TR 45.820/3 GPP 23.720  (e.g. NB-CIoT, NB-LTE) available?
For 3GPP TR 45.820 "Cellular system support for ultra-low complexity and  low throughput Internet of Things (CIoT)" and 3GPP TR 23.720 "Architecture enhancements for Cellular Internet of Things" Release 13 documents  pls. see links to 3GPP attached.
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The radio communications as well as the mobile phones operations are governed by ITU Policies and regulations for each region. You could consult with ITU and/or national ICT regulators to obtain the right frequencies for the availability for the radio and mobile phone devices interoperability and compatibility by hardware or software and both, refer to: http://www4.plala.or.jp/nomrax/ITU_Reg.htm.
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I have always used MATLAB for neural networks design. Can you suggest any other useful software? Which books or papers provide a good reference for different types of neural training algorithms or internal architectures?
Thanks!
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In Poland we use user-friendly Statistica. In this program You can make both an automatical and manual neural network. But I work only in polish version. You can contact with producer: http://www.statsoft.com/ I don't know what is a prace, becouse we have educational version.
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Is there a systematic approach that can do this. We have our system threat model, a set of attack goals, a list of atomic attacks towards the system architecture components: How to link the attacker goals to atomic attacks in a tree structure ? 
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Hi Motti
I have an idea to try manually this relationship, following the Threat Modeling methodology [1][2].
In one side you have the attack path (built by attack tree) in another you have the attacker goals. Due the methodology you can try to connect the attacker goals with the assets mapped, those assets are part of attack tree and are the goal of attacker.
[1] Frank Swiderski, Window Snyder. Threat Modeling. Microsoft Press, 2004.
[2]Adam Shostack. Threat Modeling: designing for security. John Wiley & Sons, Inc, 2014.
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I was searching for a system/architecture that includes a smart meter as well as several smart plugs distributed in the home. In particular interesting would be how such a system integrates smart appliances into the HEMS
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If you are interesting in monitoring the breakers of the power centre (which would be a good option for load >15A) I have used DENT's PowerScout 24 (http://www.dentinstruments.com/power-meter?-md) with is a multi-circuit power meter. I have used DENT's meters to create my AMPds dataset (http://ampds.org) and other datasets.
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I am looking for different CBM open standards to integrate and support interoperability among subsystems.
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There are other architectures that have been constructed to be used in the health monitoring of systems.  Many of these are standards.  However there are some which do not have standards to describe them or only have defence standards and no civil equivalents.
ISO 13374-1
            ISO 13374-1:2003 is the standard which OSA-CBM is based upon.
ISO 13381-1
            ISO 13381-1:2004 provides guidance for the development of prognosis processes. It is intended to allow the users and manufacturers of condition monitoring and diagnostics systems to share common concepts in the fields of machinery fault prognosis; to enable users to determine the necessary data, characteristics and behaviour necessary for accurate prognosis; to outline an appropriate approach to prognosis development; and to introduce prognoses concepts in order to facilitate the development of future systems and training.
ISO 18435-1
            ISO 18435-1:2009 defines an integration modelling method and its use to integrate diagnostics, capability assessment, prognostics and maintenance applications with production and control applications. The integration of other application aspects, such as security, is outside the scope of ISO 18435.
AI-ESTATE
            AI-ESTATE stands for Artificial Intelligence and Expert System Tie to Automatic Test Equipment.  This was an IEEE working group that is now the Diagnostic and Maintenance Control subcommittee within the IEEE SCC20 Committee.   AI-ESTATE is a formal structure for sharing data between diagnostic methods as described by Sheppard et al.  It is hoped that if this can be done without losing contextual information it will make it easier to reuse code between projects.  It should also make it simpler to change diagnostic methods and evaluate which works best with a certain problem.  Some aspects of this are compatible with OSA-CBM.  However OSA-CBM lacks some of the semantic functionality AI-ESTATE needs to work properly.  The concept embodied within AI-ESTATE is a good one which highlights a common problem in embedded software.  Code reuse is crucial to keeping development costs to a minimum but it can be hard to achieve as even aircraft in the same family can be very different to each other.  Providing a method for formatting diagnostic data to make it more straightforward to change diagnostic algorithms is one way of working to that end. 
IEEE 1451.2   
            This is a standard for smart transducer design.  It is not a health management architecture.  It is intended to aid design of networked control and sensor system.  This is intended to make it more straightforward to use sensors and manage their data within a system. This is however a way of making IVHM more affordable.  Designing and manufacturing a sensor to conform to a standard can increase the cost but it also increases the usability of the sensor.  The more sensors conform to this standard it increases the amount of sensors that can be sued for IVHM with less development time.  Removing the requirement to custom develop a sensor for an IVHM project application will decrease the development time and cost.  If a manufacturer were to conform their sensors to this standard it will make it easier for a system integrator to use their parts in their product and create an IVHM solution for the system that includes the component parts.
HUMS
            Health and Usage Monitoring System.  This is a technique pioneered in the North Sea Helicopter fleets. Helicopters have shown themselves to be prone to vibration lead fatigue damage.  After a series of incidents over the North Sea a vibration monitoring system was developed to help protect the workers being ferried back and forth from the oil rigs. There is a UK DEF STAN 00-970 for HUMS which is for military helicopter HUMS.  HUMS are a very similar concept to IVHM but are generally associated in industry with vibration centred monitoring of helicopters.  However HUMS has also been used as a name for more general embedded health monitoring which includes a usage component. 
CAIS
            The Common Airborne Instrumentation System is not health management technique but is intended for use during flight test & evaluation of new aircraft and systems.  It is however worthy of note as it employs many similar methods and systems to those used by IVHM.  
Generic Open Architecture      
GOA is a framework for discussing open systems and for identifying critical components and interfaces.  Space Generic Open Avionics Architecture SGOAA evolved into GOA.  Concept of Logical and Direct interfaces
FOQA
            FOQA is Flight Operations Quality Assurance.  It is a technique used widely within commercial aviation to improve aircraft use and piloting.  This is not an IVHM method but is closely related.  
ARINC 624
ARINC 624 is not an IVHM standard but it describes how an aircraft on board maintenance system should be designed and so it does have some impact on the implementation of an IVHM system.