Journal of the International Measurement Confederation (IMEKO)Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material representing achievements in the field, whose ultimate goal is an enhancement of the state-of-the-art of subjects such as: measurement and metrology fundamentals, measurement science, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures for performance analysis of measurement systems, processes and algorithms, mathematical models for measurement-oriented purposes, and distributed measurement systems in a connected world.

Notes:

    Papers including measurement results that, although important to validate any given scientific study but which offer no new insights in an area different from measurement science or technology, do not fall within the scope of this journal;

    The disciplined usage of well-known metrological terms is strongly required. Authors can access information on all relevant terms such as measurement accuracy, uncertainty, the law of propagation of uncertainty and other, similar terms: these are defined in internationally approved guidelines such as the International Vocabulary of Metrology (VIM) and Guide to the Expression of Uncertainty in Measurement (GUM), which are freely available on https://www.bipm.org/en/publications/guides/;

    The paper must clearly describe the measurement context in which the research was carried out by undertaking a critical review of the state-of-the-art of the relevant body of knowledge in instrumentation and measurement and by showing how the research presented advances it;

    The letter accompanying the submission must describe clearly how the paper satisfies the above requirements.

Papers that focus on image processing or fault diagnosis with little or no elements of measurement science or technology will not be considered within the journal scope.

Authors please note:

The journal Measurement is receiving an increasing number of papers in the area of machine learning/neural networks and other techniques based on artificial intelligence. These submissions will be desk rejected unless they:

    prove that the described research advances the state-of-the-art in measurement science and is not just an application of an available tool to known or novel problems, that is used without an appreciation of measurement-related aspects;

    show that the usage of these tools is put into the correct measurement-related context and not just in the context of machine-learning/neural network applications;

    contain enough information about the used tools, data, and results to allow, in principle, anyone to replicate the described results;

    display the use of specific metrics to strengthen the results of research activities.

It must be recalled that Measurement is interested in publishing new methods, techniques, procedures, algorithms, and alike that show how to better measure in nature and in the world. Thus, the capability to describe metrological-related details of the proposed research represents a major difference between papers published by this journal and by other journals publishing papers on similar topics. This major difference must be evident also in papers covering applications of machine learning and soft computing techniques. Failing to adhere to these guidelines will result in a paper desk-reject decision.

Authors whose manuscripts focus on the research, development and application of the science, engineering and technology of sensors and sensor systems, are welcome to submit to the journal's open access companion title, Measurement: Sensors .

Authors whose manuscripts focus on food and nutrition measurements may also wish to submit to the journal's second open access companion title, Measurement: Food.

Authors whose manuscripts focus on energy sources, heat and power generation and all other relevant fields may be interested to submit to the journal's third open access companion title, Measurement: Energy.

Special Issue on Condition monitoring in non-stationary operations (CMMNO-2024)
Submission Date: 2024-07-31

Condition monitoring is the process of monitoring the health of a machine or system to detect any potential faults or failures and take corrective actions before they cause significant damage. In non-stationary operations, the conditions of the machines or systems are constantly changing, making it more challenging to detect faults and predict failures.

This special issue of Condition monitoring in non-stationary operations (CMMNO) is part of 8th International Conference on Condition Monitoring in Non-Stationary Operations (CMMNO-2024), which will be held in Wenzhou University in Wenzhou, China. Selected papers of the conference will be invited to submit the full-length paper in the SI.

Guest editors:

Prof. Jiawei Xiang (Executive Guest Editor)
Wenzhou University, Wenzhou, China
Email: jwxiang@wzu.edu.cn
Areas of Expertise: Intelligent Condition Monitoring; Finite Element method; Structural Health Monitoring; Boundary element method; Computational mechanics

Prof. Radoslaw Zimroz
Wroclaw University of Science and Technology, Poland
Email: radoslaw.zimroz@pwr.edu.pl
Areas of Expertise: Condition Monitoring; Signal processing; Minning; Non-Stationary operation

Prof. Rajesh Kumar
Sant Longowal Institute of Engineering and Technology, Longowal, India
Email: rajesh_krs@sliet.ac.in
Areas of Expertise: Condition Monitoring, Fault Diagnosis, Vibration Analysis, Signal Processing, Image Processing

Associate Prof. Anil Kumar
Wenzhou University, Wenzhou, China
Email: 20210129@wzu.edu.cn
Areas of Expertise: Condition Monitoring, Fault Diagnosis, Fault Prognosis, Vibration Analysis, Signal Processing

Special issue information:

In addition to the general submission rules, the Invited/Prospective Authors of this SI are required to:

    Extend the technical content of the conference proceedings paper by at least 30%. The technical extension should include new methodology and results, not just a better description of the related work and the corresponding references. A description of the key changes and extension must be reported in the cover letter.
    Add the conference proceedings paper to the references.
    Partially rephrase the common paragraphs of the conference paper to keep the total similarity score below about 25% (excluding references, quotations and acknowledgements) to avoid possible copyright issues, as well as to ensure enough originality. Figures and pictures should be new or at least modified with respect to the conference proceedings paper. If some pictures are verbatim the same as the conference paper, a reference must be reported in the caption.
    The conference proceedings paper must be also uploaded into the journal’s Editorial Manager (EM) system at submission time.

Manuscript submission information:

Tentative Schedule:

Submission Open Date: 1st July 2024
Final Submission Deadline: 31st July 2024

Manuscripts must be submitted via the Measurement online submission system (Editorial Manager®): https://www.editorialmanager.com/meas/default2.aspx. Please select the article type “VSI: CMMNO-2024: Measurement” when submitting your manuscript online.

Please refer to the Guide for Authors to prepare your manuscript: https://www.elsevier.com/journals/measurement/0263-2241/guide-for-authors. 

For any further information, the authors may contact the Guest Editors.

Keywords:

Noise; Vibration; Prognosis; Deep learning; Non-stationary operations

Special Issue on Advanced Measurement, Monitoring, and Sensing Technologies for Smart Urban Mobility
Submission Date: 2024-11-30

As metropolitan areas globally tackle rapid urbanization, smart urban mobility systems become essential for addressing challenges in mobility, sustainability, and efficiency. Urban transportation now encompasses diverse modes, from traditional Mass Rapid Transit (MRT) and Light Rail Transit (LRT) to innovative solutions like electric vehicles (EVs), unmanned aerial vehicles (UAVs), electric buses, and shared mobility options such as e-scooters and bike-sharing programs. These modes are crucial for fulfilling the complex needs of urban areas and fostering sustainable development. At their heart, advanced measurement, monitoring, and sensing technologies are vital for making urban transit systems more efficient, reliable, safer, and eco-friendly. 

Utilizing real-time data alongside advanced analytics, these technologies offer indispensable insights for optimizing and effectively managing urban transit networks. This includes initiatives such as proactive maintenance, operational efficiency enhancements, passenger safety assurance, and significant reductions in environmental footprints. 

This special issue is dedicated to exploring how advanced measurement, monitoring, and sensing technologies are utilized and integrated across various urban transportation modes, ensuring systems are more adaptive, efficient, responsive, and sustainable.

Guest editors:

Dr. Zhenyu Zhao (Executive Guest Editor)
National University of Singapore, Singapore
Email: zhaozy@nus.edu.sg 
Areas of Expertise: Fault detection, advanced condition monitoring, EMC, and reliability of various transit systems (e.g., EV, UAV, MRT/LRT) and their components (e.g., battery, rail, motor); electromagnetic and hardware security; AI-based applications in above fields.

Dr. Hong Li
Beijing Jiaotong University, China
Email: hli@bjtu.edu.cn 
Areas of Expertise: Nonlinear system modeling and applications; EMC, stability analysis, and monitoring for various transportation electrification systems, including battery energy storage systems, motor drive systems, powertrains, electric vehicles, etc.

Dr. Michail Makridis
Zurich University of Applied Sciences, Switzerland
Email: makr@zhaw.ch 
Areas of Expertise: Transport systems engineering, computational intelligence algorithms, data analysis, intelligent transportation systems, experimental campaigns, traffic flow, modeling, and simulation.

Dr. Sina Bahrami
University of Michigan, United States
Email: sinab@umich.edu 
Areas of Expertise: Optimal planning and design of emerging mobility systems and services in smart cities with electric and automated vehicles.

Special issue information:

This special issue includes but not limit to the following topics:

    Advanced Fault Diagnosis Techniques in Transit Systems​
    Advanced Sensing Techniques for Traffic Flow Measurement
    Monitoring and Optimization of Battery State/Health in Transit Systems
    Assessing Electromagnetic Compatibility and Detecting Reliability in Urban Transit
    Innovations in Incident Detection and Management for Urban Mobility
    Efficiency Monitoring in Bike-Sharing and E-Scooter Systems
    Implementation of Smart Sensing Technologies in Urban Transit
    Measurement Techniques in Wireless Power Transfer for Transit Systems

Manuscript submission information:

Tentative Schedule:

    Submission Open Date: 1st June 2024
    Final Submission Deadline: 30th November 2024
    Notification of Acceptance: 31st March 2025

Manuscripts must be invited by the Guest Editors and submitted via the Measurement online submission system (Editorial Manager®):  https://www.editorialmanager.com/meas/default2.aspx. Please select the article type “VSI: Smart Urban Mobility” when submitting your manuscript online.

Please refer to the Guide for Authors to prepare your manuscript: https://www.elsevier.com/journals/measurement/0263-2241/guide-for-authors. 

For any further information, the authors may contact the Guest Editors.

Keywords:

Smart Urban Mobility; Measurement; Monitoring; Sensing.