Announcements

We are pleased to announce that the website of the MDPI Sustainability Foundation has been revamped! For the past couple of months, our UX UI team and front-end developers have been working hard to launch the website in time for the opening of the Sustainability Awards nominations.

The website is not the only thing that has had a remodeling. Indeed, the format of the Emerging Sustainability Leader Award (ESLA) has been updated. ESLA is now a competition open to individual researchers or start-ups founded by researchers under the age of 35. Nominee applications will go through 2 rounds of selection until the final 3 are decided. The finalists will then be invited to give pitch presentations during the Award Ceremony to win either first place (10,000 USD) or runner-up (2 x 5000 USD).

The World Sustainability Award, on the other hand, remains the same: a total prize money of 100,000 USD is up for grabs by senior individual researchers or groups of researchers from the international research community.

Nominations for both the World Sustainability Award and the Emerging Sustainability Leader award are now open! Check out our new website for more information on how to nominate.

Conference: The 13th China Satellite Navigation Conference
Date: 16–18 November 2022
Place: Beijing, China

Sensors (ISSN: 1424-8220) will be attending the 13th China Satellite Navigation Conference as an exhibitor. This meeting will take place from 16 to 18 November in Beijing, China.

The China Satellite Navigation Conference (CSNC) is an open academic exchange platform. It aims to strengthen academic innovation and promote the cooperation and exchange of satellite navigation systems, strengthen technological innovation and promote the engineering construction of satellite navigation systems, strengthen theoretical innovation and promote the progress of satellite navigation theories, and strengthen application innovation and promote the scientific development of satellite navigation industry. The conference has been successfully held for 12 years and has produced a large number of excellent results in academic, technical, theoretical, application, and talent aspects.

The following MDPI journals will be represented:

• Sensors;
• Remote Sensing;
• Atmosphere;
• Aerospace;
• Technologies;
• Drones;
• Signals;
• Smart Cities;
• AI;
• Geomatics.

If you are planning to attend this conference, please do not hesitate to start an online conversation with us (booth #B18). Our delegates look forward to meeting you in person and answering any questions that you may have. For more information about the conference and virtual booth, please visit the following website: https://www.beidou.org/annualmeeting.html.

1. “Comparison of Time Delay Estimation Methods Used for Fast Pipeline Leak Localization in High-Noise Environment”
by Kousiopoulos, G.-P.; Papastavrou, G.-N.; Kampelopoulos, D.; Karagiorgos, N. and Nikolaidis, S.
Technologies 2020, 8(2), 27; https://doi.org/10.3390/technologies8020027
Available online: https://www.mdpi.com/2227-7080/8/2/27

Highlights:

• An acoustic method is described for pipeline leak localization;
• Cross-Correlation and Generalized Cross-Correlation techniques are used;
• Accelerometer sensors are used;
• The paper studies the relationship between the measurement duration and execution time of the method;
• The authors develop a statistical algorithm to deal with the stochastic (non-deterministic) nature of leak signals.

2. “Analog Realization of Fractional-Order Skin-Electrode Model for Tetrapolar Bio-Impedance Measurements”
by Alimisis, V.; Dimas, C.; Pappas, G. and Sotiriadis, P. P.
Technologies 2020, 8(4), 61; https://doi.org/10.3390/technologies8040061
Available online: https://www.mdpi.com/2227-7080/8/4/61

Highlights:

• Cole models are employed for the electrode and skin cells;
• Inverse Follow the Leader Feedback (IFLF) is employed and a custom versatile topology proposed;
• Bio-impedance behaviors up to 10 kHz are captured;
• A tunable active integrated circuitry block (90 nm technology) is built to emulate the tetrapolar bio-impedance measurement setup.

3. “The Influence of Smart Manufacturing towards Energy Conservation: A Review”
by Terry, S.; Lu, H.; Fidan, I.; Zhang, Y.; Tantawi, K.; Guo, T. and Asiabanpour, B.
Technologies 2020, 8(2), 31; https://doi.org/10.3390/technologies8020031
Available online: https://www.mdpi.com/2227-7080/8/2/31

Highlights:

• Smart Manufacturing combines multiple technologies, including Cyber-Physical Systems, Internet of Things, Robotics/Automation, Big Data Analytics, and Cloud Computing;
• Today's products made using Smart Manufacturing Technologies require 50% to 75% less energy than large-scale manufactured goods;
• Digital thread/twin technology provides manufacturers with the information needed to form intelligent solutions to reduce energy use.

4. “ExerTrack—Towards Smart Surfaces to Track Exercises”
by Fu, B.; Jarms, L.; Kirchbuchner, F. and Kuijper, A.
Technologies 2020, 8(1), 17; https://doi.org/10.3390/technologies8010017
Available online: https://www.mdpi.com/2227-7080/8/1/17

Highlights:

• The paper proposes embedded capacitive proximity sensing integrated into a fitness mat to track and monitor exercise, which successfully recognize up to eight different whole-body workout exercises;
• An evaluation study involving nine participants is conducted as a proof-of-concept. Data augmentation methods are introduced that can increase data diversity and broader generalizability for human-activity recognition in quantified-self exercises, and the authors further justify the model architecture and training strategy for reproducibility.

5. “Design, Construction and Tests of a Low-Cost Myoelectric Thumb”
by Ayvali, M.; Wickenkamp, I. and Ehrmann, A.
Technologies 2021, 9(3), 63; https://doi.org/10.3390/technologies9030063
Available online: https://www.mdpi.com/2227-7080/9/3/63

Highlights:

• The authors develop a low-cost myoelectric thumb;
• Freely available 3D printing models and software can serve as a basis for further research;
• By implementing feedback, the myoelectric thumb can be used as a low-cost prosthesis.

6. “Investigation of Methods to Extract Fetal Electrocardiogram from the Mother’s Abdominal Signal in Practical Scenarios”
by Sarafan, S.; Le, T.; Naderi, A. M.; Nguyen, Q.-D.; Kuo, B. T.-Y.; Ghirmai, T.; Han, H.-D.; Lau, M. P. H. and Cao, H.
Technologies 2020, 8(2), 33; https://doi.org/10.3390/technologies8020033
Available online: https://www.mdpi.com/2227-7080/8/2/33 

Highlights:

• Various methods, including the Extended Kalman Filter (EKF), template subtraction (TS), independent component analysis (ICA), and their combinations, are rigorously investigated using data from the PhysioNet 2013 Challenge;
• Data with added Gaussian and motion noise, which mimic a practical scenario, are utilized to examine the performance of different algorithms;
• Different algorithm combinations are proposed and tested, yielding promising results;
• A comprehensive performance metric, including the F1 score, computational complexity (i.e., execution time and allocated memories), and noise robustness, is used to assess performance.

We are pleased to welcome our new Editorial Board Members, Prof. Dr. Yinghui Zhang (Xi'an University of Posts and Telecommunications) and Dr. Francesco Aggogeri (University of Brescia). We look forward to their contributions to the journal.

Peer Review Week began 19 September 2022 under the theme of “Research Integrity: Creating and Supporting Trust in Research”. Through various blog articles, podcast, and webinar, we discussed this crucial subject throughout the week, celebrating the essential role peer review plays in maintaining research quality.

To begin, we held a Webinar on the topic. Professor Peter W. Choate and Dr. Emmanuel Obeng-Gyasi joined Dr. Ioana Craciun, one of MDPI’s scientific officers, for an in-depth discussion.

We invite you to view the event recording:

During the week, the MDPI Blog in a series articles highlighted how good Peer Review safeguards research integrity. The following topics were covered:

• Peer Review Week 2022
• Research Integrity
• What We’ve Learned About Peer Review Reports
• 4 Steps to the Perfect Peer Review Report
• How to Write the Perfect Peer Review Report: An Interview
• Inviting Great Peer Reviewers

In a new edition of Insight Faster, an MDPI podcast, we were delighted to talk to the co-chairs of the Peer Review Week committee, Jayashree Rajagopalan (Senior Manager of Global Community Engagement for CACTUS) and Danielle Padula (Head of Marketing and Community Development at Scholastica) to get their take on this year’s event and its related topics.

You can find the Podcast here.

We hope you enjoy the contents!

We are pleased to announce that Prof. Dr. Bernard Gil has been appointed Editor-in-Chief of the Section “Quantum Technologies” in Technologies (ISSN: 2227-7080).

Prof. Dr. Bernard Gil has been a researcher at the CNRS (National Center of Scientific Research) since 1982. He is currently the Director of Research of Exceptional Class at the Institute of Physics (INP). He is an experimentalist and an expert in the measurement of the coupling between the electromagnetic field and the electronic states of solids. He has been studying in-depth the optical properties of semiconductors since 1994, with some specific interest in nitride semiconductors for compact-solid state lighting and energy savings linked to the utilization of this technology. He is currently very much interested in quantum technologies and in the emission of light in the deep ultraviolet range for the eradication of pathogens using as an active material boron nitride grown under different polytypes. Gil was awarded Doctor Honoris Causa of the University Saint Petersburg in 2012, and Doctor Honoris Causa of the Meijo University of Nagoya in 2013. He is the 2018 laureate of the Welker Award. His Google Scholar citation records indicate 14,000 citations, with a Hirsch factor of 60.

Keywords: wide gap semiconductors; quantum technologies; photonics; solid-state lighting

The following is a short Q&A with Prof. Dr. Bernard Gil, who shared his vision for the journal with us, as well as his views of the research area and open access publishing:

1. What appealed to you about the journal that made you want to take the role as its Section Editor-in-Chief?
I progressively moved from the optical properties of bulk materials to those of their quantum heterostructures to finally focus on their applications for quantum technologies.

2. What is your vision for the journal?
From my own experience the journal should frame all aspects of quantum technologies. I wrote this before:

Quantum technologies (QTs) consist of a vast melting pot of different disciplinary fields running from basic science domains such as mathematics, physics, chemistry, and biology, all of which are considered at a broad scale and thus more than often overlapping, combined with different technical approaches. The latter are of paramount importance in order to fabricate for these scientists, the objects for measuring and understanding what happens, sometimes at a sub-atomic level, for further controlling it and to transfer for realizing quantum devices with ad hoc designs that generally operate according to the prescriptions of quantum mechanics. Advantages can be taken of the predictions of its early days, but obviously of course of much more recently discovered effects. The building of a quantum computer, the race to the use of QTs in the field of cryptography have long been putting QTs under the lime-lights. Today’s race to find out how quantum simulators or quantum sensors can be used to solve non-quantum problems, to improve, for instance, the performance of brain scanners and for creating systems paving our ways toward better diagnosing medical conditions are typical examples required to illustrate the broad scale applicability of QTs when integrated into already existing systems. Thus, scientists of the fundamental science domains contribute on the same footing as engineers do, and economic challenges significantly generate some tropisms of developments of QTs in specific and eclectic directions, which at the end of the day form the quantum technology industry. The global challenges motivate us to open the possibility of submitting predicting ideas, including having in mind how the use QTs can be applicated in the areas of energy savings and sustainability. A substantial amount of funding is dedicated worldwide by the governing institutions for actively funding QTs.

The story begins at the stage of the growth and processing of sub-nanosized and nanosized and other materials of controlled purities such as semiconductors, metals, or any other molecular objects extensively used in the modern industry. QTs are multidisciplinary: they associate pertinent partners of different areas in networks susceptible to conceiving and fabricating a specific quantum sensor, quantum devices. It generally requires intense and profitable intergroup cross-talking exchanges before such quantum device or sensor comes to birth. Aside from simple scientific curiosity, economic motivations largely influence the development of QTs. This specific review is offered as an important forum for offering people of different areas for publishing their innovative discoveries in the multidisciplinary area of QTs. Both extended reviews and regular articles can be accepted for publication after peer-reviewing.

3. What does the future of this field of research look like?
Multidisciplinary.

4. What do you think of the development of Open Access in the publishing field?
I am not sure that my institution CNRS is in favor of that; I am even sure it is reluctant to the concept of paying a lot of money for papers being published even after being refereed. This also holds for Nature and Science. Therefore, I cannot be explicitly polled for this.

We wish Prof. Dr. Gil every success in his new position, and we look forward to his contributions to the journal.

1. “A Survey on Contrastive Self-Supervised Learning”
by Jaiswal, A.; Babu, A. R.; Zadeh, M. Z.; Banerjee, D. and Makedon, F.
Technologies 2021, 9(1), 2; https://doi.org/10.3390/technologies9010002
Available online: https://www.mdpi.com/2227-7080/9/1/2

Highlights:

• Exploration and detailed analysis of the existing state-of-the-art techniques in contrastive learning;
• Extensive evaluation of contrastive learning in various domains such as computer vision (Images, Videos), Natural Language Processing, etc., with state-of-the-art results in multiple datasets;
• Future direction of contrastive learning.

2. “Unsupervised Domain Adaptation in Semantic Segmentation: A Review”
by Toldo, M.; Maracani, A.; Michieli, U. and Zanuttigh, P.
Technologies 2020, 8(2), 35; https://doi.org/10.3390/technologies8020035
Available online: https://www.mdpi.com/2227-7080/8/2/35

Highlights:

• Gives a comprehensive overview of recent advancements in Unsupervised Domain Adaptation of deep networks for Semantic Segmentation;
• Identifies 3 main representation levels at which domain adaptation can be applied, i.e., at the input, at the intermediate feature representation or at the output of the deep network;
• Categorizes the vast range of UDA techniques into 7 groups: Domain Adversarial Learning, Generative-based Adaptation, Classifier Discrepancy, Self-Training, Entropy Minimization, Curriculum Learning and Multi-Task Learning;
• Presents the widely used case study of synthetic-to-real adaptation for the semantic understanding of road scenes;
• Provides an extensive comparison of state-of-the-art approaches on multiple benchmarks and with different segmentation models.

3. “The Road to Improved Fiber-Reinforced 3D Printing Technology”
by Kabir, S. M. F.; Mathur, K. and Seyam, A.-F. M.
Technologies 2020, 8(4), 51; https://doi.org/10.3390/technologies8040051
Available online: https://www.mdpi.com/2227-7080/8/4/51

Highlights:

• Evaluates scopes and capabilities of commercial 3D printing technology to develop fiber-reinforced composites from material (filaments) and technology (slicer) perspectives;
• Unveils detailed properties of commercial 3D printing filaments (fiber and polymer) used for printing fiber-reinforced composites;
• Demonstrates and illustrates the routes to avail high performance printed composites as well as potential avenues of improvement of the printing technology.

4. “Hardware Implementation of a Softmax-Like Function for Deep Learning”
by Kouretas, I. and Paliouras, V.
Technologies 2020, 8(3), 46; https://doi.org/10.3390/technologies8030046
Available online: https://www.mdpi.com/2227-7080/8/3/46

Highlights:

• Proposes a simplified architecture for a softmax-like function, the hardware implementation of which is based on a proposed approximation that exploits the statistical structure of the vectors processed by the softmax layers in various CNNs;
• The proposed architecture is parametrized taking into account the requirements of the targeted application;
• The proposed architecture is efficiently implemented in hardware.

5. “A Parametric EIT System Spice Simulation with Phantom Equivalent Circuits”
by Dimas, C.; Uzunoglu, N. and Sotiriadis, P. P.
Technologies 2020, 8(1), 13; https://doi.org/10.3390/technologies8010013
Available online: https://www.mdpi.com/2227-7080/8/1/13

Highlights:

• Parametric Simulation interface for an Electrical Impedance Tomography Hardware System;
• SPICE and MATLAB software are utilized to simulate the system's analog and digital parts;
• The Phantom Subject Under Test (SUT) is simulated as a frequency-dependent multiport RLC circuitry;
• Sources of measurement errors are examined.

Conference: The 10th International Conference on Smart Systems Engineering (SmaSys) 2022-Beyond Material Innovation (SMASYS2022)
Date: 6–7 October 2022
Organized by: Yamagata University, Yamagata, Japan

The International Conference on Smart Systems Engineering (SmaSys) is a series of successful conferences, starting with the first conference (SmaSys2013) held in 2013, which are organized to promote discussion on “smart systems engineering” between young, active, and motivated scientists. SmaSys covers a wide range of subjects on smart materials, devices, systems, and related research. It is an invaluable opportunity to share and exchange opinions and knowledge around various fields.

Due to the COVID-19 epidemic, SmaSys2022 will be convened as a fully online conference. COVID-19 is having a significant impact on our daily life, but various positive changes are also happening rapidly. Science, engineering, and smart systems are vital for these changes. Any new insights and networks contributing to the progress in these fields at SmaSys2022 will be greatly appreciated.

The organizing committee, including iFlex students, promises an attractive program, and we look forward to your attendance at SmaSys2022. Your contribution will have a remarkable impact on the conference.

For more information about the conference, please visit the following link: http://yzyu.sakura.ne.jp/smasys.yz.yamagata-u.ac.jp/2022_1/.

1. “A Survey on Contrastive Self-Supervised Learning”
by Jaiswal, A.; Babu, A. R.; Zadeh, M. Z.; Banerjee, D.; Makedon, F.
Technologies 2021, 9(1), 2; https://doi.org/10.3390/technologies9010002
Available online: https://www.mdpi.com/2227-7080/9/1/2

2. “Review of Battery Management Systems (BMS) Development and Industrial Standards”
by Gabbar, H. A.; Othman, A. M.; Abdussami, M. R.
Technologies 2021, 9(2), 28; https://doi.org/10.3390/technologies9020028
Available online: https://www.mdpi.com/2227-7080/9/2/28

3. “A Survey of Robots in Healthcare”
by Kyrarini, M.; Lygerakis, F.; Rajavenkatanarayanan, A.; Sevastopoulos, C.; Nambiappan, H. R.; Chaitanya, K. K.; Babu, A. R.; Mathew, J.; Makedon, F.
Technologies 2021, 9(1), 8; https://doi.org/10.3390/technologies9010008
Available online: https://www.mdpi.com/2227-7080/9/1/8

4. “Effect of Data Scaling Methods on Machine Learning Algorithms and Model Performance”
by Ahsan, M. M.; Mahmud, M. A. P.; Saha, P. K.; Gupta, K. D.; Siddique, Z.
Technologies 2021, 9(3), 52; https://doi.org/10.3390/technologies9030052
Available online: https://www.mdpi.com/2227-7080/9/3/52

5. “A Review of Extended Reality (XR) Technologies for Manufacturing Training”
by Doolani, S.; Wessels, C.; Kanal, V.; Sevastopoulos, C.; Jaiswal, A.; Nambiappan, H.; Makedon, F. Technologies 2020, 8(4), 77; https://doi.org/10.3390/technologies8040077
Available online: https://www.mdpi.com/2227-7080/8/4/77

6. “The Road to Improved Fiber-Reinforced 3D Printing Technology”
by Kabir, S. M. F.; Mathur, K.; Seyam, A. -F. M.
Technologies 2020, 8(4), 51; https://doi.org/10.3390/technologies8040051
Available online: https://www.mdpi.com/2227-7080/8/4/51

7. “Review on the Evaluation of the Impacts of Wastewater Disposal in Hydraulic Fracturing Industry in the United States”
by Yazdan, M. M. S.; Ahad, M. T.; Jahan, I.; Mazumder, M.
Technologies 2020, 8(4), 67; https://doi.org/10.3390/technologies8040067
Available online: https://www.mdpi.com/2227-7080/8/4/67

8. “Augmented Reality in Industry 4.0 and Future Innovation Programs”
by Santi, G. M.; Ceruti, A.; Liverani, A.; Osti, F.
Technologies 2021, 9(2), 33; https://doi.org/10.3390/technologies9020033
Available online: https://www.mdpi.com/2227-7080/9/2/33

9. “Wire Tool Electrode Behavior and Wear under Discharge Pulses”
by Grigoriev, S. N.; Volosova, M. A.; Okunkova, A. A.; Fedorov, S. V.; Hamdy, K.; Podrabinnik, P. A.; Pivkin, P. M.; Kozochkin, M. P.; Porvatov, A. N.
Technologies 2020, 8(3), 49; https://doi.org/10.3390/technologies8030049
Available online: https://www.mdpi.com/2227-7080/8/3/49

10. “Post-Processing of 3D-Printed Polymers”
by Dizon, J. R. C.; Gache, C. C. L.; Cascolan, H. M. S.; Cancino, L. T.; Advincula, R. C.
Technologies 2021, 9(3), 61; https://doi.org/10.3390/technologies9030061
Available online: https://www.mdpi.com/2227-7080/9/3/61

11. “Hardware Implementation of a Softmax-Like Function for Deep Learning †”
by Kouretas, I.; Paliouras, V.
Technologies 2020, 8(3), 46; https://doi.org/10.3390/technologies8030046
Available online: https://www.mdpi.com/2227-7080/9/3/61

12. “Engineering Tests to Evaluate the Feasibility of an Emerging Solar Pavement Technology for Public Roads and Highways”
by A. Coutu, R., Jr.; Newman, D.; Munna, M.; Tschida, J. H.; Brusaw, S.
Technologies 2020, 8(1), 9; https://doi.org/10.3390/technologies8010009
Available online: https://www.mdpi.com/2227-7080/8/1/9

13. “Influence of WC-Based Pin Tool Profile on Microstructure and Mechanical Properties of AA1100 FSW Welds”
by Tamadon, A.; Baghestani, A.; Bajgholi, M. E.
Technologies 2020, 8(2), 34; https://doi.org/10.3390/technologies8020034
Available online: https://www.mdpi.com/2227-7080/8/2/34

14. “An Investigation into the Application of Deep Learning in the Detection and Mitigation of DDOS Attack on SDN Controllers”
by Gadze, J. D.; Bamfo-Asante, A. A.; Agyemang, J. O.; Nunoo-Mensah, H.; Opare, K. A. -B.
Technologies 2021, 9(1), 14; https://doi.org/10.3390/technologies9010014
Available online: https://www.mdpi.com/2227-7080/8/2/34

15. “A Parametric EIT System Spice Simulation with Phantom Equivalent Circuits”
by Dimas, C.; Uzunoglu, N.; Sotiriadis, P. P.
Technologies 2020, 8(1), 13; https://doi.org/10.3390/technologies8010013
Available online: https://www.mdpi.com/2227-7080/8/1/13

16. “Perceived Usefulness, Satisfaction, Ease of Use and Potential of a Virtual Companion to Support the Care Provision for Older Adults”
by Jegundo, A. L.; Dantas, C.; Quintas, J.; Dutra, J.; Almeida, A. L.; Caravau, H.; Rosa, A. F.; Martins, A. I.; Pacheco Rocha, N.
Technologies 2020, 8(3), 42; https://doi.org/10.3390/technologies8030042
Available online: https://www.mdpi.com/2227-7080/8/3/42

17. “Comparison of iPad Pro®’s LiDAR and TrueDepth Capabilities with an Industrial 3D Scanning Solution”
by Vogt, M.; Rips, A.; Emmelmann, C.
Technologies 2021, 9(2), 25; https://doi.org/10.3390/technologies9020025
Available online: https://www.mdpi.com/2227-7080/9/2/25

18. “Deep Learning Based Fall Detection Algorithms for Embedded Systems, Smartwatches, and IoT Devices Using Accelerometers”
by Kraft, D.; Srinivasan, K.; Bieber, G.
Technologies 2020, 8(4), 72; https://doi.org/10.3390/technologies8040072
Available online: https://www.mdpi.com/2227-7080/8/4/72

19. “Electrical Discharge Machining Non-Conductive Ceramics: Combination of Materials”
by Volosova, M. A.; Okunkova, A. A.; Fedorov, S. V.; Hamdy, K.; Mikhailova, M. A.
Technologies 2020, 8(2), 32; https://doi.org/10.3390/technologies8020032
Available online: https://www.mdpi.com/2227-7080/8/2/32

20. “Unsupervised Domain Adaptation in Semantic Segmentation: A Review”
by Toldo, M.; Maracani, A.; Michieli, U.; Zanuttigh, P.
Technologies 2020, 8(2), 35; https://doi.org/10.3390/technologies8020035
Available online: https://www.mdpi.com/2227-7080/8/2/35