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Application of Sensors in Transportation in the Context of Logistics 4.0 and Industry 4.0 (Closed)

A topical collection in Sensors (ISSN 1424-8220). This collection belongs to the section "Intelligent Sensors".

Viewed by 56654

Editors

Associate Professor, Faculty of Economics, Koszalin University of Technology, 75-453 Koszalin, Poland
Interests: transport systems; logistics; city logistics; sustainable mobility; electromobility; smart cities; recycling
Special Issues, Collections and Topics in MDPI journals

Topical Collection Information

Dear Colleagues,

Logistics and transport are joint areas of interest where Industry 4.0 is concerned. Logistics would mean very little without transportation processes which take place in every facility, no matter whether it is a logistics facility, factory or any other. Industry 4.0 creates many new opportunities in all of the aforementioned areas, but at the same time, it brings several challenges. It is expected that new skills will be developed in human work, but also in the equipment and devices used to operate the production, logistics, and transport systems. It is certain as well that the development of Industry 4.0, based on digitization and automation represented for logistics, production, and transportation, will provide not only huge challenges but also opportunities for increasing efficiency. It is also worth mentioning that the similarity of logistics and production processes blurs the differences between Logistics 4.0 and Factory 4.0 and, consequently, also Industry 4.0. The objectives of papers will be to present solutions of a technical nature, especially applications of sensors, as opposed to many items in which purely economics, management, and theoretical aspects of Industry 4.0 are presented. Additionally, it will identify and provide current and future research issues, especially regarding the fact that the future of Industry 4.0 is far away of being foreordained. We invite researchers in the global logistics, production, and transportation community to contribute original research papers, as well as review articles and empirical studies, which will stimulate debate in the topic.

Dr. Mariusz Kostrzewski
Dr. Norbert Chamier-Gliszczyński 
Collection Editors

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Keywords

  • 3D printing
  • Advanced robotics
  • Artificial Intelligence (AI)
  • Augmented Reality for Logistics
  • Augmented Reality for production
  • Augmented Reality for transportation
  • Big data
  • Cloud computing
  • Cloud-based data analytics and sensors
  • Cognitive computing
  • Collaborative robot for logistics
  • Collaborative robot for production
  • Cyberphysical production system (CPPS)
  • Cybersecurity
  • Edge computing
  • Embedded system
  • Factory 4.0
  • Industrial Big Data applications for logistics
  • Industrial Big Data applications for production
  • Industrial Big Data applications for transportation
  • Industrial Internet of Things (IIoT)
  • Interconnected intelligent logistics
  • Interconnected intelligent production
  • Interconnected intelligent transportation
  • Machine learning
  • Machine-to-machine (M2M)
  • Manufacturing execution system (MES)
  • Mobile technologies
  • Multiagent systems
  • OSI model (open systems interconnection model)
  • Production control and logistics
  • Reference architecture model Industry 4.0 (RAMI 4.0)
  • RFID technology
  • Scheduling and optimization of logistics systems
  • Scheduling and optimization of production systems
  • Scheduling and optimization of transportation systems
  • Smart cyberphysical systems (SCPS)
  • Smart factory
  • Vertical integration
  • Virtual Reality (VR)

Published Papers (12 papers)

2021

Jump to: 2020

38 pages, 16130 KiB  
Article
The Utility of DSRC and V2X in Road Safety Applications and Intelligent Parking: Similarities, Differences, and the Future of Vehicular Communication
by Eduard Zadobrischi, Mihai Dimian and Mihai Negru
Sensors 2021, 21(21), 7237; https://doi.org/10.3390/s21217237 - 30 Oct 2021
Cited by 7 | Viewed by 4062
Abstract
As the technological advancement in the automotive field increases and the complexity of vehicle and infrastructure applications is extremely high, new directions and approaches are needed in this field. Supporting and developing vehicular applications dedicated to road safety by analyzing the current behavior [...] Read more.
As the technological advancement in the automotive field increases and the complexity of vehicle and infrastructure applications is extremely high, new directions and approaches are needed in this field. Supporting and developing vehicular applications dedicated to road safety by analyzing the current behavior of existing networks in various forms is imperative. This paper studies and implements a DSRC-type communications infrastructure that receives a set of controllable and adjustable indicators, which can provide messages to network drivers in a timely manner. The implementation is based on the 802.11p protocol and initially addresses pedestrian infrastructure or pedestrian safety, controlled areas, and perimeters that allow intelligent communications. The design and setting of the communication parameters in the lower layer of the DSRC stack for vehicle applications are part of this work, aspects that are also relevant in the case of autonomous vehicles. Full article
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26 pages, 3310 KiB  
Article
Risk Assessment for the Use of Drones in Warehouse Operations in the First Phase of Introducing the Service to the Market
by Agnieszka A. Tubis, Jacek Ryczyński and Arkadiusz Żurek
Sensors 2021, 21(20), 6713; https://doi.org/10.3390/s21206713 - 09 Oct 2021
Cited by 14 | Viewed by 3815
Abstract
Services, unlike products, are intangible, and their production and consumption take place simultaneously. The latter feature plays a crucial role in mitigating the identified risk. This article presents the new approach to risk assessment, which considers the first phase of introducing the service [...] Read more.
Services, unlike products, are intangible, and their production and consumption take place simultaneously. The latter feature plays a crucial role in mitigating the identified risk. This article presents the new approach to risk assessment, which considers the first phase of introducing the service to the market and the specificity of UAV systems in warehouse operations. The fuzzy logic concept was used in the risk analysis model. The described risk assessment method was developed based on a literature review, historical data of a service company, observations of development team members, and the knowledge and experience of experts’ teams. Thanks to this, the proposed approach considers the current knowledge in studies and practical experiences related to the implementation of drones in warehouse operations. The proposed methodology was verified on the example of the selected service for drones in the magazine inventory. The conducted risk analysis allowed us to identify ten scenarios of adverse events registered in the drone service in warehouse operations. Thanks to the proposed classification of events, priorities were assigned to activities requiring risk mitigation. The proposed method is universal. It can be implemented to analyze logistics services and support the decision-making process in the first service life phase. Full article
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21 pages, 1739 KiB  
Article
Ports Digitalization Level Evaluation
by Vytautas Paulauskas, Ludmiła Filina-Dawidowicz and Donatas Paulauskas
Sensors 2021, 21(18), 6134; https://doi.org/10.3390/s21186134 - 13 Sep 2021
Cited by 10 | Viewed by 3720
Abstract
Currently, seaports are actively searching for methods and ways to improve their operational efficiency. Digitalization is considered as one of the main directions of current ports’ development. Ports’ digitalization levels are varied and may depend on different factors, including port size, traditions, turnover [...] Read more.
Currently, seaports are actively searching for methods and ways to improve their operational efficiency. Digitalization is considered as one of the main directions of current ports’ development. Ports’ digitalization levels are varied and may depend on different factors, including port size, traditions, turnover and handled cargo type, etc. Ports often face decision-making challenges related to assessment of their digitization level and choice of development directions. The article aims to develop a methodology to evaluate ports’ digitalization level. A marketing research tool was used to collect the data needed for the analysis. A mathematical model allowing simulations is proposed and a case study of 30 ports located in the Baltic, North and Mediterranean Seas regions is explored. Based on conducted calculations, a ranking of analysed ports considering their digitalization level was created. The ports were compared within groups of small, medium-sized and large ports. It was estimated that the digitalization level in small and medium-sized ports is about 30% lower than the level of large seaports. The research results may be of interest to seaports striving to assess their level of digitalization and choose the best digital improvement solutions. Full article
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63 pages, 6690 KiB  
Review
Condition Monitoring of Rail Transport Systems: A Bibliometric Performance Analysis and Systematic Literature Review
by Mariusz Kostrzewski and Rafał Melnik
Sensors 2021, 21(14), 4710; https://doi.org/10.3390/s21144710 - 09 Jul 2021
Cited by 26 | Viewed by 7998
Abstract
Condition monitoring of rail transport systems has become a phenomenon of global interest over the past half a century. The approaches to condition monitoring of various rail transport systems—especially in the context of rail vehicle subsystem and track subsystem monitoring—have been evolving, and [...] Read more.
Condition monitoring of rail transport systems has become a phenomenon of global interest over the past half a century. The approaches to condition monitoring of various rail transport systems—especially in the context of rail vehicle subsystem and track subsystem monitoring—have been evolving, and have become equally significant and challenging. The evolution of the approaches applied to rail systems’ condition monitoring has followed manual maintenance, through methods connected to the application of sensors, up to the currently discussed methods and techniques focused on the mutual use of automation, data processing, and exchange. The aim of this paper is to provide an essential overview of the academic research on the condition monitoring of rail transport systems. This paper reviews existing literature in order to present an up-to-date, content-based analysis based on a coupled methodology consisting of bibliometric performance analysis and systematic literature review. This combination of literature review approaches allows the authors to focus on the identification of the most influential contributors to the advances in research in the analyzed area of interest, and the most influential and prominent researchers, journals, and papers. These findings have led the authors to specify research trends related to the analyzed area, and additionally identify future research agendas in the investigation from engineering perspectives. Full article
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32 pages, 11306 KiB  
Article
Identification of Sleeper Support Conditions Using Mechanical Model Supported Data-Driven Approach
by Mykola Sysyn, Michal Przybylowicz, Olga Nabochenko and Lei Kou
Sensors 2021, 21(11), 3609; https://doi.org/10.3390/s21113609 - 22 May 2021
Cited by 26 | Viewed by 4126
Abstract
The ballasted track superstructure is characterized by a relative quick deterioration of track geometry due to ballast settlements and the accumulation of sleeper voids. The track zones with the sleeper voids differ from the geometrical irregularities with increased dynamic loading, high vibration, and [...] Read more.
The ballasted track superstructure is characterized by a relative quick deterioration of track geometry due to ballast settlements and the accumulation of sleeper voids. The track zones with the sleeper voids differ from the geometrical irregularities with increased dynamic loading, high vibration, and unfavorable ballast-bed and sleeper contact conditions. This causes the accelerated growth of the inhomogeneous settlements, resulting in maintenance-expensive local instabilities that influence transportation reliability and availability. The recent identification and evaluation of the sleeper support conditions using track-side and on-board monitoring methods can help planning prevention activities to avoid or delay the development of local instabilities such as ballast breakdown, white spots, subgrade defects, etc. The paper presents theoretical and experimental studies that are directed at the development of the methods for sleeper support identification. The distinctive features of the dynamic behavior in the void zone compared to the equivalent geometrical irregularity are identified by numeric simulation using a three-beam dynamic model, taking into account superstructure and rolling stock dynamic interaction. The spectral features in time domain in scalograms and scattergrams are analyzed. Additionally, the theoretical research enabled to determine the similarities and differences of the dynamic interaction from the viewpoint of track-side and on-board measurements. The method of experimental investigation is presented by multipoint track-side measurements of rail-dynamic displacements using high-speed video records and digital imaging correlation (DIC) methods. The method is used to collect the statistical information from different-extent voided zones and the corresponding reference zones without voids. The applied machine learning methods enable the exact recent void identification using the wavelet scattering feature extraction from track-side measurements. A case study of the method application for an on-board measurement shows the moderate results of the recent void identification as well as the potential ways of its improvement. Full article
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31 pages, 11468 KiB  
Article
Application of MEMS Sensors for Evaluation of the Dynamics for Cargo Securing on Road Vehicles
by Jozef Gnap, Juraj Jagelčák, Peter Marienka, Marcel Frančák and Mariusz Kostrzewski
Sensors 2021, 21(8), 2881; https://doi.org/10.3390/s21082881 - 20 Apr 2021
Cited by 23 | Viewed by 3415
Abstract
Safety is one of the key aspects of the successful transport of cargo. In the case of road transport, the dynamics of a vehicle during normal events such as braking, steering, and evasive maneuver are variable in different places in the vehicle. Several [...] Read more.
Safety is one of the key aspects of the successful transport of cargo. In the case of road transport, the dynamics of a vehicle during normal events such as braking, steering, and evasive maneuver are variable in different places in the vehicle. Several manufacturers provide different dataloggers with acceleration sensors, but the results are not comparable due to different sensor parameters, measurement ranges, sampling frequencies, data filtration, and evaluation of different periods of acceleration. The position of the sensor in the loading area is also important. The accelerations are not the same at all points in the vehicle. The article deals with the measurement of these dynamic events with MEMS sensors on selected points of a vehicle loaded with cargo and with changes in dynamics after certain events that could occur during regular road transport of cargo to analyze the possibilities for monitoring accelerations and the related forces acting on the cargo during transport. The article uses evaluation times of 80, 300, and 1000 ms for accelerations. With the measured values, it is possible to determine the places with a higher risk of cargo damage and not only to adjust the packaging and securing of the cargo, but also to modify the transport routes. Concerning the purposes of securing the cargo in relation to EN 12195-1 and the minimum values of forces for securing the cargo, we focused primarily on the places where the acceleration of 0.5 g was exceeded when analyzing the monitored route. There were 32 of these points in total, all of which were measured by a sensor located at the rear of the semi-trailer. In 31 cases, the limit of 0.5 g was exceeded for an 80-ms evaluation time, and in one case, the value of 0.51 g was reached in the transverse direction for a 300-ms evaluation time. Full article
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14 pages, 4221 KiB  
Article
Occupational Noise on Floating Storage and Offloading Vessels (FSO)
by Grzegorz Rutkowski and Jarosław Korzeb
Sensors 2021, 21(5), 1898; https://doi.org/10.3390/s21051898 - 08 Mar 2021
Cited by 5 | Viewed by 2058
Abstract
The purpose and scope of this paper are to provide guidance of the potential impacts of being subjected to high level noise recorded on 1st generation (30 years old) floating storage and offloading vessels (FSO) in sector offshore. The international community recognizes that [...] Read more.
The purpose and scope of this paper are to provide guidance of the potential impacts of being subjected to high level noise recorded on 1st generation (30 years old) floating storage and offloading vessels (FSO) in sector offshore. The international community recognizes that vibroacoustic impacts from commercial ships may have negative consequences for both humans (worker’s) and marine life, especially marine mammals. As regards the effect of noise on human health, there are legal requirements imposing the noise exposure control on personnel working on ships. The acceptable noise exposure standards are established in European Union Directive 2003/10/EC (2003), the NOPSEMA Regulation (2006), the Maritime Labor Convention (MLC) guidelines (2006), and the recommendations of the International Maritime Organization IMO contained, e.g., IMO MEPC.1/Circ.833 (2014). These regulations inform employers and employees what they must do to effectively protect both the marine environment and the health and life safety of workers employed in the maritime industry offshore. This study also presents an analysis of the results of noise measurements carried out on exemplary 1st generation FSO units. Full article
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2020

Jump to: 2021

23 pages, 3157 KiB  
Article
Cyber-Attacks Risk Analysis Method for Different Levels of Automation of Mining Processes in Mines Based on Fuzzy Theory Use
by Agnieszka A. Tubis, Sylwia Werbińska-Wojciechowska, Mateusz Góralczyk, Adam Wróblewski and Bartłomiej Ziętek
Sensors 2020, 20(24), 7210; https://doi.org/10.3390/s20247210 - 16 Dec 2020
Cited by 14 | Viewed by 3830
Abstract
The rising automation level and development of the Industry 4.0 concept in the mining sector increase the risk of cyber-attacks. As a result, this article focuses on developing a risk analysis method that integrates Kaplan’s and Garrick’s approach and fuzzy theory. The proposed [...] Read more.
The rising automation level and development of the Industry 4.0 concept in the mining sector increase the risk of cyber-attacks. As a result, this article focuses on developing a risk analysis method that integrates Kaplan’s and Garrick’s approach and fuzzy theory. The proposed approach takes into account the level of automation of the operating mining processes. Moreover, it follows five main steps, including identifying the automation level in a selected mine, definition of cyber-attack targets, identification of cyber-attack techniques, definition of cyber-attack consequences, and risk ratio assessment. The proposed risk assessment procedure was performed according to three cyber-attack targets (databases, internal networks, machinery) and seven selected types of cyber-attack techniques. The fuzzy theory is implemented in risk parameter estimation for cyber-attack scenario occurrence in the mining industry. To illustrate the given method’s applicability, seven scenarios for three levels of mine automation are analyzed. The proposed method may be used to reveal the current cybersecurity status of the mine. Moreover, it will be a valuable guide for mines in which automation is planned in the near future. Full article
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39 pages, 1102 KiB  
Article
A Design of the Resilient Enterprise: A Reference Architecture for Emergent Behaviors Control
by Rob Bemthuis, Maria-Eugenia Iacob and Paul Havinga
Sensors 2020, 20(22), 6672; https://doi.org/10.3390/s20226672 - 21 Nov 2020
Cited by 12 | Viewed by 3574
Abstract
The sooner disruptive emergent behaviors are detected, the sooner preventive measures can be taken to ensure the resilience of business processes execution. Therefore, organizations need to prepare for emergent behaviors by embedding corrective control mechanisms, which help coordinate organization-wide behavior (and goals) with [...] Read more.
The sooner disruptive emergent behaviors are detected, the sooner preventive measures can be taken to ensure the resilience of business processes execution. Therefore, organizations need to prepare for emergent behaviors by embedding corrective control mechanisms, which help coordinate organization-wide behavior (and goals) with the behavior of local autonomous entities. Ongoing technological advances, brought by the Industry 4.0 and cyber-physical systems of systems paradigms, can support integration within complex enterprises, such as supply chains. In this paper, we propose a reference enterprise architecture for the detection and monitoring of emergent behaviors in enterprises. We focus on addressing the need for an adequate reaction to disruptions. Based on a systematic review of the literature on the topic of current architectural designs for understanding emergent behaviors, we distill architectural requirements. Our architecture is a hybrid as it combines distributed autonomous business logic (expressed in terms of simple business rules) and some central control mechanisms. We exemplify the instantiation and use of this architecture by means of a proof-of-concept implementation, using a multimodal logistics case study. The obtained results provide a basis for achieving supply chain resilience “by design”, i.e., through the design of coordination mechanisms that are well equipped to absorb and compensate for the effects of emergent disruptive behaviors. Full article
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25 pages, 3870 KiB  
Article
Personalization of the MES System to the Needs of Highly Variable Production
by Bożena Zwolińska, Agnieszka Anna Tubis, Norbert Chamier-Gliszczyński and Mariusz Kostrzewski
Sensors 2020, 20(22), 6484; https://doi.org/10.3390/s20226484 - 13 Nov 2020
Cited by 18 | Viewed by 3747
Abstract
The new generation Manufacturing Executions System (MES) is considered as one of the most important solutions supporting the idea of Industry 4.0. This is confirmed by research conducted among companies interested in the implementation of the Industry 4.0 concept, as well as the [...] Read more.
The new generation Manufacturing Executions System (MES) is considered as one of the most important solutions supporting the idea of Industry 4.0. This is confirmed by research conducted among companies interested in the implementation of the Industry 4.0 concept, as well as the publications of researchers who study this issue. However, if MES software is a link that connects the world of machines and business systems, it must take into account the specifics of the supported production systems. This is especially true in case of production systems with a high level of automation, which are characterised by flexibility and agility at the operational level. Therefore, personalization of the MES software is proposed for this class of production systems. The aim of the article is to present the MES system personalization method for a selected production system. The proposed approach uses the rules of Bayesian inference and the area of customisation is the technological structure of production, taking into account the required flexibility of the processes. As part of the developed approach, the variability index was proposed as a parameter evaluating the effectiveness of the production system. Then, the results of evaluation of the current system effectiveness by use of this index are presented. The authors also present the assumptions for the developed MES personalization algorithm. The algorithm uses the rules of Bayesian inference, which enable multiple adjustments of the model to the existing environmental conditions without the need to formulate a new description of reality. The application of the presented solution in a real facility allowed for determining production areas which are the determinants of system instability. The implementation of the developed algorithm enabled control of the generated variability in real time. The proposed approach to personalization of MES software for a selected class of production systems is the main novelty of the presented research and contributes to the development of the described area of research. Full article
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26 pages, 2964 KiB  
Article
Assessment of Augmented Reality in Manual Wiring Production Process with Use of Mobile AR Glasses
by Andrzej Szajna, Roman Stryjski, Waldemar Woźniak, Norbert Chamier-Gliszczyński and Mariusz Kostrzewski
Sensors 2020, 20(17), 4755; https://doi.org/10.3390/s20174755 - 22 Aug 2020
Cited by 42 | Viewed by 10365
Abstract
Digitalization of production environment, also called Industry 4.0 (the term invented by Wahlster Wolfgang in Germany) is now one of the hottest topics in the computer science departments at universities and companies. One of the most significant topics in this area is augmented [...] Read more.
Digitalization of production environment, also called Industry 4.0 (the term invented by Wahlster Wolfgang in Germany) is now one of the hottest topics in the computer science departments at universities and companies. One of the most significant topics in this area is augmented reality (AR). The interest in AR has grown especially after the introduction of the Microsoft HoloLens in 2016, which made this technology available for researchers and developers all around the world. It is divided into numerous subtopics and technologies. These wireless, see-through glasses give a very natural human-machine interface, with the possibility to present certain necessary information right in front of the user’s eyes as 3D virtual objects, in parallel with the observation of the real world, and the possibility to communicate with the system by simple gestures and speech. Scientists noted that in-depth studies connected to the effects of AR applications are presently sparse. In the first part of this paper, the authors recall the research from 2019 about the new method of manual wiring support with the AR glasses. In the second part, the study (tests) for this method carried out by the research team is described. The method was applied in the actual production environment with consideration of the actual production process, which is manual wiring of the industrial enclosures (control cabinets). Finally, authors deliberate on conclusions, technology’s imperfections, limitations, and future possible development of the presented solution. Full article
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24 pages, 3061 KiB  
Article
Mobility Prediction-Based Optimisation and Encryption of Passenger Traffic-Flows Using Machine Learning
by Syed Muhammad Asad, Jawad Ahmad, Sajjad Hussain, Ahmed Zoha, Qammer Hussain Abbasi and Muhammad Ali Imran
Sensors 2020, 20(9), 2629; https://doi.org/10.3390/s20092629 - 05 May 2020
Cited by 16 | Viewed by 4025
Abstract
Information and Communication Technology (ICT) enabled optimisation of train’s passenger traffic flows is a key consideration of transportation under Smart City planning (SCP). Traditional mobility prediction based optimisation and encryption approaches are reactive in nature; however, Artificial Intelligence (AI) driven proactive solutions are [...] Read more.
Information and Communication Technology (ICT) enabled optimisation of train’s passenger traffic flows is a key consideration of transportation under Smart City planning (SCP). Traditional mobility prediction based optimisation and encryption approaches are reactive in nature; however, Artificial Intelligence (AI) driven proactive solutions are required for near real-time optimisation. Leveraging the historical passenger data recorded via Radio Frequency Identification (RFID) sensors installed at the train stations, mobility prediction models can be developed to support and improve the railway operational performance vis-a-vis 5G and beyond. In this paper we have analysed the passenger traffic flows based on an Access, Egress and Interchange (AEI) framework to support train infrastructure against congestion, accidents, overloading carriages and maintenance. This paper predominantly focuses on developing passenger flow predictions using Machine Learning (ML) along with a novel encryption model that is capable of handling the heavy passenger traffic flow in real-time. We have compared and reported the performance of various ML driven flow prediction models using real-world passenger flow data obtained from London Underground and Overground (LUO). Extensive spatio-temporal simulations leveraging realistic mobility prediction models show that an AEI framework can achieve 91.17% prediction accuracy along with secure and light-weight encryption capabilities. Security parameters such as correlation coefficient (<0.01), entropy (>7.70), number of pixel change rate (>99%), unified average change intensity (>33), contrast (>10), homogeneity (<0.3) and energy (<0.01) prove the efficacy of the proposed encryption scheme. Full article
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