Cyber-Physical Systems

A stable supply of energy begets a vibrant economy, and to cushion the cost and environmental impact of hydrocarbon fuel utilization, a novel green biocatalyst from modified ground Yellow Oleander Seed Coat calcined at 995 • C in a muffle furnace, as recommended by the thermogravimetric analysis and acidified with 0.5 M H 2 SO 4 , was used. The transesterification process was optimized using Box-Behnken Design and RStudio, and both methods produced the same 98.89 wt.% biodiesel, with parameters of 65 minutes, methanol/oil of 8/1, acidifiedbiocatalyst of 3.5 wt.%, and 70 ⁰C. Although both modeling tools yielded the same 0.9911 R 2 value, yet RStudio p-value of < 1.37e-07 is preferable in contrast to the Box-Behnken design <0.001. Additionally, the model generated by RStudio yielded a lower Akaike Information Criterion value of 25.7, compared to the BBD model of 60.36, indicating that RStudio offers a model with superior fit or quality. Furthermore, RStudio plots yielded a preferable visualization and interpretation of the parameters, which justify the statistical superiority of RStudio over the Box-Behnken Design. A kinetic technique yielded 32.13 kJ/mol activation energy with 0.9738 R 2 while the thermodynamic techniques yielded 64.49 kJ/mol enthalpy,-0.0154 kJ/mol entropy, and Gibbs free energies; 69.69 kJmol-1 at 338 K, 69.76 kJmol-1 at 343 K, and 69.84 kJmol-1 at 348 K. These results, in addition to the fuel and physicochemical qualities of the biodiesel produced connect with globally accepted norms. Thus, this biodiesel can serve as a substitute for hydrocarbon diesel in diesel-powered engines without drawbacks, thereby boosting a cleaner and healthier ecosystem for all.

Space infrastructures are becoming increasingly important to the global society and economy. However, their cybersecurity is understudied despite previous endeavors. This motivates the present SoK, which is based on a novel methodology of five elements: space infrastructures model, missions, vulnerabilities, attacks, and defenses. The methodology establishes an "anatomy" of space infrastructures via the innovative notions of mission control flows and mission data flows, which are respectively inspired by the notions of control flows and data flows in program analysis. We show how the space infrastructure vulnerabilities, attacks, and defenses studied in the literature can be mapped to space mission control flows and mission data flows, leading to insights such as: improper memory allocation and lack of authentication are the two most exploited vulnerabilities reported; Global Navigation Satellite Systems (GNSS) security is most studied, mainly via physical layer security; and the most effective approach to attack the space segment is to pivot through the ground segment.

In response to the global imperative to address energy consumption and reduce carbon emissions in the built environment, we present a novel approach leveraging computer vision, deep learning, and IoT technologies. Our research focuses on developing an intelligent building management system to optimize Heating, Ventilation, and Air Conditioning (HVAC) operations. The primary objective is to dynamically adjust HVAC settings based on real-time occupancy detection, ensuring energy efficiency without compromising occupant comfort. Our methodology involves the implementation of computer vision algorithms for human presence detection, with occupancy data stored centrally in a Firebase database. Additionally, we introduce a user-friendly 3D interactive website enabling comprehensive visualization and management of room settings alongside occupancy monitoring. The backend of the system, powered by a Raspberry Pi, acts as a central hub for data processing, communication, and HVAC management. Results demonstrate the efficacy of our solution in reducing energy consumption, cutting carbon emissions, and enhancing occupant comfort through optimized HVAC operations and a comprehensive management platform. The interactive 3D interface facilitates efficient monitoring and control of indoor settings, improving overall building management practices. In conclusion, our research highlights the potential of cutting-edge technology to drive intelligent and sustainable solutions in the built environment. By integrating advanced technologies and providing users with intuitive tools, our system contributes to the overarching goal of achieving energy efficiency and environmental sustainability.

This paper explores the latest advancements in critical technology areas such as cloud computing, the Internet of Things (IoT), and cyber-physical systems. It provides a comprehensive review of current trends, technological challenges, and future opportunities, emphasizing the potential impact of these technologies on modern industries and infrastructure. Cloud computing offers a flexible framework in which data and resources are spread across different locations and can be accessed from various industrial environments. This technology has revolutionized the way resources such as data, services, and applications are used, stored, and shared in industrial applications. Over the past decade, industries have rapidly embraced cloud computing due to its advantages of enhanced accessibility, cost reduction, and improved performance. Moreover, the integration of cloud computing has led to significant advancements in the field of the Internet of Things (IoT). However, this quick shift to the cloud has also introduced various security concerns and challenges. Traditional security solutions are not always suitable or effective for cloud-based systems (Amit Kumar Tyagi, 2021). In recent years, cyber-physical systems (CPS) have been to many vital areas, including medical devices, smart cars, industrial systems, energy grid, etc. As these systems increasingly rely on Internet, ensuring their security requirements, which are different from those of ordinary information technology systems, has become an important research topic.

The escalating complexity and widespread deployment of autonomous systems, ranging from advanced industrial robotics to intelligent urban infrastructure, necessitate a paradigm shift in software engineering. These systems demand not only high adaptability but also rigorous security and transparent decision-making. This paper proposes a unified Software Intelligence Framework that seamlessly integrates Neural Program Synthesis (NPS), Quantum-Secure DevOps (QSD), and Explainable AI (XAI) to meet these multifaceted demands. The framework leverages advancements in NPS for AI-driven code generation, QSD for fortifying software lifecycles against emerging quantum threats, and XAI for ensuring interpretable and trustworthy decisionmaking in critical autonomous operations. We present a comprehensive literature review of the state-of-the-art in each domain, detailing their respective challenges and synergistic potential. The proposed architecture unifies these components into a continuous pipeline for specification-to-code generation, secure deployment, and runtime adaptation. A hypothetical smart city infrastructure scenario illustrates the practical application and benefits of this convergent framework, demonstrating its capacity for rapid code adaptation, post-quantum security, and human-understandable explanations of autonomous behavior. We further discuss the technical challenges inherent in such integration, along with robust evaluation strategies and the profound ethical, operational, and security implications of deploying AI-generated, quantum-secure systems in sensitive contexts. This work lays the foundation for a new multidisciplinary field essential for developing adaptable, robust, and trustworthy autonomous systems.

Keith F. Joiner-received his PhD in Calculus Education, MS in Aerospace Systems Engineering through Loughborough University in the United Kingdom, and a Master of Management. He joined the Air Force in 1985 and became an aeronautical engineer, project manager, and teacher over a 30year career before joining the University of New South Wales in 2015 as a senior lecturer in test and evaluation where he has since written 50 papers and articles linking research and practice. From 2010 to 2014, he was the Director-General of Test and Evaluation for the Australian Defence Force, where he was awarded a Conspicuous Service Cross. He is a Certified Practising Engineer and a Certified Practising Project Director. His fields of research include Aerospace Engineering, Six-Sigma Test Design, and Cybersecurity Testing and Education.

The acquisition field continues to face increasing pressures to perform under conditions of escalating complexity, uncertainty, and ambiguity. These conditions suggest that traditional approaches, practices, and acquisition technologies might be incongruent with support demands for acquisition practitioners. This research is focused on exploiting and extending recent developments in Complex System Governance (CSG) to advance the acquisition field. CSG is focused on the design, execution, and evolution of fundamental system functions necessary for control, communications, coordination, and integration of complex systems (e.g., acquisition). CSG is based in Systems Theory (fundamental laws governing complex systems), Management Cybernetics (the science of effective system organization), and Governance (provision of direction, oversight, and accountability for systems). Recent advances in CSG (Keating, Katina, & Bradley, 2015) make this an opportune time for exploitation of this field ...

Acquisition programs continue to struggle with increasing complexity. High degrees of emergence, interconnectedness, and uncertainty are the norm rather than exception. The purpose of this research is to explore extension of ongoing research in complex system pathologies for acquisition programs. Significant advances have been made in development of deeper understanding of the nature of pathologies (deviations from healthy system function) and their implications for performance of complex systems. Complex system pathologies represent “violations” of underlying system principles. These violations negatively affect system governance functions (control, oversight, accountability) resulting in degradation of system performance. Greater understanding of complex system pathologies offers insights to enhance complex system performance. This paper reports on the current state of development of a method to identify, represent, and assess systemic pathologies in complex systems. The method ex...

Context: The "Physics of Notations" (PoN) supports a systematic improvement of the cognitive effectiveness of visual modelling languages. Problem: PoN focuses on the concrete syntax of a language, building on a predefined abstract syntax. We should also consider the abstract syntax of a language when developing efforts to improve it by choosing the most adequate language constructs (concepts and their relationships). We instantiate this challenge by comparing two Multi-Agent Systems Domain Specific Languages: SEA_ML++ and DSML4MAS, and assessing the extent to which their respective constructs affect the developer experience. Method: We will perform a quasiexperiment for comparing how practitioners use both languages to solve similar modelling challenges. The experiment will have a cross-over within-subjects design and will focus on the extent to which the different language constructs impact on developer experience. These tasks will be monitored, so that we can assess their success and effort involved, including eye-tracking information. Results: This paper reports on the planned study design for this empirical comparison of two DSLs for MAS.

This paper explores the covert nature and evolving role of sleeper malware in contemporary cyber warfare and its implications for national security. It examines the lifecycle, deployment, and activation of dormant cyber threats and provides a framework for understanding their strategic use by state and non-state actors. Through a synthesis of case studies and advanced threat modeling, this study contributes to the growing field of cyber resilience and counterintelligence strategies.

This paper explores the covert nature and evolving role of sleeper malware in contemporary cyber warfare and its implications for national security. It examines the lifecycle, deployment, and activation of dormant cyber threats and provides a framework for understanding their strategic use by state and non-state actors. Through a synthesis of case studies and advanced threat modeling, this study contributes to the growing field of cyber resilience and counterintelligence strategies.

This paper proposes a new manufacturing paradigm, we call Cloud Agile Manufacturing, and whose principal objective is to offer industrial production systems as a service. Thus users can access any functionality available in the cloud of manufacturing (process design, production, management, business integration, factories virtualization, etc.) without knowledgeor at least without having to be expertsin managing the required resources. The proposal takes advantage of many of the benefits that can offer technologies and models like: Business Process Management (BPM), Cloud Computing, Service Oriented Architectures (SOA) and Ontologies. To develop the proposal has been taken as a starting point the Semantic Industrial Machinery as a Service (SIMaaS) proposed in previous work. This proposal facilitates the effective integration of industrial machinery in a computing environment, offering it as a network service. The work also includes an analysis of the benefits and disadvantages of the proposal.

This paper details a taxonomy generated for unmanned aerial vehicle (UAV) missions. Specifically, we examine the primary functions that a human operator would perform for a particular UAV mission within this taxonomy, including mission planning, management, ...

Advancements in the digitization and automation of critical infrastructures, particularly in aeronautical Communication, Navigation, and Surveillance (CNS) technologies, have led to the merging of complex physical and information networks with artificial intelligence (AI) systems. This integration has significantly enhanced the capabilities of avionics and Air Traffic Management (ATM) systems, improving data processing, information sharing, and geographic coverage. However, these advancements also make these systems more vulnerable to cybersecurity threats, physical weaknesses, and risks to data integrity. The interconnected nature of CNS infrastructure, together with ATM systems, increases the likelihood of widespread attacks, as threats can rapidly spread across connected components. Consequently, both ATM and UAS Traffic Management (UTM) systems are facing growing security challenges. Although the concept of cybersecurity in aviation is not new, integrating it seamlessly into aviation systems continues to pose significant difficulties. As AI technology improves operational efficiency and reliability within aviation systems, it has also become a key area for emerging cybersecurity threats. AI-driven intrusions and thefts are progressively replacing traditional attack methods, prompting researchers to propose defensive strategies based on AI technology. This paper critically examines the cybersecurity vulnerabilities and threats that could impact ATM and UTM systems. It categorizes potential threat actors based on their goals, motivations, and capabilities, and explores various attack methodologies based on AI technology, alongside their defensive countermeasures.

A tecnologia tem se mostrado uma vantagem competitiva em nossos ambientes industriais. Desde atividades básicas como plantio e agropecuária até a transformação e desenvolvimento do produto acabado, ela pode ser empregada a fim que agregue valor, segurança e lucratividade para as indústrias. Este artigo científico aborda a relevância das redes industriais na era da Indústria 4.0, com foco na implantação e organização de redes que integram dispositivos IoT-Internet Of Things (Internet das Coisas)-para otimizar processos e gerar vantagens competitivas. Serão explorados os diferentes tipos de redes industriais, protocolos de comunicação, tecnologias de conectividade para dispositivos IoT e equipamentos utilizados. Além disso, serão analisados os desafios e oportunidades na implementação de redes IIoT, como segurança, escalabilidade e interoperabilidade. Por fim, serão apresentados estudos de caso que demonstram como a adoção de redes IIoT pode gerar benefícios tangíveis para as indústrias, como aumento da eficiência, redução de custos e melhoria da qualidade dos produtos e serviços.

ABSTRACT: Increasing consumer interaction thanks to the development of communication facilities has great importance on company decisions. Digital transformation, one of these decisions, necessitated the transfer of actual business processes to digital. The central dynamic that reveals this necessity is the digitalization of the consumer. With the digitalization of the consumer, the attitudes of the companies towards the consumers and the expectations of the consumers from the companies have changed. In this context, it has been aimed to compile and examine the studies with the keywords "customer" and "consumer" in the publications on digital transformation in the WOS (Web of Science) database. Therefore, this study examines academically qualified studies on both digital transformation and consumers through a conceptual framework. On digital transformation, a current concept, some remarkable consumer-oriented studies have been carried out in Germany, Russia, Italy, the USA, Spain, and England. It has been observed that the keywords of digitalization, big data, e-commerce, artificial intelligence, machine learning, and digital entrepreneurship are the subject matters studied in this context. These are the most frequently used keywords in digital transformation and digital consumer. It also reveals possible literature gaps on which future studies in this context can focus. The research results extracted from 432 studies provide an overview of the studies on the digital transformation between 2010-2021. It also contributes to the literature by visualizing the role of the consumer in digital transformation.
KEYWORDS: Digital Transformation, Digital Marketing, Consumer, Bibliometric Analysis /////
ÖZET: İletişim olanaklarının gelişmesi nedeniyle artan tüketici etkileşimi, şirket kararlarında büyük öneme sahip olmuştur. Bu kararlardan biri olan dijital dönüşüm, gerçek iş süreçlerinin dijitale aktarılmasını zorunlu kılmıştır. Bu gerekliliği ortaya çıkaran temel dinamik ise tüketicinin dijitalleşmesidir. Tüketicilerin dijitalleşmesi sayesinde firmaların tüketicilere yönelik tutumu ve tüketicilerin onlardan beklentileri değişime uğramıştır. Bu bağlamda çalışmada, WOS (Web of Science) veri tabanında yer alan dijital dönüşüm üzerine yazılmış çalışmalardan "müşteri" ve "tüketici" anahtar kelimelerini içerenlerin toplanması ve incelenmesi amaçlanmıştır. Dolayısıyla çalışma, dijital dönüşüm üzerine yazılmış akademik açıdan nitelikli çalışmaları kavramsal bir çerçeve üzerinden incelenmektedir. Güncel bir kavram olan dijital dönüşüm konusunda Almanya, Rusya, İtalya, ABD, İspanya ve İngiltere'de tüketici yönelimli dikkat çekici çalışmalar yapılmıştır. Dijitalleşme, büyük veri, e-ticaret, yapay zekâ, makine öğrenimi ve dijital girişimcilik anahtar kelimelerinin bu bağlamda çalışıldığı gözlemlenmiştir. Dijital dönüşüm ve dijital tüketici bağlamında en çok kullanılan kelimeler olmuştur. Ayrıca çalışma, ileride bu alanda yapılacak çalışmaların odaklanması muhtemel literatür boşluklarını açığa çıkarmayı hedeflemektedir. 432 çalışmanın incelenmesiyle ortaya çıkarılan sonuçlar, dijital dönüşüm alanında 2010-2021 yılında dijital dönüşüm alında yapılan çalışmalara yönelik bir genel bakış sağlamaktadır. Çalışma ayrıca literatüre dijital dönüşümün rolünün literatür destekli olarak görselleştirilmesi ile de katkı sağlamaktadır.
ANAHTAR KELİMELER: Dijital Dönüşüm, Dijital Pazarlama, Tüketici, Bibliyometrik Analiz

Carpooling enables multiple users with similar travel habits to share rides, reducing vehicles on the road, leading to benefits such as lower fuel consumption, reduced traffic congestion, and lower environmental impact. However, carpooling also poses a challenge to the privacy of the users, as they may not want to reveal their location or route information to others. This research study delves into a cutting-edge approach to address these privacy concerns by leveraging homomorphic encryption (HE) within the realm of carpooling services. The proposed solution makes use of a HE scheme that supports encrypted computation on real numbers, which is suitable for carpooling applications that involve distance and time calculations. The approach enables decision makers to perform efficient and accurate route matching over encrypted data, without disclosing their sensitive information about users, thus preserving the confidentiality of the data. The proposed system is evaluated through extensive experiments and simulations, demonstrating its effectiveness in terms of both security and privacy when the system operates in normal (ideal) and abnormal (under attack) conditions. Experimental results indicate that the proposed solution offers robust resistance to various attacks, including replay attacks and data exposure, providing a robust and privacy-centric solution for carpooling services.

You as a newly qualified engineer at a leading manufacturing firm, have been tasked with exploring how the latest advancements in industrial technology can be harnessed to enhance the company's production capabilities. The firm, known for its high-quality consumer electronics, has been facing increasing competition from both domestic and international markets. To maintain its competitive edge, management has decided to invest in upgrading their manufacturing processes. You need to investigate the concepts of Industry 4.0, smart factories, and the evolution towards Industry 5.0 and prepare a comprehensive report and strategic roadmap for the company's transition. This assignment requires you to understand the current state of the industry, evaluate the benefits and challenges of these technologies, and propose a phased implementation plan that aligns with the company's goals.

With increasing humanity in space exploration and commercialization, cybersecurity has emerged as an issue that requires great importance. The present scenario has connected various space assets-satellites, spacecraft, space stations, and ground control systems-more tightly together than ever before. They are therefore prone to various forms of cyber attacks. This paper focuses on some unique challenges facing cybersecurity while trying to protect these space assets: vulnerability in satellite communications, possibility of cyber-physical attacks, and complexities of distributed space systems security. It also surveys emerging threats that include ransomware targeting critical satellite networks and cyber capabilities being weaponized by both state and non-state actors. To address all these challenges, the paper proffers the multi-layered cybersecurity framework integrating advanced encryption, real-time anomaly detection that leverages on artificial intelligence capabilities, and mechanisms of data integrity through blockchain technologies. It underlines the key importance of global cooperation, policy frameworks, as well as backup protocols in the general mitigation of threats. Through case analysis and actionable approaches, this study addresses the need to have robust scalable cybersecurity solutions with respect to safekeeping space assets and ensuring resiliency operations in the new frontier.

Smart grid reliability and efficiency are critical for uninterrupted service, especially amidst growing demand and network complexity. Wide-Area Measurement Systems (WAMS) are valuable tools for mitigating faults and reducing fault-clearing time while simultaneously prioritizing cybersecurity. This review looks at smart grid WAMS implementation and its potential for cyber-physical power system (CPPS) development and compares it to traditional Supervisory Control and Data Acquisition (SCADA) infrastructure. While traditionally used in smart grids, SCADA has become insufficient in handling modern grid dynamics. WAMS differ through utilizing phasor measurement units (PMUs) to provide real-time monitoring and enhance situational awareness. This review explores PMU deployment models and their integration into existing grid infrastructure for CPPS and smart grid development. The review discusses PMU configurations that enable precise measurements across the grid for quicker, more accurate decisions. This study highlights models of PMU and WAMS deployment for conventional grids to convert them into smart grids in terms of the Smart Grid Architecture Model (SGAM). Examples from developing nations illustrate cybersecurity benefits in cyber-physical frameworks and improvements in grid stability and efficiency. Further incorporating machine learning, multi-level optimization, and predictive analytics can enhance WAMS capabilities by enabling advanced fault prediction, automated response, and multilayer cybersecurity.

The Morphemic H2020 project covers several features from modelling cross-cloud applications, continuous and autonomous optimization and deployment and providing access to several cloud capabilities. This demo paper describes the MORPHEMIC CAMEL Designer tool responsible of the Cloud Application Modelling and Execution Language (CAMEL) design for the modelling Environment Modelio. CAMEL Designer is an open source module for graphically creating, editing and exporting CAMEL Models in XMI format. Keywords— Cloud, Fog, edge and multi-access computing and networking, Open-source projects, open standards.

The opportunity to shift from corrective and preventive to data-driven Predictive Maintenance has received a significant boost with the deeper penetration of Internet of Things (IoT) technologies in industrial environments. Processing IoT generated data nonetheless creates challenges for data management and actionable data processing. One way to handle such complexity is to introduce context information modelling and management, wherein data and service delivery are determined upon resolving the apparent context of a service or data request. In this paper, context information management is considered on the basis of a valid knowledge construct for reliability-oriented maintenance management. The aim is to produce a viable semantic organization of data for maintenance services. It is applied on an industrial case linked to maintenance of a distributed fleet of connected production grade industrial printers. The complexity of translating the data generated by such production assets to actionable information is significant, as the status of a single asset is characterised by several hundreds of failure modes and a multitude of event codes. To assess the viability of the ontology for the targeted application, a qualitative usability evaluation study of the ontology is performed.

This paper is devoted to the new methods of organizing interactive museum exhibits by means of additive technologies, programmable microelectronics and multimedia. Traditionally museum exhibition is distanced from the visitor appearing just as a visual image. But new trend is to let the visitor inside the exhibition, providing different forms of interactions. Modern museums constantly search for the new ways of presenting cultural and natural heritage taking into account that exhibitions should be at the same time scientifically accurate, attractive, memorable and, ideally, accessible for the wide audience including disabled people. In this regard, tangible user interfaces based on the Internet of Things and combined with the scientific visualization build up very promising set of technologies that brings to live cyber-physical museum exhibits. These exhibits are an alloy of physical museum items with virtual multimedia content, providing the visitor a unique experience of interactivity. The key feature of cyber-physical exhibits is their tangibility, whereby they become accessible for visually impaired people and deliver much more information for the regular visitors. There are a lot of successful attempts to build cyber-physical exhibits within the museum space. However, there is a lack of methodological basis for this, as well as the lack of high-level tools to seamlessly integrate related technologies into the existing museum infrastructure. In this paper we propose using ontology-driven adaptive multiplatform scientific visualization system SciVi as a software basis for cyber-physical museum exhibits. This system was previously successfully used in solving problems related to steering hardware and software solvers in different application domains, monitoring lightweight robotics systems and supporting custom hardware human-machine interfaces. So, it contains necessary mechanisms to adapt to the third-party digital infrastructure (including the museum one) and build all the required middleware and visualizers within it. We tested our approach by developing two cyber physical exhibits: tangible bonobo skull in the State Darwin Museum (Moscow) and tangible titanophone skulls in the Museum of Permian Antiquities (Perm). Bonobo exhibit appears to be a custom joystick in a form of corresponding skull to steer the Sketchfab-rendered 3D model of bonobo monkey head. Titanophone exhibit allows visitors to discover the age variability of titanophone synapsid in an interactive way.

В данной статье предлагается подход к созданию киберфизических музейных экспонатов на основе мето-
дов и средств научной визуализации, Интернета вещей, аддитивных технологий и онтологического инжиниринга.
Киберфизический экспонат включает в себя виртуальную и реальную составляющие, тесно переплетённые друг
с другом. Научная визуализация используется как методологическая и технологическая основа наглядного пред-
ставления виртуальной части экспоната, в роли которой могут выступать релевантный цифровой контент и
3D-реконструкции. Интернет вещей является основой создания осязаемого пользовательского интерфейса к со-
ответствующим программным средствам визуализации. Аддитивные технологии позволяют создавать вирту-
альные реконструкции и высокоточные реплики музейных экспонатов. Онтологический инжиниринг обеспечивает
адаптивные механизмы бесшовного встраивания новых киберфизических экспонатов в существующую цифровую
инфраструктуру музеев. Предложенный подход использован на практике при создании киберфизических экспона-
тов в Государственном Дарвиновском музее (г. Москва) и Музее пермских древностей (г. Пермь)

Over the recent years, the protection of the so-called 'soft-targets', i.e. locations easily accessible by the general public with relatively low, though, security measures, has emerged as a rather challenging and increasingly important issue. The complexity and seriousness of this security threat growths nowadays exponentially, due to the emergence of new advanced technologies (e.g. Artificial Intelligence (AI), Autonomous Vehicles (AVs), 3D printing, etc.); especially when it comes to large-scale, popular and diverse public spaces. In this paper, a novel Digital Twinas-a-Security-Service (DTaaSS) architecture is introduced for holistically and significantly enhancing the protection of public spaces (e.g. metro stations, leisure sites, urban squares, etc.). The proposed framework combines a Digital Twin (DT) conceptualization with additional cutting-edge technologies, including Internet of Things (IoT), cloud computing, Big Data analytics and AI. In particular, DTaaSS comprises a holistic, real-time, large-scale, comprehensive and data-driven security solution for the efficient/robust protection of public spaces, supporting: a) data collection and analytics, b) area monitoring/control and proactive threat detection, c) incident/attack prediction, and d) quantitative and data-driven vulnerability assessment. Overall, the designed architecture exhibits increased potential in handling complex, hybrid and combined threats over large, critical and popular soft-targets. The applicability and robustness of DTaaSS is discussed in detail against representative and diverse real-world application scenarios, including complex attacks to: a) a metro station, b) a leisure site, and c) a cathedral square.

With the technological development of advanced technologies and the use of the Internet of Things (IoT), the number of connected devices is increasing in manufacturing processes. As devices become more and more incorporated using more processing power, the big data is generated. However, increasing the generation of big data leads to problems related to processing and analysis. The current tendency of solving the problems of processing and analysis is via Cloud Computing technologies. However, more attention is dedicated of performing computations as close to the device as possible, relying on Edge Computing technologies. Motivated by these facts, this paper provides a comparative analysis of the roles of edge computing and cloud computing, summarizing challenges and opportunities of these technologies and providing their application in Industry 4.0.

Linear and non-linear classifiers provide different strengths for evaluating neurophysiological sensor data. The dynamic nature and non-linear trends of neurophysiological data would appear suited to the use of a non-linear classifier such as an artificial neural network. A research team explored the application of both classification methods and found that successful classification was achieved through the use of a linear classifier. This paper presents the findings of this research team at Lockheed Martin Advanced Technology Laboratories (LM ATL) during its experiences using both types of classifiers and provides a comparison of the strengths and weaknesses of each approach. Recommendations for future use of each type of classifier within augmented cognition are also presented. 1

Linear and non-linear classifiers provide different strengths for evaluating neurophysiological sensor data. The dynamic nature and non-linear trends of neurophysiological data would appear suited to the use of a non-linear classifier such as an artificial neural network. A research team explored the application of both classification methods and found that successful classification was achieved through the use of a linear classifier. This paper presents the findings of this research team at Lockheed Martin Advanced Technology Laboratories (LM ATL) during its experiences using both types of classifiers and provides a comparison of the strengths and weaknesses of each approach. Recommendations for future use of each type of classifier within augmented cognition are also presented.

Cyber-Physical System (CPS) is a symbol of the fourth industrial revolution (4IR) by integrating physical and computational processes which can associate with humans in various ways. In short, the relationship between Cyber networks and the physical component is known as CPS, which is assisting to incorporate the world and influencing our ordinary life significantly. In terms of practical utilization of CPS interacting abundant difficulties. Currently, CPS is involved in modern society very vastly with many uptrend perspectives. All the new technologies by using CPS are accelerating our journey of innovation. In this paper, we have explained the research areas of 14 important domains of Cyber-Physical Systems (CPS) including aircraft transportation systems, battlefield surveillance, chemical production, energy, agriculture (food supply), healthcare, education, industrial automation, manufacturing, mobile devices, robotics, transportation, and vehicular. We also demonstrated the challenges and future direction of each paper of all domains. Almost all articles have limitations on security, data privacy, and safety. Several projects and new dimensions are mentioned where CPS is the key integration. Consequently, the researchers and academicians will be benefited to update the CPS workspace and it will help them with more research on a specific topic of CPS. 158 papers are studied in this survey as well as among these, 98 papers are directly studied with the 14 domains with challenges and future instruction which is the first survey paper as per the knowledge of authors.

Cyber–physical systems (CPSs) are evolving from individual systems to collectives of systems that collaborate to achieve highly complex goals, realizing a cyber–physical system of systems (CPSoSs) approach. They are heterogeneous systems comprising various autonomous CPSs, each with unique performance capabilities, priorities, and pursued goals. In practice, there are significant challenges in the applicability and usability of CPSoSs that need to be addressed. The decentralization of CPSoSs assigns tasks to individual CPSs within the system of systems. All CPSs should harmonically pursue system-based achievements and collaborate to make system-of-system-based decisions and implement the CPSoS functionality. The automotive domain is transitioning to the system of systems approach, aiming to provide a series of emergent functionalities like traffic management, collaborative car fleet management, or large-scale automotive adaptation to the physical environment, thus providing significant environmental benefits and achieving significant societal impact. Similarly, large infrastructure domains are evolving into global, highly integrated cyber–physical systems of systems, covering all parts of the value chain. This survey provides a comprehensive review of current best practices in connected cyber–physical systems and investigates a dual-layer architecture entailing perception and behavioral components. The presented perception layer entails object detection, cooperative scene analysis, cooperative localization and path planning, and human-centric perception. The behavioral layer focuses on human-in-the-loop (HITL)-centric decision making and control, where the output of the perception layer assists the human operator in making decisions while monitoring the operator’s state. Finally, an extended overview of digital twin (DT) paradigms is provided so as to simulate, realize, and optimize large-scale CPSoS ecosystems.

The view of VTT (Technical Research Centre of Finland) on the development of selected information and communication technologies is presented. The views are given as technology roadmaps in the areas of interoperability and mobility in future networks, micromechanical radio frequency systems, service architectures and smart human environments. The work is a part of a theme called Future Communications Technologies, one of VTT's strategic technology themes. The purpose of the work is to help the planners and players direct their activities towards better competitiveness in this rapidly developing field.

Path planning is an important task for mobileF service robots. Most of the available path-planning algorithms are applicable only in static environments. Achieving path planning becomes a difficult task in an unknown, dynamic environment. To solve the path planning problem in an unknown dynamic environment, this paper proposes a Bidirectional Rapidly-exploring Random Tree Star-Dynamic Window Approach (BRRT *-DWA) algorithm with Adaptive Monte Carlo Localization (AMCL). Bidirectional Rapidly-exploring Random Tree Star(BRRT *) is used to generate an optimal global path plan, Dynamic Window Approach(DWA) is a local planner and Adaptive Monte Carlo Localization(AMCL) is used as a localization technique. The robot can navigate using the map file of the unknown environment created by Simultaneous Localization And Mapping (SLAM) and the data from the Light Detection and Ranging (LiDAR) sensor while avoiding dynamic and static obstacles. In addition, the object identification algorithm You Only Look Once (YOLO) was adopted, trained, and used for the robot to recognize objects and people. Results obtained from both simulation and experiment show the proposed method can achieve better performance in a dynamic environment compared with other state-of-the-art algorithms.

The cellular network standard 5G meets the networking requirements for different industrial use cases due to the advantages of low latency, high bandwidth, and high device density while providing a very good quality of service. These capabilities enable the realization of wireless digital twins (DTs), a key element of future cyber-physical production systems. DTs for prediction, monitoring, and control of machine tools need physical modeling as well as the bidirectional exchange of information between the digital and the physical world. 5G is a wireless communication technology with the potential to disruptively change industrial communication. 5G enables wireless, highly scalable, and flexible realization of even safety-and latency-critical connections. In this paper, a 5G enabled DT of a machine tool for process control, monitoring and simulation is developed and implemented. A bidirectional communication between the physical machine tool and the DT is realized via 5G. Moreover, process prediction is enabled based on physics simulation. Next to the physical modeling of the machine behavior, a 5G-capable interface between the input and output signals of the machine control system and the developed DT is implemented. Moreover, the DT is migrated in a wireless form to an edge server. Furthermore, the capabilities of the DT are demonstrated. Therefore, the architecture and implementation of the DT as well as its benefits and challenges are outlined. 1 Motivation Modern manufacturing systems that incorporate digital technologies-the so-called cyber-physical production systems (CPPS)-seek to interconnect the digital and real world. For better flexibility, scalability, and reconfigurability, CPPS aim to connect individual cyber-physical systems and soften the hierarchical automation pyramid to decentralized distribution of computing units [1]. Due to increased demand for customized products, the requirements on the connectivity, functionality, flexibility, and intelligence of machine tools are also increasing [2]. Consequently, CPPS lead to complex manufacturing systems that are increasingly challenging to control and understand, due to many different decentralized, connected systems (e.g., machine tools, automated guided vehicles, human-machine-interfaces, etc.) with different characteristics, functionalities, and thus different heterogenous information technologies [3].

It is assumed that the 1st industrial revolution began with the invention of the steam engine in the second half of the 18th century. The second industrial revolution is associated with the electricity and mass production system and developments in information technologies are also called as the 3rd industrial revolution. Today, the 4th industrial revolution has begun to be discussed at this stage where information and communication technologies have been adapted. Newly developed technologies such as artificial intelligence, big data, cloud computing, nanotechnology and the Internet of Things - IoT in Industry 4.0 have started to take place in international literature as the most interesting topics of this revolution. However, studies on industry 4.0 technologies and their effects on social, human and economic fields should be given more importance in the national literature. The aim of this study is to examine the historical development process and characteristics of industry 4.0, ...

Geleceğin üretim modellerini geliştireceği söylenen ve hızlıca içine girmekte olduğumuz yeni bir sanayi devrimi, "Endüstri 4.0" veya "4. Endüstri devrimi" olarak adlandırılıyor. Endüstri 4.0'ı oluşturacak akıllı sistemler, yenilikçi yaklaşımların, yeni teknolojilerin, ileri teknolojilere sahip bilgisayarların, yeni yazılımların ve nitelikli insan kaynağının etkileşimli çalışması ile sağlanabilmektedir. Bu süreç geleceğin endüstrisini nasıl şekillendirecek? "Nesnelerin İnterneti," "Bulut Bilişim," "Üretim Bulutu," "Artırılmış Gerçeklik" gibi kavramlar bu süreçte Endüstri 4.0 devriminin neresinde olacak? gibi sorular bu yazıda ele alınacak ve açıklanmaya çalışılacaktır. Yakın gelecekte tasarım ve üretim ortamlarının nasıl şekilleneceği ve bu döneme nasıl hazır girilebileceği konuları tartışılacaktır. Bir inceleme ve öngörü yazısı olan bu makalede bu sorulara cevap aranırken, saha tecrübelerinden edinilen gerçek uygulamaların bilişim sistemleri tarafındaki temel adımları tarif edilerek bir başlangıç yol haritası önerilmektedir.

Gelecegin uretim modellerini gelistirecegi soylenen ve hizlica icine girmekte oldugumuz yeni bir sanayi devrimi, “Endustri 4.0” veya “4. Endustri devrimi” olarak adlandiriliyor. Endustri 4.0’i olusturacak akilli sistemler, yenilikci yaklasimlarin, yeni teknolojilerin, ileri teknolojilere sahip bilgisayarlarin, yeni yazilimlarin ve nitelikli insan kaynaginin etkilesimli calismasi ile saglanabilmektedir. Bu surec gelecegin endustrisini nasil sekillendirecek? “Nesnelerin Interneti,” “Bulut Bilisim,” “Uretim Bulutu,” “Artirilmis Gerceklik” gibi kavramlar bu surecte Endustri 4.0 devriminin neresinde olacak? gibi sorular bu yazida ele alinacak ve aciklanmaya calisilacaktir. Yakin gelecekte tasarim ve uretim ortamlarinin nasil sekillenecegi ve bu doneme nasil hazir girilebilecegi konulari tartisilacaktir. Bir inceleme ve ongoru yazisi olan bu makalede bu sorulara cevap aranirken, saha tecrubelerinden edinilen gercek uygulamalarin bilisim sistemleri tarafindaki temel adimlari tarif edilerek...

and Computer Engineering Today, electronic computing devices are critically involved in our daily lives, basic infrastructure, and national defense systems. With the growing number of threats against them, hardware-based security features offer the best chance for building secure and trustworthy cyber systems. In this dissertation, we investigate ways of making hardware-based security into a reality with primary focus on two areas: Hardware Trojan Detection and Physically Unclonable Functions (PUFs). Hardware Trojans are malicious modifications made to original IC designs or layouts that can jeopardize the integrity of hardware and software platforms. Since most modern systems critically depend on ICs, detection of hardware Trojans has garnered significant interest in academia, industry, as well as governmental agencies. The majority of existing detection schemes focus on test-time because of the limited hardware resources available at run-time. In this dissertation, we explore innovative run-time solutions that utilize on-chip thermal sensor measurements and fundamental estimation/detection theory to expose changes in IC power/thermal First and foremost, I would like to thank my advisor, Prof. Ankur Srivastava, for his guidance and patience through my Ph.D. His advice, support, and friendship have been invaluable on both academic and personal levels, for which I am extremely grateful. Without him as a continuous source of inspiration and motivation, I would not have been able to improve and achieve all that I have. It has been a pleasure to work with and learn from him. I would also like to extend my gratitude to the members of my dissertation committee for their time and service. I also offer special thanks to Professor Rama Chellappa, Professor Joseph JaJa, Professor, Professor Shuvra Bhattacharyya, and Professor Andre Tits for their support, encouragement, and advice in applying to jobs in academia. My colleagues in Prof. Srivastava's research group have enriched my graduate life in many ways and deserve a special mention here as well. I owe my gratitude to Bing Shi, Caleb Serafy, Tiantao Lu, and Chongxi Bao not only for our fruitful discussions about research, but also the stress relieving conversations and jokes we shared throughout our time together in the lab. I would also like to acknowledge the financial support provided by the ECE department and Northrop Grumman for three semesters of teaching assistantship and one year of research fellowship respectively. Last, but by no means least, I thank all of my family and friends for their support and encouragement throughout my graduate studies. I would especially viii 1. D. Forte and A. Srivastava, "Manipulating Manufacturing Variations for Bet

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Systems engineers use SysML as a vendor-independent language to model Cyber-Physical Systems. However, SysML does not provide an executable form to define behavior but this is needed to detect critical issues as soon as possible. Action Language for Foundational UML (Alf) integrated with SysML can offer some degree of precision. In this paper, we present an Alf specialization that introduces the synchronous-reactive model of computation to SysML, through definition of not explicitly constrained semantics: timing, concurrency, and inter-object communication. The proposed specialization is well-suited for safety-critical systems because it is deterministic. We study one example already modeled in the literature, to compare these approaches with our one. The initial results show that the proposed specialization helps to couple complexity, provides better composition, and enables deterministic behavior definition.

The increasing complexity of modern systems poses numerous challenges at all stages of system development and operation. Continuous software and system engineering processes, e.g., DevOps, are increasingly adopted and spread across organizations. In parallel, many leading companies have begun to apply artificial intelligence (AI) principles and techniques, including Machine Learning (ML), to improve their products. However, there is no holistic approach that can support and enhance the growing challenges of DevOps. In this paper, we propose a software architecture that provides the foundations of a model-based framework for the development of AI-augmented solutions incorporating methods and tools for continuous software and system engineering and validation. The key characteristic of the proposed architecture is that it allows leveraging the advantages of both AI/ML and Model Driven Engineering (MDE) approaches and techniques in a DevOps context. This architecture has been designed, developed and applied in the context of the European large collaborative project named AIDOaRt. In this paper, we also report on the practical evaluation of this architecture. This evaluation is based on a significant set of technical solutions implemented and applied in the context of different real industrial case studies coming from the AIDOaRt project. Moreover, we analyse the collected results and discuss them according to both architectural and technical challenges we intend to tackle with the proposed architecture.

Most importantly, to my mother, you gave me everything that I am. Without your spiritual, emotional and financial support, I would not be where I am today. I am blessed to have such a great family. Your unconditional support and love has been the key for the success I have experienced in my life and in completing my doctoral degree. viii

Integrating machine learning (ML) models into backend systems is increasingly vital for driving innovation across industries. This integration enhances user engagement, operational efficiency, and data-driven decision-making. Despite its benefits, challenges such as scalability and maintenance persist, requiring careful planning and expertise in software development and ML. This paper explores the landscape of integrating ML models into backend systems by conducting a comprehensive literature review. As part of research methods, data is gathered from academic databases and technical reports, peer-reviewed papers are chosen, and case studies are analysed to find strategies, challenges, and opportunities for integration. The literature review highlights studies exploring ML integration across different sectors. From enhancing backend simulation processes to streamlining model deployment with DevOps, these studies underscore both the benefits and challenges of ML integration. Real-time data processing, privacy-preserving approaches, and domain-specific adjustments may need new concepts. While existing research provides insights into specific tools and frameworks, a comprehensive analysis of the integration process itself is needed. Further research should address challenges in data pipelines, domain understanding, and model interpretability to maximise the benefits of ML integration into backend systems and revolutionise businesses.

HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

This paper present a proposal for measuring available mental resources during the accomplishment of a task. Our proposal consists in measuring emotions provoked by perceived self-efficacy in the execution of the task. Self-efficacy is one of the most important factors that affect the resources that a person puts at the disposal of the execution of the task. When a person perceives that he/she is not being effective he/she will activate more resources to improve his performance. This self-efficacy will be reflected in the emotions that the person experiences. A good efficacy will provoke positive emotions and a bad efficacy negative emotions. The results of our study show that poor execution leads to negative emotions and psychophysiological activation as measured by pupil dilation. According to these results we propose that a possible method for measuring available resources during the execution of the task could be online measuring of emotions.

The volatility and flexibility of a production line in a smart factory demands for high dynamics during the assembly tasks and repetitive movements in an un-ergonomic body posture. Hence, the workers are exposed to the danger of developing work-related musculoskeletal disorders (MSDs). Previous studies have reported that exoskeletons help to reduce fatigue and prevent injuries during lifting, carrying, pushing, pulling, and overheadpositions tasks, improving productivity in manufacturing industry. However, no studies have reported the advantages of digital integration of an exoskeletons network in a smart factory. This paper gives an overview of benefits and challenges regarding the connectivity of exoskeletons within a smart factory. Moreover, it describes the communication architecture of a cyber-physical exoskeleton network. Finally, an experimental test of fog computing structure was conducted based on IoT messaging protocols, allowing real-time data analytics for benefits of the manufacturing process.

Problem-solving and critical thinking are also essential talents for robots in manufacturing technicians. Manufacturing environments present a myriad challenges that require quick and effective problem-solving. Professionals must be adept at diagnosing issues, identifying root causes, and implementing solutions. Critical thinking is necessary to anticipate potential problems and innovate new ways to improve robotic systems and processes. Learn more in Certified Lean Robotics in Manufacturing Technician (CLRmT) by Tonex.

An Enterprise network is a combination of different types of networks consisting of Ethernet, wireless, Voice over IP and several others. It is a fact that as the size of the organization increases so also the networks, as well as the number of computational requirements on its network, should be increased and optimized. Hence, effective management of these resources in a high-traffic environment in a reliable manner is challenging and requires a stable network flow. Fault-tolerance in an enterprise network for large organizations poses a big challenge for the network designers. In this Research work, two techniques are proposed to provide a fault tolerance system. The use of redundancy in the network infrastructure and the use of adaptive technology are proposed. Conducted simulations and research revealed that network robusity will be improved by employing these techniques. The redundancy technique is the provision of hot and cold functional capabilities that would allow system continuity and functionality in the case of component failure or capacity limitation. Redundant components that automatically take over operation when an equivalent functional component fails or seized. Riverbed Opnet Modeler Simulation tool is used to simulate the performance of the technique. As part of an increasing system, robusity and continuity in failure situations and faults, adaptive components such as H.264 codec and beyond (H.265) be employed for better performance.