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Non-Hermiticity has emerged as a new paradigm for controlling coupled-mode systems in ways that cannot be achieved with conventional techniques. One aspect of this control that has received considerable attention recently is the encircling of exceptional points (EPs). To date, most work has focused on systems consisting of two modes that are tuned by two control parameters and have isolated EPs. While these systems exhibit exotic features related to EP encircling, it has been shown that richer behavior occurs in systems with more than two modes. Such systems can be tuned by more than two control parameters, and contain EPs that form a knot-like structure. Control loops that encircle this structure cause the system’s eigenvalues to trace out non-commutative braids. Here we consider a hybrid scenario: a three-mode system with just two control parameters. We describe the relationship between control loops and their topology in the full and two-dimensional parameter space. We demonstrate this relationship experimentally using a three-mode mechanical system in which the control parameters are provided by optomechanical interaction with a high-finesse optical cavity. When multiple oscillators are tuned, degeneracies occur on a knot-shaped region in the space of tuning parameters. This knot influences how such systems can be tuned. Here, the authors reconcile two common means for visualizing this influence.

Any system of coupled oscillators may be characterized by its spectrum of resonance frequencies (or eigenfrequencies), which can be tuned by varying the system’s parameters. The relationship between control parameters and the eigenfrequency spectrum is central to a range of applications 1 – 3 . However, fundamental aspects of this relationship remain poorly understood. For example, if the controls are varied along a path that returns to its starting point (that is, around a ‘loop’), the system’s spectrum must return to itself. In systems that are Hermitian (that is, lossless and reciprocal), this process is trivial and each resonance frequency returns to its original value. However, in non-Hermitian systems, where the eigenfrequencies are complex, the spectrum may return to itself in a topologically non-trivial manner, a phenomenon known as spectral flow. The spectral flow is determined by how the control loop encircles degeneracies, and this relationship is well understood for N = 2 (where N is the number of oscillators in the system) 4 , 5 . Here we extend this description to arbitrary N . We show that control loops generically produce braids of eigenfrequencies, and for N > 2 these braids form a non-Abelian group that reflects the non-trivial geometry of the space of degeneracies. We demonstrate these features experimentally for N = 3 using a cavity optomechanical system. Control loops generically produce braids of eigenfrequencies, and these braids form a non-Abelian group that reflects the non-trivial geometry of the space of degeneracies; these features are demonstrated experimentally using a cavity optomechanical system.

The Indian Railway network is the world’s fourth largest, transporting millions of people every day. One of the most difficult challenges for travelers is crossing the overhead bridges or subways to reach the right platform. To make this experience more comfortable we have developed the automatic system termed Railway Platform Crossing Automatic Bridge (RPCAB) to connect two opposite platforms. Here, the fabricated metal frame bridge is moved using a pair of double acting hydraulically/ pneumatically actuated telescopic cylinders. After the train pulls out of the station, the bridge connects to the other side of the platform, allowing passengers to walk on the bridge to cross the tracks. The position sensors, alarms, audio/visual indicators, and actuators are all in sync with the train traffic signaling system and the master controller, a Programmable Logic Controller (PLC). To prevent any mishaps from happening, a comprehensive safety interlock system has been implemented, including position sensors, safety barricades, emergency alarms, and an audio-visual information system. The proposed mechanical bridge facilitates the passage for the passengers who are physically impaired, with heavy luggage, pregnant women, and the elderly persons to cross the platform. Additionally, it controls the congestion of passengers when the train has left the station. The proposed system is simulated using PLC simulator for testing, validation, and analysis of the system’s behavior in a simulated environment. The simulation results presented in this paper show how efficient and reliable the proposed design is. Prior to constructing a working prototype in real time, it is essential to put the system through a virtual environment. The results support the viability of applying the proposed design in real-world settings, which will improve both safety and efficiency at railway platform crossings.

The jigsaw method is a form of collaborative learning in which students work in small groups to thoroughly understand a topic and then teach it to their classmates. This study is conducted at a university with a student body that is demographically and racially representative of the institution. The primary goals of this research are to determine how the jigsaw approach affects students’ participation, collaboration, and critical thinking. This research will contribute to our understanding of how the jigsaw method can be used to improve the teaching of blockchain at the engineering undergraduate level. The research aims to benefit teachers, curriculum designers, and academic administrators by demonstrating the effects it has on students’ motivation and performance in the classroom. The findings will be used to enhance blockchain education at the engineering undergraduate level by informing the implementation and optimization of the jigsaw method.

Purpose The purpose of this paper is to dig out enablers of sustainable industrial ecosystem to develop a framework. Design/methodology/approach To test the framework statistically, a structured questionnaire was designed. Measures for the questionnaire were adopted from an extensive literature review. Further, the questionnaire was pretested and further pilot study was conducted. Adding to this, the reliability and validity of the constructs was examined using confirmatory factor analysis followed by covariance-based structural equation modeling to test research hypotheses. Findings The statistical analyses suggest that the model exceeds the threshold limit for goodness of fit after undergoing through few iterations. Normative pressure has a low effect than rest of the factors. Originality/value The present study is a unique contribution in terms of its theoretical implications and practical use. Finally, research findings are concluded and further research directions is outlined.

PurposeThe main purpose of this paper is to investigate drivers and barriers of climate change mitigation strategies (CCMS), their linkages and impact in Indian Iron and Steel Industry (IISI) in light of ninth sustainable development goal (building resilient infrastructure, promote sustainable industrialization and foster innovation).Design/methodology/approachTo identify relevant drivers and barriers, a thorough literature review and opinions of industry experts were obtained. Utilizing Total Interpretive Structural Modeling (TISM), the selected drivers and barriers were modeled separately along with Cross Impact Matrix-multiplication Applied to Classification (MICMAC).FindingsPragmatic and cost-effective technology, less supply chain complexity, robust policy and legal framework were found to have the highest driving power over all the other drivers. Findings suggest political pressure as the most critical barrier in this study. The results from TISM and MICMAC analysis have been used to elucidate a framework for the understanding of policymakers and achieve top management commitment.Practical implicationsThis paper will help researchers, academicians, industry analysts and policymakers in developing a systems approach in prioritizing CCMS in energy-intensive (coal dependent) iron and steel plants. The model outcomes of this work will aid operational research to understand the working principles in other industries as well.Originality/valueTo the best of authors' knowledge, there is paucity of reported literature for the drivers and barriers of CCMS in iron and steel industry. This paper can be considered a unique, first attempt to use data from developing nations like India to develop a model and explain relationships of the existing drivers and barriers of CCMS.

The rapid development of smart renewable energy grids (SREGs) has resulted in a vast amount of data that requires efficient access control and secure mechanisms for sharing energy records among stakeholders. This paper proposes a novel approach called the identity‐based proxy signcryption‐based scheme for SREGs (ID‐PSC‐SREGs), which ensures the secure sharing of energy records in SREGs. The ID‐PSC‐SREG scheme integrates the benefits of signature and encryption techniques, merging them into a unified algorithm and providing a comprehensive solution for the confidentiality and authenticity of energy records. Extensive security analysis demonstrates that the scheme achieves provable security against adaptive chosen ciphertext attacks (IND‐ID‐PSC‐SREG‐CCA2) and existential unforgeability against adaptive chosen message attacks (EUF‐ID‐PSC‐SREG‐CMAs) under the decisional Diffie–Hellman problem. In order to further ascertain the security of the ID‐PSC‐SREG scheme, formal verification utilizing the automated validation of internet security protocols and applications (AVISPAs) is performed. The results confirm the scheme’s safety under the On‐the‐Fly Model‐Checker (OFMC) and Constraint Logic‐based Attack Searcher (CL‐AtSe).

The extension of digital competences in the ever-changing world of technology has transported global organizations new opportunities like never before. But this expansion has also flickered a dramatic surge in cybercrime, which carriages a huge problem that needs inventive replies. The current methods of cybercrime investigation are inadequate, predominantly when it comes to finding the source of attacks. While SSL safeguards secure data transmission, it does not offer forensic support, and the TCP/IP protocol suite does not form any protocols that are intended to be operative in cybercrime investigations. To rectify these difficulties, this paper proposes adding a forensic layer below the SSL layer. This novel feature consists of three protocols that reinforce user authentication and verification: IVAP, which is intended to brace the authentication and identification; Pro_DEC, which confirms that digital evidence is composed in a forensically comprehensive manner; and Cybercrime Attribution, which supports to attribute cybercrimes by tracking the source and path of data packets. The steadiness of court procedures amended by these protocols, which bid a specific toolbox for precise threat tracing and acknowledgement. Enhanced fact-finding capabilities and national safety are the main outcomes of this preventative approach to shore up cybersecurity and make systems tougher in the face of ever-changing cyber threats.

Due to real-time data sharing in the Internet of Medical Things (IoMT), the healthcare sector has evolved significantly in recent years. However, security breaches reveal incorrect authenti- cation and susceptible access during EHR distribution of EHRs among various stakeholders. Thus, a primary objective of the National Digital Health Mission (NDHM) is to employ cutting-edge technology to strengthen the security of electronic health records (EHRs) while safeguarding patient privacy. This paper proposes a signcryption with an identity-based authentication protocol based on Elliptic curve cryptography securing the transmission of medical records. The proposed protocol is designed based on bilinear pairing, and it supports several security features, including data confidentiality and au- thentication with effective key management. The proposed protocol is shown formally complete using BAN logic. Besides, our protocol is shown secure against potential attackers using the AVISPA under the OFMC and Cl-AtSe models. Nonetheless, the empirical analysis demonstrates that the proposed protocol outperforms the existing related schemes. Therefore, our proposed protocol is more suitable to be applied in the Internet of Medical Things (IoMT) environment.

Damage detection in steel structures requires robust and intelligent techniques to ensure reliability and efficiency. Traditional damage detection techniques rely on manual inspections, which can be labour-intensive, time-consuming, and prone to human mistakes. To address these difficulties, this paper develops an ensemble deep learning technique that combines Convolutional Neural Networks (CNN) with Long Short-Term Memory (LSTM) networks for joint damage detection in a steel frame structure. Moreover, the CNN part of the network pulls out spatial features from the data, and the LSTM part finds temporal relationships, which makes damage detection more accurate. For this purpose, a steel 3D frame structure is considered. We use an impact hammer to vibrate the frame and collect time-history acceleration data under both healthy and unhealthy configurations. Frequency-domain scalogram images are generated and used as input to the CNN-LSTM network. The training, validation, and testing accuracies are found to be 94.50%, 92.89%, and 91.25%., respectively. The outcomes show that the developed technique can easily distinguish healthy and unhealthy configurations. This research can enhance predictive maintenance, reduce downtime, and make it more accurate to identify joint damages in steel frame structures.