Comprehensive Comparative Analysis Research Articles

Enhancing Visual Homing in Robotics: A Study on Blockchain Integration and Consensus Algorithms

Creating an immutable repository for vital robot and environmental data, ensuring long-term accessibility, and functioning in the absence of GPS or mapping are crucial for visual homing navigation systems. We focus on the intersection of blockchain and robotics, particularly in visual homing. Our research involves an in-depth analysis of various blockchain consensus mechanisms, highlighting their suitability for visual homing applications. The heart of blockchain functionality lies in its consensus mechanism, which facilitates agreement among network nodes. In our first study part, we conduct a comprehensive comparative analysis of key consensus algorithms, emphasizing visual homing's decentralization, fault tolerance, latency, and throughput requirements. This analysis serves as a valuable reference for researchers and developers, emphasizing the importance of aligning the chosen consensus mechanism with specific blockchain application needs. The second part of our work involves extensive experiments exploring the connection between blockchain and visual homing. We assess prominent consensus mechanisms like Proof of Work (PoW), Proof of Stake (PoS), Delegated Proof of Stake (DPoS), and Proof of Authority (PoA) within a virtual environment in Gazebo, leveraging Wide Area Visual Navigation (WAVN). Our research implementation is grounded in the ROS framework and the Gazebo simulation environment.

Comparative Analysis of Profitability between Public and Private Sector Banks in India: A Study of SBI, Syndicate Bank ICICI Bank, and HDFC Bank

This study provides a comprehensive comparative analysis of profitability between public sector banks and private sector banks in India, focusing on four prominent institutions: State Bank of India (SBI), ICICI Bank, HDFC Bank, and Syndicate Bank. By examining key financial metrics such as Return on Assets (ROA), Return on Equity (ROE), Net Interest Margin (NIM), and Cost-to-Income Ratio, this research aims to elucidate the differences in profitability and operational efficiency between these banks. The analysis draws on secondary data from various financial sources, employing descriptive statistics, graphical representations, and ratio analysis to highlight trends and performance disparities. The study reveals that while public sector banks like SBI and Syndicate Bank exhibit substantial growth in total assets and deposits, private sector banks, particularly ICICI and HDFC, demonstrate superior profitability and cost efficiency. The findings underscore the impact of management practices, technological advancements, and macroeconomic conditions on bank performance. This research provides valuable insights for investors, regulators, and bank management, contributing to a deeper understanding of the factors driving profitability in the Indian banking sector.

Reliability analysis of various modeling techniques for the prediction of axial strain of FRP-confined concrete

PurposeThe external confinement provided by the fiber-reinforced polymer (FRP) sheets leads to an improvement in the axial compressive strength (CS) and strain of reinforced concrete structural members. Many studies have proposed analytical models to predict the axial CS of concrete structural members, but the predictions for the axial compressive strain still need more investigation because the previous strain models are not accurate enough. Moreover, the previous strain models were proposed using small and noisy databases using simple modeling techniques. Therefore, a rigorous approach is needed to propose a more accurate strain model and compare its predictions with the previous models.Design/methodology/approachThe present work has endeavored to propose strain models for FRP-confined concrete members using three different techniques: analytical modeling, artificial neural network (ANN) modeling and finite element analysis (FEA) modeling based on a large database consisting of 570 sample points.FindingsThe assessment of the previous models using some statistical parameters revealed that the estimates of the newly recommended models were more accurate than the previous models. The estimates of the new models were validated using the experimental outcomes of compressive members confined with carbon-fiber-reinforced polymer (CFRP) wraps. The nonlinear FEA of the tested samples was performed using ABAQUS, and its estimates were equated with the calculations of the analytical and ANN models. The relative investigation of the estimates solidly substantiates the accuracy and applicability of the recommended analytical, ANN and FEA models for predicting the axial strain of CFRP-confined concrete compression members.Originality/valueThe research introduces innovative methods for understanding FRP confinement in concrete, presenting new models to estimate axial compressive strains. Utilizing a database of 570 experimental samples, the study employs ANNs and regression analysis to develop these models. Existing models for FRP-confined concrete's axial strains are also assessed using this database. Validation involves testing 18 cylindrical specimens confined with CFRP wraps and FE simulations using a concrete-damaged plastic (CDP) model. A comprehensive comparative analysis compares experimental results with estimates from ANNs, analytical and finite element models (FEMs), offering valuable insights and predictive tools for FRP confinement in concrete.

Unraveling Differences in the Effects of Ammonium/Amine-Based Additives on the Performance and Stability of Inverted Perovskite Solar Cells.

Additive engineering, with its excellent ability to passivate bulk or surface perovskite defects, has become a common strategy to improve the performance and stability of perovskite solar cells (PVSCs). Among the various additives reported so far, ammonium salts are considered an important branch. It is worth noting that although both ammonium-based additives (R-NH3 +) and amine-based additives (R-NH2) are derivatives of ammonia (NH3), the functions of the two can be easily confused due to their structural similarities. Moreover, there is no comprehensive comparative analysis of them in the literature. Here, the differences between phenethylammonium iodide (PEA+) and phenethylamine (PEA) additives are revealed experimentally and theoretically. The results clearly show that PEA outperforms PEA+ in terms of device performance and stability based on the following three factors: i) PEA's defect passivation capability is superior to that of PEA+; ii) PEA has better hydrophobicity to hinder water ingress; and iii) PEA completely improves the stability of PVSCs by enhancing thermal stability and inhibiting iodide migration in perovskite more effectively than PEA+. As a result, the power conversion efficiency (PCE) of the inverted methylammonium triiodide (MAPbI3) device using PEA increases by ≈15% to over 21%. More importantly, this device exhibits greater ability to prevent water invasion, thermal-induce degradation, and inhibit iodide ion migration, resulting in better long-term stability.

Ultrasound-Assisted Recovery of Cathode Active Materials Using Green Solvents: A Comparative Study

The widespread adoption of lithium-ion batteries (LIBs) in various applications has led to an increasing demand for efficient and environmentally sustainable recycling processes. This necessity stems from the broader goal of establishing a sustainable and circular economy for LIBs while simultaneously addressing the challenges within the supply chain.One of the primary challenges in LIB recycling lies in the retrieval of valuable materials from end-of-life LIBs or electrode scraps in an environmentally benign manner. In particular, reclaiming the high purity of cathode active materials is a critical step to further development of direct recycling. The recovered materials need to be binder- and carbon black-free while retaining their inherent characteristics, including morphology, crystallinity, and electrochemical activity.Traditional methods for solvent-based cathode recovery involve energy-intensive processes and often employ hazardous solvents, leading to environmental concerns and safety issues. In response, recent studies have proposed several green solvents as environmentally friendly and economically viable alternatives for sustainable cathode recovery processes.In this study, we conduct a comprehensive comparative analysis of various green solvents to assess their efficiency in recovering cathode materials from electrode scraps. We employ an ultrasound-assisted recovery process using different green solvents to compare the characteristics of the recovered cathode active materials in terms of morphology, purity, surface characteristics, and electrochemical performance. By evaluating the key challenges and advantages of each green solvent, we aim to provide valuable insights into the development of solvent-based cathode recovery.

Comparative Analysis of GARCH-Based Volatility Models of Financial Market Volatility: A Case of Nairobi Security Market PLC, Kenya

This paper conducted a comprehensive comparative analysis of various GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models to forecast financial market volatility, with a specific focus on the Nairobi Stock Exchange Market. The examined models include symmetric and asymmetric GARCH types, such as sGARCH, GJR-GARCH, AR (1) GJG-GARCH, among others. The primary objective is to identify the most suitable model for capturing the complex dynamics of financial market volatility. The study employs rigorous evaluation criteria, including the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Mean Error (ME), and Root Mean Absolute Error (RMAE), to assess the performance of each model. These criteria facilitate the selection of the optimal model for volatility forecasting. The analysis reveals that the GJR-GARCH (1,1) model emerges as the best-fit model, with AIC and BIC values of −5.5008 and −5.4902, respectively. This selection aligns with the consensus in the literature, highlighting the superiority of asymmetric GARCH models in capturing volatility dynamics. The comparison also involves symmetric GARCH models, such as sGARCH (1,1), and other asymmetric models like AR (1) GJG-GARCH. While these models were considered, the GJR-GARCH (1,1) model demonstrated superior forecasting capabilities. The study emphasizes the importance of accurate model selection and the incorporation of asymmetry in volatility modeling. The research provides essential insights into financial market volatility modeling and forecasting using both asymmetric and symmetric GARCH models. These findings have significant implications for government policymakers, financial institutions, and investors, offering improved tools for risk assessment and decision-making during periods of market turbulence.

Analysis of energy performance and load matching characteristics of various building integrated photovoltaic (BIPV) systems in office building

Building Integrated Photovoltaic (BIPV) is a key technology for achieving zero-energy buildings by generating electricity and reducing energy consumption. Although many studies have analyzed the impact of BIPV on building energy efficiency, there is a lack of comprehensive comparative analysis of various BIPV systems. This study compared the impact of various BIPV systems on office building energy performance and provided optimal solutions for different climate zones. Simulation models for PV rooftop, PV window, and PV shading systems were developed and validated in EnergyPlus. The energy performance of BIPV systems in different Chinese climates was evaluated using these models. The results show that the PV window and PV shading have the most power generation capability in Beijing, and the PV rooftop has the most power generation capability in Kunming. Energy savings in Kunming are the highest with PV rooftop, PV windows, and PV shading at 111.78 %, 39.36 %, and 44.43 %, respectively. Finally, the study calculated the self-sufficiency rate (SSR) and self-consumption rate (SCR), and their ratio, along with the load matching ratio, were used to assess loading matching. Optimal BIPV schemes were identified for each climate zone, revealing that the PV rooftop combined with the PV shading system achieved the best load matching in Kunming, Guangzhou, Changsha, Beijing, and Harbin, with ratios of 82.00 %, 69.38 %, 70.88 %, 74.78 % and 67.27 %, respectively. These results provide a valuable reference for implementing the BIPV system to achieve zero energy consumption in office buildings under different climatic conditions in China.

Spiral organization of quasi-periodic shrimp-shaped domains in a discrete predator-prey system.

In this paper, we report the discovery of some novel dynamical scenarios for quasi-periodic shrimp-shaped structures embedded within chaotic phases in bi-parameter space of a discrete predator-prey system. By constructing high-resolution, two-dimensional stability diagrams based on Lyapunov exponents, we observe the abundance of both periodic and quasi-periodic shrimp-shaped organized domains in a certain parameter space of the system. A comprehensive comparative analysis is conducted to elucidate the similarities and differences between these two types of shrimps. Our analysis reveals that, unlike periodic shrimp, quasi-periodic shrimp induces (i) torus bubbling transition to chaos and (ii) multistability with multi-tori, torus-chaotic, and multi-chaotic coexisting attractors, resulting from the crossing of its two inner antennae. The basin sets of the coexisting attractors are analyzed, and we observe the presence of intriguing basin boundaries. We also verify that, akin to periodic shrimp structures, quasi-periodic shrimps also maintain the three-times self-similarity scaling. Furthermore, we encounter the occurrence of spiral organization for the self-distribution of quasi-periodic shrimps within a large chaotic domain. We believe that these novel findings will significantly enhance our understanding of shrimp-shaped structures and the intricate dynamics exhibited by their distribution in chaotic regimes.

A comparative techno-economic analysis for implementation of carbon dioxide to chemicals processes

CO2-based carbon-neutral organics production processes could potentially reshape the chemical industry. However, their feasibility and net carbon footprint rely strongly on the sources of H2. Herein, we present a comprehensive comparative techno-economic analysis of CO2-based methanol (CO2TM) and α-olefins (CO2TO) manufacturing using various feedstock supply modes: 1) the standalone mode, with external CO2 and H2 from on-site water electrolysis, 2) the integrated mode with CO2 and H2 recovered from coal-chemical plants, and 3) the integrated mode with recycled CO2 but H2 from on-site water electrolysis. The integration of CO2TM and CO2TO into coal-to-olefins (CTO) and coal-to-methanol (CTM) facilities is currently cost-effective and can reduce net CO2 emissions by 65.7% and 68.5%, resulting in a three-fold and two-fold increase in carbon efficiency, respectively. As carbon tax policies and electrolysis technologies continue to evolve, standalone CO2TM and CO2TO are projected to become more economically competitive than CTO and CTM by 2035–2045.

Exploring Gender Disparities in Emergency Department Utilization: A Comprehensive Comparative Analysis of the Frequency of Female Versus Male Emergency Department Visits.

Background The emergency department (ED) serves as the front line for emergency patient care, a unique limbo between the realms of generalist care and specialists and outpatient and inpatient care. As the trend of utilizing emergency healthcare services has escalated in the past 10 years, it becomes interesting to look at the patient characteristics of those who have utilized the ED. This analysis can guide the operation of impartial care for all ED patients to ensure equal access and discourage disparity based on the patient's sex. Methods This cross-sectional analysis seeks to examine differences in the frequency of patient visits to the ED in the United States (US) based on the patient's sex. The study utilizes data from the period 2012 to 2021, which was derived from the Nationwide Emergency Department Sample (NEDS). Results Analyzing both the rates of female and male visits to the ED on a year-by-year basis within the study period, it was observed that a higher proportion of females visit the ED, and, in general, both females and males have visited the ED less frequently in recent years. However, while the female sex has continued to represent the majority of ED patients, the gap between the majority female population and the minority male population has decreased, especially dramatically, in recent years. Additionally, using the compiled data and a linear regression model, predicted values were forecasted to continue this trend, with a general decrease in ED visits and a narrowing of the gap between females and males from 2022 to 2032. Conclusion As discussion and policy surrounding healthcare equity, primarily based on gender, becomes a more relevant topic, it is essential to discuss and analyze data to base new healthcare policy to ensure healthcare equality in all fields of medicine, including the ED and beyond. This study aims to identify and compare the difference in the frequency of ED visits between males and females to improve patient outcomes and further discussion regarding healthcare equity.

Evaluation of machine learning and deep learning methods for early detection of internet of things botnets

The internet of things (IoT) represents a rapidly expanding sector within computing, facilitating the interconnection of myriad smart devices autonomously. However, the complex interplay of IoT systems and their interdisciplinary nature has presented novel security concerns (e.g. privacy risks, device vulnerabilities, Botnets). In response, there has been a growing reliance on machine learning and deep learning methodologies to transition from conventional connectivity-centric IoT security paradigms to intelligence-driven security frameworks. This paper undertakes a comprehensive comparative analysis of recent advancements in the creation of IoT botnets. It introduces a novel taxonomy of attacks structured around the attack life-cycle, aiming to enhance the understanding and mitigation of IoT botnet threats. Furthermore, the paper surveys contemporary techniques employed for early-stage detection of IoT botnets, with a primary emphasis on machine learning and deep learning approaches. This elucidates the current landscape of the issue, existing mitigation strategies, and potential avenues for future research.

Development and characterization of a novel intergeneric hybrid grouper (Cromileptes altivelis ♀ × Epinephelus lanceolatus ♂)

Distant hybridization often gives rise to offspring with hybrid vigor in plants and animals, and this method has also shown great potential in aquaculture. Grouper, an economically important marine species, has witnessed rapid growth in its related industry. To cultivate a new grouper variety with accelerated growth, superior meat quality, and high economic value, we successfully obtained fertilized eggs through artificial insemination, using humpback grouper (Cromileptes altivelis) as the maternal parent and giant grouper (Epinephelus lanceolatus) as the paternal parent. The hybrid groupers were successfully hatched and reared for up to 14 months. This study conducted comprehensive comparative analyses between the hybrid offspring and the parental species, focusing on embryo development, growth rate, morphological characteristics, chromosome karyotype and muscle nutrient composition. The hybrid grouper embryos completed their entire development, from fertilization to hatching, in an average duration of 20 h and 37 min, under controlled conditions of 28.5 ± 0.5 °C temperature and 28 part per thousand (ppt) salinity. Remarkably, the hybrid groupers exhibited significantly faster growth than humpback groupers, with an absolute weight growth rate 1.6 times higher. Additionally, the hybrid groupers displayed a 4.7% increase in meat yield compared to giant groupers. In terms of morphology, cluster analysis and principal component analysis were used to analyze the morphological framework data of the three grouper species, revealing that the hybrid groupers were more similar to giant groupers in their morphological framework. Chromosome karyotype and simple sequence repeats (SSR) analysis confirmed that the hybrid groupers have a total of 48 chromosomes, inheriting one set of chromosomes from each parent. This study provides a foundation for grouper hybrid breeding, and the hybrid groupers obtained in this research have the potential to become excellent commercial varieties.

Phylogenetic variations in a novel family of hyperstable apple snail egg proteins: insights into structural stability and functional trends.

The relationship between protein stability and functional evolution is little explored in proteins purified from natural sources. Here, we investigated a novel family of egg proteins (Perivitellin-1, PV1) from Pomacea snails. Their remarkable stability and clade-related functions in most derived clades (Canaliculata and Bridgesii) make them excellent candidates for exploring this issue. To that aim, we studied PV1 (PpaPV1) from the most basal lineage, Flagellata. PpaPV1 displays unparalleled structural and kinetic stability, surpassing PV1s from derived clades, ranking among the most hyperstable proteins documented in nature. Its spectral features contribute to a pale egg coloration, exhibiting a milder glycan binding lectin activity with a narrower specificity than PV1s from the closely related Bridgesii clade. These findings provide evidence for substantial structural and functional changes throughout the genus' PV1 evolution. We observed that structural and kinetic stability decreased in a clade-related fashion and was associated with large variations in defensive traits. For instance, pale PpaPV1 lectin turns potent in the Bridgesii clade, adversely affecting gut morphology, while giving rise to brightly colored PV1s providing eggs with a conspicuous, probably warning signal in the Canaliculata clade. This work provides a comprehensive comparative analysis of PV1s from various apple snail species within a phylogenetic framework, offering insights into the interplay among their structural features, stability profiles and functional roles. More broadly, our work provides one of the first examples from natural evolution showing the crucial link among protein structure, stability and evolution of new functions.

Tad pili contribute to the virulence and biofilm formation of virulent Aeromonas hydrophila.

Type IV pili (T4P) are versatile proteinaceous protrusions that mediate diverse bacterial processes, including adhesion, motility, and biofilm formation. Aeromonas hydrophila, a Gram-negative facultative anaerobe, causes disease in a wide range of hosts. Previously, we reported the presence of a unique Type IV class C pilus, known as tight adherence (Tad), in virulent Aeromonas hydrophila (vAh). In the present study, we sought to functionalize the role of Tad pili in the pathogenicity of A. hydrophila ML09-119. Through a comprehensive comparative genomics analysis of 170A. hydrophila genomes, the conserved presence of the Tad operon in vAh isolates was confirmed, suggesting its potential contribution to pathogenicity. Herein, the entire Tad operon was knocked out from A. hydrophila ML09-119 to elucidate its specific role in A. hydrophila virulence. The absence of the Tad operon did not affect growth kinetics but significantly reduced virulence in catfish fingerlings, highlighting the essential role of the Tad operon during infection. Biofilm formation of A. hydrophila ML09-119 was significantly decreased in the Tad operon deletant. Absence of the Tad operon had no effect on sensitivity to other environmental stressors, including hydrogen peroxide, osmolarity, alkalinity, and temperature; however, it was more sensitive to low pH conditions. Scanning electron microscopy revealed that the Tad mutant had a rougher surface structure during log phase growth than the wildtype strain, indicating the absence of Tad impacts the outer surface of vAh during cell division, of which the biological consequences are unknown. These findings highlight the role of Tad in vAh pathogenesis and biofilm formation, signifying the importance of T4P in bacterial infections.

The technological revolution’s impact on business management

The rapid advancement of technology in the era of the fourth industrial revolution has significantly transformed organizational management practices. This study examines the influence of technological progress on organizational management, specifically analyzing the effects of data analysis and digital management methods in response to these changes. The main objective is to determine how these technological advancements impact enterprises of various sizes in the Czech Republic. The research employed comparative and analytical approaches, utilizing survey data collected from numerous organizations. Concrete methods used in the study include a comprehensive questionnaire survey, comparative analysis, and statistical correlation analysis to assess the significance of technologies based on the classification of enterprise size. The findings demonstrate substantial disparities in the implementation and advantages of technology contingent upon the magnitude of the organization, with smaller and larger enterprises exhibiting enhanced flexibility and deliberate assimilation of novel technologies. The main conclusion is that proficient administration of technology results in competitive advantages and operational efficiencies. Companies are advised to customize their technology strategies based on their available resources and market requirements. Further analysis explores the connections between investments in technology and other organizational elements such as financial resources and personnel, highlighting the importance of developing coherent plans that successfully incorporate technology into the overall structure of the organization.

Strategic Siting of Direct Air Capture Facilities in the United States

Direct air capture (DAC) systems that capture carbon dioxide (CO2) directly from the atmosphere are garnering considerable attention for their potential role as negative emission technologies in achieving net-zero CO2 emission goals. Common DAC technologies are based either on liquid–solvent (L-DAC) or solid–sorbent (S-DAC) to capture CO2. A comprehensive multi-factor comparative economic analysis of the deployment of L-DAC and S-DAC facilities across various United States (U.S.) cities is presented in this paper. The analysis considers the influence of various factors on the favorability of DAC deployment, including local climatic conditions such as temperature, humidity, and CO2 concentrations; the availability of energy sources to power the DAC system; and costs for the transport and storage of the captured CO2 along with the consideration of the regional market and policy drivers. The deployment analysis in over 70 continental U.S. cities shows that L-DAC and S-DAC complement each other spatially, as their performance and operational costs vary in different climates. L-DAC is more suited to the hot, humid Southeast, while S-DAC is preferrable in the colder, drier Rocky Mountain region. Strategic deployment based on regional conditions and economics is essential for promoting the commercial adoptability of DAC, which is a critical technology to meet the CO2 reduction targets.

Optimal and robust control methodologies for 4DOF active suspension systems: A comparative study with uncertainty considerations

AbstractDrawing from recent developments in the field, this article explores advanced control methodologies for active suspension systems with the aim of enhancing ride comfort and vehicle handling. The study systematically and comprehensively implements, simulates, and compares five control methods: Proportional‐integral‐derivative (PID), linear quadratic regulator (LQR), , , and synthesis in the context of half‐vehicle active suspension systems. By using a detailed system model that includes parameter uncertainties and performance weights, analysis, and simulations are conducted to evaluate the performance of each control approach. The results provide valuable insights into the strengths and limitations of these methods, offering a comprehensive comparative analysis. Notably, the study reveals that control may not ensure stability for all possible combinations within a broad range of uncertainties, indicating the need for careful consideration in its application. The results and simulations thoroughly evaluate and compare the performance of each control strategy across various output responses, contributing to the advancement of more effective and reliable active suspension systems.

Comparative Study of Multilevel Converters using DQ Current Control

This paper presents a comprehensive comparative analysis of different multilevel converter topologies, including 2-level, Neutral Point-Clamped (NPC), Cascaded H-Bridge (CHB), and T-Type converters using the DQ current control strategy. The study aims to evaluate the performance of these topologies concerning current Total Harmonic Distortion (THD) and ripple in the direct and quadrature components of the current. A mathematical model of the grid is presented to facilitate the simulation study. The DQ current control scheme is implemented to regulate the current in both the direct and quadrature axes. The simulations are conducted under various operating conditions to capture the converters’ performance across different load scenarios and modulation techniques. Results indicate significant variations in the performance metrics among the different converter topologies. The 2-level converter exhibits higher THD and ripple compared to the more complex multilevel topologies.

Enhancing healthcare data privacy and security: A comparative study of regulations and best practices in the US and Nigeria

The imperative for robust healthcare data privacy and security is escalating as healthcare systems worldwide are increasingly digitized. This review paper presents a comprehensive comparative analysis of the regulatory frameworks, challenges, and best practices related to healthcare data privacy and security in the United States and Nigeria. By examining the Health Insurance Portability and Accountability Act (HIPAA) in the US and the Nigeria Data Protection Regulation (NDPR) alongside other local regulations, this study highlights the nuances of each country's approach to safeguarding patient data. The analysis extends to the effectiveness of technological solutions like encryption and blockchain, and assesses the role of governance in policy implementation. Case studies from both nations offer insights into successful strategies and underscore the gaps and opportunities for cross-country learning and improvement. The paper concludes with targeted recommendations for policymakers and healthcare providers, aiming to strengthen the security measures and propose areas for further research and development in healthcare data management. This comparative study not only sheds light on current practices but also charts a course for future collaborative efforts to enhance data privacy and security in healthcare on a global scale.

Machine identity authentication via unobservable fingerprinting signature: A functional data analysis approach for MQTT 5.0 protocol

The Industrial Internet of Things (IIoT) and Smart Manufacturing environments face significant challenges in machine identity authentication, crucial for ensuring data integrity and cybersecurity. Traditional methods like One-Class Support Vector Machines (OCSVM) often fall short in sensitivity, specificity, and explainability. This research introduces a novel Functional Data Analysis (FDA)-based model that leverages unique temporal patterns in machine-generated data to authenticate machine identities, adapting to equipment wear and tear. Through a comprehensive comparative analysis, the FDA model demonstrates superior performance and robustness in industrial settings. Additionally, we propose integrating this FDA-based approach with the MQTT 5.0 protocol, enhancing data security in IIoT communications. This work not only advances IIoT cybersecurity but also supports digital twins and predictive maintenance, contributing to a more secure and efficient Smart Manufacturing ecosystem.