Engineering Commons^™

Journal Of Roleplaying Studies And Steam (Jrpssteam) Vol. 5 [2026], Número 1 (Issue 1), Romano Ponce-Díaz Phd, Cristo Leon, Ivan Avila, Sarah Lynne Bowman, Kjell Hedgard Hugaas, Alexandra Schreiber Ma, Jaime Eduardo García Maya, Víctor Emmanuel Quintana Villarreal Vic Emma, Francisco Gonzalez Ing., Daniel Romero Benguigui, Antonio Roda-Martínez

Journal of Roleplaying Studies and STEAM

El presente número del Journal of Roleplaying Studies and STEAM examina la convergencia entre las prácticas lúdicas, el diseño narrativo y los procesos de mediación sociocultural en la investigación contemporánea. Las contribuciones reunidas en este número abordan el juego de rol como un dispositivo de producción de conocimiento, intervención psicoeducativa y reelaboración de representaciones culturales. Nos podemos atrever a señalar que la educación es la convergencia entre la ludología, las ciencias sociales, los estudios visuales y el análisis cultural; entendiendo a la educación como la actividad consciente e intencionada de transmitir información y conocimientos a las siguientes generaciones.

Martin Heidegger …

From Reactive To Predictive: A Hybrid Trust-Mediated Adoption Framework For Data-Driven Maintenance In Distributed-Authority Aviation Environments, Dustin J. Foote

International Journal of Aviation, Aeronautics, and Aerospace

Modern aviation maintenance operates within increasingly data-intensive technological environments, yet the operational integration of predictive maintenance into routine decision-making remains inconsistent across sectors. Contemporary aircraft incorporate centralized maintenance computers and condition monitoring architectures capable of fault aggregation, exceedance capture, and trend-based data collection. Although prognostics and health management research continues to advance detection and prediction methods, implementation outcomes often depend on factors beyond analytical performance alone.

This paper examines predictive maintenance adoption in distributed-authority aviation environments and argues that constraints emerge less from sensing capability than from organizational structure, decision authority dispersion, and institutional trust dynamics. For purposes of analysis, …

Digital Twin–Oriented Certification Architecture For Advanced Air Mobility, Daniel Pleffken

International Journal of Aviation, Aeronautics, and Aerospace

Advanced Air Mobility (AAM) systems introduce certification challenges associated with distributed propulsion, increasing software reliance, and tightly coupled architectures. These characteristics evolve within regulatory environments that are still adapting to emerging vehicle concepts. While digital engineering practices are increasingly adopted during system development, certification workflows remain largely document-centric, limiting lifecycle traceability and consistent reasoning about change impacts as designs and regulatory interpretations evolve. This paper proposes a Digital Twin–oriented certification architecture that integrates regulatory knowledge, system representations, Means of Compliance (MoCs), and verification artifacts within a unified model-based environment. The architecture is organized around four elements: regulatory structuring, Model-Based Systems …

Intelligent Manufacturing Of Edible Oil: From Smart Sensing To Big Data Platform, Ru Jiang, Nadirbek Yusupbekov

Chemical Technology, Control and Management

With the rapid advancement of Industry 4.0 technologies, intelligent manufacturing and big data platforms are profoundly transforming the production models of the traditional edible oil industry. The edible oil production process involves multiple complex unit operations such as refining, decolorization, and deodorization, which impose high requirements on process control and product quality monitoring. This paper presents a systematic review of key technological advances in the field of intelligent manufacturing of edible oil, establishing a comprehensive technical framework encompassing four dimensions: smart sensing, artificial intelligence applications, IoT communication, and big data platforms. The review begins by analyzing the global background and …

Data-Driven Neuro-Fuzzy Modeling And Rule Optimization For Intelligent Prediction Of Bioreactor Dynamics, Kamala Najaf Mammadzada

Chemical Technology, Control and Management

Modeling wastewater bioreactors is a challenging problem in environmental engineering because the processes are constantly changing and the microorganisms do not behave in a linear or predictable way. This makes it difficult to predict and control the system behavior. This research investigates three artificial intelligence approaches for modeling wastewater bioreactors: the Mamdani Fuzzy Inference System (FIS), the Adaptive Neuro-Fuzzy Inference System (ANFIS), and clustering-based fuzzy models. These models help us predict what is happening in the bioreactors. For instance they help us predict how the amount of substances in the water is changing over time like dS₀/dt dSs/dt …

Regular Synthesis Algorithms Of Control Devices In Nonlinear Control Systems, Husan Zakirovich Igamberdiyev, Iskandar Yusupovich Abdurakhmanov, Uktam Farkhodovich Mamirov

Chemical Technology, Control and Management

This paper examines the development of regularized algorithms for synthesizing control devices in control systems for polynomial objects, described by multidimensional Volterra functional series. The synthesis problem is solved using a two-stage procedure. In the first stage, the optimization problem is initially solved for an open-loop system. The second stage involves determining the parameters of the control device, i.e., its impulse response functions, by using the relationship between the characteristics of the open-loop and closed-loop systems. Regular algorithms are presented for finding the impulse response functions of the control device based on methods for regularizing the solution of operator equations …

Increasing The Prediction Accuracy Of Plant Oil Production Processes Through Adjusting The Parameters Of Machine Learning Models, Umidjon Ruziev, M.K. Shodiev, A.T. Rajabov

Chemical Technology, Control and Management

Vegetable oil production is characterized by high variability in output indicators due to nonlinear interactions between raw material parameters, equipment modes, and heat and mass transfer conditions. Existing approaches to applying machine learning in this field, as a rule, do not account for the impact of hyperparameter adjustments on forecasting quality across specific technological stages. The article presents a systematic methodology for adjusting model parameters (Ridge regression, SVR, GBM, LSTM) applied to three key tasks: predicting residual oil content in oil cake, color index during bleaching, and free fatty acid content during deodorization. In a set of 1000 observations, including …

Rdm Interval Arithmetic Based Weapon System Evaluation, Konul Imran Jabbarova Phd

Chemical Technology, Control and Management

For solving this issue, the paper considers a hierarchical multi-criteria decision-making problem, where the choice of a company that corresponds best to the criteria is required. Data used in this problem are presented in the form of intervals, which makes it possible to cope with uncertainty in the problem solution. Several companies working in missile production industry are chosen as alternatives for analysis. Evaluation of the selected alternatives is made based on five criteria clusters. More than twenty criteria are taken into account during evaluation.

Solving this problem is achieved with the help of the technique based on computation of …

Reliability Analysis Of Separator Control Systems, D.P. Muxitdinov, O.U. Sattarov, M.Sh. Nematov

Chemical Technology, Control and Management

This article aims to enhance the reliability, efficiency, and diagnostic capabilities of gas-liquid separators operating in hazardous technological processes. In the study, the separator is considered as a critical functional unit of an industrial system and is analyzed through structural and functional decomposition. The main operating parameters of the separator, including pressure drop (ΔP), separation efficiency and operational state are described on the basis of a mathematical model. In addition, a state model is developed for normal operation, foaming, liquid droplet carryover with the gas flow, and failure conditions. Emphasis is placed on diagnostic and monitoring issues, …

Consistency-Based Computing Of Fuzzy Eigenvalues And Fuzzy Eigenvectors: Method And Application, Kamala. R. Aliyeva Prof., Nihad Mehdiyev, Shamil Mehdi

Chemical Technology, Control and Management

The computation of eigenvalues and eigenvectors under uncertainty is a fundamental problem in fuzzy linear algebra and decision analysis. When matrix elements are represented by fuzzy numbers, classical spectral methods cannot be directly applied due to nonlinearity, ambiguity in ordering, and the propagation of uncertainty. Moreover, in many practical applications, particularly those involving pairwise comparison matrices, the reliability of eigenvalue-based results strongly depends on the consistency of the underlying data. This paper proposes a consistency-based framework for computing fuzzy eigenvalues and fuzzy eigenvectors that explicitly integrates consistency analysis into the spectral derivation process. The proposed method preserves the fuzzy structure …

Analysis Of Automatic Control Of The Channels And Ditches Cleaning Mechanism Based On Dynamic Indicators, Nasiba Siraj Amirbayova

Chemical Technology, Control and Management

The article deals with the automated design and experimental investigation of reinforced concrete irrigation channels and ditches, their interrelated channel-cleaning mechanisms, which are complex mechatronic systems integrating hydraulic, mechanical, and electronic components. A thorough methodology is suggested, hydrodynamic modeling, combining parametric analysis, and information-based design support to enhance channel concrete cover thickness, geometry, and cleaning system performance. Main structural parameters—involving channel depth, slope, bottom width, and concrete cover—are systematically defined and shown in matrix form to facilitate automated calculation and decision-making. Experimental prototypes and Solid Edge-based digital models are employed to verify the methodology, revealing vital interdependencies between structural parameters, …

Structural Decomposition-Based Control Synthesis For Multivariable Systems Using Oblique Projection Operators, Abdukaxxarov Inomjon Ilxom Ugli Mr, Oripjon Olimovich Zaripov, Jasur Usmonovich Sevinov

Chemical Technology, Control and Management

This paper proposes a novel approach to control synthesis for multivariable systems with algebraic constraints using oblique projection operators and their structural decomposition. The method transforms a standard control law into a structured form by decomposing the control input into constraint-satisfying and null-space components. A generalized oblique projector is constructed using a dual matrix, ensuring flexibility in shaping system properties. Furthermore, a recursive decomposition algorithm is developed, allowing the global projector to be represented as a sum of local operators corresponding to subsystem structures. The proposed framework enables modular control design, decoupling of interactions, and efficient implementation for large-scale systems. …

Conceptual Model For Protecting Personal Data By Depersonalization In Information Systems: Principles, Components, And Life Cycle, Zarina Ildarovna Azizova

Chemical Technology, Control and Management

This article presents a systematic approach to personal data protection through depersonalization in the context of regulatory pressure and growing cyber threats. It proposes a comprehensive conceptual model that formalizes the de-identification process as a manageable sequence of steps, from attribute classification and method selection to mandatory verification of the result. The article also provides a comparative analysis of existing depersonalization methods in terms of their applicability within the proposed model. The model serves as a basis for the development of specific algorithms, as demonstrated by the example of a data shuffling approach.

Optimization Of Renewable Energy-Based Alkaline Electrolysis Systems For Sustainable Hydrogen Production, Shokhrukhbek Kozimjon Ugli Bakhramov

Chemical Technology, Control and Management

This paper presents a comprehensive optimization study of hydrogen production systems through alkaline water electrolysis powered by photovoltaic energy sources, with a specific focus on Central Asian applications. The research systematically investigates critical operating parameters including KOH electrolyte concentration (25-30 wt%), temperature effects (25-80°C), current density optimization (100-500 mA/cm²), and electrode material performance using cost-effective 316L stainless steel. Experimental results demonstrate that optimized systems achieve solar-to-hydrogen efficiency of 13-15%, with hydrogen production costs ranging from $2-8/kg depending on system scale. The study reveals that maximum performance occurs at 30 wt% KOH concentration, 60-80°C operating temperature, and 200-400 mA/cm² current density. …

Using Ali-4 Z-Implication In Controller Design, Shamil Azer Ahmadov

Chemical Technology, Control and Management

One of the widely used theories in the information processing is Professor Zadeh's fuzzy logic theory. Fuzzy implications form the basis of this theory. When processing information using fuzzy implication, the chosen judgment method and the type of implication affect the result. Referring to the review of the relevant literature on fuzzy implications, it can be noted that there are still unresolved problems and issues. For example, fuzzy implications cannot be used in processing imperfect information or information based on probabilistic and fuzzy uncertainty. Existing fuzzy implications face limitations in practical applications. Fuzzy implications only take into account inaccuracy, but …

Uncertainty Handling In Stock Market Prediction: A Fuzzy Markov Chain Approach, Alpa Singh Rajput, Arpan Singh Rajput

Neutrosophic Systems with Applications

Predicting the stock market is never easy because it is influenced by many uncertain and constantly changing factors such as economic conditions, investor behaviour, and global events. Traditional models like the Crisp Markov Chain (CMC) try to predict market movements by using fixed probabilities for different states like bullish, bearish, or stagnant. However, real markets do not behave in such a strict way—they often move gradually between states, which these models fail to capture. To overcome this limitation, this study introduces a Fuzzy Markov Chain (FMC) model, where fuzzy logic is used to handle uncertainty and allow smoother transitions between …

Modeling Agentic Artificial Intelligence Uncertainty In Agriculture Based 6generation: A Hybrid Q-Rung Orthopair Fuzzy Mcdm Methodology, Zekra Sakr, Mona Mohamed

Neutrosophic Systems with Applications

In era of advanced intelligent revolutions, the collaboration between intelligent technologies became imperative. For instance, integrating 6G communications with agentic artificial intelligence considered a catalyst to shift agriculture sector into optimized and intelligence sector. This integration resulted in transitioning the sector from static automation to autonomous, agent-based ecosystems. Accordingly, the efficiency roles for artificial intelligence agents (AIAs), deploying and selecting optimal AIA is important. Yet, selection process is still difficult because agricultural criteria are multifaceted and there are inherent environmental uncertainties. To address these challenges and bolster the selection process, this paper suggests a hybrid multi-criteria decision-making (MCDM) that bolstered …

An Improved Logarithmic Ratio-Product Type Estimator For Mean Modeling And Estimation Under Neutrosophic Uncertainty, Anchal Yadav, Mukesh Kumar

Neutrosophic Systems with Applications

In classical statistics, population mean estimation generally assumes precise and determinate data along with known auxiliary information. However, in real-world situations where observations are imprecise or expressed in interval form, such as temperature variations or financial market data, classical approaches become less effective. To address this limitation, neutrosophic statistics provide a more flexible framework for handling uncertainty and indeterminacy. This study proposes a neutrosophic logarithmic ratio-product type estimator for estimating the finite population mean using auxiliary information. The bias and mean squared error (MSE) of the proposed estimator are derived using a first-order approximation. Furthermore, performance evaluation is carried out …

Enhanced Parametric Approach For Solving Interval-Valued Trapezoidal Neutrosophic Linear Fractional Programming Problems, Hamiden Abd El- Wahed Khalifa H.A.Khalifa, Moodi Abdulrahman Abdullah Al-Rajeh, Sultan S. Alodhaibi

Neutrosophic Systems with Applications

Neutrosophic sets (NSs) generalize the classical versions, by providing a flexible framework capable of representing incomplete, inconsistent, and unclassified data that frequently arises in practical decision frameworks. In this study, a linear fractional programming (LFP) problem with uncertain parameters is investigated. All coefficients in the objective function (OF) as well as the left- and right-hand sides of the constraints are represented using fully trapezoidal neutrosophic numbers (NNs). By employing a suitable score function, the proposed neutrosophic LFP model is transformed into an equivalent scalar LFP problem. Subsequently, a parametric solution procedure is established to regulate the neutrosophic optimum solution. This …

Gauss Elimination Method For Solving The System Of Neutrosophic Linear Equations, Elsayed Badr, Shokry Nada, Saeed Ali, Aya Rabie

Neutrosophic Systems with Applications

This paper proposes a unified computational framework for solving linear systems under trapezoidal Neutrosophic uncertainty. The system is formulated as A( I )x = b( I ), where both the coefficient matrix and the right-hand side vector incorporate an indeterminacy parameter I, expressed as A( I ) = A₀ + IA₁ and b( I ) = b₀ + Ib₁. A decomposition strategy is developed to separate the model into deterministic and indeterminacy components, yielding a solution of the form x( I ) = x₀ + Ix₁. The deterministic component is obtained via …

Implementation Of Kansei Engineering Method In Designing Spreadable Cheese Packaging, Novi Purnama Sari, Mega Analisa, Suci Puji Lestari, Khofifah Nur Amalia

Makara Journal of Technology

Some spreadable cheese packaging uses flexible plastic without additional features and easily damaged boxes. This packaging causes several problems, such as difficulty in re-storage, loss of product information due to damaged box packaging, wasteful use of packaging materials, and making the product less hygienic. The purpose of this study is to develop packaging that focuses on consumer emotions. The packaging was developed using the Kansei Engineering method, supported by Principal Component Analysis (PCA) as a determinant of the design concept, and Quantification Theory Type 1 (QTT1) to identify design elements. This study produced 46 packaging samples and 40 Kansei words. …

The Impact Of People Interests In Evaluating The Open Public Spaces' Quality In The City Centre, Hasan Hadi, Adil Al-Saidi, Haitham Alshamari

HBRC Journal

The quality of open public spaces in city centres significantly affects people's satisfaction and responses to their built environment. The significance of these areas allow people to assess their performance. this paper addresses the issue of People's interests that affect their evaluation of public urban spaces in city centres. The research applied an ontological methodology that is people's experiences determine the spatial quality of the public spaces in city centres. In order to discover and assess the seven value variables, it recommended diagnosing a random sample of users as a group (A) and (B). The urban space in the historic …

Mapping The Void In Electric Vehicle (Ev) Adoption Research: Uncovering Lack Of Socio-Economic Study In The Global South, Satvik Pandey, Rahul Tiwari, Rajat Soni

Mansoura Engineering Journal

Electric Vehicles (EVs) are considered an effective contemporary alternative to Internal Combustion Engine (ICE) vehicles. Research in the domain of EV is being conducted globally across a variety of fields; among them, our study explored research on consumer adoption. Going through the bibliometric analysis of the data taken from the Scopus database, what came to our attention is the minimal amount of work that is done on understanding consumers of EVs. From the literature, we found that consumer preferences are shaped through the influence of several parameters related to EVs, and this influence varies according to the consumer’s socio-economic and …

Multicriteria Analysis Of Vehicle Exhausts Emission Using Fuzzy Analytic Hierarchy, Sunday Ayoola Oke, Ibraheem Adedotun Abdul, Ismaila Badmus, John Rajan, Swaminathan Jose, Adekunle Adetayo Yekinni, Kabiru Alani Olaiya, Mofoluwaso Kehinde Adeniran, Pandiaraj Benrajesh

Makara Journal of Technology

This study employs the fuzzy analytic hierarchy process (FAHP) to identify the critical factors and their degree of relevance to the vehicle emission process. Its innovation lies in the potential to blend ambiguity and uncertainty with the established AHP. FAHP transforms information into a defuzzification state through signal-to-noise ratios, normalization, and pairwise comparison. The principal parameters considered are revenue, sold packing units, CAGR, packing materials, consumption, and CO2 emissions (A, B, C, D, E, and F, respectively). From the normalized defuzzified weight result, consumption (Parameter E) is the best (normalized weight, 0.8685917), while CO2 emissions (Parameter F) was the worst …

The Pid-Based Three Quadcopter Uavs Formation Control Under External Disturbance, Vo Van An, Trinh Luong Mien

Makara Journal of Technology

This paper presents the design and evaluation of a formation control strategy for three quadcopter UAVs, based on a PID controller in a leader–follower structure, under the influence of external disturbances. Each UAV employs a six-degree of-freedom dynamic model and utilises a cascade PID control architecture, in which the inner control loop stabilises the attitude. In contrast, the outer control loop regulates position and maintains the formation. The PID parameters are tuned using the Ziegler–Nichols method to ensure simple implementation and low computational cost. The performance of the control system is evaluated through simulations in the MATLAB environment for two …

Molecular Catalysts For Electrochemical Nitrogen Activation Toward Sustainable Ammonia Synthesis, Jin-Xiu Han, Hao Xue, Xian-Biao Fu

Journal of Electrochemistry

Homogeneous electrocatalytic nitrogen reduction reaction (NRR) provides a powerful framework to interrogate molecular nitrogen-fixation pathways under mild conditions. By tuning the metal center, ligand architecture, and reaction medium, these systems enable capturing key intermediates and delivering mechanistic insight at the molecular-level resolution. Nevertheless, advances remain constrained by highly reduced operating potentials, intense competition from the hydrogen evolution reaction (HER), limited durability in turnover, and inadequate long-term stability.

In this review, we take electron delivery to the molecular active site as the guiding principle for organizing homogeneous electrochemical N₂ activation and transformation. We classify reported systems into direct electron transfer …

Water-Driven Solid Electrolyte Interphase Governs Continuous-Flow Ammonia Electrosynthesis, Peng-Bo Liu, Sheng-Liang Zhai, Ji Huang, Zhong-Shuo Zhang, Jie Zeng, Shao-Feng Li

Journal of Electrochemistry

Flow-cell architectures have emerged as a powerful platform for continuous and stable lithium-mediated nitrogen reduction (Li-NRR), enabling ambient-condition electrochemical ammonia synthesis and offering a promising alternative to Haber-Bosch processes. However, Li-NRR is exceptionally sensitive to trace water, and even minor variations in water content can profoundly alter interfacial chemistry. Here, we systematically investigate how initial water concentration affects Li-NRR performance in a continuous-flow cell. Excess water drives the formation of a thick solid electrolyte interphase (SEI) layer, which may impede nitrogen access to metallic lithium and hinder lithium-ion transport. As a result, the ammonia Faradaic efficiency collapses from ~61% to …

Insertion Of Noble Metal Free Cathodic Catalyst Layer With Fe-N-C Catalyst For Boosted Performance Of Pemfc, Shi Zhou, Muhammad Tariq, Asif Nadeem Tabish, Muhammad Salman, Fan-Di Ning, Muhammad Rayyan Tayyab, Ran-Ran Peng, Meng-Geng Hao, Wen-Mu Li, Xiao-Chun Zhou

Journal of Electrochemistry

Economical Fe-N-C catalysts are considered as promising alternatives to platinum group metal catalysts for proton exchange membrane fuel cells (PEMFCs). Despite exhibiting robust activity on rotating disk electrodes, their performance within membrane electrode assemblies often experiences limitations, such as decreased O₂ diffusion, high H₂O₂ formation, low proton conduction, and a lower electron transfer number. In this study, key factors, including proton transport, electron conduction, and gas diffusion within air-breathing PEMFCs, have been investigated by adjusting cathode catalyst layer (CCL) compositions. From the experimental results, the optimal peak power density was obtained when the loading of Fe-N-C …

A Comparative Study Of Tin Electrorefining In Molten Licl–Kcl–Cacl₂: Experimental Two-Electrode Current Control And Theoretical Three-Electrode Potential Control, Bryant Johnson, George Ankrah, Ander Fuller, Devin Rappleye

Reviews, Analyses, and Instructional Studies in Electrochemistry (RAISE)

Molten salt electrorefining is a mature technology for metal recovery, yet conventional current‑controlled, two‑electrode operation provides limited electrochemical selectivity and restricted insight into electrode‑specific behavior. In this work, a simplified model is developed to compare current‑controlled two‑electrode electrorefining data with a potential‑controlled three‑electrode electrorefining simulation using tin in molten LiCl–KCl–CaCl₂ as a surrogate for plutonium processing. The model examines anodic and cathodic limitations under fixed‑potential operation and evaluates implications for selectivity, efficiency, and runtime relative to experimentally demonstrated two‑electrode performance. Results indicate that independent potential control enables operation closer to thermodynamic selectivity limits, with the potential to suppress impurity oxidation …

Evaluation Of Quantification Methods Applied To Overlapping Ftir Features, Benjamin P. Diehl

Reviews, Analyses, and Instructional Studies in Electrochemistry (RAISE)

Quantifying overlapping FTIR spectral features is critical for electrochemical analysis but often requires complex deconvolution. This work systematically evaluates several area ratio and proxy-based quantification methods using a controlled synthetic spectral model with varying signal-to-noise ratio, peak spacing, width, background, and data resolution. Constrained peak fitting and fixed-window integration consistently exhibit near-perfect monotonicity (Spearman ≈ 1.000) and linearity (Pearson ≈ 0.999–1.000) across all conditions. In contrast, derivative and moment-based metrics show sensitivity to peak overlap, width, and background. These results demonstrate that physically grounded area-based methods provide the most robust and reliable quantification of overlapping FTIR features.