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In order to obtain stable and reliable configuration transformation ability, reliability optimization design is regarded as an effective way to reduce the probability of kinematic function failure for the constrained metamorphic mechanism. Based on the structural composition principle of multi-configuration source metamorphic mechanism that can operate in an under-actuated state, the modularized calculation methods are established for the force analysis of augmented Assur groups including metamorphic kinematic joints. According to the equivalent resistance gradient model of metamorphic mechanisms, with considering the uncertainties in the link dimensions, masses, and compliance parameters et al., a probabilistic evaluation method for describing the configuration transformation ability of the constrained metamorphic mechanism is established. Based on reliability evaluation and reliability sensitivity analysis, a reliability optimization design method for improving the configuration transformation ability is proposed, and then the optimization design is carried out for tolerances of random variables focusing on those structural parameters with higher reliability sensitivity, so that the optimized results can satisfy the requirements of both reliability and economic simultaneously. Finally, the feasibility and effectiveness of the proposed method is verified by the illustration of a paper folding metamorphic mechanism. The research provides the foundation of reliability design of metamorphic mechanisms to obtain the high-probability repeated execution ability of configuration transformation, it also has theoretical and practical significance to promote the engineering application of metamorphic mechanisms. [ABSTRACT FROM AUTHOR]

Long Short-Term Memory (LSTM)-Based Dog Activity Detection Using Accelerometer and Gyroscope. The third paper, authored by Jeong et al. [[14]], introduced a fall detection system that combines a simple threshold method (STM) and LSTM, creating the STM-LSTM-based fall detection system. With rapid advancements in artificial intelligence (AI), the Internet of Things (IOTs), and communication networks, the future of information and communication engineering (ICE) promises remarkable opportunities and challenges. 10.3390/app12199801 18 Zhang M., Wang C., Zhu W., Shen Y. An Intelligent DOA Estimation Error Calibration Method Based on Transfer Learning. [Extracted from the article]

X. Li, D. Zhang, and Y. Hou [[21]] monitored ground deformation during the excavation process of shield tunnels in water-rich strata and verified the results using the numerical software FLAC 3D. Thus, secondary grouting of the existing tunnel should be carried out promptly before the tunnel underpass excavation. The first paper, authored by X. Li, Y. Yang, X. Li, and H. Liu [[14]], introduced three shield tunnel construction cases to acquire the main driving parameters for the evaluation of cutting head clogging. The second paper, prepared by J. Du, Q. Fang, J. Wang, and G. Wang [[2]], divided the process of a high-speed train passing through a railway tunnel into three stages, according to the spatial relationship between the train and the tunnel. [Extracted from the article]

This article studies the migration and settlement laws of backflow proppants after fracturing tight sandstone. This paper proposes a fitting method based on a multi-task learning network to address the issue of interference from multiple physical parameters during the transport and settlement processes of proppants. This method can effectively handle multi-dimensional interference factors and fit the mapping logic of multiple engineering parameters to transport patterns through the continuous correction of multi-layer networks. We first introduce the characteristics of tight sandstone reservoirs and their important value in mining, as well as the status of current research on the migration and settlement laws of proppants at home and abroad. Based on this, we then deeply analyze the sedimentation rate model of proppants in tight sandstone backflow and the equilibrium height of proppants under multiple factors of interference while considering the distribution characteristics of proppants. In order to more accurately simulate the transport and settlement laws of proppants, this paper introduces a multi-task learning network. This network can comprehensively consider multi-dimensional parameters, learn the inherent laws of data through training, and achieve accurate fitting of the transport and settlement laws of proppants. This study trained and tested the model using actual production data, and the results showed that the proposed model can fit the input–output relationship well, thus effectively supporting the study of proppant transport and settlement laws. [ABSTRACT FROM AUTHOR]

Currently, the fundamental tenets of systems engineering are supported by a model-based approach to minimize risks and avoid design changes in late development stages. The models are used to formalize, analyze, design, optimize, and verify system development and artifacts, helping developers integrate engineering development across domains. Although model-based development is well established in specific domains, such as software, mechanical systems, and electrical systems, its role in integrated development from a system perspective is still a challenge for industry. The model-based systems engineering (MBSE) tool-chain is an emerging technique in the area of systems engineering and is expected to become a next-generation approach for supporting model integration across domains. This article presents a literature review to highlight the usage and state of the art to generally specify the current understanding of MBSE tool-chain concepts. Moreover, the results are used for identifying the usage, advantages, barriers, concerns, and trends of tool-chain development from an MBSE perspective. [ABSTRACT FROM AUTHOR]

With the advent of the era of big data and information technology, deep learning (DL) has become a hot trend in the research field of artificial intelligence (AI). The use of deep learning methods for parameter inversion, disease identification, detection, surrounding rock classification, disaster prediction, and other tunnel engineering problems has also become a new trend in recent years, both domestically and internationally. This paper briefly introduces the development process of deep learning. By reviewing a number of published papers on the application of deep learning in tunnel engineering over the past 20 years, this paper discusses the intelligent application of deep learning algorithms in tunnel engineering, including collapse risk assessment, water inrush prediction, crack identification, structural stability evaluation, and seepage erosion in mountain tunnels, urban subway tunnels, and subsea tunnels. Finally, it explores the future challenges and development prospects of deep learning in tunnel engineering. [ABSTRACT FROM AUTHOR]

With the continuous development of the geological engineering field, high-voltage electric pulse plasma rock-fracturing technology has become a research hotspot in recent years. It is now widely recognized that this fracturing technology has many application prospects and great economic benefits. Through the research process of this technology, it has proven to be an efficient and new type of rock-fracturing technology, which overcomes the problems of high cost, low efficiency, high safety risk, and serious pollution associated with traditional rock-fracturing technology. Also, it has unique advantages in terms of protecting the environment and reducing damage to the surrounding buildings. This paper reviews the research history of plasma shock wave influencing factors and pulsed discharge plasma rock-fracturing technology, summarizes the research on this technology from the perspectives of the mechanism of high-voltage electric pulse plasma rock fracturing and practical application, and discusses the feasibility of this technology when applied to the field of tunnel boring as well as the future development direction. This technology can be better used in the tunnel-boring field, which can greatly improve the tunnel-boring efficiency, but at present, the research on plasma rock-fracturing-assisted tunnel boring is still in the laboratory research stage, which lacks systematic research equipment and judging indexes, and the follow-up should focus on improving the systematic research capabilities of the plasma rock-fracturing-assisted tunnel-boring equipment, and systematically and comprehensively carry out research on rock-fracturing by plasma-assisted excavation equipment. [ABSTRACT FROM AUTHOR]

The digital transformation has created an environment that fosters the development of effective chatbots. Through the fusion of artificial intelligence and data, these chatbots have the capability to provide automated services, optimize customer experiences, and reduce workloads for employees. These chatbots can offer 24/7 support, answer questions, perform transactions, and provide rapid information, contributing significantly to the sustainable development processes of businesses and organizations. ChatGPT has already been applied in various fields. However, to ensure that there is a chatbot providing accurate and useful information in a narrow domain, it is necessary to build, train, and fine-tune the model based on specific data. In this paper, we introduce EduChat, a chatbot system for university-related questions. EduChat is an effective artificial intelligence application designed by combining rule-based methods, an innovative improved random forest machine learning approach, and ChatGPT to automatically answer common questions related to universities, academic programs, admission procedures, student life, and other related topics. This chatbot system helps provide quick and easy information to users, thereby reducing the time spent searching for information directly from source documents or contacting support staff. The experiments have yielded positive results. [ABSTRACT FROM AUTHOR]

The article discusses the evolution stages of the UWB antenna and the parametric analysis of the UWB notch antenna. This collection of research papers explores various aspects of antenna design and high-speed wireless communication, delving into the forefront of technology for modern telecommunications. The fabricated and tested MIMO antenna shows UWB response and good isolation between the antenna elements, making it suitable for UWB MIMO applications. [Extracted from the article]

Featured Application: This work examines the detection of dashed lines in engineering sketches, a subproblem of the more ambitious challenge of automating the reconstruction of 3D models from sketches (sketch-based modeling), which remains unresolved. The detection of dashed lines helps gather valuable information for the interpretation of sketches and consequently improves the quality of the reconstructed 3D models. Sketch-based modeling remains relevant partly because it is aligned with advances in additive manufacturing, e.g., 3D printing, and the mass customization of manufacturing systems. Sketch-based modeling simplifies the CAD/CAM process and allows non-expert users to create their own designs. It also allows designers to quickly create conceptual prototypes of products from sketches, which facilitates the exploration of ideas. Sketched drawings sometimes include non-solid lines drawn as sets of consecutive strokes. They represent dashed lines, which are useful for various purposes. Recognizing such dashed lines while parsing drawings is reasonably straightforward if they are outlined with a ruler and compass but becomes challenging when they are hand-drawn. The problem is manageable if the strokes are drawn consecutively so we can leverage the entire sequence. However, it becomes more challenging if they are drawn unordered, and/or we do not have access to the sequence (like in batch vectorization). In this paper, we describe a new approach to identify groups of strokes as depicting single hand-drawn dashed lines. The approach does not use sequence information and is tolerant with irregularities and imprecisions of the strokes. Our goal is to identify hidden lines of sketched engineering line-drawings, which would enable the interpretation of line-drawings with hidden edges, which currently cannot be efficiently vectorized. We speculate that other fields like hand-drawn graph interpretation may also benefit from our approach. [ABSTRACT FROM AUTHOR]

Tensegrity structures are prestressed and self-stable pin-connected frameworks built up mainly from two kind of elements, in compression (bars) and in tension (tendons). It has been 75 years since the first official appearance of tensegrity, although the present paper includes proof that states that they are in fact more than 100 years old. Throughout these years, tensegrity structures have been capturing engineers', architects' and artists' attention with their peculiar properties. In the last decade, new applications have been found based on tensegrity, although there are not any compilations about them. This paper aims to fill this gap by giving an overview of all the recent real applications that tensegrity has had during its short life, at the same time exposing its potential in all the fields it has contributed to (AEC, robotics, space, etc.) The methodology for performing this review has been revisiting the most relevant publications in several scientific databases. This has led to a new discovery: the first cable-dome by Snelson. As a conclusion, tensegrity has been providing useful solutions to previous problems since they have appeared, but their potential can still grow in an exponential way due to the new technologies and discoveries of the last decade. [ABSTRACT FROM AUTHOR]

Quantum calculus can provide new insights into the nonlinear behaviour of functions and equations, addressing problems that may be difficult to tackle by classical calculus due to high nonlinearity. Iterative methods for solving nonlinear equations can benefit greatly from the mathematical theory and tools provided by quantum calculus, e.g., using the concept of q-derivatives, which extends beyond classical derivatives. In this paper, we develop parallel numerical root-finding algorithms that approximate all distinct roots of nonlinear equations by utilizing q-analogies of the function derivative. Furthermore, we utilize neural networks to accelerate the convergence rate by providing accurate initial guesses for our parallel schemes. The global convergence of the q-parallel numerical techniques is demonstrated using random initial approximations on selected biomedical applications, and the efficiency, stability, and consistency of the proposed hybrid numerical schemes are analyzed. [ABSTRACT FROM AUTHOR]

Featured Application: This work offers a global image of the current use of virtual, augmented, and mixed reality in the field of materials science and engineering, constituting a useful means to open new lines of research and explore new uses of these technologies in this field. The increasing use of reality-virtuality technologies (RVTs, which encompass virtual, augmented, and mixed reality) in different fields over the last decade is a phenomenon for which materials science and engineering (MSE) is no exception. To obtain an overview of the implementation of RVTs in MSE, this team conducted a systematic search of the scientific literature published since 2010 addressing the use of RVTs in MSE. Forty-one relevant papers were selected and analyzed in depth to reach several conclusions, including: (i) most of the works (67.3%) are focused on the MSE area of materials structure, processing, and properties, which implies that there are great possibilities for research in other MSE areas; (ii) most of the works (86.8%) are aimed exclusively at education or research, which means that there are many fields outside of the university in which the use of RVT tools has not been developed and evaluated; (iii) the most used technology is virtual reality (85.1%), which means that there are many research possibilities focused on augmented and mixed reality. Researchers can find in the present work examples of the use of RVTs in MSE as well as other relevant information useful to open new lines of research and ideas that can contribute to their current and future work. [ABSTRACT FROM AUTHOR]

In the research proposed by Zeng et al. [[4]], the long-span steel truss slab track was used to analyze a new type of sleeper slab track structure with an experimental method. In order to study the mechanical properties and long-term performance of the new type of sleeper slab track structure, this paper carried out a full-scale indoor modal loading test of the concrete sleeper slab track structure to provide a reference for the engineering application. This paper carried out research on the dynamic effects of LVT heavy-haul railway wheels and rails and provided a technical reference for the structural design of heavy-haul railway track structures. The European Commission is developing a Single European Transport Area and has promoted a modal shift from road to rail to achieve a more competitive and resource-efficient transport system. [Extracted from the article]

The development of Xiongan New Area in Hebei Province, China, as a significant national choice, has considerable strategic significance for the integrated growth of Beijing, Tianjin, and Hebei. This paper proposes a cloud model for the suitability evaluation of the construction of Xiongan New Area based on entropy weight analysis, taking into account the geological conditions, groundwater environment, environmental geological problems, and other factors of the suitability of image city development. According to the research, the suitability evaluation findings for the project building employing the cloud model are in strong accord with those of the traditional model and have some application potential. The evaluation's findings indicate that the project construction in Xiongan New Area is acceptable, with suitable and relatively suitable sites making up 81.4% of the total area and excellent circumstances for project development, construction, and usage. This study offers helpful direction for Xiongan New Area's urban land-space design and serves as a useful point of comparison for studies looking at the viability of other deep Quaternary Plain region engineering buildings. [ABSTRACT FROM AUTHOR]

Moth-flame optimization is a typical meta-heuristic algorithm, but it has the shortcomings of low-optimization accuracy and a high risk of falling into local optima. Therefore, this paper proposes an enhanced moth-flame optimization algorithm named HMCMMFO, which combines the mechanisms of hybrid mutation and chemotaxis motion, where the hybrid-mutation mechanism can enhance population diversity and reduce the risk of stagnation. In contrast, chemotaxis-motion strategy can better utilize the local-search space to explore more potential solutions further; thus, it improves the optimization accuracy of the algorithm. In this paper, the effectiveness of the above strategies is verified from various perspectives based on IEEE CEC2017 functions, such as analyzing the balance and diversity of the improved algorithm, and testing the optimization differences between advanced algorithms. The experimental results show that the improved moth-flame optimization algorithm can jump out of the local-optimal space and improve optimization accuracy. Moreover, the algorithm achieves good results in solving five engineering-design problems and proves its ability to deal with constrained problems effectively. [ABSTRACT FROM AUTHOR]

With the growing demand for transportation, there has been a significant increase in road-related projects, leading to potential risks in the safety of existing structures. This paper presents a study on the influence of new tunnel construction on the stability of an adjacent existing tunnel and provides valuable insights for the safety technology evaluation of similar tunnel crossing projects. In order to evaluate the influence of tunnel excavation on adjacent tunnels, the excavation process of a new tunnel near the original tunnel is simulated using the finite element software Midas GTS. This analysis includes the evaluation of static and dynamic responses. The results indicate that the horizontal and vertical displacements caused by the excavation of the railway tunnel are minimal. Furthermore, during the blasting excavation of the railway tunnel, the vibration velocity experienced by the highway tunnel remains below the safe allowable limit. These findings demonstrate that in this project, the influence of blasting excavation for the railway tunnel on the highway tunnel is both safe and manageable. [ABSTRACT FROM AUTHOR]

With the rise of the fourth industrial revolution, traditional methods of analyzing investment have been transformed into intelligent methods under big data and the Internet of Things. This has created a new approach to solving practical engineering problems. This paper examines the formation and evolution of the application of inversion theory in tunnel and underground engineering, summarizing research progress using traditional and intelligent inversion analysis methods to identify three types of target unknown quantities in tunnels and underground projects: initial ground stress, support structure load, and tunnel characteristic parameters. It also offers an outlook on how to optimize inversion analysis methods to solve more challenging and complex tunneling problems in the context of informatization, digitalization, and intelligence. In the current research process of tunnel and underground space engineering problems, the inversion theory system has been improved, but inversion analysis methods still face many challenges. These include the low reliability of initial ground stress inversion under complex geological conditions, the lack of indicators to objectively evaluate the accuracy of inversion analysis, and the high costs of intelligent inversion analysis means. Moving forward in the context of big data and the information era, the future development direction for inversion theory and inversion methods in tunnel and underground space engineering is to combine new monitoring technology, computer vision technology, and simulation analysis technology to establish multifaceted intelligent inversion analysis models. [ABSTRACT FROM AUTHOR]

For the mine of large goaf, there are many factors that affect the filling quality. In order to improve the filling quality, it is necessary to identify the factors that have a significant impact. In this paper, the fuzzy mathematical method was used to analyze the five main factors (PC32.5cement sand ratio, slurry concentration, number of slurry lowering, dehydration and drainage, and tailing particle size grading) affecting the filling quality. The priority of each influence factor was calculated, and the priority set was established. It is found that the slurry launching point and particle size grading of the tailings have an obvious effect on filling quality. After increasing the slurry launching point and optimizing the particle size grading, the strength and uniformity of the filling body are improved. [ABSTRACT FROM AUTHOR]

The fractured zone poses a significant risk to construction safety and structure durability in tunnel engineering. However, the effect of excavation methods has not been thoroughly investigated in previous studies. This paper presents a series of 1:30 scale 3D model tests on fault tunnels under the coupling effect of different fault dip angles and construction steps. We measured and analyzed the rock mass deformation and lining structure stress to explore the influence of tunnel excavation by the CD method. The model test results were verified by numerical simulation using the prototype tunnel parameters. Our results show that steeper fault dips correspond to greater radial pressure of the surrounding rock, and pressure in both haunt positions changes more significantly than that in the vault position, while pressure in the side-wall position changes only slightly. Additionally, considerable deformation can be observed in the vault and both haunt positions, with a rock mass relaxation range of less than 1.0 D. For the lining structure stress of each point in the second excavation cycle, larger lining stress is measured in the case of a fault dip of 75° than that in cases when the fault dip equals 45° and 60°, respectively. The biggest stress is observed in the side-wall position after the mid-partition is mantled to form a closed-loop lining structure. Overall, our findings provide valuable insights into the construction response of tunnels through faults and highlight the importance of considering excavation methods in tunnel engineering. [ABSTRACT FROM AUTHOR]

The Faculty of Engineering of the University of Debrecen has a long-standing tradition of developing electric and pneumatic-driven prototype race cars. These vehicles are regular participants in domestic and international university competitions. For more conscious development, thus, for more successful racing, a vehicle dynamics simulation program was developed by our research group. One of the main parts of the above program is the simulation of the drive system, including the electric motor. The input data for the motor simulation programs are the electromagnetic and dynamic characteristics of the motor. Most of these characteristics are usually not specified in the motor catalogue; thus, they have to be measured. In this paper, a detailed description of a recently developed measurement system (MS), which is capable of measuring all the above-mentioned characteristics, is presented. Additionally, by applying it, test measurements can also be performed on the motors to check the accuracy of the output functions generated by the simulation programs. Several experimental arrangements and procedures for specific experimental tasks are also presented here as examples for the application of the MS. [ABSTRACT FROM AUTHOR]

Featured Application: Providing road transportation infrastructure using traditional design methods and materials comes at a considerable cost. The use of naturally available materials using New-age Modified Emulsions (NME) has been successfully implemented and tested. Proven material compatible nanotechnologies enhancement of materials, incorporating modern material sciences can considerably reduce the unit costs of road infrastructure and improve basic service delivery. However, the successful implementation of these new nanotechnology solutions depends on the assessment and scientific evaluation of various factors that will ensure success of implementation as addressed in this paper. Good transportation systems are pre-requisites to economic development. Empirically developed, archaic test methods are traditionally used for materials classification used in road construction. This system normally classifies naturally available materials subjected to chemical weathering conditions, as unsuitable for use in the load-bearing road pavement layers. Consequently, design standards normally require the use of imported materials at considerable costs, severely restricting road network development under scenarios of limited funding. The introduction of applicable nanotechnologies has been shown to enable the use of naturally available materials in all pavement layers at a substantial reduction in costs. The successful roll-out of these nanotechnology solutions depends on a sound, scientifically based approach. Aspects such as toxicity, health and safety, etc. must be addressed in a holistic approach together with material compatibility and fundamental engineering requirements. The successes achieved over the last decade, introducing material compatible New-age Modified Emulsions (NME), are based on fundamental concepts that need to be considered in a holistic test, evaluation and implementation strategy. This paper identifies fundamental concepts related to nanotechnology implementation in the context of road pavement engineering, which needs to be addressed to ensure successful implementation. Ad hoc implementation of new-age technologies without adequate scientific evaluation could prove detrimental. [ABSTRACT FROM AUTHOR]

In view of the problems of rapid construction and deformation control of large cross-section tunnels in complex urban environments, the concept of "timely high-strength support" was put forward to form strong support over time and bear the load of surrounding rock in real time, and innovatively developed the spatial reticulated grid bolt-shotcrete support structure (SRGB). The research in this paper focuses on the supporting principle, bearing mechanical properties, snatch simulation test, construction process, and engineering application effects. The components of the SRGB and their respective functions were expounded in detail. The failure modes and deformation characteristics of the tested components were revealed through the indoor loading test, and the performance characteristics of the spatial reticulated grid concrete components with high strength and high rigidity were displayed. With the help of the multi-functional operation trolley, the assembly process test of the spatial reticulated grid was carried out, which verified the feasibility of mechanized construction and the rationality of structural design. Relying on the underground tunnel project of Guangzhou Metro, the spatial reticulated grid structure was successfully used as the initial support of the tunnel for the first time, forming a complete set of mechanized rapid construction technology for a large cross-section tunnel, and constructing a timely high-strength support system suitable for the complex urban environment. The research results provide a new idea and new technology for the mechanized rapid construction and efficient support of large cross-section tunnels. [ABSTRACT FROM AUTHOR]

In the field of mechanical equipment manufacturing, the focus of research and development is not on weight reduction, but on how to choose between the rigidity and performance of components (such as strength or flexibility). For this contradiction, lightweight is one of the best solutions. The problems associated with lightweight were initially considered and systematically studied in aircraft manufacturing in engineering. Therefore, lightweight has been greatly developed in aviation research and has played an increasingly important role in construction machinery. This paper presents a brief description of the current status of lightweight in machinery by reviewing some significant progress made in the last decades. Potential research topics are also discussed from the four aspects of material, structure, bionics, and manufacturing, and they forecast the development trend of lightweight in the future construction machinery. The entire body of literature about the field is not covered due to the limitation of the length of paper. The scope of this review is limited and closely related to the development of lightweight technology in engineering applications. [ABSTRACT FROM AUTHOR]

Shield tunneling is becoming the preferred construction scheme for metro construction because of its advantages of fast construction speed and small disturbance. However, limited by process defects, the stratum movements induced by the construction of shield tunnels still affects the safety of nearby underground structures and aboveground buildings. Therefore, the reliable prediction of stratum movements is important. Described in this paper is an analysis method of the Greenfield stratum movements (Greenfield is an area of land that has not yet had buildings on it, stratum movements means the movement of various soil layers) caused by shield tunnel construction combining an elastic half-space model of mirror source–sink method with the use of modified analytical method. Based on the theoretical formula in this paper, not only can the curve of surface settlement trough be calculated, but also the three-dimensional displacement field of deep soil can be obtained. By comparing vertical and horizontal contour maps of Greenfield stratum movements, good consistency between theoretical formula results and centrifugal test results are shown. This solves the defects and limitations of existing two-dimensional formulas; furthermore, based on this, it is convenient to evaluate the effect on the other skewed underground structures through the elastic foundation beam and other similar methods; therefore, this paper can provide a wide guidance and service for the design and construction of underground engineering in the future. [ABSTRACT FROM AUTHOR]

This study focuses on the use of petrology as a useful tool in construction applications (i.e., concrete). More specifically, this study investigates how the petrogenetic characteristics of ultramafic rocks derived from ophiolite complexes (Veria–Naousa, Gerania) can act as a key tool for the prediction of the final behaviour of ultramafic aggregates as concrete aggregates. For this reason, their petrographic, chemical and mineralogical characteristics were examined and correlated with their engineering properties for evaluating their suitability as concrete aggregates. This study had come up, for the first time, that the genesis environment of the ultramafic rocks is the determinant factor for their physico-mechanical characteristics. Their suitability is relevant to the impact of their mineralogical and structural characteristics both from the two different ophiolite complexes (Veria–Naousa and Gerania). Except serpentinization, the basic alteration process-index of ultramafic rocks, there are also other chemical indices which can be used for ultramafic rocks that may determine their properties. In this context the term 'fertility rate' (FR) was introduced which may characterize ultramafic rocks as fertile or not. Furthermore, the Ultramafic Rock Health Index (U.R.H.I.) as well as the Normalized U.R.H.I. (U.R.H.I.N) was also introduced and correlated with the engineering properties of the investigated aggregate rocks. The last index aims to assess and quantify the overall health conditions, encompassing the two major modifying factors that include removal of primary mineral phases, as well as the extent of serpentinization. The main conclusion of this paper is that the genesis environment of the ultramafic rocks is the critical factor that determines their mineralogical, petrographic and chemical characteristics which consequently determines the basic engineering properties of rocks that determine their suitability or not as concrete aggregates. [ABSTRACT FROM AUTHOR]

Featured Application: The obtained kinds of borehole camera images of long or deep holes in the tunnels of the building Sichuan-Tibet Railway. Digital panoramic borehole imaging technology has been widely used in the practice of drilling engineering. Based on many high-definition panoramic borehole images obtained by the borehole imaging system, this paper puts forward an automatic recognition method based on clustering and characteristic functions to perform intelligent analysis and automatic interpretation researches, and successfully applied to the analysis of the borehole images obtained at the Wudongde Hydropower Station in the south-west of China. The results show that the automatic recognition method can fully and quickly automatically identify most of the important structural planes and their position, dip, dip angle and gap width and other characteristic parameter information in the entire borehole image. The recognition rate of the main structural plane is about 90%. The accuracy rate is about 85%, the total time cost is about 3 h, and the accuracy deviation is less than 4% among the 12 boreholes with a depth of about 50 m. The application of automatic recognition technology to the panoramic borehole image can greatly improve work efficiency, reduce the time cost, and avoid the interference caused by humans, making it possible to automatically recognize the structural plane parameters of the full-hole image. [ABSTRACT FROM AUTHOR]

Featured Application: The engineering properties obtainable during the construction of road pavement layers using reactive stabilising agents are traditionally determined using a trail-and-error approach based on material indicator tests, some developed more than a century ago. These tests inhibit the limitations associated with an empirically derived test or method, often leading to costly failures. The introduction of proven and applicable nanotechnologies to treat or stabilise granular material for use in pavement layers could result in the rejection of these technologies if not based on the understanding of the basic chemistry of both the stabilising agent and the mineralogy of the granular materials. This article gives a basic explanation of elementary chemistry that will affect the physical engineering properties (stresses and strains) that can be expected using available, proven and cost-effective nanotechnologies to improve granular materials for use in a pavement structure. Nanoscale organofunctional silanes have been developed, tested and successfully applied to protect stone buildings in Europe against climatic effects since the 1860s. The same nanotechnologies can also be used in pavement engineering to create strong chemical bonds between a stabilising agent and granular material. The attachment of the organofunctional silane to a material also changes the surface of the material to become hydrophobic, thereby considerably reducing future chemical weathering. These properties allow naturally available materials to be used in any pavement layer at a low risk. In the built environment, scientists soon determined that the successful use of an organo-silane depends on the type and condition of the stone to be treated. The same principles apply to the implementation of applicable nanotechnologies in pavement engineering. Understanding the basic chemistry, determining the properties of the stabilising agent and the organofunctional modifying agent and the chemical interaction with the primary and secondary minerals of the material are essential for the successful application of these technologies in pavement engineering. This paper explains some basic chemistry, which fundamentally influences engineering outputs that can be achieved using New-age (Nano) Modified Emulsions (NME) stabilising agents with naturally available granular materials in all road pavement layers below the surfacing. [ABSTRACT FROM AUTHOR]

Featured Application: This work may be used to improve the accuracy of attitude stability of flexible meteorological satellites. Periodic disturbance may cause serious effects on the attitude of meteorological satellites, and the attenuation of periodic disturbance is required. In this paper, a fundamental study on the optimal design of constant compensations against known-law periodic disturbance for meteorological satellites is investigated. An analytical solution for the relationship between the frequency and amplitude ratios and the response of a typical second-order vibration system is firstly derived. The compensation and disturbance torques are determined according to practical engineering. The criteria for designing the optimal compensations are based on the analytical and simulation results. Then, the criteria are applied to a flexible spacecraft actuated by constant control torque in the presence of sustained periodic disturbance. The optimal compensation torque parameters for spacecraft are acquired based on former criteria. The compensate effectiveness of the optimal compensation torque is provided and compared with results of other selections in the frequency and amplitude ratio domain. Numerical simulation results and experimental results clearly demonstrate the good performance of proposed criteria. This work provides a significant reference for the vibration attenuation of meteorological satellites in the present of periodic disturbance. [ABSTRACT FROM AUTHOR]

Featured Application: Quick and non-destructive applications of Infrared Thermography on rocks. Infrared thermography is a growing technology in the engineering geological field both for the remote survey of rock masses and as a laboratory tool for the non-destructive characterization of intact rock. In this latter case, its utility can be found either from a qualitative point of view, highlighting thermal contrasts on the rock surface, or from a quantitative point of view, involving the study of the surface temperature variations. Since the surface temperature of an object is proportional to its emissivity, the knowledge of this last value is crucial for the correct calibration of the instrument and for the achievement of reliable thermal outcomes. Although rock emissivity can be measured according to specific procedures, there is not always the time or possibility to carry out such measurements. Therefore, referring to reliable literature values is useful. In this frame, this paper aims at providing reference emissivity values belonging to 15 rock types among sedimentary, igneous and metamorphic categories, which underwent laboratory emissivity estimation by employing a high-sensitivity thermal camera. The results show that rocks can be defined as "emitters", with emissivity generally ranging from 0.89 to 0.99. Such variability arises from both their intrinsic properties, such as the presence of pores and the different thermal behavior of minerals, and the surface conditions, such as polishing treatments for ornamental stones. The resulting emissivity values are reported and commented on herein for each different studied lithology, thus providing not only a reference dataset for practical use, but also laying the foundation for further scientific studies, also aimed at widening the rock aspects to investigate through IRT. [ABSTRACT FROM AUTHOR]

The aim of the current paper is to present a mimetic algorithm called the chaotic evolutionary programming Powell's pattern search (CEPPS) algorithm for the solution of the multi-fuel economic load dispatch problem. In the CEPPS algorithm, the exploration process is maintained by chaotic evolutionary programming, whereas exploitation is taken care off by a pattern search. The proposed CEPPS has two variants based on the Gauss map and the tent map. Seven generalized benchmark test functions and six cases of the multi-fuel economic load dispatch problem are considered for the performance analysis. It is observed from the analysis that the CEPPS solution procedure based on the tent map exhibits superiority to obtain an excellent solution and better convergence characteristics than traditional chaotic evolutionary programming. Further, the performance investigation for the considered economic load dispatch shows that the Gauss map CEPPS solution procedure performs better than the tent map based CEPPS to obtain the solution of the multi-fuel economic dispatch problem. [ABSTRACT FROM AUTHOR]

The vibration of rock breaking in tunnel excavation may cause serious damage to nearby buildings if it is not controlled properly. With reference to a hard rock tunnel in China, the vibration response to the high-pressure gas expansion method (HPGEM), an emerging rock-breaking approach, was investigated with field tests, theoretical derivations, and numerical simulations, then comparisons with the traditional dynamite blast were performed. Firstly, the vibration velocity prediction formulas of the two methods were fitted based on the field tests. Subsequently, the accuracy of the formula was verified by numerical simulation, and the vibration attenuation law of the HPGEM was explored. Comparisons were made between the blast and HPGEM, particularly the differences in peak particle velocity (PPV) for different agent qualities, distance from the blasting center, and engineering conditions. Furthermore, this study also analyzed the relationship between the agent qualities and the rock-breaking volume under different cases, finding that the HPGEM has slight vibration and good rock-breaking effect. The HPGEM is thus fully capable of replacing dynamite blasting to carry out rock-breaking operations in certain special areas. [ABSTRACT FROM AUTHOR]

Extended reality offers unique ways to create mediated spaces that enhance and help popularize experiences across several domains, including entertainment, creativity, and culture. There are still issues that hinder the widespread adoption of the medium, such as the over-reliance on scripted sequences, generalized approaches, and curated asset production. Artificial intelligence can be used to, in part, alleviate these issues, but this comes with its own set of challenges, such as factual inaccuracy or hallucinations. We delve into prompt engineering methods for the GPT API, enhancing context understanding to enable more realistic performances in historical event recreations. Specifically, we experiment with the Great Fire of Smyrna in 1922 as our historical context, situating the AI agent in the middle of chaos as a resident that has been affected by the event. Our experiments demonstrate that refined prompt engineering techniques significantly reduce factual inaccuracies and enhance the emotional resonance of AI-generated dialogues, which can lead to more immersive and engaging XR experiences. Our experiments indicate that AI can effectively support historical recreations by providing dynamic and contextually appropriate interactions. [ABSTRACT FROM AUTHOR]

Excavator–truck operations, characterized by their repetitive excavation and loading tasks, present a prime candidate for automation. While numerous studies have aimed to automate the earthworks, practical implementations remain scarce. This research introduces a task component design focused on excavator–truck operation planning to improve the functionality of an earthwork automation system. To address this, fundamental task primitives necessary for executing excavation tasks were engineered, and a web-based system was developed to automate the generation of work plans for both point and trench excavation through algorithmic processes. Additionally, a JSON-based protocol was introduced to facilitate efficient integration with other subsystems. Field tests were conducted to validate the effectiveness of the newly developed algorithm and protocol within the broader context of earthwork automation systems. The results demonstrated the successful implementation of the task components, confirming their operational viability and seamless integration into the existing earthwork automation framework. [ABSTRACT FROM AUTHOR]

To realize the design process of bionic mechatronic systems, involving mapping from engineering to biology and inversion from biology to engineering, a novel design paradigm is introduced that integrates BioTRIZ with multi-factor coupling bionics. In the mapping stage from engineering to biology, BioTRIZ is employed to frame the concrete engineering issue as a general conflicting problem. The biological solution is refined by amalgamating the BioTRIZ solution derived from the contradiction matrix with biological instances. In the inversion stage of biology to engineering, a novel approach is proposed for constructing a bionic multi-factor coupling model, drawing inspiration from the establishment of biological multi-factor coupling model. This allows for a seamless correspondence between biological elements, such as morphology and behavior, and their respective engineering counterparts, including structure and algorithms. This correspondence ultimately achieves the engineering conceptual model that is rooted in biological principles. The practical application of this methodology is exemplified through a multi-biometric fusion bionic active vision system, underscoring its feasibility and efficacy. [ABSTRACT FROM AUTHOR]

A battery track engineering vehicle faces challenges such as derailment and other safety concerns when navigating an R20m minimum radius curve, primarily owing to its low vertical and horizontal stabilities. To address these issues, a methodology integrating genetic optimization algorithms with a rigid and flexible coupled multi-body dynamics simulation is proposed to optimize the primary suspensions of the bogie of the vehicle. Initially, a multi-objective optimization model combining rigid and flexible coupled multi-body dynamics of battery track engineering vehicles with a genetic optimization algorithm was formulated. Subsequently, the optimal Latin hypercube design was applied to analyze the sensitivity of vertical and horizontal stability to various suspension parameters. Finally, a non-dominated sorting genetic algorithm (NSGA-II) and an archive-based micro genetic algorithm (AMGA) were applied to optimize the primary suspensions to enhance stability. Consequently, a set of optimal suspension parameter combinations was obtained. A notable enhancement was observed in the lateral stability of the optimized battery track engineering vehicles by 23.33% and in the vertical stability by 3.5% when traversing the R20m minimum radius curve, thereby establishing a theoretical foundation for further improving the running safety of railway vehicles and resolving the shortcomings of less research on the smallest radius curve. [ABSTRACT FROM AUTHOR]

As vehicles with high accident and casualty rates within the road transportation system, engineering vehicles have been receiving much attention and emphasis in terms of safety. Accurate analyses and evaluations of risk factors in vehicle operation are imperative for enhancing the management level of engineering vehicles. This study explores the differences between various types of drivers by analyzing the driving characteristics of professional drivers. The evaluation index system is developed and quantified by integrating factors related to engineering vehicle drivers, road environment, and industry management. Additionally, the risk assessment model is developed using the error backpropagation algorithm. The optimal model is determined by comparing the number of nodes in different hidden layers, the activation function, and regularization optimization. The prediction accuracy of this model's coefficient of determination is 0.912, indicating that the model has validity. This study is conducive to improving the safety level of engineering vehicle operation in order to reduce the rate of vehicle traffic accidents, the severity of accidents, and the consequences of losses. It also has practical application value in safeguarding social security. [ABSTRACT FROM AUTHOR]

In the context of Industry 4.0, industrial environments are at a crossroads, facing the challenge of greater flexibility and significant technical skills gaps. In this situs, Augmented Reality (AR) emerges as a transformative tool, enhancing the synergy between technical staff and emerging technologies. This article focuses on exploring the integration of AR in Industry 4.0, with a particular emphasis on its role in improving technical assistance and training. The research addresses the ways in which AR not only facilitates more efficient processes but also acts as an essential bridge for training and skills development in constantly changing technological environments. It investigates the significant impact of AR on both optimising work processes and training workers to meet the emerging challenges of Industry 4.0. Through a qualitative analysis, the studies are categorised according to their application domains, grouping them into specific thematic areas. Subsequently, a meta-analysis is conducted to determine the actual impact of AR in the sector. The findings reveal a positive and significant correlation between the implementation of AR and its effectiveness in assistance and training in the framework of Industry 4.0. Finally, the article delves into an analysis of current limitations and challenges, providing insights into possible developments and trends in the use of AR for assistance and training in Industry 4.0. [ABSTRACT FROM AUTHOR]

10.3390/app9224820 12 Li T., Su Q., Kaewunruen S. Saturated Ground Vibration Analysis Based on a Three-Dimensional Coupled Train-Track-Soil Interaction Model. Cai et al. [[16]] developed a series of shaking-table tests for a ten-story suspended concrete structure that was equipped with viscous dampers in order to evaluate the dynamic responses and vibration damping performance of suspended structures. Due to uncertainties stemming from climate change, natural and man-made disasters, and extreme events, unexpected disruptions in the operation of our countries' infrastructure may put the functioning of our societies and their economies at risk. 10.3390/app9234991 13 Hamarat M., Papaelias M., Silvast M., Kaewunruen S. The Effect of Unsupported Sleepers/Bearers on Dynamic Phenomena of a Railway Turnout System under Impact Loads. [Extracted from the article]

Marchenko et al. [[2]] reported an autonomous power system that consists of photovoltaic converters, wind turbines, storage batteries, a biomass gasification power plant, and a diesel power plant. This method is the most efficient compared with the active frequency drift method with positive feedback, and is able to protect utility service personnel and power system equipment from the islanding phenomenon of distributed generation. At present, the field of thermal power engineering is dominated by the following two main areas of development: (1) the development and implementation of new technologies using renewable energy sources; and (2) upgrading commonly used power-generation technologies by improving the efficiency of industrial equipment and optimizing operating conditions. [Extracted from the article]

The goal of computer-aided surgery is to supplement human limitations in surgery, improve the consistency of surgical procedures, and achieve higher quality surgical operations while reducing the time they take. 10.3390/app11199122 2 Lee J., Lee C., Chung D., Lee H., Park J. Analysis of Age-Based Bone Mineral Density in the Korean Adult Population Using Dual-Energy X-ray Absorptiometry. Kim et al. [[9]] evaluated the potency of a deep-sea water thalassotherapy (DSWTT)-based exercise program on fatigue and muscle rehabilitation, with findings indicating a considerable effect on muscle recovery in particular. [Extracted from the article]

Nowadays, services related to IT technologies have assumed paramount importance in most sectors, creating complex systems involving different stakeholders. Such systems are subject to unpredictable risks that differ from what is usually expected and cannot be properly managed using traditional risk assessment approaches. Consequently, ensuring their reliability represents a critical task for companies, which need to adopt resilience engineering tools to reduce the occurrence of failures and malfunctions. With this goal in mind, the current study proposes a risk assessment procedure for cloud migration processes that integrates the application of the Functional Resonance Analysis Method (FRAM) with tools aimed at defining specific performance requirements for the suppliers of this service. In particular, the Critical-To-Quality (CTQ) method was used to define the quality drivers of the IT platform customers, while technical standards were applied to define requirements for a security management system, including aspects relevant to the supply chain. Such an approach was verified by means of its application to a real-life case study, which concerns the analysis of the risks inherent to the supply chain related to cloud migration. The results achieved can contribute to augmenting knowledge in the field of IT systems' risk assessment, providing a base for further research. [ABSTRACT FROM AUTHOR]

A new 3D mesoscale computational approach to simulate the mechanical behavior of soil–rock mixtures (SRMs) with the consideration of the grain-crushing process is proposed in this study. The proposed approach adopts a random SRM mesostructure generation algorithm to create a random SRM structure. Based on the generated mesostructure, the whole simulation area is divided into discrete cubic numbers, and the mesostructure is transformed into a material distribution matrix as an input for the computational approach. The computational approach is achieved by the coupling calculation of Matlab and COMSOL. Theimulations are presented alongside experimental data to validate the efficiency of the proposed approach. The simulation results indicate that the proposed computational approach can accurately capture the mechanical behavior of SRMs under loadings. This method helps to predict the physical properties of SRMs and has promising applications in engineering. [ABSTRACT FROM AUTHOR]

Effective product styling designs must increasingly address users' emotional requirements. This study introduces a product styling design method combining electroencephalography (EEG) and eye tracking for multimodal measurement based on the Kansei engineering theory. The feasibility of determining a target image using a similarity calculation model is verified. An experimental paradigm based on implicit measures is presented for product styling cognition research. This paradigm involves determining the target image, sample selection, target image matching experiments, and product styling cognition experiments. Based on the combined EEG and eye-tracking measurements, insights into product-form cognition are deduced to provide a scientific basis for product-form innovation design. Notably, variations in event-related potential during user cognition of product styling are more evident in the product-styling perception phase than in the evaluation phase. In the styling perception phase, samples with "high match" with the target image elicit more pronounced EEG responses than those with "low match". These findings demonstrate the viability of understanding product-form cognition through multimodal implicit measurements, addressing issues such as the pronounced subjectivity inherent in traditional methods. Furthermore, this approach provides a pioneering technique for Kansei engineering research and offers a methodology for multimodal implicit measurements of product innovation design. [ABSTRACT FROM AUTHOR]

The use of geomaterials spans long back into human history and relicts of man's endeavours remain as evidence of practical use of rocks and minerals for the benefit of evolving societies. This was made by calcining limestone with clay to produce cement clinker that could be ground and mixed with water to produce a waterproof ("hydraulic") cement. The solutions were considered by Gartner [[9]] who described low energy cement clinkers: (A) Pozzolan-based cements. Developments throughout the late 19th and early 20th centuries saw industrialisation of cement production on a global scale, such that by the mid-twentieth century, cement and concrete were the preferred materials for construction in many projects. [Extracted from the article]

Multiferroic ceramic composites have been engineered to incorporate multiple desired physical properties within a single ceramic component. The objective of this study was to create such composites through pressure less sintering ferroelectric-doped PZT and nickel–zinc ferrite at a temperature of 1250 °C. The growth of ferrite grains was found to be influenced by the concentration of the ferroelectric PZT phase. Consequently, an increase in the ferrite content decreased the average particle size of nickel–zinc ferrite by a factor of 1.8. After impedance spectroscopy, the multiferroic ceramic composites can be categorized into two groups: those with low ferrite content (<20%) and those with a high ferrite content (>20%). Composites with a high ferrite content are suitable for dual-band filters or shield applications. The impedance spectroscopy analysis revealed that the resonance frequency can be shifted to higher frequency ranges. Therefore, it was demonstrated that modifying the composition of the multiferroic composite allows for tailoring the impedance behavior to shield living and working spaces against such radiation to meet the demands of the 21st century. [ABSTRACT FROM AUTHOR]

10.3390/app11198875 28 Chen F., Du Y., Qiu T., Xu Z., Zhou L., Xu J., Sun M., Li Y., Sun J. Design of an Intelligent Variable-Flow Recirculating Aquaculture System Based on Machine Learning Methods. The monograph presents an extract from the reality of smart agriculture, where the combination of modern technologies, innovative solutions, and sustainable approaches to food production classifies this part of science as highly interdisciplinary, multifaceted, and technologically advanced. Contemporary Systems for Intelligent Farming This monograph delves into various aspects of intelligent agriculture research, covering studies of crop diseases, pest detection, plant nutrition, precision farming technologies, and post-harvest techniques using machine learning-based artificial intelligence algorithms. This monograph aims not only to provide an understanding of smart agriculture, but also to inspire the reader to think about the future of agriculture and the ways in which modern food production methods can be improved. [Extracted from the article]

The recycling of waste materials has become an important topic worldwide. Wastes can be effectively used in concrete to improve its characteristics. This study aimed to research cement mortar's physical properties, mechanical properties, and durability. In a cement mortar with a fixed water-to-binder ratio (W/B) of 0.5, waste polyethylene (PE) was added at sand volume ratios of 0%, 1%, 2%, 3%, and 4%. Cement was replaced with 0%, 10%, and 20% ground granulated blast furnace slag (GGBFS). The results showed that the slump and flow of mortar tended to decline as the added amount of waste PE increased, but they also increased with the increased replaced amount of GGBFS. The setting time of mortar was shortened as the waste PE increased but delayed as the amount of GGBFS increased. In terms of mechanical properties, the compressive strength of mortar declined as the replaced amount of waste PE increased. Using the GGBFS to replace part of the cement can improve the later mortar strength. This study found that when the added waste PE was within 2% and the replacement amount of GGBFS was 10%, the goal of recycling waste was reached most effectively, while maintaining the concrete's mechanical properties. [ABSTRACT FROM AUTHOR]

Nowadays, the Internet of Things (IoT) devices and applications have rapidly expanded worldwide due to their benefits in improving the business environment, industrial environment, and people's daily lives. However, IoT devices are not immune to malicious network traffic, which causes potential negative consequences and sabotages IoT operating devices. Therefore, developing a method for screening network traffic is necessary to detect and classify malicious activity to mitigate its negative impacts. This research proposes a predictive machine learning model to detect and classify network activity in an IoT system. Specifically, our model distinguishes between normal and anomaly network activity. Furthermore, it classifies network traffic into five categories: normal, Mirai attack, denial of service (DoS) attack, Scan attack, and man-in-the-middle (MITM) attack. Five supervised learning models were implemented to characterize their performance in detecting and classifying network activities for IoT systems. This includes the following models: shallow neural networks (SNN), decision trees (DT), bagging trees (BT), k-nearest neighbor (kNN), and support vector machine (SVM). The learning models were evaluated on a new and broad dataset for IoT attacks, the IoTID20 dataset. Besides, a deep feature engineering process was used to improve the learning models' accuracy. Our experimental evaluation exhibited an accuracy of 100% recorded for the detection using all implemented models and an accuracy of 99.4–99.9% recorded for the classification process. [ABSTRACT FROM AUTHOR]

Featured Application: In the context of the widespread use of industrial robot modules, this study proposes a method for designing and evaluating the morphological characteristics and combination schemes of industrial robot modules, which meets the research and application needs of Kansei Engineering in robot module design. How to effectively match the relationship between users' perceptual demands and the characteristics of industrial robot modules becomes a pressing issue when perceptual demands become a significant determinant of whether users purchase and employ industrial robots. In this regard, we propose a Kansei Engineering-based method for industrial robot module configuration, using the module design of a glass substrate transfer robot as an example. First, the method analyzes the perceptual demand characteristics of the target user, utilizing the semantic difference method, and then establishes a mapping relationship between the user's perceptual demand and the robot design elements, utilizing the hierarchical inference method. On the basis of this mapping relationship, the robot module for transfer glass substrates is then designed. Finally, orthogonal design and conjoint analysis were used to effectively and objectively analyze user preferences for various module configuration alternatives. The results indicate that the industrial robot's shape, color, and material are the three appearance characteristics that influence the user's perceptual demands. The slender, rigid design features of the industrial robot, such as the streamlined drive shaft, lengthwise expanded body structure, integrated body structure, and hidden plugs, as well as the simple color scheme and smooth metal surface, are key elements in the industrial robot's perceptual design. The turn shaft module and lift shaft module have respective weights of 35.040% and 31.120%, determining whether the glass substrate transfer robot can create a simple style. In the context of the widespread use of industrial robot modules, the methods and findings of this study offer new ideas for the design of industrial robot modules and broaden the research and applications of Kansei Engineering in module design. [ABSTRACT FROM AUTHOR]