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In this paper, I discuss the emerging field of conceptual engineering from the perspective of the philosophy of mind and cognitive science. I explore the role the latter disciplines can and do play by specifically focusing on how different notions of what a concept is affects the general conceptual engineering framework, both positively and negatively, before considering a particular account that eschews talk of concepts altogether. I call this project 'Cappelen's challenge' as it draws from suggestive remarks in his work (Cappelen, H. 2018. Fixing Language: Conceptual Engineering and the Limits of Revision. Oxford: Oxford University Press). I argue that by appreciating the range of options that each theory of concepts brings with it, the field as a whole can come to better grips with its foundations. [ABSTRACT FROM AUTHOR]

Conceptual engineering is the method for assessing and improving our concepts. Some have recently claimed that the implementation of such method in the form of ameliorative projects is truth-driven and should thus be epistemically constrained, ultimately at least (Simion, Mona. 2018b. "The 'Should' in Conceptual Engineering." Inquiry: An Interdisciplinary Journal of Philosophy 61 (8): 914–928; cf. Podosky, Paul-Mikhail Catapang. 2018. "Ideology and Normativity: Constraints on Conceptual Engineering." Inquiry: An Interdisciplinary Journal of Philosophy, Online first, 1–15. doi:10.1080/0020174X.2018.1562374). This paper challenges that claim on the assumption of a social constructionist analysis of ideologies, and provides an alternative, pragmatic and cognitive framework for determining the legitimacy of ameliorative conceptual projects overall. The upshot is that one should not ameliorate for the sake of truth or knowledge, in the case of ideologies – at least, not primarily. [ABSTRACT FROM AUTHOR]

In this paper, a unified gas kinetic particle (UGKP) method is developed for radiative transfer in both absorbing and anisotropic scattering media. This numerical method is constructed based on our theoretical work on the model reduction for an anisotropic scattering system. The macroscopic solver of this method directly solves the macroscopic anisotropic diffusion equations, eliminating the need to solve higher-order moment equations. The reconstruction of macroscopic scattering source in the microscopic solver, based on the multiscale equivalent phase function we proposed in this work, has also been simplified as one single scattering process, significantly reducing the computational costs. The proposed method has also the property of asymptotic preserving. In the optically thick regime, the proposed method solves the diffusion limit equations for an anisotropic system. In the optically thin regime, the kinetic processes of photon transport are simulated. The consistency and efficiency of the proposed method have been validated by numerical tests in a wide range of flow regimes. The novel equivalent scattering source reconstruction can be used for various transport processes, and the proposed numerical scheme is widely applicable in high-energy density engineering applications. [ABSTRACT FROM AUTHOR]

Offset boosting is a crucial passage for chaotic signal modification in chaos-based engineering. Searching an offset controller for a 3D chaotic system is usually complex, let alone two independent nonbifurcating offset constants. This paper constructs a class of chaotic systems, providing a single constant posing direct offset boosting for two dimensions. This offset boostable chaotic system regime has multiple typical control modes, including a system variable single control, synchronous common control, reverse control, and differential control. This new type of chaotic systems also finds two-dimensional offset boosting combined with amplitude control. [ABSTRACT FROM AUTHOR]

This research paper presents the Principal Component Analysis (PCA) technique, and its practical application to machine learning. The objective is to address the problem of dimensional reduction or data compression. Based on an intuitive analysis, this document will help bring economists and other professionals in the social sciences closer to these ideas, which are generally alien to their discussions. [ABSTRACT FROM AUTHOR]

In this paper, the authors review extant natural language processing models in the context of undergraduate mechanical engineering education. These models have advanced to a stage where it has become increasingly more difficult to discern computer vs. human-produced material, and as a result, have understandably raised questions about their impact on academic integrity. As part of our review, we perform two sets of tests with OpenAI's natural language processing model (1) using GPT-3 to generate text for a mechanical engineering laboratory report and (2) using Codex to generate code for an automation and control systems laboratory. Our results show that natural language processing is a potentially powerful assistive technology for engineering students. However, it is a technology that must be used with care, given its potential to enable cheating and plagiarism behaviours given how the technology challenges traditional assessment practices and traditional notions of authorship. [ABSTRACT FROM AUTHOR]

The Ion Cyclotron Range of Frequency (ICRF) heating system of the China Fusion Engineering Test Reactor (CFETR) is intended to provide plasma heating with a minimum power output of 20 MW, which demands the Radio Frequency (RF) window to possess a higher performance requirement. This paper presents the design of an RF window for the CFETR ICRF heating system and focuses primarily on the design and confirmation of its electromagnetic performance. The RF window can be effectively matched in the operating frequency range and has an S11 of under −59 dB. The geometry of the cone type ceramics was optimized to reduce the surface tangential electric field distribution. An analysis of the electric field distribution of the RF window at 50 kV indicates that the pressure side was below 2.3 kV/mm and the vacuum side was below 1.3 kV/mm. Furthermore, a transmission line test bench with an open-terminated setup was constructed to conduct withstand voltage tests on the mockup, and the results showed that the mockup could withstand 62 kV for 2 s and 47 kV for 120 s. [ABSTRACT FROM AUTHOR]

Oral and maxillofacial diseases are one of the most prevalent diseases in the world, which not only seriously affect the health of patients' oral and maxillofacial tissues, but also bring serious economic and psychological burdens to patients. Therefore, oral and maxillofacial diseases require effective treatment. Traditional treatments have limited effects. In recent years, nature exosomes have attracted increasing attention due to their ability to diagnose and treat diseases. However, the application of nature exosomes is limited due to low yield, high impurities, lack of targeting, and high cost. Engineered exosomes can be endowed with better comprehensive therapeutic properties by modifying exosomes of parent cells or directly modifying exosomes, and biomaterial loading exosomes. Compared with natural exosomes, these engineered exosomes can achieve more effective diagnosis and treatment of oral and maxillary system diseases, and provide reference and guidance for clinical application. This paper reviews the engineering modification methods of exosomes and the application of engineered exosomes in oral and maxillofacial diseases and looks forward to future research directions. [ABSTRACT FROM AUTHOR]

Polydimethylsiloxane (PDMS)—the simplest and most common silicone compound—exemplifies the central characteristics of its class and has attracted tremendous research attention. The development of PDMS‐based materials is a vivid reflection of the modern industry. In recent years, PDMS has stood out as the material of choice for various emerging technologies. The rapid improvement in bulk modification strategies and multifunctional surfaces has enabled a whole new generation of PDMS‐based materials and devices, facilitating, and even transforming enormous applications, including flexible electronics, superwetting surfaces, soft actuators, wearable and implantable sensors, biomedicals, and autonomous robotics. This paper reviews the latest advances in the field of PDMS‐based functional materials, with a focus on the added functionality and their use as programmable materials for smart devices. Recent breakthroughs regarding instant crosslinking and additive manufacturing are featured, and exciting opportunities for future research are highlighted. This review provides a quick entrance to this rapidly evolving field and will help guide the rational design of next‐generation soft materials and devices. [ABSTRACT FROM AUTHOR]

Quantum dots (QDs) have attracted wide attention from academia and industry because of their advantages such as high emitting efficiency, narrow half-peak width, and continuously adjustable emitting wavelength. QDs light emitting diodes (QLEDs) are expected to become the next generation commercial display technology. This paper reviews the progress of QLED from physical mechanism, materials, to device engineering. The strategies to improve QLED performance from the perspectives of quantum dot materials and device structures are summarized. [ABSTRACT FROM AUTHOR]

An adaptive system is able to adapt at runtime to dynamically changing environments and to new requirements. Adaptive systems can be single adaptive entities or collective ones that consist of several collaborating entities. Rigorous engineering requires appropriate methods and tools that help guaranteeing that an adaptive system lives up to its intended purpose. This paper introduces the special section on "Rigorous Engineering of Collective Adaptive Systems." It presents the 11 contributions of the section categorizing them into five distinct research lines: correctness by design and synthesis, computing with bio-inspired communication, new system models, machine learning, and programming and analyzing ensembles. [ABSTRACT FROM AUTHOR]

Finding all the roots of a nonlinear equation is an important and difficult task that arises naturally in numerous scientific and engineering applications. Sequential iterative algorithms frequently use a deflating strategy to compute all the roots of the nonlinear equation, as rounding errors have the potential to produce inaccurate results. On the other hand, simultaneous iterative parallel techniques require an accurate initial estimation of the roots to converge effectively. In this paper, we propose a new class of global neural network-based root-finding algorithms for locating real and complex polynomial roots, which exploits the ability of machine learning techniques to learn from data and make accurate predictions. The approximations computed by the neural network are used to initialize two efficient fractional Caputo-inverse simultaneous algorithms of convergence orders ς + 2 and 2 ς + 4 , respectively. The results of our numerical experiments on selected engineering applications show that the new inverse parallel fractional schemes have the potential to outperform other state-of-the-art nonlinear root-finding methods in terms of both accuracy and elapsed solution time. [ABSTRACT FROM AUTHOR]

For layered metamaterial devices, the reflection and transmission coefficients at an interface typically depend on the properties of the coupling between different layers. In this paper, we set out to engineer the reflection/transmission behaviour at boundaries to obtain desirable properties such as achieving total reflection and transmission. Based on the quantum graph formulation for modelling metamaterials developed in Sci. Rep. 12 (1), 18006 (2022), we tailor the interface reflection and transmission coefficients by patterning the boundary with resonant elements at each interface vertex. By tuning the internal lengths of the resonant elements, we demonstrate both minimization and maximization of the reflection coefficient via a scattering formulation. In addition, we present an interface set-up incorporating beyond-nearest-neighbour connections, which yields narrow-band transmission for certain angles only, creating an angular filtering interface. [ABSTRACT FROM AUTHOR]

This paper provides a real application of a popular swarm-intelligence optimisation method. The aim is to analyse the efficiency of various settings of the marine predator algorithm (MPA). Four crucial numerical parameters of the MPA are statistically analysed to propose the most efficient setting for solving engineering problems. Besides population size, particle velocity parameter P, Lévy flight parameter β , and fish aggregating device (FAD) probabilities are studied. Finally, 193 various settings, including fixed values and dynamic changes of the MPA parameters, are experimentally compared when solving 13 engineering problems. Standard statistical approaches are employed to highlight significant differences in various MPA settings. The setting of two MPA parameters (P, FADs) significantly influences MPA performance. Three newly proposed MPA settings outperform the original variant significantly. The best results provide the MPA variant with the dynamic linear change of P from 0.5 to 0. These parameters influence the velocity of prey and predator individuals in all three stages of the MPA search process. Decreasing the value of P showed that decreasing the velocity of individuals during the search provides good performance. Further, lower efficiency of the MPA with higher FAD values was detected. It means that more occasional use of fish aggregating devices (FADs) can increase the solvability of engineering problems. Regarding population size, lower values ( N = 10 ) provided significantly better results compared with the higher values ( N = 500 ). [ABSTRACT FROM AUTHOR]

Digital twin (DT) is the latest technology, which helps in generation of exact digital replica of the physical system. In this work, an in-house DT of a thermovacuum chamber and payload is developed. This research paper covers the development and implementation of an in-house cross-platform software application, a mobile AR app, and a Microsoft HoloLens 2 application, which provides real-time sensor data with voice control. The objective of this research is to study the potential of DT technology in real time monitoring of testing of payloads in thermovac system. Results demonstrate that the developed software applications provide a comprehensive 1 : 1 scale 3D visualization of the chamber along with essential sensor parameters for users to monitor the chamber and payload status, leading to a more effective decision making. [ABSTRACT FROM AUTHOR]

Based on the greening and low interference disposal requirements of coal gangue in high-yield and high-efficiency mines in Inner Mongolia and Shaanxi, and by integrating the existing theories and technologies such as underground filling technology of coal gangue, mine yellow mud grouting technology, and the evolution law of mining overburden fractures, a technology of filling goaf with coal gangue slurry for green disposal of coal gangue is proposed. The principle and technical framework of the technology of filling goaf with coal gangue slurry are clarified. This paper expounds on the technological process of technology of filling goaf with coal gangue slurry, establishes three types of slurry filling systems, such as centralized ground layout, ground and underground coordinated layout, and centralized underground layout, and constructs three slurry filling methods, including low-level grouting, adjacent level grouting, and high-level grouting, forming seven kinds of technology models of filling goaf with coal gangue slurry, including ground centralized pulping + high-level grouting, ground centralized pulping + adjacent grouting, ground centralized pulping + low level grouting, ground and underground coordinated pulping + adjacent grouting, ground and underground coordinated pulping + low level grouting, underground centralized pulping + adjacent grouting, and underground centralized pulping + low level grouting, and gives the selection process of technology models of filling goaf with coal gangue slurry. Based on the different conditions and requirements of Haidaze Coal Mine and Huangling No. 2 Coal Mine, engineering tests were carried out on two different technology modes, namely, ground and underground coordinated pulping + low level grouting and ground and underground coordinated pulping + adjacent grouting, based on simulation tests of low level grouting and adjacent grouting. The tests prove the feasibility of filling goaf with coal gangue slurry and explore the way for the theoretical research of the technology of filling goaf with coal gangue slurry and greening and low interference disposal of coal gangue. [ABSTRACT FROM AUTHOR]

An effective dead-time control strategy for the three-phase dual active bridge (3P-DAB) converter of a distribution system is studied to reduce the switching losses of power switches and improve the under-light-load power conversion efficiency. Because of the advantages of a dual-active bridge converter, such as an inherent zero-voltage switching (ZVS) capability without any additional resonant tank and a seamless bi-directional power transition, this is an attractive topology for bi-directional application. The 3P-DAB converter is apt for high-power applications such as aircraft due to an interleaved structure, which can reduce conduction losses. However, the design of the dead time depends on engineering experience and empirical methods. In order to overcome the conventional practicality of the dead-time design method, the effective control of dead time is proposed based on the theoretical analysis. In this paper, the overall explanation of the 3P-DAB converter is shown with operation principles. In addition, the dead-time effect of the 3P-DAB converter is examined and the practical variable dead-time control strategy is studied. Finally, experimental results validate the proposed variable dead-time control strategy using a 25 kW prototype 3P-DAB converter. [ABSTRACT FROM AUTHOR]

Abstract Steel structures are invariably analyzed and designed excluding the global stiffening effect of the roof cladding. Including this effect historically required complex design methods or deprecated standards. This paper presents a simplified numerical modeling method which allows this stiffening effect to be included. The method is an extension of the already established Component Method but utilizes only elements commonly available in typical design and analysis software. The results of the models were favorably compared to standardized test cases; an average difference of 0.24 mm maximum displacement was found, corresponding to a 3.4% discrepancy. The consistency of these results implies that the proposed model can be considered to be used for scientific and practical purposes when assessing a building’s most realistic behavior is necessary. [ABSTRACT FROM AUTHOR]

Effective communication is especially important in the wearable robots (WRs) community, which encloses a great variety of devices across different application domains, e.g., healthcare, occupational, and consumer. In this paper we present a vocabulary of terms with the aim to create a common understanding of terms and concepts among the different fields of expertise relevant in the WRs community. Our goal is to develop shared documentation that could serve as a reference to facilitate the use of accepted definitions in the field. The presented vocabulary is the result of different focus group discussions among experts in the field. The resulting document was then validated by presenting it to the WR community through an online survey. The results of the survey highlight a strong agreement in terms of acceptance of the vocabulary, its usefulness, and applicability of the proposed definitions as well as an overall appreciation for its purpose and target. This work represents a pilot study providing unique material for the WR community, encouraging the use of shared agreed definitions. The reported version of the vocabulary has been made available as a live document in a github repository, for public commenting and further improvements. [ABSTRACT FROM AUTHOR]

This paper delves into the technical aspects and viability of integrating artificial intelligence (AI) and knowledge-based engineering (KBE) tools in practical design. The goal is to digitally embed the hands-on expertise and technical boundaries set by seasoned professionals during intricate engineering and preparatory phases. We showcase how AI/KBE tools might emulate human cognitive processes to make well-informed choices. The article also probes the prospective economic and modernization repercussions of this innovation. Our findings suggest that such an integration is feasible and can amplify the decision-making efficacy and advance the sophistication of CAD/CAM systems in the shipbuilding realm. Furthermore, this investigation underscores the promising future of AI/KBE tools in ship design and advocates for continued exploration and innovation in this sector to fully harness its advantages. [ABSTRACT FROM AUTHOR]

Technical challenges associated with the treatment of silt subgrades frequently arise in coastal and river delta areas. Given the importance of environmental sustainability, the selection of efficient, cost-effective, and eco-friendly techniques for silt subgrade stabilization is paramount. While recycled polyester fibers primarily sourced from discarded polyester bottles have not yet been systematically employed in silt subgrade reinforcement, their potential is considerable. This paper offers a comprehensive review of the existing literature on the microstructural, physicochemical, and mechanical properties of silt, summarizing prior advancements in silt stabilization methodologies. Building upon this foundation, we introduce a novel approach utilizing recycled polyester fibers for silt subgrade improvement, outlining both its application prospects and challenges, which require further investigation. The findings of this study serve as a robust scientific foundation for the broader adoption and engineering implementation of this technology. [ABSTRACT FROM AUTHOR]

The ultimate objective of modern engineering applications in mining and material science is to develop good quality novel materials with desirable qualities. Machine Learning (ML) is used in the mining industry to provide solutions to complex problems of the mining industry and improve the efficiency of the overall system. ML methods are increasingly being used by materials scientists to uncover hidden trends in data and generate predictions. Furthermore, data centric techniques can provide useful insights into the basic processes that influence material behaviour while simultaneously reducing human labour in large data processing. The ability of persons to find new materials and infer complex relationships is important for the development of new materials. Large amounts of machine-readable data must be available to use statistical methodologies to speed materials research. In mining engineering, ML can be used for analyzing geographical data, assessing the risk of rock fall, predicting equipment failures and impact of mining activities on the environment etc. Material science data may be used in a variety of ways, including property prediction, the search for new materials and discovering synthesis methods. Selecting proper machine learning techniques to provide solutions is very important and that is discussed here. The purposes of this paper are to provide a comprehensive list of different ML techniques which are applied for the mining and material science domain. [ABSTRACT FROM AUTHOR]

Currently, spatiotemporal information, positioning and navigation have become important new infrastructures. Driven by general artificial intelligence, the era of intelligence led by large models has arrived. The increasingly powerful large models will play a more and more important role in the intelligent processing and applications of spatiotemporal information. First, this paper uses large models as the research paradigm and summarizes the current status and progress of large models in intelligent processing of spatiotemporal information in surveying and mapping. In addition, it analyzes the challenges faced by large models in intelligent processing of spatiotemporal information in surveying and mapping. We elaborate three key technologies in spatiotemporal information large models for surveying and mapping, including multi-modal fusion and understanding architecture design, prompt engineering optimization by fine-tuning, and human-in-theloop guidance for decision-making. Finally, the depth of industry understanding, data security risks, content credibility, and training deployment cost optimization are addressed to predict the development trend of spatiotemporal information large models. [ABSTRACT FROM AUTHOR]

Tamarind is widely consumed as fruit and spices in India. Tamarind contains pulp, seeds, shell and fibres. The pulp, which makes up between 30 and 50% of the mature fruit, is rich in reducing sugars, pectin, protein, fiber, and cellulose substances. Study of various physical engineering properties such as moisture content, fruit size, length, width, thickness, and weight (pulp, seed, shell, etc.) is important for designing the post-harvest machineries of tamarind. Major unit operations for processing of tamarind includes drying, dehulling, deseeding, pressing and storage. Traditional and mechanical approaches are used for these operations. Mechanical approaches of tamarind processing are carried out by dehuller and deseeder machinery. One of the crucial unit procedures in the processing of tamarind is deseeding which can be done by deseeder, mechanically. Processing of raw tamarind into value-added goods may increase its worth in addition to increase in shelf life. Additionally, it boosts the income of producers and processors. Value added products of tamarind are pulp, tamarind juice concentrate, tamarind pulp powder, tamarind pickle, tamarind jam, tamarind syrup, tamarind candy, tamarind kernel powder, dried fruit block, tamarind chutney and beverages. Tamarind is also rich in major amino acids phytochemicals and hence it carries the properties of antidiabetic, antibacterial, antivenomic, antioxidant. This paper provides an overview of the engineering properties, processing technologies, value added products, technologies and machineries developed/available for tamarind and its health benefits which will further help in machinery, protocol, technology and product design and development. [ABSTRACT FROM AUTHOR]

In this paper, we address the lack of a unified approach to understanding engineering practice by developing and presenting a taxonomy of common engineering activities. The taxonomy consists of 86 common engineering activities linked to 17 engineering competencies and the 11 International Engineering Alliance graduate attributes. The list of activities was developed using a six-step process, including multiple systematic literature searches and surveying engineers. The taxonomy provides a critical foundation for better understanding what engineers do, particularly in the Australian and New Zealand context. The taxonomy has potential utility in both engineering practice research and engineering education curriculum reform. [ABSTRACT FROM AUTHOR]

Within digital forensics, a notable emphasis is placed on the detection of the application of fundamental image-editing operators, including but not limited to median filters, average filters, contrast enhancement, resampling, and various other operations closely associated with these techniques. When conducting a historical analysis of an image that has potentially undergone various modifications in the past, it is a logical initial approach to search for alterations made by fundamental operators. This paper presents the development of a deep-learning-based system designed for the purpose of detecting fundamental manipulation operations. The research involved training a multilayer perceptron using a feature set of 36 dimensions derived from the gray-level co-occurrence matrix, gray-level run-length matrix, and normalized streak area. The system detected median filtering, mean filtering, the introduction of additive white Gaussian noise, and the application of JPEG compression in digital Images. Our system, which utilizes a multilayer perceptron trained with a 36-feature set, achieved an accuracy of 99.46% and outperformed state-of-the-art deep-learning-based solutions, which achieved an accuracy of 97.89%. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new fifth-order family of derivative-free iterative methods for solving nonlinear equations. Numerous iterative schemes found in the existing literature either exhibit divergence or fail to work when the function derivative is zero. However, the proposed family of methods successfully works even in such scenarios. We extended this idea to memory-based iterative methods by utilizing self-accelerating parameters derived from the current and previous approximations. As a result, we increased the convergence order from five to ten without requiring additional function evaluations. Analytical proofs of the proposed family of derivative-free methods, both with and without memory, are provided. Furthermore, numerical experimentation on diverse problems reveals the effectiveness and good performance of the proposed methods when compared with well-known existing methods. [ABSTRACT FROM AUTHOR]

A response from the author of the article "Feather structure, biomechanics and biomimetics: the incredible lightness of being" that was published in the 2014, volume 155 issue, is presented.

Post-industrial cities often find themselves at a crossroads as to whether to find a new identity or embrace their industrial past. In late 2017, after the closure of major manufacturing plants in the region, the Australian city of Geelong was designated a UNESCO City of Design and embraced a "Clever and Creative" strategy which acknowledged Geelong's industrial and design past in responding to contemporary technological, demographic, and economic challenges. However, questions remain as to which versions of the past are valued by the local community and how these stories can be shared. To better understand the social value of design and manufacturing heritage in Geelong as well as to get initial feedback on how to interpret this type of heritage through novel immersive extended reality (XR) experiences, the researchers took a community-led approach. This paper reports on the results of the initial online community surveys (N = 55–137) and in-person stakeholder interviews (N = 5) with carefully selected representatives of the local government, education, heritage, tourism, and engineering sectors. The study's outcome demonstrates the importance of design and manufacturing heritage for the local community's identity. Moreover, this type of heritage provides a source of inspiration, learning opportunities for future creative problem-solvers, and economic opportunities through tourism. By engaging with the social value of design and manufacturing heritage, this paper argues that more effective and targeted storytelling, game-like applications, and other digital immersive experiences such as extended reality (XR) can be used to better engage with audiences. [ABSTRACT FROM AUTHOR]

As the increasingly serious water pollution problem affects the sustainable development of the ecological environment, the research of water pollution treatment engineering cannot be delayed. Among them, the performance evaluation of water pollution treatment engineering is a major focus. After reading the existing studies, it is found that most of the existing performance evaluation indicators of water pollution treatment engineering have qualitative indicators and there is an unbalanced preference representation. Intuitionistic multiplicative linguistic sets can be a good representation of the qualitative preference and non-preference of decision-makers in the context of decision-making containing unbalanced phenomena. Therefore, to better solve the problem of water pollution treatment engineering, this paper introduces intuitionistic multiplicative linguistic sets to the problem of water pollution treatment engineering and proposes an effective theory for it. First, considering the multiplicative nature of the intuitionistic multiplicative linguistic set, a new score function and accuracy function are defined, and on this basis, the priority rules of intuitionistic multiplicative linguistic set are given to prepare for the subsequent water pollution treatment engineering performance ranking. And the distance measure of intuitionistic multiplicative linguistic set is introduced and a CRITIC attribute weight determination model under intuitionistic multiplicative linguistic set is obtained on this basis. Secondly, the Choquet integral operator is applied to better represent the correlation between elements. However, the nature of membership degree and non-membership degree shows that it is not reasonable to aggregate the information of intuitionistic multiplicative linguistic sets with a single increasing and decreasing transformation. Therefore, in this paper, we propose the IMLS bi-direction exponent Choquet integral operator, which is inspired by the bi-direction Choquet integral. Lastly, we improve the original preference function of the classical PROMETHEE II method to obtain the bi-directional PROMETHEE II method in intuitionistic multiplicative linguistic information. Finally, a numerical case is also provided to illustrate the scientific and rational application of the bi-directional PROMETHEE II method in intuitionistic multiplicative linguistic information for the performance evaluation of water pollution treatment engineering. [ABSTRACT FROM AUTHOR]

Using critical race methodology as a methodological framework, this paper explores how 16 Black men PhD scientists and engineers describe their undergraduate and graduate school choices and how race and racism influenced these processes. Our analysis yielded two descriptive themes focused on counterspaces for Black men in science and engineering (S&E). Implications for higher education researchers and practitioners, and S&E faculty interested in supporting the persistence of Black men pursuing and completing S&E postsecondary degrees are offered within. This paper contributes to the literature by investigating the connections between racism, counterspaces, and undergraduate and graduate choices of Black men pursuing S&E. [ABSTRACT FROM AUTHOR]

To improve the local mining and global search ability of quantum-behaved particle swarm optimization algorithm ( QPSO), this paper proposed an improved QPSO algorithm( DSQPSO). DSQPSO algorithm introduced the double strategies co-evolution to adjust the particle position update formula. Firstly, in order to fully reflect the advantage of individual exploration and the characteristic of collective guidance, this paper put forward two kinds of ideas of attraction points to achieve better integration of individuals and the swarm as well as information exchange. Secondly, it redefined the search scope of the particle through considering the relationship between the optimal average position and the global optimum and individual's historical optimum respectively. Moreover, in the iterative process, DSQPSO used the random perturbation mechanism to adjust the global optimal position in order to help the diversity of the swarm to be preserved. Based on 18 test functions, this paper compared DSQPSO with PSO, QPSO, RQPSO and LQPSO in convergence accuracy and robustness. Furthermore, in terms of the optimization results, it compared the improved algorithm with eight intelligent algorithms on two practical engineering optimization problems. Experiments indicate that whether in benchmarking or in engineering application, DSQPSO has obvious advantages in calculation precision and convergence effect. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of the architectural design of deep learning models in combination with a feature engineering approach considering the temporal variation in the features in the case of tropospheric ozone forecasting. Although deep neural network models have shown successful results by extracting features automatically from raw data, their performance in the domain of air quality forecasting is influenced by different feature analysis approaches and model architectures. This paper proposes a simple but effective analysis of tropospheric ozone time series data that can reveal temporal phases of the ozone evolution process and assist neural network models to reflect these temporal variations. We demonstrate that addressing the ozone evolution phases when developing the model architecture improves the performance of deep neural network models. As a result, we evaluated our approach on the CNN model and showed that not only does it improve the performance of the CNN model, but also that the CNN model in combination with our approach boosts the performance of the other deep neural network models such as LSTM. The development of the CNN, LSTM-CNN, and CNN-LSTM models using the proposed approach improved the prediction performance of the models by 3.58%, 1.68%, and 3.37%, respectively. [ABSTRACT FROM AUTHOR]

Under certain conditions, impulses, delays, and nonlocal conditions are known to be negligible in comparison with the duration of the process. From the practical (engineering) point of view, delays and nonlocal conditions are intrinsic phenomena of a system that do not violate certain properties of it, such as the controllability. In other words, as a rule, the controllability is robust under the influence of impulses, delays and nonlocal conditions. In this paper, we apply Rothe's fixed-point theorem to prove the interior approximate controllability of the semilinear heat equation with impulses, delays and nonlocal conditions. Also we obtain conditions under which the system considered is approximately controllable. [ABSTRACT FROM AUTHOR]

Based on the analysis of operation system capability testing and evaluation, this paper studies the data resource system of operation system capability testing and evaluation from operation, business and engineering aspects. A 3-View Data resource framework is presented. And some suggestions on data resource construction are given. The research can help to clarify the data needs, improve the consistent understanding of joint operation system capability evaluation data, and promote the development of the data resource and data integrated service platform. [ABSTRACT FROM AUTHOR]

This paper employs an innovative investigation approach to study pore evolution in Al-Si-Mg-Cu alloy within aluminum foam sandwiches (AFS) by integrating data from heating–expansion ratio curves, in situ observation of synchronous radiation, and microscopic analysis of the matrix's microstructure at different stages. Additionally, the cavity design and plate type control for large-scale AFS production are explored. Findings categorize the precursor heating into three stages: rapid heating, solid–liquid transition, and stable foaming. During solid–liquid transition, the expansion rate experiences a sudden drop, associated with pore nucleation and edge cracking of precursors. Pores nucleate as elongated crack-like structures along the rolling direction, guided by the Mg-enriched regions. In stable foaming, these pores evolve, become spherical, and the matrix rapidly expands. Using square tubes for sealing on the preform cavity sides creates a dense edge zone during rolling, halting crack propagation into the powder core. Adopting edge sealing during foaming mitigates boundary effects, thereby improving AFS panel flatness. [ABSTRACT FROM AUTHOR]

This paper studies the service quality (SQ) of higher education institutes (HEI), offering professional courses from the perspective of faculty as they are the service providers as well as a major stakeholder in the educational arena. PHEISQUAL (Professional higher education institute service quality) scale has been developed to measure the service quality of HEI offering professional course using mixed methodology. Four factors namely—Training & Placement, Faculty Resource, Learning Infrastructure, and Assessment & Evaluation have been extracted. The scale has been subjected to rigorous analysis of scale development process and has complied with same. Thus this study accrues a new instrument to measure service quality of professional institutes offering higher education by taking into account the technical as well as operational factors. [ABSTRACT FROM AUTHOR]

This paper investigates the ethical and professional responsibilities of engineering Graduate Students (GSs) and Faculty Members (FMs) in relation to Graduate Recruitment Offers (GROs). The authors developed an academic survey for data collection and subsequently evaluated the collected data based on common ethical theories and principles, as well as relevant professional codes of conduct. Based on the survey responses, this study identified the most common driving and preventive reasons for FMs and GSs not to honor a signed GRO. Further, the perception of GSs and FMs in relation to GROs was investigated using statistical methods. Finally, the authors provided an educational framework in the form of a checklist aimed at promoting ethical and professional decision-making as related to GROs. Ultimately, the outcomes of this research can be incorporated into senior seminar courses to enhance engineering undergraduate students' ethical education and promote their ethical thinking as they grow into professional roles. [ABSTRACT FROM AUTHOR]

This paper describes a study related to the learning of decision-making heuristics such as preference matrix, break-even point and decision tree from the perspective of using a computational tool. With their respective algorithms, a virtual learning environment through a mobile application (app) aimed at Engineering students was developed. To answer the research questions posed in this report, an empirical study was conducted to assess the effectiveness, efficiency and cost in solving decision-making problems with and without the use of the app. The results in this study suggest that the use of the app in learning decision-making skills facilitates the mathematical process for students, and that by using critical thinking competence, they can make assertive and accurate decisions considering different alternatives. [ABSTRACT FROM AUTHOR]

In their highly influential paper, Yarkoni, Tal, and Jacob Westfall. 2017. "Choosing Prediction over Explanation in Psychology: Lessons from Machine Learning." Perspectives on Psychological Science 12 (6):1100–1122. the authors highlight difficulties in traditional explanatory research in the field of psychology and argue in favour of novel data-driven science. By applying machine-learning methods to large data sets, predictive power has been shown to increase significantly. Geological engineers are responsible for a wide range of applications, including the design of tunnels, dams, foundations, and mines. While the field of geological engineering stands on solid mechanistic grounds, we argue that its predictive aspect aligns more closely with psychology than other mechanistic sciences. We therefore propose a paradigm shift in geological engineering research towards a prediction-centric approach. Potentially, this could enhance cost-effectiveness in structural design and lead to substantial societal savings. [ABSTRACT FROM AUTHOR]

In order to solve the problem of bypassing detection methods for DNS covert channel（DCC） traffic deformation strategies, this paper proposed a DCC detection method based on traffic slice. In this method, the traffic of the experimental environment was firstly divided into batches based on the sliding window, and then obtained the traffic slice based on the aggregation of each host-end IP. Each slice contains DNS packets and Web packets belonging to the same host in a short time span. Then, for the DNS data volume, DNS request behavior, DNS response behavior, and association behavior correlation behavior with WEB of DNS in the slice, it implement DCC-detection-oriented feature engineering and create detection models on this basis. Comparative experiments show that the detection accuracy of the constructed DCC detection model on the conventional DCC traffic datasets is 99.83%,and the false positive rate is only 0.08%.On the deformed DCC traffic datasets with six types of different traffic deformation strategies, the detection ability of the DCC detection model is more than 95% on average, which is better than the other detection schemes. It proves that the proposed method is effective in dealing with DCC traffic deformation. Moreover, the proposed method, which can effectively detect DCC communication within a single traffic slice, is a detection method with good real-time performance. [ABSTRACT FROM AUTHOR]

Learnability in Automated Driving (LiAD) is a neglected research topic, especially when considering the unpredictable and intricate ways humans learn to interact and use automated driving systems (ADS) over the sequence of time. Moreover, there is a scarcity of publications dedicated to LiAD (specifically extended learnability methods) to guide the scientific paradigm. As a result, this generates scientific discord and, thus, leaves many facets of long-term learning effects associated with automated driving in dire need of significant research courtesy. This, we believe, is a constraint to knowledge discovery on quality interaction design phenomena. In a sense, it is imperative to abstract knowledge on how long-term effects and learning effects may affect (negatively and positively) users' learning and mental models. As well as induce changeable behavioural configurations and performances. In view of that, it may be imperative to examine operational concepts that may help researchers envision future scenarios with automation by assessing users' learning ability, how they learn and what they learn over the sequence of time. As well as constructing a theory of effects (from micro, meso and macro perspectives), which may help profile ergonomic quality design aspects that stand the test of time. As a result, we reviewed the literature on learnability, which we mined for LiAD knowledge discovery from the experience perspective of long-term learning effects. Therefore, the paper offers the reader the resulting discussion points formulated under the Learnability Engineering Life Cycle. For instance, firstly, contextualisation of LiAD with emphasis on extended LiAD. Secondly, conceptualisation and operationalisation of the operational mechanics of LiAD as a concept in ergonomic quality engineering (with an introduction of Concepts for Applying Learnability Engineering (CALE) research based on LiAD knowledge discovery). Thirdly, the systemisation of implementable long-term research strategies towards comprehending behaviour modification associated with extended LiAD. As the vehicle industry revolutionises at a rapid pace towards automation and artificially intelligent (AI) systems, this knowledge is useful for illuminating and instructing quality interaction strategies and Quality Automated Driving (QAD). [ABSTRACT FROM AUTHOR]

In this paper, we study the interaction of Nitrogen Vacancies in Diamond (NVD) with quantized cavity field. The system is explored analytically and the effect of the system parameters is analyzed. The stability of a quantum system with influencing factors is investigated using the Mandal Parameter. The generated correlation between the NVD and the quantized cavity field is quantified using the negativity. This study also investigates geometric phase and its dependence on the system parameters. The results show that this system holds great potential applications in quantum computation and quantum memory. Additionally, the features of the system can be controlled by the system parameters. [ABSTRACT FROM AUTHOR]

In this paper, we explore the dynamics of quantum correlations in an isolated physical quantum under the influence of intrinsic coherence. We characterize the quantum correlations in the hybrid system using the granular model to investigate the amount of coherent-chaotic fractions, and we particularly use the spherical droplets to measure the specific correlations. Likewise, we examine the effect of coherence on the source evolution of these quantifiers within engineering applications. In particular, the behavior of the multiparticle correlations in terms of the system parameters and the coherence rate is investigated and analyzed in detail to explore the source intrinsic dimensions. We found that the correlations with genuine interferences behave slightly unsymmetrical for identical parameters characterizing the considered complex system and that the genuine correlations are more meaningful than primary interference which probed the chaotic peculiarities against the coherence phenomena. Our results also show that the robustness of quantum correlations can be modulated by adjusting the coherent rate, source physical properties and the initial conditions. [ABSTRACT FROM AUTHOR]

Implementation of a complex circuit with hardware components in a conventional way seems to be quite difficult for the students. Resultant wave-shapes may not be accurate and determined values of different parameters may not be exact. Due to inaccurate outcomes and time-consuming process in a conventional way, researchers despond to continue their approach. In this paper, a trainer kit has been developed which is just like a laboratory with necessary components and aims to implement multivibrators (Bistable, Monostable, and Astable) and RC phase shift oscillators in the laboratory. A variable power supply is constructed in the trainer kit that provides 9 V dc to the multivibrators and 15 V dc to the oscillator. Potentiometer, voltage regulator, different active and passive components such as resistors, capacitor, op-amp, transistor, and numerous jumper wires are introduced in this kit. The trainer kit ascertains an easy implementation by eliminating complexity and assures accurate wave-shapes at the oscilloscope within a short time. To validate the proposed system, a survey program has been introduced among many students and faculty members. The outcome of the survey is the demonstration of student and instructor views and opinions which acknowledges the trainer kit as an efficient and compatible working platform. [ABSTRACT FROM AUTHOR]

Mathematics modelling is a vital competency for students of all ages. In this study, we aim to fill the research gap about valid and reliable tools for assessing and grading mathematical modeling problems, particularly those reflecting multiple steps of the modelling cycle. We present in this paper the design of a reliable and valid assessment tool aimed at gauging the level of mathematical modelling associated with real-world modeling problems in a scientific-engineering context. The study defines and bases the central modelling processes on the proficiency levels identified in PISA Mathematics. A two-dimensional rubric was developed, reflecting the combined assessment of the type and level of a modelling process. We identified criteria that enable a clear comparison and differentiation among the different levels across each of the modelling processes. These criteria allow for concrete theoretical definitions for the various modelling processes, introducing a well-defined mathematical modelling framework from a didactical viewpoint, which can potentially contribute to promoting modelling competencies or the understanding of modelling by teachers and students. Theoretical, methodological and practical implications are discussed. [ABSTRACT FROM AUTHOR]

Password alone is currently not trusted for user online authentication and security as threats from hackers continue to grow, requiring highly efficient defense safeguard protection against unauthorized users. Therefore, CAPTCHA techniques came into the picture as an automated assistance to distinguish between humans and robots. The CAPTCHA has several applications in the online security domain requiring to be merged with encrypted hash function benefitting from the facility of the graphical password schemes. This paper proposes engineering an authentication technique using graphical CAPTCHA with an AES encrypted hash password to maintain applicable security accessing systems. We propose three layered security system that joins highly efficient security mechanisms to avoid users’ stress of entering password many times or different other hectic routines in order to save account accessing. [ABSTRACT FROM AUTHOR]

In order to further promote the research and application of BIM technology in caisson gravity wharf project, this paper takes the No. 9 and No. 10 berths project of Dalanping South Operation Area, Dalanping Port Area, Qinzhou Port as an example, applies BIM technology to the construction management of traditional hydraulic wharf, introduces BIM technology in the construction process, and establishes a three-dimensional information model. On this basis, the comprehensive application of BIM technology was carried out for the project, and the effective combination of BIM technology and site construction was realized. With the advantages of visualization and informationization of BIM technology, engineering quantity statistics, construction progress simulation, design optimization, project results display and other work can be realized. BIM technology can empower traditional hydraulic projects, improve management level, enhance performance ability, and obtain good economic and social benefits, which provides a reference for similar projects and has certain promotion and reference significance. [ABSTRACT FROM AUTHOR]