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This paper aims to numerically validate the aerodynamic performance and benefits of variable camber rate morphing wings, by comparing them to conventional ones with plain flaps, when deflection angles vary, assessing their D reduction or L/D improvement. Many morphing-related research works mainly focus on the design of morphing mechanisms using smart materials, and innovative mechanism designs through materials and structure advancements. However, the foundational work that establishes the motivation of morphing technology development has been overlooked in most research works. All things considered, this paper starts with the verification of the numerical model used for the aerodynamic performance analysis and then conducts the aerodynamic performance analysis of (1) variable camber rate in morphing wings and (2) variable deflection angles in conventional wings. Finally, we find matching pairs for a direct comparison to validate the effectiveness of morphing wings. As a result, we validate that variable camber morphing wings, equivalent to conventional wings with varying flap deflection angles, are improved by at least 1.7% in their L/D ratio, and up to 18.7% in their angle of attack, with α = 8° at a 3% camber morphing rate. Overall, in the entire range of α, which conceptualizes aircrafts mission planning for operation, camber morphing wings are superior in D, L/D, and their improvement rate over conventional ones. By providing the improvement rates in L/D, this paper numerically evaluates and validates the efficiency of camber morphing aircraft, the most important aspect of aircraft operation, as well as the agility and manoeuvrability, compared to conventional wing aircraft. [ABSTRACT FROM AUTHOR]

Featured Application: The research within this paper can provide a feasible, technical means for the design of new high-contact-ratio gears and can effectively promote the progress of gear transmission technology. The research results can be applied to the transmission systems of complex equipment such as tanks, armored vehicles, and ships, which is of great significance to improving their performance. Tooth root bending stress and surface contact stress are two major determinants of the load carrying capacity of gear drives. Generally, a high contact ratio has the potential to enhance the gear strength. In this paper, the basic procedures and methods for constructing a high-contact-ratio (HCR) internal spur gear pair with the arc path of the contact are presented. The effects of design and modification parameters such as deflection angle, modification angle, and addendum coefficient on gear drive are analyzed in detail based on 2D finite-element models (FEMs). A comparison of experimental and finite-element analyses (FEA) of the bending stress, contact stress, and contact ratio between HCR and involute internal spur gear drives was conducted to demonstrate the advantages of the HCR gear drive in terms of load capacity. The results show that appropriately increasing the deflection angle and addendum coefficient is beneficial for reducing bending and contact stresses. It was also observed that the bending and contact stresses of a HCR pinion are lower than those of an involute one. Moreover, the contact ratio increases with input torque. [ABSTRACT FROM AUTHOR]

Probabilistic models of competence assessment join the benefits of automation with human judgment. We start this paper by replicating two preexisting probabilistic models of peer assessment ( P G 1 -bias and PAAS). Despite the use that both make of probability theory, the approach of these models is radically different. While P G 1 -bias is purely Bayesian, PAAS models the evaluation process in a classroom as a multiagent system, where each actor relies on the judgment of others as long as their opinions coincide. To reconcile the benefits of Bayesian inference with the concept of trust posed in PAAS, we propose a third peer evaluation model that considers the correlations between any pair of peers who have evaluated someone in common: P G -bivariate. The rest of the paper is devoted to a comparison with synthetic data from these three models. We show that P G 1 -bias produces predictions with lower root mean squared error (RMSE) than P G -bivariate. However, both models display similar behaviors when assessing how to choose the next assignment to be graded by a peer, with an " R M S E decreasing policy" reporting better results than a random policy. Fair comparisons among the three models show that P G 1 -bias makes the lowest error in situations of scarce ground truths. Nevertheless, once nearly 20 % of the teacher's assessments are introduced, PAAS sometimes exceeds the quality of P G 1 -bias' predictions by following an entropy minimization heuristic. P G -bivariate, our new proposal to reconcile PAAS' trust-based approach with P G 1 -bias' theoretical background, obtains a similar percentage of error values to those of the original models. Future work includes applying the models to real experimental data and exploring new heuristics to determine which teacher's grade should be obtained next to minimize the overall error. [ABSTRACT FROM AUTHOR]

Featured Application: The resulting collection of Russian poetic texts annotated in terms of rhetorical structure theory provide data for investigating the author's styles of poetic reasoning. Potentially the corpus can give additional data for machine learning, particularly in its application to poetic text's generation and simulating the author's styles. The paper considers the pragmatic textual level and focuses on peculiarities of reasoning realized in the lyric verses written by the representatives of Russian classic poetry. The investigated material of poetic texts includes the verses written by A.K. Tolstoy, K.K. Sluchevsky, and I.F. Annensky. The purposes of the study involve adapting the rhetorical structure theory (RST) to poetic texts, annotating these texts, searching for regularities of poetic reasoning specific to the considered authors. Applying RST to poetic texts was a novel task; the lack of experience made it necessary to adapt the method, that is, to elaborate the adequate set of rhetorical relations and to specify two sets of criteria: segmenting a text and identifying the relations. The resulting set of relations consists of 34 items. After annotating the texts in terms of the adopted RST, several lines of comparison were the objects of investigation. They include collating the frequency spectrums of relations and the semantical groups of relations for the three authors, as well as comparing two periods of creativity for A.K. Tolstoy and K.K. Sluchevsky. The results of the comparative investigation revealed certain regularities both in the distribution of isolated relations and the distribution of semantically grouped relations. [ABSTRACT FROM AUTHOR]

The design of shallow foundations is performed in accordance with different building regulations depending on geotechnical and geological conditions. This paper involves the design calculations applying Kazakhstani and European approaches. The design of shallow foundations in Nur-Sultan city in Kazakhstan was implemented by the calculation of bearing capacity and elastic settlement in accordance with the design procedures provided in SP RK 5.01-102-2013: Foundations of buildings and structures, and Eurocode 7: Geotechnical design. The calculated results of bearing capacity and elastic settlement for two types of shallow foundations, such as pad foundation and strip foundation, adhering to Kazakhstani and European approaches are relatively comparable. However, the European approach provided higher values of bearing capacity and elastic settlement for the designed shallow foundation compared to the Kazakhstani approach. The difference in the results is explained by the application of different values of partial factors of safety for the determination of bearing capacity and different methods for the calculation of the elastic settlement of shallow foundations (i.e., elasticity theory and layer summation method). [ABSTRACT FROM AUTHOR]

As the educational landscape evolves, understanding and fostering student adaptability has become increasingly critical. This study presents a comparative analysis of XAI techniques to interpret machine learning models aimed at classifying student adaptability levels. Leveraging a robust dataset of 1205 instances, we employed several machine learning algorithms with a particular focus on Random Forest, which demonstrated highest accuracy at 91%. The models' precision, recall and F1-score were also evaluated, with Random Forest achieving a precision of 0.93, a recall of 0.94, and an F1-score of 0.94. Our study utilizes SHAP, LIME, Anchors, ALE, and Counterfactual explanations to reveal the specific contributions of various features impacting adaptability predictions. SHAP values highlighted 'Class Duration' significance (mean SHAP value: 0.175); LIME explained socio-economic and institutional factors' intricate influence. Anchors provided high-confidence rule-based explanations (confidence: 97.32%), emphasizing demographic characteristics. ALE analysis underscored the importance of 'Financial Condition' with a positive slope, while Counterfactual scenarios highlighted the impact of slight feature variations of 0.5 change in 'Class Duration'. Consistently, 'Class Duration' and 'Financial Condition' emerge as key factors, while the study also underscores the subtle effects of 'Institution Type' and 'Load-shedding'. This multi-faceted interpretability approach bridges the gap between machine learning performance and educational relevance, presenting a model that not only predicts but also explains the dynamic factors influencing student adaptability. The synthesized insights advocate for educational policies accommodating socioeconomic factors, instructional time, and infrastructure stability to enhance student adaptability. The implications extend to informed and personalized educational interventions, fostering an adaptable learning environment. This methodical research contributes to responsible AI application in education, promoting predictive and interpretable models for equitable and effective educational strategies. [ABSTRACT FROM AUTHOR]

Near-infrared spectroscopy is a non-invasive, rapid, and efficient analytical method widely employed in agricultural quality assessment. This study aims to explore the potential of Fourier transform near-infrared (FT-NIR) spectroscopy in the analysis of wheat quality in comparison to traditional physicochemical methods. Key quality parameters such as protein content, bulk density, dough extensibility, development and stability time, wet gluten, and extension area were considered. To compare the similarities between the two methods in an irregular manner and to make the trials more representative, randomized combinations of different samples were made by planting different wheat genotypes in different locations. In wheat protein determination (r = 0.92, p < 0.001), the correlation between protein determinations was very high and highly statistically significant. This indicates that the Fourier transform near-infrared (FT-NIR) assay is highly consistent and accurate with the physicochemical method for protein determination. In the quality indices of bulk density (r = 0.46, p < 0.05), dough extensibility (r = 0.46, p < 0.05), development time (r = 0.37, p < 0.05), stability time (r = 0.49, p < 0.01), wet gluten (r = 0.54, p < 0.01), and dough extension area (r = 0.63, p < 0.001), there was a positive correlation between the two assays. Although the correlation was lower compared to the protein assay, it was still statistically significant. This suggests that the FT-NIR assay also has some accuracy in these indices, although there may be some differences from the physicochemical method. Through comparative analysis, we found that in wheat quality assessment, FT-NIR showed a strong correlation and was highly significant in the determination of wheat protein content; in the determination of the extension area, although highly significant, the correlation coefficient was not high, and there was a positive correlation between the two, and a lower correlation was shown in the bulk density, dough extensibility, and development time. These results indicate that FT-NIR can assess the wheat protein content quality indicator. However, its ability to accurately assess wheat quality indicators such as density, dough extensibility, development and stability time, wet gluten, and dough extensibility needs further investigation. [ABSTRACT FROM AUTHOR]

In the process of conveying coarse-grained minerals, the internal flow-through passage components of mining pumps are subject to wear. The flow of coarse particles in such pumps is complex and changes constantly, making it necessary to study the non-steady-state wear characteristics and test the flow passage components. The evolution of the surface wear rate for the flow passage components during one third of a rotation cycle (120°) of a mining pump impeller with small, design, and large flow rates was analyzed in this study based on a discrete phase model (DPM). The flow that occurs during an entire rotation cycle of the impeller was investigated. The wear test was carried out with a small test pump with the same specific speed as and a similar structure to that of the deep-sea mining pump. The test results were compared with the numerical calculation results of the deep-sea mining pump obtained by using the same numerical calculation method and wear model, and the test wear area was found to be more consistent with the numerical calculation wear area. The results show that the numerical calculation method used in this article can more accurately predict the surface wear of the passage components of the mining pump and provides a suitable method for the prediction of the wear characteristics of the mining pump. [ABSTRACT FROM AUTHOR]

The emergence of social media, the worldwide web, electronic transactions, and next-generation sequencing not only opens new horizons of opportunities but also leads to the accumulation of a massive amount of data. The rapid growth of digital data generated from diverse sources makes it inapt to use traditional storage, processing, and analysis methods. These limitations have led to the development of new technologies to process and store very large datasets. As a result, several execution frameworks emerged for big data processing. Hadoop MapReduce, the pioneering framework, set the ground for forthcoming frameworks that improve the processing and development of large-scale data in many ways. This research focuses on comparing the most prominent and widely used frameworks in the open-source landscape. We identify key requirements of a big framework and review each of these frameworks in the perspective of those requirements. To enhance the clarity of comparison and analysis, we group the logically related features, forming a feature vector. We design seven feature vectors and present a comparative analysis of frameworks with respect to those feature vectors. We identify use cases and highlight the strengths and weaknesses of each framework. Moreover, we present a detailed discussion that can serve as a decision-making guide to select the appropriate framework for an application. [ABSTRACT FROM AUTHOR]

The transition towards Servitization in the IT Business is extremely challenging because IT Enterprises must transform partly or entirely from hardware manufacturers into service providers. Moreover, Servitization does not occur all at once; it is a long and continuous process. Thus, in order to succeed, a company must determine which phase of this process it is in within a short time period, due to the dynamic competition in the modern IT Business. An examination of such a transition is crucial for accurate enterprise resource planning and for business success in general. Accordingly, to gain a better understanding of this process/transition in the IT industry, five major players were analyzed. We provide a foundation of the definitions and concepts regarding Servitization. Based on this foundation, every major player is analyzed by business segment. Then, those business segments are broken down into the offerings delivered to the customers. Depending on the offering, an analysis of the revenue is performed. In addition, we discuss the challenges and their effects on every company, and then we examine the similarities and differences in the process. We conclude with a brief statement of our primary achievements, and possible future investigation directions/topics are suggested. [ABSTRACT FROM AUTHOR]

Recently, high frequency bands (above 6 GHz) have attracted more attention for the next generation communication systems due to the limited frequency resources below 6 GHz. To reveal the influence of frequency on propagation channels, channel characterization results at 14.6 and 3.6 GHz bands based on measurements in an indoor scenario and in a reverberation chamber are presented. The measurement results indicate minimal differences in path loss exponents, shadow fading standard deviation, root-mean-square (RMS) delay spread and coherence bandwidth for the two frequency bands, while the path loss at 14.6 GHz band is clearly larger than that at the 3.6 GHz band. Furthermore, the underlying factors that influence the channel characteristics are investigated. It is found that the RMS delay spread is independent of the frequency in the scenario where free space propagation and/or reflection are the main mechanisms. Measurements in the reverberation chamber verify this inference. [ABSTRACT FROM AUTHOR]