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The purpose of the study is to establish a predictive model for sustainable wire electrical discharge machining (WEDM) by using adaptive neuro fuzzy interface system (ANFIS). Machining was done on Titanium grade 2 alloy, which is also nicknamed as workhorse of commercially pure titanium industry. ANFIS, being a state-of-the-art technology, is a highly sophisticated and reliable technique used for the prediction and decision-making.

Keeping in the mind the complex nature of WEDM along with the goal of sustainable manufacturing process, ANFIS was chosen to construct predictive models for the material removal rate (MRR) and power consumption (Pc), which reflect environmental and economic aspects. The machining parameters chosen for the machining process are pulse on-time, wire feed, wire tension, servo voltage, servo feed and peak current.

The ANFIS predicted values were verified experimentally, which gave a root mean squared error (RMSE) of 0.329 for MRR and 0.805 for Pc. The significantly low RMSE verifies the accuracy of the process.

ANFIS has been there for quite a time, but it has not been used yet for its possible application in the field of sustainable WEDM of titanium grade-2 alloy with emphasis on MRR and Pc. The novelty of the work is that a predictive model for sustainable machining of titanium grade-2 alloy has been successfully developed using ANFIS, thereby showing the reliability of this technique for the development of predictive models and decision-making for sustainable manufacturing.

The purpose of this study is to reveal the friction reduction performance and mechanism of granular flow lubrication during the milling of difficult-to-machining materials and provide a high-performance lubrication method for the precision cutting of nickel-based alloys.

The milling tests for Inconel 718 superalloy under dry cutting, flood lubrication and granular flow lubrication were carried out, and the milling force and machined surface quality were used to evaluate their friction reduction effect. Furthermore, based on the energy dispersive spectrometer (EDS) spectrums and the topographical features of machined surface, the lubrication mechanism of different granular mediums was explored during granular flow lubrication.

Compared with flood lubrication, the granular flow lubrication had a significant force reduction effect, and the maximum milling force was reduced by about 30%. At the same time, the granular flow lubrication was more conducive to reducing the tool trace size, repressing surface damage and thus achieving better surface quality. The soft particles had better friction reduction performance than the hard particles with the same particle size, and the friction reduction performance of nanoscale hard particles was superior to that of microscale hard particles. The friction reduction mechanism of MoS₂ and WS₂ soft particles is the mending effect and adsorption film effect, whereas that of SiO₂ and Al₂O₃ hard particles is mainly manifested as the rolling and polishing effect.

Granular flow lubrication was applied in the precision milling of Inconel 718 superalloy, and a comparative study was conducted on the friction reduction performance of soft particles (MoS₂, WS₂) and hard particles (SiO₂, Al₂O₃). Based on the EDS spectrums and topographical features of machined surface, the friction reduction mechanism of soft and hard particles was explored.

The purpose of this paper is to design a modified version of the double sampling plan to handle the inspection processes requiring a minimum sample size to assure the median life for the products under the new Weibull–Pareto distribution. The economic design of the proposed plan is also considered to assure the product's lifetime with minimum cost.

The authors have developed an optimization model for obtaining the required plan parameters by solving simultaneously two non-linear inequalities and such inequalities have been formed based on the two points on the operating characteristic curve approach.

The results show that the average sample number, average total inspection and total inspection cost under the proposed plan are smaller than the same of a single sampling plan. This means that the proposed plan will be more efficient than a single sampling plan in reducing inspection effort and cost while providing the desired protection.

The proposed modified double sampling plan designed to assure the median life of the products under the new Weibull–Pareto distribution is not available in the literature. The proposed plan will be very useful in assuring the product median lifetime with minimum sample size as well as minimum cost in all the manufacturing industries.

The purpose of this paper is to investigate the effect of the replacement of natural coarse aggregate (NCA) with different percentages of recycled coarse aggregate (RCA) on properties of low calcium fly ash (FA)-based geopolymer concrete (GPC) cured at oven temperature. Further, this paper aims to study the effect of partial replacement of FA by ground granulated blast slag (GGBS) in GPC made with both NCA and RCA cured under ambient temperature curing.

M25 grade of ordinary Portland cement (OPC) concrete was designed according to IS: 10262-2019 with 100% NCA as control concrete. Since no standard guidelines are available in the literature for GPC, the same mix proportion was adopted for the GPC by replacing the OPC with 100% FA and W/C ratio by alkalinity/binder ratio. All FA-based GPC mixes were prepared with 12 M of sodium hydroxide (NaOH) and an alkalinity ratio, i.e. sodium hydroxide to sodium silicate (NaOH:Na₂SiO₃) of 1:1.5, subjected to 90^°C temperature for 48 h of curing. The NCA were replaced with 50% and 100% RCA in both OPC and GPC mixes. Further, FA was partially replaced with 15% GGBS in GPC made with the above percentages of NCA and RCA, and they were given ambient temperature curing with the same molarity of NaOH and alkalinity ratio.

The workability, compressive strength, split tensile strength, flexural strength, water absorption, density, volume of voids and rebound hammer value of all the mixes were studied. Further, the relationship between compressive strength and other mechanical properties of GPC mixes were established and compared with the well-established relationships available for conventional concrete. From the experimental results, it is found that the compressive strength of GPC under ambient curing condition at 28 days with 100% NCA, 50% RCA and 100% RCA were, respectively, 14.8%, 12.85% and 17.76% higher than those of OPC concrete. Further, it is found that 85% FA and 15% GGBS-based GPC with RCA under ambient curing shown superior performance than OPC concrete and FA-based GPC cured under oven curing.

The scope of the present paper is limited to replace the FA by 15% GGBS. Further, only 50% and 100% RCA are used in place of natural aggregate. However, in future study, the replacement of FA by different amounts of GGBS (20%, 25%, 30% and 35%) may be tried to decide the optimum utilisation of GGBS so that the applications of GPC can be widely used in cast in situ applications, i.e. under ambient curing condition. Further, in the present study, the natural aggregate is replaced with only 50% and 100% RCA in GPC. However, further investigations may be carried out by considering different percentages between 50 and 100 with the optimum compositions of FA and GGBS to enhance the use of RCA in GPC applications. The present study is further limited to only the mechanical properties and a few other properties of GPC. For wider use of GPC under ambient curing conditions, the structural performance of GPC needs to be understood. Therefore, the structural performance of GPC subjected to different loadings under ambient curing with RCA to be investigated in future study.

The replacement percentage of natural aggregate by RCA may be further enhanced to 50% in GPC under ambient curing condition without compromising on the mechanical properties of concrete. This may be a good alternative for OPC and natural aggregate to reduce pollution and leads sustainability in the construction.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

Drawing on new insights from the perspectives and experiences of board members, the purpose of this study is to determine the board attributes that influence board roles in improving the integration of corporate social responsibility (CSR) into corporate governance structures. In total, 10 in-depth semi-structured interviews were conducted with directors of listed Jordanian companies to explore their perceptions of the effect of board of directors' composition on CSR and CSR disclosure (CSRD). The key findings show that boards with a diverse range of directors is essential independent/nonexecutive members, directors with business and/or accounting backgrounds, and foreign members to determine if they aim to better manage their CSR. To take CSR to the next level in the Arab region, we need to strengthen corporate governance mechanisms, and put more pressures on companies to make changes in board composition. For example, we suggest that companies that appoint business-educated and foreign members to their boards tend to engage in more impactful social and environmental-related activities and reflect their sustainable development more effectively. The study responds to calls for further research adopting qualitative methods, such as case studies and interviews in order to obtain a complete and in-depth understanding of the influence of board composition on CSR/CSRD. The findings provide useful insights for practice, policymakers, and future research.

The purpose of this paper is to solve the challenging problem of automatic carrier landing with the presence of environmental disturbances. Therefore, a global fast terminal sliding mode control (GFTSMC) method is proposed for automatic carrier landing system (ACLS) to achieve safe carrier landing control.

First, the framework of ACLS is established, which includes flight glide path model, guidance model, approach power compensation system and flight controller model. Subsequently, the carrier deck motion model and carrier air-wake model are presented to simulate the environmental disturbances. Then, the detailed design steps of GFTSMC are provided. The stability analysis of the controller is proved by Lyapunov theorems and LaSalle’s invariance principle. Furthermore, the arrival time analysis is carried out, which proves the controller has fixed time convergence ability.

The numerical simulations are conducted. The simulation results reveal that the proposed method can guarantee a finite convergence time and safe carrier landing under various conditions. And the superiority of the proposed method is further demonstrated by comparative simulations and Monte Carlo tests.

The GFTSMC method proposed in this paper can achieve precise and safe carrier landing with environmental disturbances, which has important referential significance to the improvement of ACLS controller designs.

This study aims to construct a sentiment series generation method for danmu comments based on deep learning, and explore the features of sentiment series after clustering.

This study consisted of two main parts: danmu comment sentiment series generation and clustering. In the first part, the authors proposed a sentiment classification model based on BERT fine-tuning to quantify danmu comment sentiment polarity. To smooth the sentiment series, they used methods, such as comprehensive weights. In the second part, the shaped-based distance (SBD)-K-shape method was used to cluster the actual collected data.

The filtered sentiment series or curves of the microfilms on the Bilibili website could be divided into four major categories. There is an apparently stable time interval for the first three types of sentiment curves, while the fourth type of sentiment curve shows a clear trend of fluctuation in general. In addition, it was found that “disputed points” or “highlights” are likely to appear at the beginning and the climax of films, resulting in significant changes in the sentiment curves. The clustering results show a significant difference in user participation, with the second type prevailing over others.

Their sentiment classification model based on BERT fine-tuning outperformed the traditional sentiment lexicon method, which provides a reference for using deep learning as well as transfer learning for danmu comment sentiment analysis. The BERT fine-tuning–SBD-K-shape algorithm can weaken the effect of non-regular noise and temporal phase shift of danmu text.

The purpose of this chapter is to cover banking efficiency using the concept of the Meta frontier function and to study group and subgroup differences in the production technology. This study estimates the technical efficiency (TE) and technology gap ratios (TGRs) for banks in Islamic countries. Using the assumption of the convex hull of the Meta frontier production set using the virtual Meta frontier within the nonparametric approach as presented by Battese and Rao (2002), Battese et al. (2004), and O'Donnell et al. (2007, 2008) and after relaxing this assumption, the study investigates if there is a significant difference between these two methods. To overcome the deterministic criterion addressed to nonparametric approach, the bootstrapping technique has been applied. The first part of this chapter covers the analytical framework necessary for the definition of a Meta frontier function and its estimation using nonparametric data envelopment analysis (DEA) in the case where we impose the assumption of the convex production set and follows in the case of relaxation of this assumption. Then we estimated the TE and the TGR in concave and nonconcave Meta frontier cases by applying the Bootstrap-DEA approach. The empirical part will be reserved for highlighting these methods on data bank to study the technical and technological performance level and prove if there is a difference between the two methods. Three groups of banks namely commercial, investment, and Islamic banks in 17 Islamic countries over a period of 16 years between 1996 and 2011 are used.

The development of the digital age has made data and information more transparent, enhancing the strategic perspectives of both buyers (strategic waiting) and sellers (price fluctuations) in their decision-making. This research investigates the optimal dynamic pricing strategy of the content product developer in relation to their consideration of consumer fairness concerns to elucidate the impact of consumer fairness concerns on the dynamic pricing strategy of the developer.

This paper assumes that monopolistic content developers implement a dynamic pricing strategy for the content product. Through constructing a two-period dynamic pricing game model, this research investigates the optimal decisions of the content developer, contingent upon their consideration or disregard of consumer fairness concerns. In the extension section, the authors additionally account for the influence of myopic consumers on these optimal decisions.

Our findings reveal that the degree of consumer fairness concerns significantly influences the developer’s optimal dynamic pricing decision. When a developer offers content products with lower depth, there is a propensity for the developer to refrain from incorporating consumer fairness concerns into a dynamic pricing strategy. Conversely, in cases where the developer offers a high-depth content product, consumer fairness concerns benefit the developer. Furthermore, our analysis reveals a consistent benefit for the developer from the inclusion of myopic consumers.

Few studies have delved into the conjoined influence of consumer fairness concerns and strategic behavior on dynamic pricing strategy. Our findings indicate that consumer fairness concerns can enhance the efficiency of the value chain for content products under specific conditions. This paper not only enriches the existing literature on dynamic pricing by incorporating consumer fairness concerns theoretically but also offers practical insights. The outcomes of this research can guide content product developers in devising optimal dynamic pricing strategies.