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Assess the realistic impacts of implementing an Radio Frequency Identification (RFID)/Internet of Things (IoT) uniforms’ distribution system for managing medical personnel’s scrubs in operating rooms. The authors use a hybrid simulation framework to address the following objectives and challenges: a) reduce and control operating rooms’ level of inventory; b) stabilize scrubs’ demand and c) improve infection control and prevention of cross-contamination (through scrubs over manipulation and hoarding).

The authors adopt a Design Science approach. This methodological approach is used to design, develop, create and evaluate information technology “artifacts” (e.g. constructs, models, methods and instantiations) intended to solve organizational problems and make research contributions (Peffers et al., 2007). More specifically, the authors follow the Design Science Research Methodology process model which includes six steps: problem identification and motivation, definition of the objectives for a solution, design and development, demonstration, evaluation, and communication.

To assess the realistic impacts of implementing an RFID-IoT uniforms’ distribution system for managing medical personnel’s scrubs in operating rooms, the authors adopted a design science approach and initiated the research by documenting the business case and reviewed the existing literature to build a comparative analysis of existing uniforms’ distribution systems. The authors used a hybrid simulation model to assess the impact of three business cases: present mode of operation, implementing smart shelves or the smart distributors. The authors show that smart dispensers allow a greater control on scrubs’ utilization while eliminating the cross-contamination of the medical personnel.

Through this research study, the authors provide hospitals’ managers a scientific support for uniforms’ (scrubs) distribution process improvement. The authors use a hybrid simulation model to compare innovative solutions for uniforms’ distribution systems in the form of “smart cabinets” supported by Radio Frequency Identification (RFID)/Internet of Things (IoT) technologies and choose the most appropriate design for the hospital to meet two main challenges: a) inefficiency of uniform replenishment-distribution system and b) noncompliancy with infection control regulations caused by the distribution system.

From a methodological perspective, this paper addresses concerns from researchers calling quantitative research methods and using case-based research strategy to address IoT issues and assess the system in practice. From a broader point of view, this work confirms the predominant interest of RFID-IoT research work in the arena of supply chain management and logistics as the technology is used for tracking purpose and for monitoring applications. It is also one response to the research community suggesting that “hospitals should evaluate the medical effectiveness of the new technologies as well as the cost before adoption”.

This study addresses the production optimization of a cellular manufacturing system (CMS) in magnetic production enterprises. Magnetic products and raw materials are more critical to transport than general products because the attraction or repulsion between magnetic poles can easily cause traffic jams. This study needs to address a method to promote the scheduling efficiency of the problem.

To address this problem, this study formulated a mixed-integer linear programming (MILP) model to describe the problem and proposed an auction and negotiation-based approach with a local search to solve it. Auction- and negotiation-based approaches can obtain feasible and high-quality solutions. A local search operator was proposed to optimize the feasible solutions using an improved conjunctive graph model.

Verification tests were performed on a series of numerical examples. The results demonstrated that the proposed auction and negotiation-based approach with a local search operator is better than existing solution methods for the problem identified. Statistical analysis of the experiment results using the Statistical Package for the Social Sciences (SPSS) software demonstrated that the proposed approach is efficient, stable and suitable for solving large-scale numerical instances.

An improved auction and negotiation-based approach was proposed; The conjunctive graph model was also improved to describe the problem of CMS with traffic jam constraint and build the local search operator; The authors’ proposed approach can get better solution than the existing algorithms by testing benchmark instances and real-world instances from enterprises.

This study aims to elucidate the machining properties of low-cost expanded clay-reinforced syntactic foams by using different neural network models for the first time in the literature. The main goal of this endeavor is to create a casting machining-neural network modeling flow-line for real-time foam manufacturing in the industry.

Samples were manufactured via an industry-based die-casting technology. For the slot milling tests performed with different cutting speeds, depth of cut and lubrication conditions, a 3-axis computer numerical control (CNC) machine was used and the force data were collected through a digital dynamometer. These signals were used as input parameters in neural network modelings.

Among the algorithms, the scaled-conjugated-gradient (SCG) methodology was the weakest average results, whereas the Levenberg–Marquard (LM) approach was highly successful in foreseeing the cutting forces. As for the input variables, an increase in the depth of cut entailed the cutting forces, and this circumstance was more obvious at the higher cutting speeds.

The effect of milling parameters on the cutting forces of low-cost clay-filled metallic syntactics was examined, and the correct detection of these impacts is considerably prominent in this paper. On the other side, tool life and wear analyses can be studied in future investigations.

It was indicated that the milling forces of the clay-added AA7075 syntactic foams, depending on the cutting parameters, can be anticipated through artificial neural network modeling.

It is hoped that analyzing the influence of the cutting parameters using neural network models on the slot milling forces of metallic syntactic foams (MSFs) will be notably useful for research and development (R&D) researchers and design engineers.

This work is the first investigation that focuses on the estimation of slot milling forces of the expanded clay-added AA7075 syntactic foams by using different artificial neural network modeling approaches.

Intent detection (ID) and slot filling (SF) are two important tasks in natural language understanding. ID is to identify the main intent of a paragraph of text. The goal of SF is to extract the information that is important to the intent from the input sentence. However, most of the existing methods use sentence-level intention recognition, which has the risk of error propagation, and the relationship between intention recognition and SF is not explicitly modeled. Aiming at this problem, this paper proposes a collaborative model of ID and SF for intelligent spoken language understanding called ID-SF-Fusion.

ID-SF-Fusion uses Bidirectional Encoder Representation from Transformers (BERT) and Bidirectional Long Short-Term Memory (BiLSTM) to extract effective word embedding and context vectors containing the whole sentence information respectively. Fusion layer is used to provide intent–slot fusion information for SF task. In this way, the relationship between ID and SF task is fully explicitly modeled. This layer takes the result of ID and slot context vectors as input to obtain the fusion information which contains both ID result and slot information. Meanwhile, to further reduce error propagation, we use word-level ID for the ID-SF-Fusion model. Finally, two tasks of ID and SF are realized by joint optimization training.

We conducted experiments on two public datasets, Airline Travel Information Systems (ATIS) and Snips. The results show that the Intent ACC score and Slot F1 score of ID-SF-Fusion on ATIS and Snips are 98.0 per cent and 95.8 per cent, respectively, and the two indicators on Snips dataset are 98.6 per cent and 96.7 per cent, respectively. These models are superior to slot-gated, SF-ID NetWork, stack-Prop and other models. In addition, ablation experiments were performed to further analyze and discuss the proposed model.

This paper uses word-level intent recognition and introduces intent information into the SF process, which is a significant improvement on both data sets.

This paper aims to propose a semianalytical model of a squirrel-cage induction machine (SCIM), considering local magnetic saturation and eddy-currents induced in the rotor bars.

The regions of the rotor and stator are divided into elementary subdomains (E-SDs) characterized by general solutions at the first harmonic of the magneto-harmonic Maxwell’s equations. These E-SDs are connected in both directions (i.e., along the r- and θ-edges).

The calculation of the magnetic field has been validated for various values of slip and iron permeability. All electromagnetic quantities were compared with those obtained using a two-dimensional finite-element method. The semianalytical results are satisfactory compared with the numerical results, considering both the amplitude and waveform.

Expansion of the recent analytical model (E-SD technique) for the full prediction of the magnetic field in SCIMs, considering the local saturation effect and the eddy-currents induced in the rotor bars.

The goal of this study is to determine the values of the process parameters that should be used during the machining of ceramic tile using the abrasive water jet (AWJ) process in order to achieve the lowest possible values for surface roughness and kerf taper angle.

In the present work, ceramic tile is processed by the AWJ process and experimental data were recorded using the RSM approach based Box–Behnken design matrix. The input process factors were water jet pressure, jet traverse speed, abrasive flow rate and standoff distance, to determine the surface roughness and kerf taper angle. ANOVA was used to check the adequacy of model and significance of process parameters. Further, the elite opposition-based learning grasshopper optimization (EOBL-GOA) algorithm was implemented to identify the simultaneous optimization of multiple responses of surface roughness and kerf taper angle in AWJ.

The suggested EOBL-GOA algorithm is suitable for AWJ of ceramic tile, as evidenced by the error rate of ±2 percent between experimental and predicted solutions. The surfaces were evaluated with an SEM to assess the quality of the surface generated with the optimal settings. As compared with initial setting of the SEM image, it was noticed that the bottom cut surface was nearly smooth, with less cracks, striations and pits in the improved optimal results of the SEM image. The results of the analysis can be used to control machining parameters and increase the accuracy of AWJed components.

The findings of this study present an innovative method for assessing the characteristics of the nontraditional machining processes that are most suited for use in industrial and commercial applications.

This study aims to understand how free-play credits affect risk-seeking behavior in slot players. Extant results suggest they encourage risk aversion, counter to the primary aim of increasing spend per visit. The results inform operators as to the effectiveness of what has become the primary play incentive for casino marketers within many of the world’s markets.

Within a quasi-experimental grouped design, 365 days of player-level performance data from four different casinos were analyzed to determine whether player losses (casino revenues) and time played differed on visits that included free-play redemptions from those that did not. Hypotheses were tested via paired-samples t-tests and Mann–Whitney U tests.

On balance, neither player losses nor time played were significantly different on the free-play visits. Neither the house money effect nor the endowment effect was supported. The results were most consistent with the prospect-theory-with-memory editing rule. No findings indicated increased risk-seeking behavior associated with the free-play offers.

Casino operators are afforded insight related to how costly free-play campaigns affect gaming spend and playtime. Both are critical to understanding the impact of free-play on the gambler’s experience.

The 365-day samples extended existing research by analyzing the impact of free-play offers on risk-taking behaviors within the scope of a perpetual/ongoing campaign. Comparisons of observed daily behavior/outcomes were made between separate tiers of like-kind gamblers from each of four different casinos. Quasi-hedonic editing rules were applied to a multistage decision framework.

The purpose of this paper is to exploit the optimal performances of each magnetic material in terms of low iron losses and high saturation flux density to improve the efficiency and the power density of the selected motor.

This paper presents a study to improve the power density and efficiency of e-motors for electric traction applications with high operating speed. The studied machine is a yokeless-stator axial flux permanent magnet synchronous motor with a dual rotor. The methodology consists in using different magnetic materials for an optimal design of the stator and rotor magnetic circuits to improve the motor performance. The candidate magnetic materials, adapted to the constraints of e-mobility, are made of thin laminations of Si-Fe nonoriented grain electrical steel, Si-Fe grain-oriented electrical steel (GOES) and iron-cobalt Permendur electrical steel (Co-Fe).

The mixed GOES-Co-Fe structure allows to reach 10 kW/kg in rated power density and a high efficiency in city driving conditions. This structure allows to make the powertrain less energy consuming in the battery electric vehicles and to reduce CO₂ emissions in hybrid electric vehicles.

The originality of this study lies in the improvement of both power density and efficiency of the electric motor in automotive application by using different magnetic materials through a multiobjective optimization.

This study aims to examine the problems of the concession system that Macao has long-term adopted to regulate its gaming industry and discuss alternatives.

Theoretical reflection was used to provide qualitatively different insights about governmental supervision of the gaming industry.

Two options for reform are proposed: (1) replace the concession system with a licensing system that does not restrict the number of concessionaires or the period of concession or (2) adopt a modified form of the concession system that changes the number of concessionaires, period of concessions and methods for selecting concessionaires.

This study’s results have implications for the Macao government and other gaming jurisdictions in Asia.

This study provides a comprehensive examination of the concession system for governmental supervision of the gaming industry.

Although existing studies provide valuable insight into how destinations create stimuli that support meaningful experiences, perceptions of different experiencescapes in the tourism context remain to be explored. This research aims to explore the experiencescape stimuli of female digital nomads.

The study adopted a qualitative research method and was structured by combining multiple qualitative data collection tools with a triangulated approach to examining the experiencescape.

Based on the experiences of female digital nomads toward destinations, their perception of the experiencescape, which includes sensory, functional, social, natural and cultural stimuli, has been revealed. From the explanations regarding the metaphors, the female digital nomads in the research have positive perceptions about destination experiences and are satisfied with being digital nomads.

The fact that the research is the first to focus on digital nomadism and experiencescape and that it reveals the perspective of female digital nomads who share their experiences in virtual communities, which is a research topic that is little emphasized in the literature, is a contribution to the theoretical framework on the subject. The practical contribution is that it will guide studies to improve and re-plan experiences in line with the stimuli emphasized by the female digital nomads studied. The results can play a supporting role in developing the market for female digital nomads.

This research offers a new perspective on exploring female digital nomads' perceptions of the destination experiencescape.