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A comprehensive investigation on the outlet air position effects on the thermal comfort and air quality has been achieved. In addition, airflow and temperature distributions in ventilated cavities filled with an air-CO₂ mixture with mixed convection are predicted. The airflow enters from the cavity through an opening in the lower side of the left vertical wall and exits through the opening in one wall of the cavity. This paper aims to investigate the outlet location effect, four different placement configurations of output ports are considered. Three of them are placed on the upper side and the fourth on top of the opposite side of the inlet opening. A uniform heat and CO₂ contaminant source are applied on the left vertical wall, while the remaining walls are impermeable and adiabatic to heat and solute. The cooling efficiency inside the enclosure and the average fluid temperature are computed for different Reynolds and Rayleigh numbers to find the most suitable fluid outlet position that ensures indoor comfortable conditions while effectively removing heat and the contaminant. This is demonstrated by three relevant indices, namely, the effectiveness for heat removal, the contaminant removal and the index of indoor air quality.

The simulations were performed via the finite-volume scSTREAM CFD solver V11. Three different values of CO₂ amount are considered, namely, 10³, 2 × 10³ and 3 × 10³ ppm, the Reynolds number being in the range 100 ≤ Re ≤ 800.

Based on the findings obtained, it is the configuration whose air outlet is placed near the heat source and the contaminant, which provides a better air distribution and a ventilation efficiency compared to the others ventilation strategies.

The studies on heat and mass transfers by natural and forced convection in ventilated cavities remain a fruitful research topic. Thereby, such a study deals with different ventilation strategies through cavities containing an air-CO₂ mixture subjected to a mixed regime. In particular, the air inlet velocity and contaminant sources’ effects on thermal comfort and air quality have been investigated.

This study used Data Envelopment Analysis (DEA) to measure and evaluate the operational efficiency of 26 isolation hospitals in Egypt during the COVID-19 pandemic, as well as identifying the most important inputs affecting their efficiency.

To measure the operational efficiency of isolation hospitals, this paper combined three interrelated methodologies including DEA, sensitivity analysis and Tobit regression, as well as three inputs (number of physicians, number of nurses and number of beds) and three outputs (number of infections, number of recoveries and number of deaths). Available data were analyzed through R v.4.0.1 software to achieve the study purpose.

Based on DEA analysis, out of 26 isolation hospitals, only 4 were found efficient according to CCR model and 12 out of 26 hospitals achieved efficiency under the BCC model, Tobit regression results confirmed that the number of nurses and the number of beds are common factors impacted the operational efficiency of isolation hospitals, while the number of physicians had no significant effect on efficiency.

The limits of this study related to measuring the operational efficiency of isolation hospitals in Egypt considering the available data for the period from February to August 2020. DEA analysis can also be an important benchmarking tool for measuring the operational efficiency of isolation hospitals, for identifying their ability to utilize and allocate their resources in an optimal manner (Demand vs Capacity Dilemma), which in turn, encountering this pandemic and protect citizens' health.

Despite the intensity of studies that dealt with measuring hospital efficiency, this study to the best of our knowledge is one of the first attempts to measure the efficiency of hospitals in Egypt in times of health' crisis, especially, during the COVID-19 pandemic, to identify the best allocation of resources to achieve the highest level of efficiency during this pandemic.

This study aims to examine the relationship between the internal control manager attributes and the firms’ operational efficiency. The internal control manager designs and maintains the firms’ policies and procedures to certify the effectiveness of its internal control system.

The study is an empirical research based on a sample of public companies listed on the Korean Stock Exchange from year 2011 to 2015. The authors derive measures of operational efficiency using the data envelopment analysis tool.

This study shows that the operational efficiency increases with internal control managers’ task-related knowledge and diverse firm knowledge, consistent with human capital theory. Also, the results reveal that internal control managers, equity ownership has a curvilinear relationship with the operational efficiency, indicating that excessive managerial ownership can deteriorate the firm value.

While many studies have examined the association between the internal control system and financial reporting quality, this paper is differentiated from prior studies by focussing on the internal control managers’ personal attributes. This is important, as the internal control system is essentially built by internal control managers who are in charge. This study contributes to accounting literature by shedding light on the role of internal control managers in enhancing the firms’ operational efficiency.

The purpose of this study is to propose a novel super-efficiency DEA model to appraise the relative efficiency of DMUs with zero data and stochastic data. Our model can work with both variable returns to scale (VRS) and constant returns to scale (CRS).

This study proposes a new stochastic super-efficiency DEA (SSDEA) model to assess the performance of airlines with stochastic and zero inputs and outputs.

This paper proposes a new analysis and contribution to the knowledge of efficiency assessment with stochastic super-efficiency DEA model by (1) using input saving and output surplus index for efficient DMUs to get the optimal solution; (2) obtaining efficiency scores from the proposed model that are equivalent to original stochastic super-efficiency model when feasible solutions exist. A case study is given to illustrate the applicability of our proposed model. Also, poor performance reasons are identified to improve the performance of inefficient airlines.

For the first time, a new SSDEA model for ranking DMUs is proposed. The introduced model produces a feasible solution when dealing with zero input or output. This paper applies the input saving and output surplus concept to rectify the infeasibility problem in the stochastic DEA model.

With the advent of the Montreal Protocol, the removal of flux residues from printed circuit assemblies using solvents based on CFC‐113 is no longer an acceptable option. An alternative range of cleaning technologies is being developed and marketed for this purpose, and the aim of this work was to study the efficiency of a variety of these alternative cleaning regimes after IR reflow soldering. The results indicated that: (i) all the cleaning regimes were capable of removing flux and flux residues after standard IR reflow soldering; (ii) as the level of flux contamination under the components increased, the ability of the cleaning regimes to clean the boards decreased; (iii) the cleaning regimes had varying problems in removing the flux residues after the non‐standard (overheat) IR profile processing; (iv) when additional flux is introduced under the components (i.e., non‐standard IR reflow), the delay between soldering and cleaning becomes important; and (v) the cleaning regimes exhibited a wide variation in their ability to clean under components with small stand‐off heights.

Indoor biocontamination is recognized as a potential public health problem. The concentration of indoor pollutants is varied, depending on air filtration, air distribution systems and air cleaning devices. One portable air cleaning device, “Ionizer Air clean‐er/Air clinic” was investigated. The ability of particles to remain airborne or pass through filters depends on the size and density of particles. Air clinic device removed bacterial and mould contaminants in efficiencies up to 98.7 per cent and 67 per cent respectively, after 30 minutes of operation. After purification, Penicilliumspecies were predominant. Small particles (≤q4μm) are passed through filter mates. The negative ions produced by the device are effective for removing suspended particulates in efficiency up to 99 per cent. The disadvantages of this device are: the need to change the filter after short period of operation, and the unpleasant odour emitted from the device during operation due to ionization of particles.

The objective of CNC machining is to produce mechanical parts with designed quality most efficiently. To generate CNC tool paths for machining a sculptured part using a three‐axis CNC machine, surface geometry, cutter shape and size, as well as tool path interval and direction need to be considered. In this work, the relation between the direction of a tool motion and cutting efficiency is studied. A new measure of cutting efficiency in three‐axis CNC milling – the length of effective cutting edge (ECE) is introduced. The ECE length is mathematically proven to reach its maximum when the tool cuts a sculptured surface along its steepest tangent direction at the cutter contact point. The steepest tangent direction is thus proven to be the most efficient tool feed direction in three‐axis sculptured part machining. The study identifies tool feed direction as a new control parameter in CNC tool path planning, and forms the foundation for further research on three‐axis tool path generation of sculptured parts.

The importance of container transportation has increased due to the globalization of the world economy. The purpose of this research is at proposing a framework to enhance the container terminals performance through evaluating efficiency and competitiveness.

The researchers used data envelopment analysis to assess the efficiency and fuzzy analytic hierarchy process to measure competitiveness of container terminals. The proposed framework captures key performance indicators to evaluate the container terminals' performance and identify areas that need improvement. It was applied to the Egyptian container terminals from the period of 2015–2019 as an empirical study.

Findings highlights the highest utilization of resources of Alexandria port while more attention should be given to the level of service provided. On the other hand, El-Sokhna should focus on more utilization of the available resources. The performance evaluation showed that the rest of Egyptian terminal ports should improve both competitiveness and efficiency at different levels based on their performance ranking.

The developed framework can be used as an evaluation tool to evaluate the performance of container terminals in other countries, and can be utilized as a performance benchmark tool to compare the performance of container terminals of competing ports.

The developed framework can help policymakers to assess efficiency and competitiveness based on both quantitative data and experts' judgement in order to help in formulating government logistics strategy.

The research provides a comprehensive framework to measure and evaluate competitiveness and efficiency of container terminals based on both quantitative data and experts' judgement.

This chapter proposes a new technique based on the data envelopment analysis (DEA) method to evaluate the scale efficiency with considering the environmental influences. Using this method, we can get the pure scale efficiency which has eliminated the environmental factors and random errors that might influence the production process. Our approach extends the three-stage-DEA model by Fried, Lovell, Schmidt, and Yaisawarng (2002) to the five-stage DEA model. Afterward, in order to measure the scale efficiency of the China’s universities more accurately, this chapter gives an empirical study on the scale efficiency of the top universities in China by applying the five-stage DEA model. The results show that the efficiency levels of many universities are indeed affected by external environmental variables and random factors. According to the levels of pure technical efficiency and scale efficiency, we divide China’s universities into four types, and we also propose some suggestions for the inefficient universities to improve their scale efficiency.