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As hospitals are the most costly service providers in every healthcare systems, special attention should be given to their performance in terms of resource allocation and consumption. The purpose of this paper is to evaluate technical, allocative and economic efficiency in intensive care units (ICUs) of hospitals affiliated by Yazd University of Medical Sciences (YUMS) in 2015.

This was a descriptive, analytical study conducted in ICUs of seven training hospitals affiliated by YUMS using data envelopment analysis (DEA) in 2015. The number of physicians, nurses, active beds and equipment were regarded as input variables and bed occupancy rate, the number of discharged patients, economic information such as bed price and physicians’ fees were mentioned as output variables of the study. Available data from study variables were retrospectively gathered and analyzed through the Deap 2.1 software using the variable returns to scale methodology.

The study findings revealed the average scores of allocative, economic, technical, managerial and scale efficiency to be relatively 0.956, 0.866, 0.883, 0.89 and 0.913. Regarding to latter three types of efficiency, five hospitals had desirable performance.

Given that additional costs due to an extra number of manpower or unnecessary capital resources impose economic pressure on hospitals also the fact that reduction of surplus production plays a major role in reducing such expenditures in hospitals, it is suggested that departments with low efficiency reduce their input surpluses to achieve the optimal level of performance.

The authors applied a DEA approach to measure allocative, economic, technical, managerial and scale efficiency of under-study hospitals. This is a helpful linear programming method which acts as a powerful and understandable approach for comparative performance assessment in healthcare settings and a guidance for healthcare managers to improve their departments’ performance.

The purpose in this paper is to develop a systematic literature review aiming to reveal innovation opportunities associated with the thematic collaboration and trust in the reverse logistics field.

The authors adopted a parallel analysis approach segregating the systematic literature review papers in two groups at NVivo®, collaboration and trust in the supply chain and collaboration and trust in reverse logistics, aiming to explore in the first group of papers insights for innovation on collaboration and trust in reverse logistics. The content analysis strategy was supported by the knowledge exchange theory described in Gravier et al. (2008).

Reverse logistics is hardly dissociated from broader sustainable supply chain management approaches, which make all considerations on collaboration and trust designed for such approaches valuable and valid for reverse logistics. Collaboration and trust concepts in supply chain and in reverse logistics contexts are quite similar, while collaboration/trust is mandatory for managing networks in sustainable approaches and in reverse logistics, as well. Downstream and upstream, the chain disruptive innovation business models may be developed between focal companies and returns system third-party logistics providers, fourth-party logistics providers or end-customers, in a business-to-customer collaboration approach. Several collaboration technologies are listed in three perspectives: knowledge sharing, knowledge generation and knowledge implementation.

This study uses a specific protocol for the systematic literature review, and due to inclusion and exclusion criteria, other protocols can provide different results. The strategy of analysis under the knowledge exchange perspective may give a type of result different from other perspectives.

This research systematizes the existing knowledge on the collaborations and trust, which is a priority basis for reverse logistics, providing insights to researchers and practitioners in the area and identifying an agenda for future studies.

This paper aims to identify and analyze the barriers to the implementation of the United Nations Industrial Development Organization’s programxk for export consortia in the Iranian handmade carpet industry.

To accomplish its objectives, the study relied on a mixed (qualitative and quantitative) research method. Primarily, unstructured interviews were conducted to identify the effective barriers. Then, the validity of the barriers identified was evaluated through content validity ratio analysis. Finally, the interrelationships between the barriers were determined using the rough decision-making trial and evaluation laboratory technique (DEMATEL).

Results revealed that “a lack of leadership,” “a traditional business environment” and “a lack of awareness of consortium benefits” were the most significant causal barriers. Meanwhile, the most important effect barriers were “a lack of long-term vision,” “a lack of business ethics” and “a lack of motivation.”

The findings and results could help the stakeholders of the handmade carpet industry in Iran to improve existing export consortium programs, increasing the country’s share in the global markets in this industry.

This investigation seeks to fill an existing gap in the literature on export consortium formation in the handmade carpet industry by providing a network of barriers for the first time.

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy.

To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress.

The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance.

The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.

This paper aims to evaluate the effect of optimal use of rooftop photovoltaic (PV) systems on improving the loss of life (LOL) of distribution transformers, reducing power losses as well as the unbalance rate of the 69-bus distribution network.

The problem is studied in three scenarios, considering different objective functions as multi-objective optimization in balanced and unbalanced operations. Meta-heuristic golden ratio optimization method (GROM) is used to determine the optimal size of the rooftop PV in the network.

The simulation results show that in all scenarios, the GROM by optimally installing the rooftop PV is significantly capable to reduce the transformer distribution loss of loss, unbalance rate and power loss as well as reduce the temperature of the oil and transformer winding. Also, the lowest %LOL, power loss and unbalance rate occurred in the second scenario for the balanced network and first scenario, respectively. In addition, the results showed that the unbalance of the network results in increased power losses and LOL of the distribution transformer.

The better capability of GROM is proved compared with the grey wolf optimization algorithm with better objective function and by achieving better values of LOL, unbalance rate and power loss. The results also showed that the %LOL, unbalance and power losses are weakened compared to without considering the PV cost but the achieved results are realistic and cost-effective.

The purpose of this paper is to introduce an innovative transversal tubular braid texture and to study the elastic behavior of its 3 D printed structure comparatively to 3 D printed longitudinal tubular braid texture (maypole) to be used as reinforcement.

Regarding the lack of proper machines for the production of the proposed texture, the structure of samples was produced as a tubular lattice braid texture using a 3 D printer with the fused deposition modeling method subsequent to simulation by Rhinoceros software. The produced specimens were composited by polyurethane resin. The composite samples were evaluated by the split disk mechanical test to obtain their hoop stress. The structures of the reinforced composites were theoretically analyzed by ANSYS software.

The results of the mechanical test and theoretical analysis showed that the composites reinforced with transversal tubular lattice braid have higher strength compared to the composites reinforced with longitudinal ones. This assured that the composite reinforced by transversal tubular lattice braid is reliable to be used as high-performance tube for different applications.

Further work is carried out to produce the innovated complex structure continuously by a specially designed machine and fibrous materials to reinforce tubular composites in an industrial continual process to be applied for high-pressure fluids flows.

The purpose of this paper is to evaluate the performance of Malaysian Public Universities on the web using correspondence analysis.

Webometrics methods and correspondence analysis were used toanalyze the attributes of websites. In total, 20 Public University Websites were surveyed which were accessible on Malaysia Government Website.

The results show that Malaysian Public Universities have functioned pretty well on the web. As a whole, University of Malaya has performed properly in almost all criteria but University Pertahanan National Malaysia has had a weak function based on all evaluation criteria among other universities. Correspondence analysis classified the surveyed universities' websites into three groupings which were related based on some attributes.

The paper evaluates performance of Malaysian Public Universities' websites based on criteria obtained from Alexa databank.

The objective of this study is to investigate the effect of service excellence and guest delight on guest affective commitment to luxury restaurants, more specifically, the mediating effect of guest delight in the relationship between service excellence and guest affective commitment.

Data were collected from 270 guests with a response rate of 67.5%. SmartPLS software was used for data analysis.

The findings indicate that service excellence and guest delight had increased guest affective commitment to the luxury restaurant. It has been determined that guest delight acts as a mediator between service excellence and guest affective commitment.

Providing a high level of service excellence and delighting, thereby encouraging luxury guests to have a high level of commitment to the restaurant. Therefore, luxury guests' expectations must be exceeded to obtain their commitment to the restaurant.

This research study provides a substantial contribution to the hospitality literature by providing a significant concept of guest delight that can offer the opportunity to establish a new understanding of guest affective commitment in the luxury restaurant context.

This chapter presents a general equilibrium model that embeds the issue of national security within a two-country Heckscher–Ohlin model of international trade. “National security” is defined as a public good that is an increasing function of a country's own defense expenditure and a decreasing function of the other country's defense expenditure. Defense is a non-traded public good produced by capital and labor, along with two tradable private goods in each country. The model is solved as a Nash equilibrium in defense expenditures and a Walrasian equilibrium for the two traded goods and the factors of production. It is shown that opening to international trade raises defense expenditures in each country since national security is a normal good in each of them. If defense is more capital-intensive than both tradable goods then trade lowers the cost of defense for the labor-abundant country and raises it for the capital-abundant country.

Pattern recognition systems often have to handle problem of large volume of training data sets including duplicate and similar training samples. This problem leads to large memory requirement for saving and processing data, and the time complexity for training algorithms. The purpose of the paper is to reduce the volume of training part of a data set – in order to increase the system speed, without any significant decrease in system accuracy.

A new technique for data set size reduction – using a version of modified frequency diagram approach – is presented. In order to reduce processing time, the proposed method compares the samples of a class to other samples in the same class, instead of comparing samples from different classes. It only removes patterns that are similar to the generated class template in each class. To achieve this aim, no feature extraction operation was carried out, in order to produce more precise assessment on the proposed data size reduction technique.

The results from the experiments, and according to one of the biggest handwritten numeral standard optical character recognition (OCR) data sets, Hoda, show a 14.88 percent decrease in data set volume without significant decrease in performance.

The proposed technique is effective for size reduction for all pictorial databases such as OCR data sets.

State-of-the-art algorithms currently used for data set size reduction usually remove samples near to class's centers, or support vector (SV) samples between different classes. However, the samples near to a class center have valuable information about class characteristics, and they are necessary to build a system model. Also, SV s are important samples to evaluate the system efficiency. The proposed technique, unlike the other available methods, keeps both outlier samples, as well as the samples close to the class centers.