Adopting the relationship marketing approach in health institutions and evaluating the weights of its dimensions will benefit the effectiveness of marketing strategies. This study aimed to determine the critical levels of relationship marketing orientation components in private health institutions using the analytical hierarchy process (AHP). In the study, relationship marketing orientation was evaluated according to six criteria in line with the opinions of five experts for employees and 20 people who previously benefited from health services for their customers. As a result, the criterion with the highest priority value was communication with 0.259, and the best health company A. Furthermore, the AHP method results were compared with TOPSIS, EDAS, and CODAS methods. In addition, the Spearman Correlation method was used to determine the correlation between the results.
The study aims to develop a decision-making framework by integrating queuing theory and multi-criteria decision-making (MCDM) tools, namely TOPSIS, EDAS, CoCoSo, and TODIM to select a roll-over car washing machine for an oil station. The queue, technical and financial characteristics of the alternatives are added to the decision-making process. The decision matrix includes five criteria and five alternatives. One million weight sets are created randomly, and MCDM techniques are applied to interpret the results statistically. Results indicate that Alternative 3 is statistically superior to the others. The proposed procedure can help decision makers to make decisions when expert knowledge isn’t available, and it can be applied for other purposes by making small changes.
Background: The importance and market share of e-commerce has been increasing with the COVID-19 pandemic in recent days. Employees sometimes cannot go to the workplace due to epidemics such as COVID-19 that is spreading rapidly around the world, natural disasters and accidents. Companies can continue to serve their customers with the internet infrastructure and computer technologies they will provide to their employees. Thus, e-commerce companies can provide a sustainable competitive advantage in the sector. Working with the right suppliers is one of the important decisions that will improve the service quality of the firms and affect the sustainability of the enterprise. Methods: This study aims to select the best laptop for a company in the online trade industry using Entropy-based EDAS, CODAS and TOPSIS methods. In the study, 6 alternative laptops have been evaluated according to hard disk capacity, ram, battery power, processor speed, weight, price criteria. The Entropy method has been used to identify the weights of the criteria in the study. These criteria weights have been used in EDAS, CODAS and TOPSIS methods. TOPSIS, EDAS and CODAS methods have been used to determine the best alternative. Also, the correlation between the results of the TOPSIS, EDAS and CODAS methods has been examined with the Spearman Correlation approach. Results: As a result of the Entropy method, it has been determined that the most important criterion is the hard disk capacity criterion. TOPSIS, EDAS and CODAS method results have been compared and the most suitable alternative has been selected. According to the results of the study, the best alternative has been selected as A5. Spearman Correlation analysis results show that there was a strong positive relationship between the methods used and the results obtained. Conclusions: The study differs from existing studies in the literature in that it is the first study in which laptop selection was made using TOPSIS, EDAS and CODAS methods together. The results of this study can be compared with the results of future studies that will be carried out using different MCDM methods and different data.
EDAS (EGNOS Data Access Service) is the EGNOS internet broadcast service, which provides free of charge access to the data collected and generated by the EGNOS infrastructure. EDAS disseminates over the Internet, both in real time and via an FTP archive, the raw data of the GPS, GLONASS (no commitment on GLONASS data is provided (1)) and EGNOS GEO satellites collected by the receivers located at the EGNOS reference stations, which are mainly distributed over Europe and North Africa. The EDAS services offer several types of GNSS data in various protocols and formats, such as DGNSS corrections. This paper reports on the results of some in-field tests conducted by ESSP and Topcon Agriculture to confirm the suitability of EDAS DGNSS corrections for precision farming in Europe. The European Commission (EC) is the owner of EGNOS system (including EDAS) and has delegated the exploitation of EGNOS to the European GNSS Agency (GSA). EDAS service provision is performed by ESSP, as EGNOS Services Provider, under contract with the GSA, the EGNOS program manager. In the ENC 2018 article “EDAS (EGNOS Data Access Service): Differential GPS corrections performance test with state-of-the-art precision agriculture system”, ESSP and Topcon Agriculture presented the results of the first in-field test conducted in a dynamic and real-life environment in the summer of 2017. The test results indicated that the EDAS DGNSS corrections could enable a reliable pass-to-pass accuracy performance for a wide range of precision agriculture applications and become an attractive solution for cereal farms, when the farm is located in the vicinity of an EGNOS reference station. In particular, Topcon Agriculture acknowledged that the observed performance was sufficient to support the following precision agriculture applications: spraying and spreading of any crop type, tilling and harvesting of cereal. Then, ESSP and Topcon Agriculture engaged in additional testing activities to further characterise the EDAS DGPS performance in different scenarios (i.e. at various European locations and with a variety of distances between the designated farm and the target EGNOS reference station). In each test, multiple runs with the rover tractors have been performed over the reference patterns predefined in the Topcon guidance systems. Data recorded during the tests has been analysed in detail, looking at the key performance indicators (e.g. cross track error and pass-to-pass performance) that characterize the EDAS DGPS performance for precision agriculture applications. Different techniques for the computation of the pass-to-pass accuracy performance have been used, including a procedure to measure live in the field and a post-processing alternative. The diversity of scenarios available allows drawing conclusions on the applicability of EDAS DGPS corrections (in terms of maximum distance from the target EGNOS station) for precision agriculture and also understanding the impact of operationally relevant aspects such as the quality of the mobile internet coverage (highly variable across Europe). The EDAS system and its architecture, the main types of data disseminated through EDAS services and the online information available to the EDAS users are introduced in this paper. In particular, the EDAS Ntrip service is described in detail, since it provides the differential corrections to the GPS and GLONASS satellites at the EGNOS reference stations in RTCM format, which are the basis for the present study. The article also reports on the results of the latest tests, which have been performed using Topcon receivers, vehicles and auto-steering systems. In all cases, two different Topcon guidance systems on board tractors were running simultaneously to assess the EDAS DGPS positioning performance with respect to a the reference provided by a top-performing RTK-based Topcon solution. The objective of this paper is to draw conclusions on the use of EDAS DGPS corrections as a reliable free-of-charge alternative for precision farming in Europe (especially for cereal farms), based on the available performance results from the testing campaign and the feedback from the involved precision agriculture experts.
Standard Guidance, Navigation, and Control (GN&C) systems take state data from a navigation system and create a trajectory that minimizes some a-priori determined cost function. These cost functions are typically time, money, weight, or any general physically realizable quantity. Previous work has been done to show the effectiveness of using risk as the sole objective function. However, this previous work used Poisson distributions and historical estimates to achieve this goal. In this paper we present the situation-risk assessment (SRA) method contained within the intelligent situation assessment and collision avoidance (iSC) platform. The SRA method uses data clustering, and pattern recognition to create a historically based estimate of guidance probabilities. These are then used in data driven, dynamic models to create the future probability fields of the situation. This probability, along with the other agent’s goals and objectives, are then used to create a minimum risk guidance solution in the nautical environment.
Even though satellite-based positioning increases rescue workers’ safety and efficiency, signal availability, reliability, and accuracy are often poor during fire operations, due to terrain formation, natural and structural obstacles or even the conditions of the operation. In central Europe, the stakeholders report a strong necessity to complement the location for mixed indoor-outdoor and GNSS blocked scenarios. As such, location information often needs to be augmented. For that, European Global Navigation Satellite System Galileo could help by improving the availability of the satellites with different features. Moreover, a multi-sensored collaborative system could also take advantage of the rescue personnel who are already involved in firefighting and complement the input data for positioning. The Autonomous Indoor & Outdoor Safety Tracking System (AIOSAT) is a multinational project founded through the Horizon 2020 program, with seven partners from Spain, Netherlands and Belgium. It is reaching the first year of progress (out of 3) and the overarching objective of AIOSAT system is to advance beyond the state of the art in tracking rescue workers by creating a high availability and high integrity team positioning and tracking system. On the system level approach, this goal is achieved by fusing the GNSS, EDAS/EGNOS, pedestrian dead reckoning and ultra-wide band ranging information, possibly augmented with map data. The system should be able to work both inside buildings and rural areas, which are the test cases defined by the final users involved in the consortium and the advisory board panel of the project.
Failure Mode and Effect Analysis (FMEA) is a key risk management tool used in detecting and eradicating potential failure for the purpose of improving the reliability and safety of a system. However, the traditional FMEA in spite of its popularity has inadequacies that have hindered the effectiveness of the tool in analyzing risk of failure modes. Due to the shortcomings of the technique, different improved versions have been suggested in the literature in order for risk to be analysed more effectively but majority of these versions are computationally challenging. In this paper, a simple approach is in troduced for improving the risk analysis capability of the FMEA. The approach utilizes Evaluation based on Distance from Average Solution (EDAS) as an alternative to RPN of FMEA in analyzing risk of failure. A case study of the turbocharger system of a diesel engine is applied to demonstrate the usefulness of the method. The result obtained from the EDAS method were compared with approaches in the literature previously used to address risk analysis of a turbo charger. The result of the analysis indicated that the EDAS method is a feasible alternative technique for risk analysis.
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Selection of materials for a specific application is one of the extremely demanding problems in a synchronised manufacturing environment as it directly determines perceptible quality and cost of the product. Material selection is a complex process, intending to choose the best material while satisfying a pre-decided set of requirements. Material selection decision is made during preliminary product design stage. An improperly chosen material leads not only to an early component failure but also to a redundant cost involvement. There are numerous materials and various criteria influencing the material selection process for a particular application. Although a good amount of multi-criteria decision-making (MCDM) methods are available to deal with this type of selection applications, this paper aims to propose a hybrid method of design of experiments (DOE) and evaluation based on distance from average solution (EDAS) to solve material selection problems in current industrial applications. DOE and EDAS are used jointly to determine the critical material selection criteria and their interactions by fitting a polynomial to the experimental data in a multiple linear regression analysis. A gear material selection problem is demonstrated to establish the application competence of the DOE-EDAS method. Application results were validated with the results of the previous researchers and they indicate that the proposed DOE-EDAS hybrid model is straightforward, robust and practical in solving complex MCDM problems.
Wood plastic composite (WPC) is a lightweight material, resistant against corrosion and damage, with recyclability of consuming materials. These materials usually used in marine structures frequently due to their unique features. In order to strengthen beams made by this material, usually Fibre-reinforced plastic (FRP) sheets are used, and one of the fracture modes in these beams is debonding of FRP sheet from the surface of the beams. To deal with this problem some grooves are used in the surface of the beam to improve the contact surface. The grooves include longitudinal, transverse and diagonal grooves. The main goal of this study is to assess different grooving methods in WPC-FRP beams. In this regard, primarily criteria (improving resistance, performance speed, performance complexity, performance costs, displacement and absorbing energy) were determined through interviews with experts in this field in order to assess the beams. Then, SWARA method employed to evaluate criteria with a policy based perspective and finally EDAS method applied for evaluating related alternatives. Based on obtained results, the longitudinal groove method is the best way of strengthening WPC beams to prevent debonding.
We wszystkich gałęziach transportu (lotniczym, drogowym, kolejowym i morskim) pozycja użytkownika może być określana za pomocą nawigacyjnych systemów satelitarnych (NSS) - dwóch globalnych, amerykańskiego GPS i rosyjskiego GLONASS oraz satelitarnych systemów wspomagających SBAS, w Europie EGNOS (European Geostationary Navigation Overlay Service). W artykule opisano obecny stan jego trzech segmentów, kosmicznego, naziemnego i użytkownika, jego trzech serwisów: otwartego (OS), bezpieczeństwa życia (SoL) i dostępu do danych (EDAS).
EN
In all modes of transport (area, road, rail and maritime) user's position can be obtained from satellite navigation systems, two global -American GPS and Russian GLONASS, and satellite based augmentation system SBAS, in Europe EGNOS (European Geostationary Navigation Overlay Service). Current its three segments, spatial, terrestrial and user, all three services - Open Service (OS), Safety of Life (SoL) and EGNOS Data Access Service (EDAS) are presented in this paper.
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Interval-valued fuzzy soft decision making problems have obtained great popularity recently. Most of the current methods depend on level soft set that provide choice value of alternatives to be ranked. Such choice value always encounter the equal condition that the optimal alternative can't be gained. Most important of all, the current decision making procedure is not in accordance with the way that the decision makers think about the decision making problems. In this paper, we initiate a new axiomatic definition of interval-valued fuzzy distance measure and similarity measure, which is expressed by interval-valued fuzzy number (IVFN) that will reduce the information loss and keep more original information. Later, the objective weights of various parameters are determined via grey system theory, meanwhile, we develop the combined weights, which can show both the subjective information and the objective information. Then, we present three algorithms to solve interval-valued fuzzy soft decision making problems by Multi- Attributive Border Approximation area Comparison (MABAC), Evaluation based on Distance from Average Solution (EDAS) and new similarity measure. Three approaches solve some unreasonable conditions and promote the development of decision making methods. Finally, the effectiveness and feasibility of approaches are demonstrated by some numerical examples.
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