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The increasing demand for image dehazing-based applications has raised the value of efficient evaluation and benchmarking for image dehazing algorithms. Several perspectives, such as inhomogeneous foggy, homogenous foggy, and dark foggy scenes, have been considered in multi-criteria evaluation. The benchmarking for the selection of the best image dehazing intelligent algorithm based on multi-criteria perspectives is a challenging task owing to (a) multiple evaluation criteria, (b) criteria importance, (c) data variation, (d) criteria conflict, and (e) criteria tradeoff. A generally accepted framework for benchmarking image dehazing performance is unavailable in the existing literature. This study proposes a novel multi-perspective (i.e., an inhomogeneous foggy scene, a homogenous foggy scene, and a dark foggy scene) benchmarking framework for the selection of the best image dehazing intelligent algorithm based on multi-criteria analysis. Experiments were conducted in three stages. First was an evaluation experiment with five algorithms as part of matrix data. Second was a crossover between image dehazing intelligent algorithms and a set of target evaluation criteria to obtain matrix data. Third was the ranking of the image dehazing intelligent algorithms through integrated best–worst and VIseKriterijumska Optimizacija I Kompromisno Resenje methods. Individual and group decision-making contexts were applied to demonstrate the efficiency of the proposed framework. The mean was used to objectively validate the ranks given by group decision-making contexts. Checklist and benchmarking scenarios were provided to compare the proposed framework with an existing benchmark study. The proposed framework achieved a significant result in terms of selecting the best image dehazing algorithm.

Increasing demand for open-source software (OSS) has raised the value of efficient selection in terms of quality; usability is an essential quality factor that significantly affects system acceptability and sustainability. Most large and complex software packages partitioned across multiple portals and involve many users — each with their role in the software package; those users have different perspectives on the software package, defined by their knowledge, responsibilities, and commitments. Thus, a multi-perspective approach has been used in usability evaluation to overcome the challenge of inconsistency between users’ perspectives; the inconsistency challenge would lead to an ill-advised decision on the selection of a suitable OSS. This study aimed to assist the public and private organizations in evaluating and selecting the most suitable OSS. The evaluation of the OSS software packages to choose the best one is a challenging task owing to (a) multiple evaluation criteria, (b) criteria importance, and (c) data variation; thus, it is considered a sophisticated multi-criteria decision making (MCDM) problem; moreover, the multi-perspective usability evaluation framework for OSS selection lacks in the current literature. Hence, this study proposes a novel multi-perspective usability evaluation framework for the selection of OSS based on the multi-criteria analysis. Integration of best-worst method (BWM) and VIKOR MCDM techniques has been used for weighting and ranking OSS alternatives. BWM is utilized for weighting of evaluation criteria, whereas VIKOR is applied to rank OSS-LMS alternatives. Individual and group decision-making contexts, and the internal and external groups aggregation were used to demonstrate the efficiency of the proposed framework. A well-organized algorithmic procedure is presented in detail, and a case study was examined to illustrate the validity and feasibility of the proposed framework. The results demonstrated that BWM and VIKOR integration works effectively to solve the OSS software package benchmarking/selection problems. Furthermore, the ranks of OSS software packages obtained from the VIKOR internal and external group decision making were similar; the best OSS-LMS based on the two ways was ‘Moodle’ software package. Among the scores of groups in the objective validation, significant differences were identified; this indicated that the ranking results of internal and external VIKOR group decision making were valid, which pointed to the validation of the framework.

The growing trend of urban population has led to an increase in worn-out urban textures. Although various policies have been proposed to organize these textures, past data such as detailed and comprehensive plans in Iranian cities have afforded to achieve desirable results. For this purpose, Landsat satellite images taken on December 8, 2019 were used. Hence, this study tried to provide the latest method of information on urban worn-out textures with a new method and identify areas prone to becoming dysfunctional textures. For this purpose, Landsat 8 satellite images (December 2020) have been used. In this regard, in order to analyze the ENVI environment, two methods have been used: (1) The command of emissivity; (2) the calculation of the normalized and emissive vegetation cover index NDVI (Esfandiari, Darabad Fariba, Raoof Mostafazadeh, Amirhesam Pasban, and Behruoz Nezafat Takleh. 2022. “Integrating Terrain and Vegetation Indices to Estimate and Identify the Soil Erosion Risk Amoughin Watershed, Ardabil.” Journal of Spatial Analysis and Environmental Hazarts, 9(1): 77–96.) represents the reflection of solar energy from the earth’s surface, which indicates the types of vegetation conditions. To calculate the temperature of the city surface, LST (earth surface temperature in remote sensing refers to the heat measured by a radiometer in a momentary field of view) (Pirnazar et al., 2018). as well as to express the consequences of worn-out textures from the Driving forces-Pressure-State Impact-Response (DPSIR) model. Also, the best–worst method (BWM) is one of the newest and most effective multi-criteria decision-making techniques, which is used to weigh the factors and decision criteria and determine the priority of decisions (Sadeghi Darvaze et al., 2019) has been used to express the preference of the solutions for the organization of worn-out textures. Finally, the geographic information system (GIS) which refers to a set of hardware, software, geographic data and human resources that is used to collect, analyze and apply all geographic information (Mirzapour, 2019) has been used to express numerical calculations and display maps. The results of examining the surface temperature of the land using two emissivity and emissivity commands (Figs. 2 and 3; Tables 9 and 10) showed that the surface of Zanjan city is divided into five classes in terms of worn-out conditions, in which the first class with the lowest recorded temperature of the graph was the most worn-out part of the city and corresponded to the initial cores of the city. It includes 9.6% of the city’s area, but the second class consisting of 10% of the city’s worn-out area was ranked second. Also, the results of the BWM method refer to citizen participation, regeneration with an economy-oriented approach, accurate identification of urban worn-out textures and exposed areas of the city (as a high authority in organizing the urban worn-out textures of Zanjan).