A well-regarded as well as powerful method named the ‘analytic hierarchy process’ (AHP) uses mathematics and psychology for making and analysing complex decisions. This article aims to present a brief review of the consistency measure of the judgments in AHP. Judgments should not be random or illogical. Several researchers have developed different consistency measures to identify the rationality of judgments. This article summarises the consistency measures which have been proposed so far in the literature. Moreover, this paper describes briefly the functional relationships established in the literature among the well-known consistency indices. At last, some thoughtful research directions that can be helpful in further research to develop and improve the performance of AHP are provided as well.

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M icroemulsions serve as ideal candidates as potential drug delivery system due to their specialized qualities of improved solubilisation of drug, extended shelf life and ease of method of preparation and administration to patients. The unique features of microemulsions are thermodynamically stable, clear, colloidal dispersion of water and oil that are stabilized by surfactant and cosurfactant. Microemulsion typically has a droplet diameter of approximately 100 nm or less. Microemulsions have numerous applications in pharmaceutics and many other industries. In the present review we shall discuss about the various aspects of microemulsion with respect to the field of non steroidal anti inflammatory drug, along with its preparation, evaluation and research work carried out in microemulsion.

Nowadays, utility of the multi-criteria decision making (MCDM) technique in tackling real-world complex problems has risen tremendously. Even the United Nations is focusing on decision-making in order to accomplish Agenda 2030, as stated in its paragraph 48. The desire to promote sustainable development (SD) necessitates complex decision models, which could be achieved through the use of an efficient MCDM approach. Analytical Hierarchy Process (AHP) is one of the most efficient MCDM techniques that is incorporated in this study. The purpose of this work is to provide a contrasting of AHP's application that emerged between 2011 and 2022, rather than to reflect on its methodological improvements. Its application encompasses a wide range of disciplines including Renewable Energy, Sustainable manufacturing, Natural Hazards, Environmental Pollution, Landfill waste management and many others which lies explicitly or implicitly under the theme of SD. Previously, many reviews have been conducted that concentrated on a single decision topic; moreover, this review explore the comprehensive viewpoint of decision problems. As per statistical results, Middle Eastern countries such as Iran placed top in terms of applying AHP application in different sectors. GIS and fuzzy logic are the most often used approaches to incorporate AHP across all disciplines. Notably, the findings indicate that the most decision problem have selection and assessment as a major concern whereas, environmental, economical, LULC & DFR are more frequently used criteria.

The digital image proves critical evidence in the fields like forensic investigation, criminal investigation, intelligence systems, medical imaging, insurance claims, and journalism to name a few. Images are an authentic source of information on the internet and social media. But, using easily available software or editing tools such as Photoshop, Corel Paint Shop, PhotoScape, PhotoPlus, GIMP, Pixelmator, etc. images can be altered or utilized maliciously for personal benefits. Various active, passive and other new deep learning technology like GAN approaches have made photo-realistic images difficult to distinguish from real images. Digital image tamper detection now focuses on determining the authenticity and consistency of digital photos. The major research problems use generic solutions and strategies, such as standardized data sets, benchmarks, evaluation criteria and generalized approaches.This paper overviews the evaluation of various image tamper detection methods. A brief discussion of image datasets and a comparative study of image criminological (forensic) methods are included in this paper. Furthermore, recently developed deep learning techniques along with their limitations have also been addressed. This study aims to comprehensively analyze image forgery detection methods using conventional and advanced deep learning approaches.