No abstract

Rural credit is one of the most critical inputs for farm production across the globe. Despite so many advances in digitalization in emerging and developing economies, still a large part of society like small farm holders, rural youth, and women farmers are untouched by the mainstream of banking transactions. Machine learning-based technology is giving a new hope to these individuals. However, it is the banking or non-banking institutions that decide how they will adopt this advanced technology, to have reduced human biases in loan decision making. Therefore, the scope of this study is to highlight the various AI-ML- based methods for credit scoring and their gaps currently in practice by banking or non-banking institutions. For this study, systematic literature review methods have been applied; existing research articles have been empirically reviewed with an attempt to identify and compare the best fit AI-ML-based model adopted by various financial institutions worldwide. The main purpose of this study is to present the various ML algorithms highlighted by earlier researchers that could be fit for a credit assessment of rural borrowers, particularly those who have no or inadequate loan history. However, it would be interesting to recognize further how the financial institutions could be able to blend the traditional and digital methods successfully without any ethical challenges.

Data mining is a process of finding correlations and collecting and analysing a huge amount of data in a database to discover patterns or relationships. Flight delay creates significant problems in the present aviation system. Data mining techniques are desired for analysing the performance in which micro-level causes propagate to make system-level patterns of delay. Analysing flight delays is very difficult – both when looking from a historical view as well as when estimating delays with forecast demand. This paper proposes using Decision Tree (DT), Support Vector Machine (SVM), Naive Bayesian (NB), K-nearest neighbour (KNN) and Artificial Neural Network (ANN) to study and analyse delays among aircrafts. The performance of different data mining methods is found in the different regions of the updated datasets on these classifiers. Finally, the result shows a significant variation in the performance of different data mining methods and feature selection for this problem. This paper aims to deal with how data mining techniques can be used to understand difficult aircraft system delays in aviation. Our aim is to develop a classification model for studying and reducing delay using different data mining methods and, in this manner, to show that DT has a greater classification accuracy. The different feature selectors are used in this study in order to reduce the number of initial attributes. Our results clearly demonstrate the value of DT for analysing and visualising how system-level effects happen from subsystem-level causes.

Repetitive use of a hand tool requiring large forces along with unnatural postures can cause musculoskeletal disorders in the upper extremity. Cleco pliers are used to install fasteners to sheet metals in aircraft manufacturing. The present study compares two types of mechanical Cleco piers in terms of repetition, grip force, posture, and discomfort and identifies their major design features which affect the ergonomic interface between the hand and the tool.

A usability test was conducted for an operating manual developed for the BraidMagic braiding machine. The manual consisted of five sections including (1) Safeguards, (2) Parts and Specifications, (3) Operating Instructions, (4) Maintenance, (5) Warranty and Service. For each section of the manual, various performance and preference measures were applied and opinions regarding likes, dislikes, and suggestions were surveyed. Five cosmetology students participated in this usability study, consisting of seven test modules. The manual received a high evaluation for satisfaction (overall mean = 4.6; range = 4.3 to 4.9) as measured on a 5-point Likert scale throughout the seven modules. Based on the usability test, recommendations were made for better usability of the manual. This study indicated that usability testing is an effective tool to identify potential usability problems in a systematic manner.