This research delves into the urgent requirement for innovative agricultural methodologies amid growing concerns over sustainable development and food security. By employing machine learning strategies, particularly focusing on non-parametric learning algorithms, we explore the assessment of soil suitability for agricultural use under conditions of drought stress. Through the detailed examination of varied datasets, which include parameters like soil toxicity, terrain characteristics, and quality scores, our study offers new insights into the complexities of predicting soil suitability for crops. Our findings underline the effectiveness of various machine learning models, with the decision tree approach standing out for its accuracy, despite the need for comprehensive data gathering. Moreover, the research emphasizes the promise of merging machine learning techniques with conventional practices in soil science, paving the way for novel contributions to agricultural studies and practical implementations.

This study explores the attributes of service quality for overseas residents provided by island county governments, using the example of the Kinmen County Government’s service center in central Taiwan. This research aims to identify key service elements that can enhance the satisfaction of Kinmen overseas residents. Drawing upon the SERVQUAL scale and a comprehensive literature review, service quality is divided into five dimensions: “administrative service,” “life counseling,” “information provision,” among others, comprising 24 service quality elements. A total of 311 valid questionnaires were collected through a survey, and Kano’s two-dimensional quality and IPA analysis were used to classify service factors. The Kano two-dimensional quality analysis revealed that “employment counseling,” “entrepreneurship counseling,” and “setting up service counters at airports and terminals during festivals” belong to attractive quality. Nine elements were classified as “one-dimensional quality” and “must-be quality,” including “one-stop service,” “exclusive consultation hotline,” and “exclusive website reveals information.” Through Quality Function Deployment (QFD), service elements that align with Kano’s two-dimensional quality and IPA priority improvement were selected for detailed study, including “financial assistance in emergencies,” “subsidy for transportation expenses back home,” “subsidies for education allowances,” and “various subsidy application information.” Following expert discussions and questionnaire surveys, eight strategies for improving key service quality elements were identified. This research not only provides actionable insights for the Kinmen County Government but also offers valuable strategies that can be applied to similar contexts globally, where remote and rural populations require specialized governmental support.

A method for studying the resilience of energy and socio-ecological systems is considered; it integrates approaches developed at the International Institute of Applied Systems Analysis and the Melentyev Institute of Energy Systems (MESI) of the Siberian Branch of the Russian Academy of Sciences. The article discusses in detail the methods of using intelligent information technologies, in particular semantic technologies and knowledge engineering (cognitive probabilistic modeling), which the authors propose to use in assessing the risks of natural and man-made threats to the resilience of the energy sector and social and ecological systems. More attention is paid to the study and adaptation of the integral indicator of quality of life, which makes it possible to combine these interdisciplinary studies.