Input-output Association Research Articles

Efficiency of public investment in education in Peru, 2016-2022: A comparative analysis by region

The study analyzes the level of technical efficiency of public investment in Education at the primary and secondary level in Peru, 2016 to 2022. Data envelopment analysis – DEA was used and for the association between the provision of resources and educational quality. the panel data fixed effects model. The results indicate that there are relative differences in efficiency between the regions, registering an average score of 49% for the primary level and 38% for the secondary level, with the most efficient being Moquegua, Tacna, Arequipa and Ica, and the least efficient being Loreto, Huánuco, Ucayali, and San Martín. From the input-output association, classroom size, infrastructure in good condition and public investment have a direct relationship, while students per teacher and per computer, the relationship is inverse with respect to educational achievement in communication and mathematics at the primary and secondary level. This suggests that inefficient regions should increase educational attainment at the primary and secondary levels by an average of 51% and 62%, respectively, while maintaining the same level of spending. Therefore, to improve their efficiency within the framework of public policies, they can adopt the management implemented by regions such as Moquegua and Tacna.

An Innovative Discussion on Ideological and Political Education for College Students Based on Digital Mining

Abstract In this paper, a self-organized data mining model for college students’ ideological and political education is constructed. Firstly, a suitable input-output association set is specified to build the model, and then one or more are selected as the outer criterion to filter the model. The models of each layer are evaluated by the outer criterion, and the optimal complexity model is established by finding the model structure and the law of system operation through the selection of different models. Then unknown correlations between factors of ideological and political education were mined from the data samples, and the system variables were predicted and analyzed. Finally, the model is applied to analyze the effect of ideological education and the influencing factors of College A. The p-value of the degree of matching between education level and professional level is 0.456, and the education level will have a significant influence on ideological and political education. The research in this paper is important for the development of ideology and politics in colleges and universities.

Cross-Site Scripting Guardian: A Static XSS Detector Based on Data Stream Input-Output Association Mining

The largest number of cybersecurity attacks is on web applications, in which Cross-Site Scripting (XSS) is the most popular way. The code audit is the main method to avoid the damage of XSS at the source code level. However, there are numerous limits implementing manual audits and rule-based audit tools. In the age of big data, it is a new research field to assist the manual auditing through machine learning. In this paper, we propose a new way to audit the XSS vulnerability in PHP source code snippets based on a PHP code parsing tool and the machine learning algorithm. We analyzed the operation sequence of source code and built a model to acquire the information that is most closely related to the XSS attack in the data stream. The method proposed can significantly improve the recall rate of vulnerability samples. Compared with related audit methods, our method has high reusability and excellent performance. Our classification model achieved an F1 score of 0.92, a recall rate of 0.98 (vulnerable sample), and an area under curve (AUC) of 0.97 on the test dataset.

Fuzzy Rules Emulated Discrete-Time Controller Based on Plant’s Input–Output Association

In this work, an adaptive controller is designed by an adaptive network called fuzzy rules emulated network (FREN) for a class of nonlinear discrete-time systems when the mathematical model is completely neglected. The characteristic curve between the plant’s input and output is drawn by results of the experimental setup. The design parameters are determined by the characteristic curve and utilized to design the controller. The network structure of FREN controller is established by the set of human knowledge-based IF-THEN rules according to the relation between the plant’s input and output. The theoretical result is provided to guarantee the convergence of tracking error of the learning algorithm. Furthermore, experimental systems with the LED current control and the robotic system are constructed to validate the performance of the proposed controller.

INPUT–OUTPUT ANALYSIS: THE NEXT 25 YEARS

This year marks the 25th anniversary of the International Input–Output Association and the 25th volume of Economic Systems Research. To celebrate this anniversary, a group of eight experts provide their views on the future of input–output. Looking forward, they foresee progress in terms of data collections, methods, theory testing, and focus and scope.

L'analyse input-output en Europe: tendances de la recherche et applications

Indubitably born in the USA, input-output analysis has an important European history, from its very beginnings in the Soviet Union to the postwar huge development of I/O techniques in West and North Europe. This paper studies the European experience of input-output analysis by surveying and analyzing some of the national experiences and especially the works in Great Britain of Richard Stone and his team. We show in particular how European economists have taken leadership in I/O research since the 1950s and more recently with the creation in 1989 of the journal of the International Input-Output Association, Economic System Research. In the latter European influence tends to focus works on theoretical and methodological issues more than empirical issues and applications.

Global Sensitivity Analysis Techniques for Probabilistic Ground Water Modeling

Global sensitivity analysis techniques are better suited for analyzing input-output relationships over the full range of parameter variations and model outcomes, as opposed to local sensitivity analysis carried out around a reference point. This article describes three such techniques: (1) stepwise rank regression analysis for building input-output models to identify key contributors to output variance, (2) mutual information (entropy) analysis for determining the strength of nonmonotonic patterns of input-output association, and (3) classification tree analysis for determining what variables or combinations are responsible for driving model output into extreme categories. These techniques are best applied in conjunction with Monte Carlo simulation-based probabilistic analyses. Two examples are presented to demonstrate the applicability of these methods. The usefulness of global sensitivity techniques is examined vis-a-vis local sensitivity analysis methods, and recommendations are provided for their applications in ground water modeling practice.

Foreword: 10th Volume of Economic Systems Research Journal of the International Input–Output Association

(1998). Foreword: 10th Volume of Economic Systems Research Journal of the International Input–Output Association. Economic Systems Research: Vol. 10, No. 1, pp. 1-2.

Foreword to the Journal of the International Input–Output Association

"Foreword to the Journal of the International Input–Output Association." Economic Systems Research, 1(1), pp. 3–4