Mihajlo Pupin Institute

About: Mihajlo Pupin Institute is a facility organization based out in Belgrade, Serbia. It is known for research contribution in the topics: Robot & Robot kinematics. The organization has 153 authors who have published 297 publications receiving 3576 citations. The organization is also known as: Institut Mihajlo Pupin.

Modelling and simulation of a supply chain in an uncertain environment

Abstract: This paper describes fuzzy modelling and simulation of a supply chain (SC) in an uncertain environment, as the first step in developing a decision support system. An SC is viewed as a series of facilities that performs the procurement of raw material, its transformation to intermediate and end-products, and distribution and selling of the end-products to customers. All the facilities in the SC are coupled and interrelated in a way that decisions made at one facility affect the performance of others. SC fuzzy models and a simulator cover operational SC control. The objective is to determine the stock levels and order quantities for each inventory in an SC during a finite time horizon to obtain an acceptable delivery performance at a reasonable total cost for the whole SC. Two sources of uncertainty inherent in the external environment in which the SC operates were identified and modelled: customer demand and external supply of raw material. They were interpreted and represented by fuzzy sets. In addition to the fuzzy SC models, a special SC simulator was developed. The SC simulator provides a dynamic view of the SC and assesses the impact of decisions recommended by the SC fuzzy models on SC performance.

An overview and comparison of supervised data mining techniques for student exam performance prediction

Abstract: Recent increase in the availability of learning data has given educational data mining an importance and momentum, in order to better understand and optimize the learning process and environments in which it occurs. The aim of this paper is to provide a comprehensive analysis and comparison of state of the art supervised machine learning techniques applied for solving the task of student exam performance prediction, i.e. discovering students at a “high risk” of dropping out from the course, and predicting their future achievements, such as for instance, the final exam scores. For both classification and regression tasks, the overall highest precision was obtained with artificial neural networks by feeding the student engagement data and past performance data, while the usage of demographic data did not show significant influence on the precision of predictions. To exploit the full potential of the student exam performance prediction, it was concluded that adequate data acquisition functionalities and the student interaction with the learning environment is a prerequisite to ensure sufficient amount of data for analysis.

Stability of Linear Feedback Systems with Random Communication Delays

Abstract: Integral control of large-scale systems implies application of control and information exchange via communication networks in which random delays may exist. The design of such systems rely on conservative sufficient stability tests for systems with random, time-varying delays. In this report, necessary and sufficient conditions are found for zero-state mean-square exponential stability of the considered class of control systems. Numerical tests for zero-state stability are outlined and illustrated by a simple example. Finally, the results are also demonstrated on specific hardware, multiprocessor real-time control network which has been recently developed.