Since its inception, Systems Engineering (SE) has developed as a distinctive discipline, and there has been significant progress in this field in the past two decades. Compared to other engineering disciplines, SE is not affirmed by a set of underlying fundamental propositions, instead it has emerged as a set of best practices to deal with intricacies stemming from the stochastic nature of engineering complex systems and addressing their problems. Since the existing methodologies and paradigms (dominant patterns of thought and concepts) of SE are very diverse and somewhat fragmented. This appears to create some confusion regarding the design, deployment, operation, and application of SE. The purpose of this paper is 1) to delineate the development of SE from 1926–2017 based on insights derived from a histogram analysis, 2) to discuss the different paradigms and school of thoughts related to SE, 3) to derive a set of fundamental attributes of SE using advanced coding techniques and analysis, and 4) to present a newly developed instrument that could assess the performance of systems engineers. More than Two hundred and fifty different sources have been reviewed in this research in order to demonstrate the development trajectory of the SE discipline based on the frequency of publication.

In this paper, we investigate two competing pay-tv platforms or free-to-air media platforms that consist of two groups of agents: viewers and advertisers. The pay-tv platforms can receive revenues from charging viewers pay-per-view prices and advertising, while the free-to-air platforms can only obtain all incomes from advertising. We discuss and compare advertising intensities and program content provisions of the two competing media platforms. Our findings show that if the extent to which viewers dislike advertising (the nuisance for advertising) is more massive than the marginal benefit that advertisers receive from an additional viewer, the pay-tv stations tend to maximally differentiate their program content and charge the viewers higher pay-per-view prices. If the nuisance approaches to the marginal benefit, however, both stations should offer similar program content, and charge the viewers lower prices under certain conditions. Particularly, if both platforms provide duplicated content, they should subsidize the viewers. In contrast, we show that the free-to-air media platforms never duplicate program content with a positive nuisance for advertising, and tend to offer maximal differentiated content if the nuisance is sufficiently large. Moreover, we reveal that if the viewers greatly dislike advertising (care less about advertising), the advertising volume of the pay-tv platforms is lower (higher) than that of the free-to-air platforms. Finally, we extend our base model to the case in which a pay-tv platform competes against a free-to-air station, and numerically show that the profit of the pay-tv platform may be larger or smaller than that of the free-to-air station.

This paper uses ideas from biological evolution to analyze the evolution of the securities market in which rational and irrational traders coexist. A market evolutionary model is developed to describe the dynamic trajectories of rational and irrational traders’ wealth. The main question is, are irrational traders eliminated as the securities market evolves. The paper considers the impact of new entrants on the security market long-term equilibrium. In addition, it discusses the existence and uniqueness of the long-term equilibrium The paper finds that, under some market conditions, irrational traders could survive in the long run.

The network analysis of a technological system combines the interindustry transactions with a matrix of sectoral innovative efforts as measured by R&D investment intensity. The matrixes of interindustry transactions of R&D-embodied products (innovations) are weighted matrixes where the interindustry flows measure the intensity of the innovation diffusion. In the past, studies using this approach in innovation studies have transformed weighted matrixes into binary matrixes of zero and one element where the flows less than a selected threshold value were considered to be zero and the flows greater than the threshold value were counted as one. Such matrix transformation leads to the loss of a great deal of information. In the present study, using degree and clustering coefficients for both binary direct as well as weighted direct techno-economic networks of the manufacturing sector of the German economy, we show that the binary directed network analysis is incapable of refined ranking of interindustry innovation transactions. The total degree index based on the weighted network of the German techno-economic system assigns a unique ranking to each sector, and clustering coefficients show that at least 75% of sectors in the network of Germany have two links with the other industries. However, the same indices based on the binary network are incapable of such refined ranking.

Proper supply of spares is critical to guarantee safe operation, improve service quality and reduce maintenance costs. This paper proposes a condition-based spare ordering model for a two-stage degrading system, which consists of inflection point transfer process and two-stage degradation process with continuous degradation process and random external shocks. External shocks itself does not directly lead to system failure, but it will speed up the degradation process. In turn, degradation can also make the system more vulnerable to shocks. In general, the degradation rate at the defective stage is greater than that at the normal stage. The proposed model depends on system degradation process and spare lead-time. In order to achieve accurate maintenance and deal with emergency maintenance caused by system rapid degradation after inflection point transfer time, the model considers both the regular lead-time and expedited lead-time. Before inflection point transfer time, regular spare ordering policy is performed. After inflection point transfer time, expedited spare ordering policy is implemented. The decision variable of the model is the ordering time. The objective of this study is to determine the optimal ordering time such that the expected cost rate is minimized. Finally, a numerical example is presented to illustrate the proposed model and sensitivity analysis on critical parameters is carried out.

Optical Character Recognition is the mechanical or electronic conversion of images of typed, handwritten or printed text into machine-encoded text for online reading and study. In this OCR technique, Tamil handwritten character recognition is one of the most needed and challengeable subjects of research. An encounter between selection and extraction of proper features eliminates the issues faced by the Tamil handwritten recognition. The character and the writers complexities are the major difficulties and challenges faced by this recognition system. Eventually, the character complexity can be overcome by any pre-extraction or selection process, wherein, structured or statistical pre-extraction algorithm can be designed, discovering the essential features, in the case of writer difficulties. The challenges of Tamil handwritten characters are structure over looping; unnecessary character portion; structure discontinuations and so on. The character portions in this research are chosen by implementing a new algorithm called the Junction Point Elimination (JPE) after conscientious analysis done on the existing algorithms like Zoning, Zoning and Junction Point (ZJP) and the Junction Point (JP) based feature pre-extraction process. The novelty behind this work is introducing an algorithm in order to truncate the problem in the existing feature selection and pre-extraction algorithms. Suitable feature extraction and classification algorithm are chosen and applied on the features extracted by JPE to test whether the same can be reached in successful manner. The final analysis and experiments shows that the JPE is better than the others.