The visibility of models: using technology as a bridge between mathematics and engineering

Engineering mathematics is traditionally conceived as a set of unambiguous mathematical tools applied to solving engineering problems, and it would seem that modern mathematical software is making the toolbox metaphor ever more appropriate. We question the validity of this metaphor, and make the case that engineers do in fact use mathematics as more than a set of passive tools—that mathematical models for phenomena depend critically on the settings in which they are used, and the tools with which they are expressed. The perennial debate over whether mathematics should be taught by mathematicians or by engineers looks increasingly anachronistic in the light of technological change, and we think it is more instructive to examine the potential of technology for changing the relationships between mathematicians and engineers, and for connecting their respective knowledge domains in new ways

Interaction Between Trade and Competition: Why a Multilateral Approach for the United States?

This thesis consists of two essays and an introduction. The main theme is technological knowledge that is not based on the natural sciences.The first essay is about rules of thumb, which are simple instructions, used to guide actions toward a specific result, without need of advanced knowledge. Knowing adequate rules of thumb is a common form of technological knowledge. It differs both from science-based and intuitive (or tacit) technological knowledge, although it may have its origin in experience, scientific knowledge, trial and error, or a combination thereof. One of the major advantages of rules of thumb is the ease with which they can be learned. One of their major disadvantages is that they cannot easily be adjusted to new situations or conditions. Engineers commonly use rules, theories and models that lack scientific justification. How to include these in introductory technology education is the theme of the second essay. Examples include rules of thumb based on experience, but also models based on obsolete science or folk theories. Centrifugal forces, heat and cold as substances, and sucking vacuum all belong to the latter group. These models contradict scientific knowledge, but are useful for prediction in limited contexts where they are used when found convenient. The role of this kind of models in technology education is the theme of the second essay. Engineers’ work is a common prototype for pupils’ work with product development and systematic problem solving during technology lessons. Therefore pupils should be allowed to use the engineers’ non-scientific models when doing design work in school technology. The acceptance of these could be experienced as contradictory by the pupils: a model that is allowed, or even encouraged in technology class is considered wrong when doing science. To account for this, different epistemological frameworks must be used in science and technology education. Technology is first and foremost about usefulness, not about the truth or even generally applicable laws. This could cause pedagogical problems, but also provide useful examples to explain the limitations of models, the relation between model and reality, and the differences between science and technology.QC 20111118</p

Defeating Ambiguity: Modeling Problems with Calculus

Many first year calculus students struggle to see the value in learning single variable calculus. They often focus their efforts on learning the rules of differentiation and integration, losing sight of the broader picture for how calculus is leveraged to solve problems. While rudimentary calculus problems are necessary for the sake of understanding basic rules and concepts, larger and more complex problems are critical to opening the doors for students to gain a practical understanding of the applications. Through a series of Problem Solving Labs and written reports, the single variable calculus program at West Point not only focuses on learning calculus, but also how the core concepts can be used to conduct quantitative analysis that can be communicated to decision makers. Throughout the semester-long course, single variable calculus students complete 4 to 5 different Problem Solving Labs where they leverage technological tools such as excel and mathematica to develop mathematical models to formulate overall recommendations. Each lab report prompt is designed to present an ambiguous problem that requires critical assumptions to enable mathematical modeling.https://digitalcommons.usmalibrary.org/presentations/1006/thumbnail.jp

Knowledge reuse integrating the collaboration from experts in industrial maintenance management

Distributed environments, technological evolution, outsourcing market and information technology (IT) are factors that considerably influence current and future industrial maintenance management. Repairing and maintaining the plants and installations requires a better and more sophisticated skill set and continuously updated knowledge. Today, maintenance solutions involve increasing the collaboration of several experts to solve complex problems. These solutions imply changing the requirements and practices for maintenance; thus, conceptual models to support multidisciplinary expert collaboration in decision making are indispensable. The objectives of this work are as follows: (i) knowledge formalization of domain vocabulary to improve the communication and knowledge sharing among a number of experts and technical actors with Conceptual Graphs (CGs) formalism, (ii) multi-expert knowledge management with the Transferable Belief Model (TBM) to support collaborative decision making, and (iii) maintenance problem solving with a variant of the Case-Based Reasoning (CBR) mechanism with a process of solving new problems based on the solutions of similar past problems and integrating the experts’ beliefs. The proposed approach is applied for the maintenance management of the illustrative case study

Models for Oil Refinery Waste Management Using Determined and Fuzzy Conditions

This study developed models to solve problems of optimisation, production, and consumption in waste management based on methods of system analysis. Mathematical models of the problems of optimisation and sustainable waste management in deterministic conditions and in a fuzzy environment were formulated. The income from production was maximised considering environmental standards that apply to the field of macroeconomics and microeconomics. The proposed approach used MANAGER software to formalise and solve the problem of revenue optimisation with production waste management to optimise the production of oil products with waste management at a specific technological facility of the Atyrau oil refinery in Kazakhstan. Based on the combined application of the principles of maximin and Pareto optimality, a formulation of the problem of production optimisation with waste management was obtained and a heuristic algorithm for solving the formulated fuzzy optimisation problem with waste management was developed.info:eu-repo/semantics/publishedVersio

Actualization of expert models with the help of neural networks

У статті розглянуті питання, пов'язані із застосуванням експертних систем для інноваційних технічних рішень. Проведено аналіз методів для вирішення практичних завдань, заснованих на статистичному моделюванні предметної області. Встановлено, що створення моделей експертних оцінок за допомогою нейронних мереж і реалізація цього підходу для оцінок структури інноваційного технологічного устаткування є перспективним напрямком. Особливістю таких моделей, є здатність багатовимірної апроксимації даних. Показано можливості та переваги використання математичних моделей на базі однорідних мереж для розв'язання обернених задач в оптимізаційній постановці. Викладений підхід був реалізований для оцінок структури інноваційного технологічного устаткування для механоскладального виробництва верстатів-роботів з кінематикою паралельної структури. В якості вихідної інформації про об'єкт прийнята фасетна класифікація структур механізмів з кінематикою паралельної структури. Фасетний метод класифікації стосовно верстатів-роботів дає можливість описати безліч можливих рішень для аналізу і вибору їх структури. Результати цієї оцінки показали якісне збіг з рівнями значущості елементів механізму з кінематикою паралельної структури на безлічі прецедентів, схильних до експертними оцінками.The article deals with issues related to the use of expert systems for innovative technical solutions. The analysis of methods for solving practical problems based on statistical modeling of the subject area. It has been established that the creation of expert assessment models using neural networks and the implementation of this approach for assessing the structure of innovative technological equipment is a promising direction. A feature of such models is the ability of multidimensional approximation of data. The possibilities and advantages of using mathematical models based on homogeneous networks for solving inverse problems in an optimization formulation are shown. The described approach was implemented to assess the structure of innovative technological equipment for the mechanical assembly production of machine-robots with the kinematics of a parallel structure. As a source of information about the object, a faceted classification of the structures of mechanisms with the kinematics of a parallel structure was adopted

Modelling and Inverse Problems of Control for Distributed Parameter Systems; Proceedings of IFIP(W.G. 7.2)-IIASA Conference, July 24-28, 1989

The techniques of solving inverse problems that arise in the estimation and control of distributed parameter systems in the face of uncertainty as well as the applications of these to mathematical modelling for problems of applied system analysis (environmental issues, technological processes, biomathematical models, mathematical economy and other fields) are among the major topics of research at the Dynamic Systems Project of the Systems and Decision Sciences (SDS) Program at IIASA. In July 1989 the SDS Program was a coorganizer of a regular IFIP (WG 7.2) conference on Modelling and Inverse Problems of Control for Distributed Parameter Systems that was held at IIASA, and was attended by a number of prominent theorists and practitioners. One of the main purpose of this meeting was to review recent developments and perspectives in this field. The proceedings are presented in this volume

Multidimensional model of assessment of economic thinking in college students

The Economic Thinking in undergraduates is a strategic aspect of research in the framework of higher education, given its critical impact on the development of skills and professional standards expected in front of the Scientific and Technological Innovation. The main contribution of this study focuses on the development of a Multidimensional Model of Assessment of Economic Thinking, from the perspective of Self-Organizing Systems. The methodology has an approach empirical-analytic. In relation to the instruments and results correspond to a perspective of Adaptative System based in Item Response Theory (IRT), Complexity Theory and Fractal Models (L-system) about the competence in solving economic problems, knowledge of financial aspects, responsible consumption, sustainable development, and the attitudes to understanding the economic world

Root cause analysis of low throughput situations using boosting algorithms and the TreeShap analysis

Detecting and diagnosing the root cause of failures in mobile networks is an increasingly demanding and time consuming task, given its technological growing complexity. This paper focuses on predicting and diagnosing low User Downlink (DL) Average Throughput situations, using supervised learning and the Tree Shapley Additive Explanations (SHAP) method. To fulfill this objective, Boosting classification models are used to predict a failure/non-failure binary label. The influence of each counter on the overall model’s predictive performance is performed based on the TreeSHAP method. From the implemen tation of this technique, it is possible to identify the main causes of low throughput, based on the analysis of the most critical counters in fault detection. Furthermore, from the identification of these counters, it is possible to define a system for diagnosing the most probable throughput degradation cause. The described methodology allowed not only to identify and quantify low throughput situations in a live network due to the occurrence of misadjusted configuration parameters, radio problems and network capacity problems, but also to outline a process for solving them.info:eu-repo/semantics/publishedVersio