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3Additions to the book "Systems Design and Engineering" by Bonnema et.al. Subjects were chosen based on the Systems Engineering needs for Small and Medium Enterprises, as researched in the SESAME project. The
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Both Software Engineering and Machine Learning have become recognized disciplines. In this article I analyse the combination of the two: engineering of machine learning applications. I believe the systematic way of working for machine learning applications is at certain points different from traditional (rule-based) software engineering. The question I set out to investigate is “How does software engineering change when we develop machine learning applications”?. This question is not an easy to answer and turns out to be a rather new, with few publications. This article collects what I have found until now.
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From the article: This paper describes the external IT security analysis of an international corporate organization, containing a technical and a social perspective, resulting in a proposed repeatable approach and lessons learned for applying this approach. Part of the security analysis was the utilization of a social engineering experiment, as this could be used to discover employee related risks. This approach was based on multiple signals that indicated a low IT security awareness level among employees as well as the results of a preliminary technical analysis. To carry out the social engineering experiment, two techniques were used. The first technique was to send phishing emails to both the system administrators and other employees of the company. The second technique comprised the infiltration of the office itself to test the physical security, after which two probes were left behind. The social engineering experiment proved that general IT security awareness among employees was very low. The results allowed the research team to infiltrate the network and have the possibility to disable or hamper crucial processes. Social engineering experiments can play an important role in conducting security analyses, by showing security vulnerabilities and raising awareness within a company. Therefore, further research should focus on the standardization of social engineering experiments to be used in security analyses and further development of the approach itself. This paper provides a detailed description of the used methods and the reasoning behind them as a stepping stone for future research on this subject. van Liempd, D., Sjouw, A., Smakman, M., & Smit, K. (2019). Social Engineering As An Approach For Probing Organizations To Improve It Security: A Case Study At A Large International Firm In The Transport Industry. 119-126. https://doi.org/10.33965/es2019_201904l015
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In the fall of 1999, an international integrated product development pilot project based on collaborative engineering was started with team members in two international teams from the United States, The Netherlands and Germany. Team members interacted using various Internet capabilities, including, but not limited to, ICQ (means: I SEEK YOU, an internet feature which immediately detects when somebody comes "on line"), web phones, file servers, chat rooms and Email along with video conferencing. For this study a control group with all members located in the USA only also worked on the same project.
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The Department of Electrical and Electronic Engineering at the Fontys University of Professional Education in Eindhoven, The Netherlands, offers a course which is being developed around the principles of Concurrent Engineering. From research we found that in general students are not completely aware of aspects of cost-effectiveness but they are fully oriented towards technical problem solving. In order to improve on this aspects, we introduced the framework of "design to cost": learn to choose the right tools, concepts and technologies in a way that successful products can be designed and developed. This second edition of the course, based on 'design to cost', showed to be very successful and was strengthening our self-confidence. So in the third edition we started to work together with the regional industry. The companies paid for the development and, this money is used for intensive group coaching by tutors and specialists. It turned out that the contacts with the industry proved to be a very stimulating factor for the students. Working together with industry raises the quality of the education and it proved to be an excellent preparation for the final thesis period of the students.
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In the current discourses on sustainable development, one can discern two main intellectual cultures: an analytic one focusing on measuring problems and prioritizing measures, (Life Cycle Analysis (LCA), Mass Flow Analysis (MFA), etc.) and; a policy/management one, focusing on long term change, change incentives, and stakeholder management (Transitions/niches, Environmental economy, Cleaner production). These cultures do not often interact and interactions are often negative. However, both cultures are required to work towards sustainability solutions: problems should be thoroughly identified and quantified, options for large change should be guideposts for action, and incentives should be created, stakeholders should be enabled to participate and their values and interests should be included in the change process. The paper deals especially with engineering education. Successful technological change processes should be supported by engineers who have acquired strategic competences. An important barrier towards training academics with these competences is the strong disciplinarism of higher education. Raising engineering students in strong disciplinary paradigms is probably responsible for their diminishing public engagement over the course of their studies. Strategic competences are crucial to keep students engaged and train them to implement long term sustainable solutions.
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Undergraduate students who seek a bachelor degree in Dutch universities of applied sciences are supposed to learn also research skills so that they can provide innovative solutions to real problems of the society and businesses in their future careers. Current education and textbooks on research skills are not tuned well to software engineering disciplines. This paper describes our vision about the scope and model of the research suitable for software engineering disciplines in Dutch universities of applied sciences. Based on literature study we identify a number of research models that are commonly used in computer science. Through reviewing a number of graduation reports in our university, we further identify which of the research models are most suitable for the (graduation) projects of software engineering disciplines and also investigate their shortcomings with respect to the desired research skills. Our study reveals that the approach of most graduation works is close to the implementation-based (also called build-based or proof by example based) research model. In order to be considered as a realization of sound applied research, however, most of theses graduation works need to be improved on a number of aspects such as problem context definition, system/prototype evaluation, and critical literature study.
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Background In Dutch engineering education, female students outperform male students.
Using an interactionalist framework, this study explores factors that contribute to this gender-based difference.
Purpose
This study aims to answer two questions: Do female and male students differ in background characteristics, engagement factors, and academic success? Are differences in the relationships among background characteristics, engagement factors, and academic success gender-specific?
Design/method
Data on male and female engineering undergraduate students from five Dutch universities were subjected to linear structural modeling to compare potential gender differences in the relationships among the focal variables. Two structural models were considered.
Results
Female students spent more time on independent study, reported more social inte- gration, completed more credits, and were more likely to stay in engineering than were male students. Academic integration and intention to persist were important for comple- tion of credits for both genders. Social integration was only important for men’s academic success. Females seemed to benefit less from good preparation through active learning during secondary education, and the effect of a high grade point average on math was neg- ative for females but positive for males.
Conclusions
Interactionalist concepts can explain academic success, but the relationships among concepts vary by gender. Males’ intentions to persist in engineering are an outcome
of engagement processes during the first year, whereas females’ intentions to persist in engineering are manifest at the start of the first year.
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The past two years I have conducted an extensive literature and tool review to answer the question: “What should software engineers learn about building production-ready machine learning systems?”. During my research I noted that because the discipline of building production-ready machine learning systems is so new, it is not so easy to get the terminology straight. People write about it from different perspectives and backgrounds and have not yet found each other to join forces. At the same time the field is moving fast and far from mature. My focus on material that is ready to be used with our bachelor level students (applied software engineers, profession-oriented education), helped me to consolidate everything I have found into a body of knowledge for building production-ready machine learning (ML) systems. In this post I will first define the discipline and introduce the terminology for AI engineering and MLOps.
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