Fighting Complexity in Computer Systems

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Attracting and Retaining Women in Computer Science and Engineering: Evaluating the Results Abstract Computer science and engineering communities have been exploring a variety of activities and techniques to attract and retain more students, especially women and minorities, to computer science and computer engineering degree programs1. This paper briefly describes the efforts and results of a plan for actively recruiting young women into undergraduate computer engineering and computer science programs hosted by the University of North Texas (UNT). It also describes a series of activities aimed at improving the retention rate of students already in our programs, particularly during the freshman year. Such recruitment and retention efforts are critical to the country’s efforts to increase the number of engineering professionals, and are a priority for the Computer Science and Engineering (CSE) Department at UNT. We initially designed a three-part plan to achieve our recruitment and retention goals: • Sponsorship of portable and mobile summer computer engineering robotics camps for middle and high-school women students, coordinating with the regional Girl Scouts councils and other organizations to help with the recruitment; • Creation of an Ambassador program using young women currently enrolled in the upper division of current computer science and computer engineering programs as a form of outreach to area high schools and junior colleges; and • Expansion of our successful undergraduate mentoring program by using the Ambassador cohort mentioned above as mentors for incoming freshman and first-year transfer women entering our programs. This paper will focus primarily on the summer camp program and present an analysis of the results we have seen to date after 2 years of camp activities. Results from student surveys and parent surveys will be presented. The paper concludes with recommended changes and improvements in the program, as well as a discussion of adaptations that would create programs suitable for implementation at other institutions as well as programs aimed at a different target population. The three phases previously enumerated each build upon currently accepted educational practices. The robotics summer camp in particular used problem-based learning approaches, similar to those described in The Power of Problem-Based Learning2. This study clearly demonstrates the significant benefits of teaching students how to think by using a problem-based approach. We also developed a mobile laboratory so that the summer camp can be held at several locations, thus broadening and expanding the reach of the camps to traditionally underserved populations and geographical regions. Similarly, both the ambassador and mentoring programs derive from research showing how the recruitment and retention of women in engineering- related fields can be increased by providing opportunities to develop student-to-student relationships3, 4.

Computational science and engineering (CSE) faces a number of open issues. There is no core community; CSE is a diverse collection of researchers from different disciplines. Linguistic and practical obstacles hinder effective information exchanges. New journals are just now getting started. Still in the process of establishing itself, the CSE community must now set standards and define quality research. One of the most important intellectual challenges of this new field is to develop new algorithms. This, in turn, depends heavily on advances in computer architectures. Over the past two decades, the interplay between advances in hardware and algorithms has resulted in near exponential growth in computing power and consequently in the scope of the problems we can address. A discussion is given on CSE education, focusing on the syllabus, setting up a CSE course, and the CSE Project (CSEP) which involves the production of a set of hypermedia teaching materials.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Research has substantially increased in modern times due to availability and search facility of literature sources through Internet. Carrying out research and proving that it is done is a necessity for excellent academic career and for satisfying requirements of Master or PhD degrees in most universities. There is no recipe book for producing the research with desired taste and quantity, however, general methodology does exist. This paper presents crucial parts concerning research process in Computer Science and Engineering (CSE). The paper discusses the important parts of research methodology in CSE including research problem formulation, literature review, research design, and research communication. The paper presents each phase of the research process with essential ingredients, moreover, wherever required, the paper also provides pointers for further reading. The presented discussion is in the context of research applicable in CSE field. Therefore, we expect that this paper would become a good starting point for newbie researchers in CSE.

Creating an optimal conditions for producing generations of successful Computer scientists and engineers is very demanding. Many aspects have to be taken into consideration. One of the factors is the quality of the Bachelor's education system that actually enables the diplomas in Computer Science and Engineering. However, the students enrolling in the Bachelor's system have to be optimally prepared to follow the curriculum. In this paper we present some of the many factors that influenced the generations of Computer scientists and engineers that have earned their BSc degree in the Faculty of Computer Science and Engineering, and the institutions that preceded this Faculty in the years before 2011. Such factors, investigated in this paper are: the changes in the primary and secondary educational system and the aspects of these systems that influence the informatics knowledge of the pupils on one hand, and on the other hand the evolution of the system of competitions in informatics that sparkles the interest in the talented pupils and enables the most talented and hardworking ones to compete in the international Olympiads in informatics. As a result of improving these two parallel systems, the number of enrolled students in the faculties that teach Computer Science and Engineering has raised. Moreover, some of these pupils have turned into great entrepreneurs and have started their own successful software companies.

In 1997 a new interdisciplinary Diploma program in Computational Science and Engineering (CSE) was started at ETH Zurich. We report on the changes of the curriculum due to the Bologna Declaration of June 19, 1999 by the European Ministers of Education. The new Bachelor program in CSE at ETH Zurich started in October 2003 and the Master program in CSE will follow in October 2005. We will describe both programs in some detail as well as the design principles. We will also discuss the boundary conditions imposed by ETH and we will give some preliminary experiences.

Machine Learning (ML) has become essential in several industries. In Computational Science and Engineering (CSE), the complexity of the ML lifecycle comes from the large variety of data, scientists' expertise, tools, and workflows. If data are not tracked properly during the lifecycle, it becomes unfeasible to recreate a ML model from scratch or to explain to stackholders how it was created. The main limitation of provenance tracking solutions is that they cannot cope with provenance capture and integration of domain and ML data processed in the multiple workflows in the lifecycle, while keeping the provenance capture overhead low. To handle this problem, in this paper we contribute with a detailed characterization of provenance data in the ML lifecycle in CSE; a new provenance data representation, called PROV-ML, built on top of W3C PROV and ML Schema; and extensions to a system that tracks provenance from multiple workflows to address the characteristics of ML and CSE, and to allow for provenance queries with a standard vocabulary. We show a practical use in a real case in the O&G industry, along with its evaluation using 239,616 CUDA cores in parallel.

Abstract: Owing to the entry of COVID-19, starting from the year 2000, India managed online education well for more than a year and a half. Now, the question is to understand whether the online mode of education is as effective as the face-to-face classes. This study intends to focus on identifying the challenges and finding the opportunities to enhance the quality of online engineering education with respect to Computer Science and Engineering (CSE) branch. A survey was conducted using a questionnaire involving the chosen 2nd year, 3rd year, and 4th year students of CSE department, Velammal College of Engineering &amp; Technology, Madurai (VCET), who have had the experience of acquiring knowledge through both offline and online modes. The spreadsheet software was used to filter, organize as well as visualize quantitative data, and descriptive methodology was adopted for the data analysis. The result of the study will lay a scope to understand the existing gaps in online CSE education and the proposed ideas to fill the same enhancing the resources. Further, this study may play a pivotal role in making effective online CSE education at par with face-to-face classes completely possible and preferable. Keywords: COVID-19; CSE; digital skills; online education; Velammal College of Engineering &amp; Technology.

The utility of complexity metrics during code reviews for CSE software projects

Computer Science and Engineering (CSE) is a dynamic and rapidly evolving field that encompasses a wide range of topics, from fundamental algorithms and programming languages to cutting-edge technologies like Artificial Intelligence (AI), Quantum Computing and Cyber security. This paper provides a comprehensive overview of CSE, tracing its historical development and exploring the latest advancements and emerging trends in the field. The paper highlights the core concepts and principles of CSE, discusses the interdisciplinary nature and examines how it has become an integral part of modern society. Additionally, it provides an analysis of the most recent advancements in CSE, covering topics such as Artificial intelligence, Block chain, Cloud computing and Internet of Things (IoT) etc., overall, this paper aims to provide readers with a comprehensive understanding of the current landscape of CSE and some of the technological trends that are shaping its future.

This article presents two case studies aimed at exploring the use of self-explanations in the context of computational science and engineering (CSE) education. The self-explanations were elicited as students’ in-code comments of a set of worked-examples, and the cases involved two different approaches to CSE education: glass box and black box. The glass-box approach corresponds to a programming course for materials science and engineering students that focuses on introducing programming concepts while solving disciplinary problems. The black-box approach involves the introduction of Python-based computational tools within a thermodynamics course to represent disciplinary phenomena. Two semesters of data collection for each case study allowed us to identify the effect of using in-code comments as a self-explanation strategy on students’ engagement with the worked-examples and students’ perceptions of these activities within each context. The results suggest that the use of in-code comments as a self-explanation strategy increased students’ awareness of the worked-examples while engaging with them. The students’ perceived uses of the in-code commenting activities include: understanding the example, making a connection between the programming code and the disciplinary problem, and becoming familiar with the programming language syntax, among others.

With rapid development of modern society, the requirements for high precise temperature and humidity is growing rapidly, for example production, storage, transportation, environment etc., these all have strict requirements for temperature and humidity testing, so the real-time monitoring of temperature and humidity and alarm prompt is extremely important. In this paper, a temperature and humidity automatic alarm recorder is designed, which uses stm32 as control center, combines the technique of sensor technology, GSM technology and serial port to finish button control measurement of temperature and humidity or two road all the way. In the study, the system's hardware and software design are introduced in detail and testing results show that the system can realize the function of the temperature and humidity measurement record and alarm.

the University of Amsterdam, May 20-31, 1974.This Tract collects the lecture notes of five of the courses given.The sixth course, given by Dr. R. Kowalski on Predicate Logic as a Programming Language in Artificial Intelligence, is scheduled to appear elsewhere.We are very grateful to the Netherlands Organization for the Advancement of Pure Research (Z.W.O.)

DfAnalyzer is a tool for monitoring, debugging, and analyzing dataflows generated by Computational Science and Engineering (CSE) applications. It collects strategic raw data, registering provenance data, and enabling query processing, all asynchronously and at runtime. DfAnalyzer provides lightweight dataflow components to be invoked by CSE applications using High-Performance Computing (HPC), in the same way computational scientists plug HPC (e.g., PETSc) and visualization (e.g., ParaView) libraries. We show DfAnalyzer’s main functionalities and how to analyze dataflows in CSE applications at runtime. The performance evaluation of CSE executions for a complex multiphysics application shows that DfAnalyzer has negligible time overhead on the total elapsed time.

It is often observed that software engineering (SE) processes and practices for computational science and engineering (CSE) lag behind other SE areas [7]. This issue has been a concern for funding agencies, since new research increasingly relies upon and produces computational tools. At the same time, CSE research organizations find it difficult to prescribe formal SE practices for funded projects.Theoretical and experimental science rely heavily on independent verification of results as part of the scientific process. Computational science should have the same regard for independent verification but it does not.In this paper, we present an argument for using reproducibility and independent verification requirements as a driver to improve SE processes and practices. We describe existing efforts that support our argument, how these requirements can impact SE, challenges we face, and new opportunities for using reproducibility requirements as a driver for higher quality CSE software.

A brief informal memorandum, extolling the promise of supercomputers, began the countdown for the launch of an Institute for Applied Mathematics and Computer Science at the NASA Langley Research Center in Hampton, Virginia. The name was changed before launch to the Institute for Computer Applications in Science and Engineering, and the acronym ICASE is now recognized around the world for its computational science and engineering (CSE) research. For over two decades the ICASE research program, in addition to being computational, has been multidisciplinary and multisectoral. ICASE thrives on interfaces: those between applied mathematics, application areas, and computer science; and those between NASA academia, and industry. Its purpose is to serve as a forerunner and build expertise in areas of growing or future relevance to Langley. The paper discusses some of the ICASE programs in mathematics and computer science. >