An on-line introduction to computational science via CSEP

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.

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.

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 & 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 & Technology.

From the earliest hardware and software through the latest, complexity has been something computer engineers, scientists and programmers have had to fight. Important fields of research and technology have originated, developed, or matured as side-effects of this fight. Some of these fields, such as computational complexity and planar graphs, address fundamental theories of broad significance. Others, such as reduced instruction set architectures, compiler-compilers, and high-level languages, are more applied. Other advances have actually contributed to complexity. In the area of building predictable real-time systems, for example, advances in computer performance (direct memory access, hierarchical storage, multiprocessing, and so on1) have led only to statistical performance improvements. But predictable, deterministic performance is still elusive. Some would argue that the easy availability of generic OS services may be responsible for a very significant increase in application complexity, not to mention a decrease in program robustness and correctness. Fighting complexity is not a futile task. Despite chronic lack of attention (and thus funding), much-needed complexity-fighting methods and tools will emerge. Eventually, a new generation of computer scientists, engineers, and programmers will emerge who are skilled at using these methods and tools. One day, the invention of a supertool will be as well-received as the construction of a supercomputer. Until that day, we have quite a bit of work to do. rom forest to finished product, wood moves through a series of stages that are little changed from sawmill practices of a hundred years ago. Many of the subjective decisions workers make along the way directly affect the quality and yield of the wood products. Wood grows more valuable and labor more expensive every day. At the same time, technology now exists to provide more complete information to decision makers.

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.

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.

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.

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. >

The Exascale Computing Project (ECP) provides a unique opportunity to advance computational science and engineering (CSE) through an accelerated growth phase in extreme-scale computing. Central to the project is the development of next-generation applications and software technologies that can exploit emerging architectures for optimal performance and provide high-fidelity, multiphysics, multiscale capabilities. However, disruptive changes in computer architectures and the complexities of tackling new frontiers in extreme-scale modeling, simulation, and analysis present daunting challenges to the productivity of software developers and the sustainability of software artifacts. Members of the CSE community - especially at extreme scales but more broadly at all scales of computing - face an urgent need to improve developer productivity, positively impacting product quality, development time, and staffing resources, and software sustainability, reducing the cost of maintaining, sustaining, and evolving software capabilities.

This study focuses on gender issues in terms of participation, achievement and duration of studies at the Tertiary level of education in Computer Science and Engineering (CS&E). For this reason, 1957 degrees earned by Computer Engineers were studied. These diplomas cover a 21 year period of graduation at the Computer Engineering and Informatics Department (CEID), University of Patras, Greece. The analysis of the data shows that: a) male graduate students outnumbered the female ones by three to one, b) in terms of achievement, no significant differences exist between male and female graduate computer engineers, and c) female students complete their studies earlier than their male counterparts.