8,434 research outputs found
A User Study for Evaluation of Formal Verification Results and their Explanation at Bosch
Context: Ensuring safety for any sophisticated system is getting more complex
due to the rising number of features and functionalities. This calls for formal
methods to entrust confidence in such systems. Nevertheless, using formal
methods in industry is demanding because of their lack of usability and the
difficulty of understanding verification results. Objective: We evaluate the
acceptance of formal methods by Bosch automotive engineers, particularly
whether the difficulty of understanding verification results can be reduced.
Method: We perform two different exploratory studies. First, we conduct a user
survey to explore challenges in identifying inconsistent specifications and
using formal methods by Bosch automotive engineers. Second, we perform a
one-group pretest-posttest experiment to collect impressions from Bosch
engineers familiar with formal methods to evaluate whether understanding
verification results is simplified by our counterexample explanation approach.
Results: The results from the user survey indicate that identifying refinement
inconsistencies, understanding formal notations, and interpreting verification
results are challenging. Nevertheless, engineers are still interested in using
formal methods in real-world development processes because it could reduce the
manual effort for verification. Additionally, they also believe formal methods
could make the system safer. Furthermore, the one-group pretest-posttest
experiment results indicate that engineers are more comfortable understanding
the counterexample explanation than the raw model checker output. Limitations:
The main limitation of this study is the generalizability beyond the target
group of Bosch automotive engineers.Comment: This manuscript is under review with the Empirical Software
Engineering journa
The conceptualisation, practice and value of Design Thinking in Entrepreneurship Education – an Educator’s Perspective
The thesis illustrates how entrepreneurship educators understand Design Thinking (conceptual understanding), how and on what level they apply it in their entrepreneurship teaching (educational practice) and why and for what perceived value they choose to do so (perceived value). By adopting a more critical and differentiated perspective on this integration than previously reported in the existing literature, this research study provides novel insights to the question of the conceptualization, practice and value of Design Thinking for Entrepreneurship Education – from an educator’s perspective. It follows an interpretive and qualitative approach, drawing upon semi-structured interviews from 29 entrepreneurship educators from Higher Education in the UK andNorthern Europe. Thus, the thesis demonstrates that entrepreneurship educators integrate Design Thinking in many ways and for different reasons.As a result, this thesis synthesises existing perspectives on Design Thinking (toolset, process, mindset) and defines a framework for the four forms (selective, idea-centric, procedural, holistic) of Design Thinking integration in the context of Entrepreneurship Education. The findings suggest that perceived values of Design Thinking could be explicit and implicit and that entrepreneurship educators integrate Design Thinking to provide value for their students’ learning but also to develop their own teaching practice. Overall, this study contributes to unfolding the Design Thinking concept and advocating a common ground among educators’ sense-making of a Design Thinking integration in Entrepreneurship Education. In conclusion, this study reaffirmed the wide application of Design Thinking within Entrepreneurship Education but presented the new centrality of the educator’s perspective at the core of the discussion on its utility and thus, moving towards convergence of a common understanding. The findings of this research would be of interest for entrepreneurshipeducators and entrepreneurship education researchers who seek a more profound and reflective integration of Design Thinking within Entrepreneurship Education
Student Success in Co-operative Education: An Analysis of Job Postings and Performance Evaluations
Co-operative education (co-op) programs combine coursework and work internships and have become popular worldwide. In this analysis, we use two separate co-op datasets to understand employer expectations and factors that contribute to student success.
First, we analyze over 13000 unique filled job postings from work terms in 2021. We group skills using k-means analysis and frequency counting to characterize the types of co-op jobs available to students, finding that co-op students are frequently required to possess both technical skills (such as knowledge of specific tools) and soft skills (such as communication). Next, we construct two separate weighted bipartite graphs linking the groups of academic programs advertised to by employers to either the required skills or titles of each job. By using community detection to co-cluster the nodes in each graph, we determine the types of skills and roles expected by employers for students in different programs. We find significant differences in the expectations of employers for students in each program, including the importance of soft skills for arts students and the prevalence of data science and artificial intelligence skills in many academic programs.
Second, using over 45000 performance evaluations collected separately for in-person (2019) and remote (2021) internship positions, we uncover the characteristics of successful co-op students. Each evaluation includes an overall performance rating and written comments and recommendations provided by the supervisor. By using logistic regression and word frequency counting to analyze supervisors’ general and recommendation comments, we find the most successful students to be excellent leaders and innovators, with remote students also being praised for their independence. Supervisors encourage remote students to be innovative and learn technological skills, while the supervisors of in-person students recommend improving oral communication and presentation abilities.
By identifying the job roles and required skills expected by employers for students in different academic programs, institutions can better prepare students for appropriate jobs. By understanding the skills that contribute to student success in remote and in-person contexts, students can focus on developing the most important skills for their intended work environment. Together, these findings highlight important skills that students should acquire in their early careers
Saggitarius: A DSL for Specifying Grammatical Domains
Common data types like dates, addresses, phone numbers and tables can have
multiple textual representations, and many heavily-used languages, such as SQL,
come in several dialects. These variations can cause data to be misinterpreted,
leading to silent data corruption, failure of data processing systems, or even
security vulnerabilities. Saggitarius is a new language and system designed to
help programmers reason about the format of data, by describing grammatical
domains -- that is, sets of context-free grammars that describe the many
possible representations of a datatype. We describe the design of Saggitarius
via example and provide a relational semantics. We show how Saggitarius may be
used to analyze a data set: given example data, it uses an algorithm based on
semi-ring parsing and MaxSAT to infer which grammar in a given domain best
matches that data. We evaluate the effectiveness of the algorithm on a
benchmark suite of 110 example problems, and we demonstrate that our system
typically returns a satisfying grammar within a few seconds with only a small
number of examples. We also delve deeper into a more extensive case study on
using Saggitarius for CSV dialect detection. Despite being general-purpose, we
find that Saggitarius offers comparable results to hand-tuned, specialized
tools; in the case of CSV, it infers grammars for 84% of benchmarks within 60
seconds, and has comparable accuracy to custom-built dialect detection tools.Comment: OOPSLA 202
Elements of Ion Linear Accelerators, Calm in The Resonances, Other_Tales
The main part of this book, Elements of Linear Accelerators, outlines in Part
1 a framework for non-relativistic linear accelerator focusing and accelerating
channel design, simulation, optimization and analysis where space charge is an
important factor. Part 1 is the most important part of the book; grasping the
framework is essential to fully understand and appreciate the elements within
it, and the myriad application details of the following Parts. The treatment
concentrates on all linacs, large or small, intended for high-intensity, very
low beam loss, factory-type application. The Radio-Frequency-Quadrupole (RFQ)
is especially developed as a representative and the most complicated linac form
(from dc to bunched and accelerated beam), extending to practical design of
long, high energy linacs, including space charge resonances and beam halo
formation, and some challenges for future work. Also a practical method is
presented for designing Alternating-Phase- Focused (APF) linacs with long
sequences and high energy gain. Full open-source software is available. The
following part, Calm in the Resonances and Other Tales, contains eyewitness
accounts of nearly 60 years of participation in accelerator technology.
(September 2023) The LINACS codes are released at no cost and, as always,with
fully open-source coding. (p.2 & Ch 19.10)Comment: 652 pages. Some hundreds of figures - all images, there is no data in
the figures. (September 2023) The LINACS codes are released at no cost and,
as always,with fully open-source coding. (p.2 & Ch 19.10
Knowledge extraction from unstructured data
Data availability is becoming more essential, considering the current growth of web-based data. The data available on the web are represented as unstructured, semi-structured, or structured data. In order to make the web-based data available for several Natural Language Processing or Data Mining tasks, the data needs to be presented as machine-readable data in a structured format. Thus, techniques for addressing the problem of capturing knowledge from unstructured data sources are needed. Knowledge extraction methods are used by the research communities to address this problem; methods that are able to capture knowledge in a natural language text and map the extracted knowledge to existing knowledge presented in knowledge graphs (KGs). These knowledge extraction methods include Named-entity recognition, Named-entity Disambiguation, Relation Recognition, and Relation Linking. This thesis addresses the problem of extracting knowledge over unstructured data and discovering patterns in the extracted knowledge. We devise a rule-based approach for entity and relation recognition and linking. The defined approach effectively maps entities and relations within a text to their resources in a target KG. Additionally, it overcomes the challenges of recognizing and linking entities and relations to a specific KG by employing devised catalogs of linguistic and domain-specific rules that state the criteria to recognize entities in a sentence of a particular language, and a deductive database that encodes knowledge in community-maintained KGs. Moreover, we define a Neuro-symbolic approach for the tasks of knowledge extraction in encyclopedic and domain-specific domains; it combines symbolic and sub-symbolic components to overcome the challenges of entity recognition and linking and the limitation of the availability of training data while maintaining the accuracy of recognizing and linking entities. Additionally, we present a context-aware framework for unveiling semantically related posts in a corpus; it is a knowledge-driven framework that retrieves associated posts effectively. We cast the problem of unveiling semantically related posts in a corpus into the Vertex Coloring Problem. We evaluate the performance of our techniques on several benchmarks related to various domains for knowledge extraction tasks. Furthermore, we apply these methods in real-world scenarios from national and international projects. The outcomes show that our techniques are able to effectively extract knowledge encoded in unstructured data and discover patterns over the extracted knowledge presented as machine-readable data. More importantly, the evaluation results provide evidence to the effectiveness of combining the reasoning capacity of the symbolic frameworks with the power of pattern recognition and classification of sub-symbolic models
Meta-ontology fault detection
Ontology engineering is the field, within knowledge representation, concerned with using logic-based formalisms to represent knowledge, typically moderately sized knowledge bases called ontologies. How to best develop, use and maintain these ontologies has produced relatively large bodies of both formal, theoretical and methodological research.
One subfield of ontology engineering is ontology debugging, and is concerned with preventing, detecting and repairing errors (or more generally pitfalls, bad practices or faults) in ontologies. Due to the logical nature of ontologies and, in particular, entailment, these faults are often both hard to prevent and detect and have far reaching consequences. This makes ontology debugging one of the principal challenges to more widespread adoption of ontologies in applications.
Moreover, another important subfield in ontology engineering is that of ontology alignment: combining multiple ontologies to produce more powerful results than the simple sum of the parts. Ontology alignment further increases the issues, difficulties and challenges of ontology debugging by introducing, propagating and exacerbating faults in ontologies.
A relevant aspect of the field of ontology debugging is that, due to the challenges and difficulties, research within it is usually notably constrained in its scope, focusing on particular aspects of the problem or on the application to only certain subdomains or under specific methodologies. Similarly, the approaches are often ad hoc and only related to other approaches at a conceptual level. There are no well established and widely used formalisms, definitions or benchmarks that form a foundation of the field of ontology debugging.
In this thesis, I tackle the problem of ontology debugging from a more abstract than usual point of view, looking at existing literature in the field and attempting to extract common ideas and specially focussing on formulating them in a common language and under a common approach. Meta-ontology fault detection is a framework for detecting faults in ontologies that utilizes semantic fault patterns to express schematic entailments that typically indicate faults in a systematic way. The formalism that I developed to represent these patterns is called existential second-order query logic (abbreviated as ESQ logic). I further reformulated a large proportion of the ideas present in some of the existing research pieces into this framework and as patterns in ESQ logic, providing a pattern catalogue.
Most of the work during my PhD has been spent in designing and implementing
an algorithm to effectively automatically detect arbitrary ESQ patterns in arbitrary ontologies. The result is what we call minimal commitment resolution for ESQ logic, an extension of first-order resolution, drawing on important ideas from higher-order unification and implementing a novel approach to unification problems using dependency graphs. I have proven important theoretical properties about this algorithm such as its soundness, its termination (in a certain sense and under certain conditions) and its fairness or completeness in the enumeration of infinite spaces of solutions.
Moreover, I have produced an implementation of minimal commitment resolution for ESQ logic in Haskell that has passed all unit tests and produces non-trivial results on small examples. However, attempts to apply this algorithm to examples of a more realistic size have proven unsuccessful, with computation times that exceed our tolerance levels.
In this thesis, I have provided both details of the challenges faced in this regard,
as well as other successful forms of qualitative evaluation of the meta-ontology fault detection approach, and discussions about both what I believe are the main causes of the computational feasibility problems, ideas on how to overcome them, and also ideas on other directions of future work that could use the results in the thesis to contribute to the production of foundational formalisms, ideas and approaches to ontology debugging that can properly combine existing constrained research. It is unclear to me whether minimal commitment resolution for ESQ logic can, in its current shape, be implemented efficiently or not, but I believe that, at the very least, the theoretical and conceptual underpinnings that I have presented in this thesis will be useful to produce more
foundational results in the field
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The History of Periodicals in Hungarian Secondary Mathematics Education Between 1867 and 1956
The purpose of this study was to determine how secondary mathematics education changes in Hungary between 1867 and 1956 were reflected in journal articles of that time. In an attempt to accomplish this purpose, the researcher sought to identify which major political and socioeconomic factors affected the role and content of periodicals, how the content and approach of the topics changed, and who were the most prominent and influential authors of the periodicals between 1867 and 1956. This research investigates Journal of the National Association of Secondary School Teachers, the first periodical devoted to Hungarian secondary education published between 1868 and 1944, and Teaching of Mathematics, the first Hungarian periodical dedicated to mathematic education published between 1953 and 1956. The researcher employed historical-research methodology to examine the articles of the periodicals and categorize them based on similar content such as curriculum, teaching methods, school mathematics, and book/textbook reviews. The study also provides brief summaries of several articles.
This research has shown that the history of Hungarian education in general was often influenced by foreign and domestic politics and ideologies. Studying journal articles provides a unique opportunity to observe real-time communication between educators and administrators and to analyze the effect of social and political changes which influenced mathematics education.
Between 1867 and 1956, Hungary underwent major political and social changes—a dual Monarchy with Austria, independence as a truncated state, and occupation by Germany and later the Soviet Union. These changes significantly altered Hungary as a country and impacted its education system. While every country has undergone political and ideological influences in its educational history, Hungary was particularly affected by neighboring countries such as Germany and later the Soviet Union.
Taking the broader perspective of the evolution of periodicals, this study demonstrated that the history of periodicals as a general form of scientific communication has passed through several stages. The journals, in some respects, are a bridge between educators and were affected by the political atmosphere of the country.
In general, this study has shown that Journal of the National Association of Secondary School Teachers and Teaching of Mathematics were heavily influenced by social and political changes in Hungary, as well as foreign influences from countries such as Germany and the Soviet Union. These factors collectively formed Hungarian mathematics education between 1867 and 1956
Modelling, Monitoring, Control and Optimization for Complex Industrial Processes
This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors
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