Economics and Engineering for Preserving Digital Content

Progress towards practical long-term preservation seems to be stalled. Preservationists cannot afford specially developed technology, but must exploit what is created for the marketplace. Economic and technical facts suggest that most preservation ork should be shifted from repository institutions to information producers and consumers. Prior publications describe solutions for all known conceptual challenges of preserving a single digital object, but do not deal with software development or scaling to large collections. Much of the document handling software needed is available. It has, however, not yet been selected, adapted, integrated, or deployed for digital preservation. The daily tools of both information producers and information consumers can be extended to embed preservation packaging without much burdening these users. We describe a practical strategy for detailed design and implementation. Document handling is intrinsically complicated because of human sensitivity to communication nuances. Our engineering section therefore starts by discussing how project managers can master the many pertinent details.

Trialing project-based learning in a new EAP ESP course: A collaborative reflective practice of three college English teachers

Currently in many Chinese universities, the traditional College English course is facing the risk of being ‘marginalized’, replaced or even removed, and many hours previously allocated to the course are now being taken by EAP or ESP. At X University in northern China, a curriculum reform as such is taking place, as a result of which a new course has been created called ‘xue ke’ English. Despite the fact that ‘xue ke’ means subject literally, the course designer has made it clear that subject content is not the target, nor is the course the same as EAP or ESP. This curriculum initiative, while possibly having been justified with a rationale of some kind (e.g. to meet with changing social and/or academic needs of students and/or institutions), this is posing a great challenge for, as well as considerable pressure on, a number of College English teachers who have taught this single course for almost their entire teaching career. In such a context, three teachers formed a peer support group in Semester One this year, to work collaboratively co-tackling the challenge, and they chose Project-Based Learning (PBL) for the new course. This presentation will report on the implementation of this project, including the overall designing, operational procedure, and the teachers’ reflections. Based on discussion, pre-agreement was reached on the purpose and manner of collaboration as offering peer support for more effective teaching and learning and fulfilling and pleasant professional development. A WeChat group was set up as the chief platform for messaging, idea-sharing, and resource-exchanging. Physical meetings were supplementary, with sound agenda but flexible time, and venues. Mosoteach cloud class (lan mo yun ban ke) was established as a tool for virtual learning, employed both in and after class. Discussions were held at the beginning of the semester which determined only brief outlines for PBL implementation and allowed space for everyone to autonomously explore in their own way. Constant further discussions followed, which generated a great deal of opportunities for peer learning and lesson plan modifications. A reflective journal, in a greater or lesser detailed manner, was also kept by each teacher to record the journey of the collaboration. At the end of the semester, it was commonly recognized that, although challenges existed, the collaboration was overall a success and they were all willing to continue with it and endeavor to refine it to be a more professional and productive approach

Highly focused document retrieval in aerospace engineering : user interaction design and evaluation

Purpose – This paper seeks to describe the preliminary studies (on both users and data), the design and evaluation of the K-Search system for searching legacy documents in aerospace engineering. Real-world reports of jet engine maintenance challenge the current indexing practice, while real users’ tasks require retrieving the information in the proper context. K-Search is currently in use in Rolls-Royce plc and has evolved to include other tools for knowledge capture and management. Design/methodology/approach – Semantic Web techniques have been used to automatically extract information from the reports while maintaining the original context, allowing a more focused retrieval than with more traditional techniques. The paper combines semantic search with classical information retrieval to increase search effectiveness. An innovative user interface has been designed to take advantage of this hybrid search technique. The interface is designed to allow a flexible and personal approach to searching legacy data. Findings – The user evaluation showed that the system is effective and well received by users. It also shows that different people look at the same data in different ways and make different use of the same system depending on their individual needs, influenced by their job profile and personal attitude. Research limitations/implications – This study focuses on a specific case of an enterprise working in aerospace engineering. Although the findings are likely to be shared with other engineering domains (e.g. mechanical, electronic), the study does not expand the evaluation to different settings. Originality/value – The study shows how real context of use can provide new and unexpected challenges to researchers and how effective solutions can then be adopted and used in organizations.</p

Simulation in manufacturing and business: A review

Copyright @ 2009 Elsevier B.V.This paper reports the results of a review of simulation applications published within peer-reviewed literature between 1997 and 2006 to provide an up-to-date picture of the role of simulation techniques within manufacturing and business. The review is characterised by three factors: wide coverage, broad scope of the simulation techniques, and a focus on real-world applications. A structured methodology was followed to narrow down the search from around 20,000 papers to 281. Results include interesting trends and patterns. For instance, although discrete event simulation is the most popular technique, it has lower stakeholder engagement than other techniques, such as system dynamics or gaming. This is highly correlated with modelling lead time and purpose. Considering application areas, modelling is mostly used in scheduling. Finally, this review shows an increasing interest in hybrid modelling as an approach to cope with complex enterprise-wide systems

Corpus Statistics for Measuring Business Process Similarity

In a rapidly changing environment, organizations must adapt their business processes continuously. While numerous methods enable enterprises to conceptualize and analyze their organizational structure, the task of business process modeling remains complex and time-consuming. However, by reusing and adapting existing process models, enterprises can reduce the task’s complexity while improving the quality of results. To facilitate the identification of adaptable processes, several techniques of business process similarity (BPS) have been proposed in recent years. Although most approaches produce sound results in controlled evaluations, this paper argues that their applicability is limited when analyzing real-world processes, which do not fully comply with notational labeling specifications. Consequently, we aim to enhance existing BPS techniques by using corpus statistics to account for the explanatory power of words within labels of process models. Results from our evaluation suggest that corpus statistics can improve BPS computations and can positively influence the quality of practical implications

Recommending Recommendations to Support the Defense Acquisition Workforce

Excerpt from the Proceedings of the Nineteenth Annual Acquisition Research SymposiumThis paper presentings the preliminary results of a research study to support the Defense Acquisition Workforce with a Natural Language Processing (NLP)/Machine Learning (ML) prototype of a system to determine what are the most relevant recommendations that stakeholders are providing to the Defense Acquisition community. The problem addressed by the research study is in the realm of NLP and ML and it is part of the quite popular category of “recommendation systems.” Unlike the majority of the cases in this category, though, this task does not focus on numerical data representing behaviors (like in shopping recommendations), but on extracting user-specific relevance from text and “recommending” a document or part of it. In order to identify important pieces of these texts, subjective text analysis is required to be run. The method used for the analysis is the “room theory framework” by Lipizzi et al. (2021) which applies the Framework Theory by Marvin Minsky (1974) through the use of text vectorization. This framework has three main components: a vectorized corpus representing the knowledge base of the specific domain (the “room”), a set of keywords or phrases defining the specific points of interest for the recommendation (the “benchmarks”) and the documents to be analyzed. The documents are then vectorized using the “room” and compared to the “benchmarks.” The sentences/paragraphs within a given document that are most similar to the benchmarks, and thus presumably the most important parts of the document, are highlighted. This enables the DAU reviewers to submit a document, run the program, and be able to clearly see what recommendations will be the most useful.Approved for public release; distribution is unlimited

Recommending Recommendations to Support the Defense Acquisition Workforce

Excerpt from the Proceedings of the Nineteenth Annual Acquisition Research SymposiumThis paper presentings the preliminary results of a research study to support the Defense Acquisition Workforce with a Natural Language Processing (NLP)/Machine Learning (ML) prototype of a system to determine what are the most relevant recommendations that stakeholders are providing to the Defense Acquisition community. The problem addressed by the research study is in the realm of NLP and ML and it is part of the quite popular category of “recommendation systems.” Unlike the majority of the cases in this category, though, this task does not focus on numerical data representing behaviors (like in shopping recommendations), but on extracting user-specific relevance from text and “recommending” a document or part of it. In order to identify important pieces of these texts, subjective text analysis is required to be run. The method used for the analysis is the “room theory framework” by Lipizzi et al. (2021) which applies the Framework Theory by Marvin Minsky (1974) through the use of text vectorization. This framework has three main components: a vectorized corpus representing the knowledge base of the specific domain (the “room”), a set of keywords or phrases defining the specific points of interest for the recommendation (the “benchmarks”) and the documents to be analyzed. The documents are then vectorized using the “room” and compared to the “benchmarks.” The sentences/paragraphs within a given document that are most similar to the benchmarks, and thus presumably the most important parts of the document, are highlighted. This enables the DAU reviewers to submit a document, run the program, and be able to clearly see what recommendations will be the most useful.Approved for public release; distribution is unlimited