Object linking in repositories

This topic is covered in three sections. The first section explores some of the architectural ramifications of extending the Eichmann/Atkins lattice-based classification scheme to encompass the assets of the full life cycle of software development. A model is considered that provides explicit links between objects in addition to the edges connecting classification vertices in the standard lattice. The second section gives a description of the efforts to implement the repository architecture using a commercially available object-oriented database management system. Some of the features of this implementation are described, and some of the next steps to be taken to produce a working prototype of the repository are pointed out. In the final section, it is argued that design and instantiation of reusable components have competing criteria (design-for-reuse strives for generality, design-with-reuse strives for specificity) and that providing mechanisms for each can be complementary rather than antagonistic. In particular, it is demonstrated how program slicing techniques can be applied to customization of reusable components

Applying Hierarchical Tag-Topic Models to Stack Overflow

Stack Overflow is a question and answer site for programming questions. It has become one of the most widely used resources for programmers, with many programmers accessing the site multiple times per day. A threat to the continued success of Stack Overflow is the ability to efficiently search the site. Existing research suggests that the inability to find certain questions results inunanswered questions, long delays in answering questions, or questions which are unable to be found by future visitors to the site. Further research suggests that questions with poor tag quality are particularly vulnerable to these issues.In this thesis, two approaches are considered for improving tag quality and search efficiency: automatic tag recommendations for question authors, and organizing the existing set of tags in a hierarchy from general to specific for Stack Overflow readers. A hierarchical organization is proposed for it\u27s ability to assist exploratory searches of the site.L2H, a hierarchical tag topic model, is a particularly interesting solution to these approaches because it can address both approaches with the same model. L2H is evaluated in detail on several proposed evaluation criteria to gauge it\u27s fitness for addressing these search challenges on Stack Overflow

Matching Possible Mitigations to Cyber Threats: A Document-Driven Decision Support Systems Approach

Cyber systems are ubiquitous in all aspects of society. At the same time, breaches to cyber systems continue to be front-page news (Calfas, 2018; Equifax, 2017) and, despite more than a decade of heightened focus on cybersecurity, the threat continues to evolve and grow, costing globally up to $575 billion annually (Center for Strategic and International Studies, 2014; Gosler & Von Thaer, 2013; Microsoft, 2016; Verizon, 2017). To address possible impacts due to cyber threats, information system (IS) stakeholders must assess the risks they face. Following a risk assessment, the next step is to determine mitigations to counter the threats that pose unacceptably high risks. The literature contains a robust collection of studies on optimizing mitigation selections, but they universally assume that the starting list of appropriate mitigations for specific threats exists from which to down-select. In current practice, producing this starting list is largely a manual process and it is challenging because it requires detailed cybersecurity knowledge from highly decentralized sources, is often deeply technical in nature, and is primarily described in textual form, leading to dependence on human experts to interpret the knowledge for each specific context. At the same time cybersecurity experts remain in short supply relative to the demand, while the delta between supply and demand continues to grow (Center for Cyber Safety and Education, 2017; Kauflin, 2017; Libicki, Senty, & Pollak, 2014). Thus, an approach is needed to help cybersecurity experts (CSE) cut through the volume of available mitigations to select those which are potentially viable to offset specific threats. This dissertation explores the application of machine learning and text retrieval techniques to automate matching of relevant mitigations to cyber threats, where both are expressed as unstructured or semi-structured English language text. Using the Design Science Research Methodology (Hevner & March, 2004; Peffers, Tuunanen, Rothenberger, & Chatterjee, 2007), we consider a number of possible designs for the matcher, ultimately selecting a supervised machine learning approach that combines two techniques: support vector machine classification and latent semantic analysis. The selected approach demonstrates high recall for mitigation documents in the relevant class, bolstering confidence that potentially viable mitigations will not be overlooked. It also has a strong ability to discern documents in the non-relevant class, allowing approximately 97% of non-relevant mitigations to be excluded automatically, greatly reducing the CSE’s workload over purely manual matching. A false v positive rate of up to 3% prevents totally automated mitigation selection and requires the CSE to reject a few false positives. This research contributes to theory a method for automatically mapping mitigations to threats when both are expressed as English language text documents. This artifact represents a novel machine learning approach to threat-mitigation mapping. The research also contributes an instantiation of the artifact for demonstration and evaluation. From a practical perspective the artifact benefits all threat-informed cyber risk assessment approaches, whether formal or ad hoc, by aiding decision-making for cybersecurity experts whose job it is to mitigate the identified cyber threats. In addition, an automated approach makes mitigation selection more repeatable, facilitates knowledge reuse, extends the reach of cybersecurity experts, and is extensible to accommodate the continued evolution of both cyber threats and mitigations. Moreover, the selection of mitigations applicable to each threat can serve as inputs into multifactor analyses of alternatives, both automated and manual, thereby bridging the gap between cyber risk assessment and final mitigation selection

Scale Economies and Synergies in Horizontal Merger Analysis

Three years ago, the Antitrust Division and the Federal Trade Commission revised their Horizontal Merger Guidelines to articulate in greater detail how they would treat claims of efficiencies associated with horizontal mergers: claims that are frequently made, as for instance in the recently proposed merger between Heinz and Beech-Nut in the market for baby food. While these revisions to the Guidelines have a solid economic basis, they leave open many questions, both in theory and in practice. In this essay, we evaluate some aspects of the treatment of efficiencies, based on three years of enforcement experience under the revised Guidelines, including several litigated mergers, and based on economic principles drawn from oligopoly theory regarding cost savings, competition, and consumer welfare.

Concept coupling learning for improving concept lattice-based document retrieval

© 2017 Elsevier Ltd The semantic information in any document collection is critical for query understanding in information retrieval. Existing concept lattice-based retrieval systems mainly rely on the partial order relation of formal concepts to index documents. However, the methods used by these systems often ignore the explicit semantic information between the formal concepts extracted from the collection. In this paper, a concept coupling relationship analysis model is proposed to learn and aggregate the intra- and inter-concept coupling relationships. The intra-concept coupling relationship employs the common terms of formal concepts to describe the explicit semantics of formal concepts. The inter-concept coupling relationship adopts the partial order relation of formal concepts to capture the implicit dependency of formal concepts. Based on the concept coupling relationship analysis model, we propose a concept lattice-based retrieval framework. This framework represents user queries and documents in a concept space based on fuzzy formal concept analysis, utilizes a concept lattice as a semantic index to organize documents, and ranks documents with respect to the learned concept coupling relationships. Experiments are performed on the text collections acquired from the SMART information retrieval system. Compared with classic concept lattice-based retrieval methods, our proposed method achieves at least 9%, 8% and 15% improvement in terms of average MAP, IAP@11 and P@10 respectively on all the collections

Design Ltd.: Renovated Myths for the Development of Socially Embedded Technologies

This paper argues that traditional and mainstream mythologies, which have been continually told within the Information Technology domain among designers and advocators of conceptual modelling since the 1960s in different fields of computing sciences, could now be renovated or substituted in the mould of more recent discourses about performativity, complexity and end-user creativity that have been constructed across different fields in the meanwhile. In the paper, it is submitted that these discourses could motivate IT professionals in undertaking alternative approaches toward the co-construction of socio-technical systems, i.e., social settings where humans cooperate to reach common goals by means of mediating computational tools. The authors advocate further discussion about and consolidation of some concepts in design research, design practice and more generally Information Technology (IT) development, like those of: task-artifact entanglement, universatility (sic) of End-User Development (EUD) environments, bricolant/bricoleur end-user, logic of bricolage, maieuta-designers (sic), and laissez-faire method to socio-technical construction. Points backing these and similar concepts are made to promote further discussion on the need to rethink the main assumptions underlying IT design and development some fifty years later the coming of age of software and modern IT in the organizational domain.Comment: This is the peer-unreviewed of a manuscript that is to appear in D. Randall, K. Schmidt, & V. Wulf (Eds.), Designing Socially Embedded Technologies: A European Challenge (2013, forthcoming) with the title "Building Socially Embedded Technologies: Implications on Design" within an EUSSET editorial initiative (www.eusset.eu/

SHPIA 2.0: An Easily Scalable, Low-Cost, Multi-purpose Smart Home Platform for Intelligent Applications

Sensors, electronic devices, and smart systems have invaded the market and our daily lives. As a result, their utility in smart home contexts to improve the quality of life, especially for the elderly and people with special needs, is getting stronger and stronger. Therefore, many systems based on smart applications and intelligent devices have been developed, for example, to monitor people’s environmental contexts, help in daily-life activities, and analyze their health status. However, most existing solutions have drawbacks related to accessibility and usability. They tend to be expensive and lack generality and interoperability. These solutions are not easily scalable and are typically designed for specific constrained scenarios. This paper tackles such drawbacks by presenting SHPIA 2.0, an easily scalable, low-cost, multi-purpose smart home platform for intelligent applications. It leverages low-cost Bluetooth Low Energy (BLE) devices featuring both BLE connected and BLE broadcast modes, to transform common objects of daily life into smart objects. Moreover, SHPIA 2.0 allows the col- lection and automatic labeling of different data types to provide indoor monitoring and assistance. Specifically, SHPIA 2.0 is designed to be adaptable to different home-based application scenarios, including human activity recognition, coaching systems, and occupancy detection and counting. The SHPIA platform is open source and freely available to the scientific community, fostering collaboration and innovation

Some Reflections on Long-Term Lessons and Implications of the Access to Justice Technology Bill of Rights Process

The Washington State Access to Justice Technology Bill of Rights (ATJ-TBoR) process (Process), described in detail in both its substantive and procedural aspects in other papers in this volume, has the potential to have a major impact on access to justice in the state—its first and primary goal. In addition, however, it has the potential to have broader implications in the legal world, in the process of legal innovation, in access to other services, and internationally. This paper is intended to start the debate about these implications and how they can be optimized and maximized