Decision Analytics in Practice: Improving Data Analytics in Pulsed Power Environments Through Diagnostic and Subsystem Clustering

Modern day processes depend heavily on data-driven techniques that use large datasets clustered into relevant groups help them achieve higher efficiency, better utilization of the operation, and improved decision making. However, building these datasets and clustering by similar products is challenging in research environments that produce many novel and highly complex low-volume technologies. In this work, the author develops an algorithm that calculates the similarity between multiple low-volume products from a research environment using a real-world data set. The algorithm is applied to pulse power operations data, which routinely performs novel experiments for inertial confinement fusion, radiation effects, and nuclear stockpile stewardship. The author shows that the algorithm is successful in calculating similarity between experiments of varying complexity such that comparable shots can be used for further analysis. Furthermore, it has been able to identify experiments not traditionally seen as identical

Reverse Nearest Neighbor Heat Maps: A Tool for Influence Exploration

We study the problem of constructing a reverse nearest neighbor (RNN) heat map by finding the RNN set of every point in a two-dimensional space. Based on the RNN set of a point, we obtain a quantitative influence (i.e., heat) for the point. The heat map provides a global view on the influence distribution in the space, and hence supports exploratory analyses in many applications such as marketing and resource management. To construct such a heat map, we first reduce it to a problem called Region Coloring (RC), which divides the space into disjoint regions within which all the points have the same RNN set. We then propose a novel algorithm named CREST that efficiently solves the RC problem by labeling each region with the heat value of its containing points. In CREST, we propose innovative techniques to avoid processing expensive RNN queries and greatly reduce the number of region labeling operations. We perform detailed analyses on the complexity of CREST and lower bounds of the RC problem, and prove that CREST is asymptotically optimal in the worst case. Extensive experiments with both real and synthetic data sets demonstrate that CREST outperforms alternative algorithms by several orders of magnitude.Comment: Accepted to appear in ICDE 201

Why Small Deals Don’t Get Done: Evidence From Rural Entrepreneurs

For myriad reasons, rural entrepreneurs may want to harvest by selling their business. While these entrepreneurs may look for inspiration to larger, public deals, there are few relevant insights to glean from these deals. Despite the high stakes involved for rural entrepreneurs and potential buyers, researchers have placed little attention on dealmaking at the lower end of the spectrum. We address this lack of research by answering the research question: Why do deals involving small companies go unconsummated? Because research on why large deals fall through is sparse and of limited applicability, we ground our research using insights from the venture financing arena (venture capitalists and angel investors) about why deals between entrepreneurs and investors do not close successfully. Applying a novel dataset from an economic development effort in a small southwestern U.S. city, we analyze the reasons why an investor group investigated 20 potential small deals, but none eventually closed. We found that issues both with the potential buyers and sellers led to the deal failures, with issues involving the valuation and also the selling entrepreneur being the most common deal-breakers. Furthermore, through this investigation, we gained insights into the challenges of an investor-driven model for economic development

The Digital Foundation Platform -- A Multi-layered SOA Architecture for Intelligent Connected Vehicle Operating System

Legacy AD/ADAS development from OEMs centers around developing functions on ECUs using services provided by AUTOSAR Classic Platform (CP) to meet automotive-grade and mass-production requirements. The AUTOSAR CP couples hardware and software components statically and encounters challenges to provide sufficient capacities for the processing of high-level intelligent driving functions, whereas the new platform, AUTOSAR Adaptive Platform (AP) is designed to support dynamically communication and provide richer services and function abstractions for those resource-intensive (memory, CPU) applications. Yet for both platforms, application development and the supporting system software are still closely coupled together, and this makes application development and the enhancement less scalable and flexible, resulting in longer development cycles and slower time-to-market. This paper presents a multi-layered, service-oriented intelligent driving operating system foundation (we named it as Digital Foundation Platform) that provides abstractions for easier adoption of heterogeneous computing hardware. It features a multi-layer SOA software architecture with each layer providing adaptive service API at north-bound for application developers. The proposed Digital Foundation Platform (DFP) has significant advantages of decoupling hardware, operating system core, middle-ware, functional software and application software development. It provides SOA at multiple layers and enables application developers from OEMs, to customize and develop new applications or enhance existing applications with new features, either in autonomous domain or intelligent cockpit domain, with great agility, and less code through re-usability, and thus reduce the time-to-market.Comment: WCX SAE World Congress Experience 202

The IS Core - VI: Further Along the Road to the IT Artifact

In one of the recent additions to the IS identity and diversity discussion, Alter questions the definition and relevance of IT artifact as defined by Benbasat and Zmud. In terms of definition, we believe that there is no substantial difference between Alter\u27s work system construct and IT artifact. However, when it comes to enhancing the relevance of and guiding the diversity in IT research, Alter\u27s boundary based approach may be less powerful than a core, IT-artifact based approach. Alter\u27s focus on systems, nonetheless, has it merits and therefore we suggest a possible convergence of Alter and Benbasat and Zmud\u27s constructs

Community environment, cognitive impairment and dementia in later life: results from the Cognitive Function and Ageing Study

Background: Few studies have investigated the impact of the community environment, as distinct from area deprivation, on cognition in later life. This study explores cross-sectional associations between cognitive impairment and dementia and environmental features at the community level in older people. Method: The postcodes of the 2424 participants in the year-10 interview of the Cognitive Function and Ageing Study in England were mapped into small area level geographical units (Lower-layer Super Output Areas) and linked to environmental data in government statistics. Multilevel logistic regression was conducted to investigate associations between cognitive impairment (defined as MMSE3 in GMS-AGECAT) and community level measurements including area deprivation, natural environment, land use mix and crime. Sensitivity analyses tested the impact of people moving residence within the last two years. Results: Higher levels of area deprivation and crime were not significantly associated with cognitive impairment and dementia after accounting for individual level factors. Living in areas with high land use mix was significantly associated with a nearly 60% reduced odds of dementia (OR: 0.4; 95% CI: 0.2, 0.8) after adjusting for individual level factors and area deprivation, but there was no linear trend for cognitive impairment. Increased odds of dementia (OR: 2.2, 95% CI: 1.2, 4.2) and cognitive impairment (OR: 1.4, 95% CI: 1.0, 2.0) were found in the highest quartile of natural environment availability. Findings were robust to exclusion of the recently relocated. Conclusion: Features of land use have complex associations with cognitive impairment and dementia. Further investigations should focus on environmental influences on cognition to inform health and social policies

Interface Complexity and Elderly Users: Revisited

The ever-increasing functionality of today’s software applications comes in tandem with added complexity, which may hinder elderly citizens’ full participation in the digital world. Building upon Van Slyke et al’s (2004) extension to TAM, the authors explicate the relationships between software functionality/complexity and users’ perceived usefulness and ease-of-use of software. The influence of age difference on these relationships is also examined

Decision Making, IT Governance, and Information Systems Security

The complex issue of IS security involves organizational factors. Decision making, an important area of organizations, however, has only been studied to a limited extent in relation to IS security. In this paper we explore the relationship between organizational distribution of decision rights and IS security. We review the security literature and identify three aspects of an organization as what we term the pillars bolstering the success of IS security – people, processes/structures, and technology. We top our IS Security Architecture with the integrative truss of IS security strategy. Employing Weill and Ross’ (2004) IT governance archetypes, we link this IS Security Architecture to IT governance, and propose that IT governance patterns can enhance security when the governance archetype in place matches the decision profile required by a security practice

Influence of Social Context and Affect on Individuals\u27 Implementation of Information Security Safeguards

Individuals’ use of safeguards against information security risks is commonly conceptualized as the result of a risk-benefit analysis. This economic perspective assumes a “rational actor” whereas risk is subjectively perceived by people who may be influenced by a number of social, psychological, cultural, and other “soft” factors. Their decisions thus may deviate from what economic risk assessment analysis would dictate. In this respect, a phenomenon interesting to study is that on social network sites (SNSes) people tend to, despite a number of potential security risks, provide an amount of personal information that they would otherwise frown upon. In this study we explore how people’s affect toward online social networking may impact their use of privacy safeguards. Since building social capital is a main purpose of online social networking, we use social capital theory to examine some potential contextual influence on the formation of the affect. More specifically, we adopt the perspective proposed by Nahapiet and Ghoshal (1998), which views social capital as a composite of structural, relational, and cognitive capitals. Preliminary analysis of 271 survey responses shows that (a) a person’s structural and relational embeddedness in her online social networks, as well as her cognitive ability in maintaining those networks, are positively related to her affect toward SNSes; (b) a person’s affect toward SNSes moderates the relationship between her perception of privacy risk and the privacy safeguards she implements on the SNSes