13 research outputs found

    An Intelligent Decision Support System for the Empty Unit Load Device Repositioning Problem in Air Cargo Industry

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    Unit load devices (ULDs) are containers and pallets used in the air cargo industry to bundle freight for efficient loading and transportation. Mainly due to imbalances in global air transportation networks, deficits and surpluses of ULDs are the result and require stock balancing through the repositioning of (empty) ULDs. Following a design science research approach, we (1) elaborate the hitherto uninvestigated problem class of empty ULD repositioning (EUR) and (2) propose an intelligent decision support system (IDSS) that incorporates a heuristic for the given problem and combines artificial intelligence (i.e., rule-based expert system technology) with business analytics. We evaluate the IDSS with real-world data and demonstrate that the proposed solution is both effective and efficient. In addition, our results provide empirical evidence regarding the positive economic and ecological impact of leveraging the potential of ULD pooling in multi-carrier networks

    Big Data and the Data Value Chain: Translating Insights from Business Analytics into Actionable Results - The Case of Unit Load Device (ULD) Management in the Air Cargo Industry

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    Business intelligence and analytics enjoy a great deal of attention today. However, there is a lack of studies considering the full data value chain from (raw) data through business analytics to valuable decisions, i.e. also scrutinizing the latter stages of the data value chain, namely timely deployment and operational usage of valuable insights as demanded by practice. Following a design science approach, we develop a concept for the fast and flexible integration of valuable insights into daily decision support. A key feature of our concept is to provide valuable insights from business intelligence in an understandable manner to decision makers using a rule-based expert systems approach. In order to demonstrate the feasibility of our concept, we implemented a prototype in a complex real-world scenario, i.e. unit load device (ULD) management in the air cargo industry. This research in progress presents our preliminary findings and outlines the potential of the proposed concept

    Conceptualization of the Human-Machine Symbiosis – A Literature Review

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    The vision of a symbiotic partnership between humans and machines has existed since the 1960s. With this paper we provide the first conceptualization of the human-machine symbiosis (HMS) and make three important contributions: we present the fundamentals of HMS by focusing on objectives, requirements, and boundaries; we propose a framework for the design of HMS; and we review HMS research and, specifically, what the literature says with respect to whether HMS has already been achieved

    Exploring Design Principles for Human-Machine Symbiosis: Insights from Constructing an Air Transportation Logistics Artifact

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    This paper reports the findings of a proactive design science research project involving the construction, evaluation, and organizational introduction of an information technology (IT) artifact in the context of air transportation logistics. Drawing on our insights from instantiating an IT artifact and embedding it into the organization of a major provider of unit load device management for airlines, we explore the idea that IS-driven automation in digitalizing environments is more limited by socio-economic factors than digital-technological capabilities. Both our IT artifact and the abstracted design principles we generated through heuristic theorizing (HT) are novel, enhancing the information system (IS) design knowledge base of human-machine symbiosis and IT artifacts. Overall, our findings contribute to a better understanding of how to design human-machine symbiosis in information systems

    Tracking cell turnover in human brain using 15N-thymidine imaging mass spectrometry

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    Microcephaly is often caused by an impairment of the generation of neurons in the brain, a process referred to as neurogenesis. While most neurogenesis in mammals occurs during brain development, it thought to continue to take place through adulthood in selected regions of the mammalian brain, notably the hippocampus. However, the generality of neurogenesis in the adult brain has been controversial. While studies in mice and rats have provided compelling evidence for neurogenesis occurring in the adult rodent hippocampus, the lack of applicability in humans of key methods to demonstrate neurogenesis has led to an intense debate about the existence and, in particular, the magnitude of neurogenesis in the adult human brain. Here, we demonstrate the applicability of a powerful method to address this debate, that is, the in vivo labeling of adult human patients with 15N-thymidine, a non-hazardous form of thymidine, an approach without any clinical harm or ethical concerns. 15N-thymidine incorporation into newly synthesized DNA of specific cells was quantified at the single-cell level with subcellular resolution by Multiple-isotype imaging mass spectrometry (MIMS) of brain tissue resected for medical reasons. Two adult human patients, a glioblastoma patient and a patient with drug-refractory right temporal lobe epilepsy, were infused for 24 h with 15N-thymidine. Detection of 15N-positive leukocyte nuclei in blood samples from these patients confirmed previous findings by others and demonstrated the appropriateness of this approach to search for the generation of new cells in the adult human brain. 15N-positive neural cells were easily identified in the glioblastoma tissue sample, and the range of the 15N signal suggested that cells that underwent S-phase fully or partially during the 24 h in vivo labeling period, as well as cells generated therefrom, were detected. In contrast, within the hippocampus tissue resected from the epilepsy patient, none of the 2,000 dentate gyrus neurons analyzed was positive for 15N-thymidine uptake, consistent with the notion that the rate of neurogenesis in the adult human hippocampus is rather low. Of note, the likelihood of detecting neurogenesis was reduced because of (i) the low number of cells analyzed, (ii) the fact that hippocampal tissue was explored that may have had reduced neurogenesis due to epilepsy, and (iii) the labeling period of 24 h which may have been too short to capture quiescent neural stem cells. Yet, overall, our approach to enrich NeuN-labeled neuronal nuclei by FACS prior to MIMS analysis provides a promising strategy to quantify even low rates of neurogenesis in the adult human hippocampus after in vivo15N-thymidine infusion. From a general point of view and regarding future perspectives, the in vivo labeling of humans with 15N-thymidine followed by MIMS analysis of brain tissue constitutes a novel approach to study mitotically active cells and their progeny in the brain, and thus allows a broad spectrum of studies of brain physiology and pathology, including microcephaly

    Augmenting the Evaluation and Mapping of Progress in Scientific Research: A Human-Machine Symbiosis Perspective

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    In this paper we propose and demonstrate a software tool for symbiotic human-machine analysis, applicable for structured literature reviews (SLR). We present a seed-based search of bibliographic information, resulting in document clustering and graph visualization. Through a collaborative human-machine effort we show how to detect potential bridging articles and paradigm shifts. The overarching goal is to support the SLR process, especially for developing fields of science, as well as interdisciplinary fields, where similar concepts can be overlooked as they are associated with different keywords and belong to different groups, yet share common ideas. Finally, we demonstrate the application of the tool with two literature search and visualization examples

    Collaborative Literature Search System: An Intelligence Amplification Method for Systematic Literature Search

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    In this paper, we present a method for systematic literature search based on the symbiotic partnership between the human researcher and intelligent agents. Using intelligence amplification, we leverage the calculation power of computers to quickly and thoroughly extract data, calculate measures, and visualize relationships between scientific documents with the ability of domain experts to perform qualitative analysis and creative reasoning. Thus, we create a foundation for a collaborative literature search system (CLSS) intended to aid researches in performing literature reviews, especially for interdisciplinary and evolving fields of science for which keyword-based literature searches result in large collections of documents beyond humans’ ability to process or the extensive use of filters to narrow the search output risks omitting relevant works. Within this article, we propose a method for CLSS and demonstrate its use on a concrete example of a literature search for a review of the literature on human-machine symbiosis
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