Designing Workshops for the Introduction of Lean Enablers to Engineering Programs

AbstractThere is a large and growing body of knowledge regarding so-called Lean best practices, including most recently in the area of program management and systems engineering. However, there is little elaboration of how these documented best practices are to be introduced to a professional workforce. One way of introducing new practices to a workforce is through the use of training workshops. Such workshops often emerge from training programs or consulting arrangements, but there is no well-defined method or framework to systematically design workshops for the implementation of a new body of knowledge.This study focuses on the development of a framework that facilitates the systematic design of workshops focused specifically on the introduction of Lean principles and practices to program management and the professional workforce in a program environment. The framework is based on a thorough review of literature on training, workshop delivery, and Lean principles, as well as empirical evidence obtained from data collection and interactions with training professionals from industry.The framework provides a systematic design process for workshops, including: a) the assessment of the need for a workshop, b) the definition of workshop goals and objectives, c) the definition of workshop topics, d) the development of an agenda and the theoretical content of the workshops, and e) the selection of the right teaching techniques as well as the right simulations and active learning devices. In each of these steps the framework provides content for the prospective educators.The framework is embodied in an Excel-based tool that allows the user to quickly assemble a structure for the workshop, including the topic, an agenda and defined goals, and also the theoretical content about the Lean principles. Another element of the framework is the designation of the organizational hierarchy levels to be addressed, with educational techniques adapted to each level. The framework was validated through interactions with training professionals in a large automobile manufacturer, and using subject matter experts from a variety of industrial sectors

Should I stay or should I go? : On forces that drive and prevent MBSE adoption in the embedded systems industry

[Context] Model-based Systems Engineering (MBSE) comprises a set of models and techniques that is often suggested as solution to cope with the challenges of engineering complex systems. Although many practitioners agree with the arguments on the potential benefits of the techniques, companies struggle with the adoption of MBSE. [Goal] In this paper, we investigate the forces that prevent or impede the adoption of MBSE in companies that develop embedded software systems. We contrast the hindering forces with issues and challenges that drive these companies towards introducing MBSE. [Method] Our results are based on 20 interviews with experts from 10 companies. Through exploratory research, we analyze the results by means of thematic coding. [Results] Forces that prevent MBSE adoption mainly relate to immature tooling, uncertainty about the return-on-investment, and fears on migrating existing data and processes. On the other hand, MBSE adoption also has strong drivers and participants have high expectations mainly with respect to managing complexity, adhering to new regulations, and reducing costs. [Conclusions] We conclude that bad experiences and frustration about MBSE adoption originate from false or too high expectations. Nevertheless, companies should not underestimate the necessary efforts for convincing employees and addressing their anxiety

Strategies and Best Practices for Model-based Systems Engineering Adoption in Embedded Systems Industry

[Context] Model-based Systems Engineering (MBSE) advocates the integrated use of models throughout all development phases of a system development life-cycle. It is also often suggested as a solution to cope with the challenges of engineering complex systems. However, MBSE adoption is no trivial task and companies, especially large ones, struggle to achieve it in a timely and effective way. [Goal] We aim to discover what are the best practices and strategies to implement MBSE in companies that develop embedded software systems. [Method] Using an inductive-deductive research approach, we conducted 14 semi-structured interviews with experts from 10 companies. Further, we analyzed the data and drew some conclusions which were validated by an on-line questionnaire in a triangulation fashion. [Results] Our findings are summarized in an empirically validated list of 18 best practices for MBSE adoption and through a prioritized list of the 5 most important best practices. [Conclusions] Raising engineers’ awareness regarding MBSE advantages and acquiring experience through small projects are considered the most important practices to increase the success of MBSE adoption.BMBF, 01IS15058, Verbundprojekt SPEDiT: Software Platform Embedded Systems - Dissemination und Transfe

VisualDecisionLinc: A visual analytics approach for comparative effectiveness-based clinical decision support in psychiatry

Comparative Effectiveness Research (CER) is designed to provide research evidence on the effectiveness and risks of different therapeutic options on the basis of data compiled from subpopulations of patients with similar medical conditions. Electronic Health Record (EHR) system contain large volumes of patient data that could be used for CER, but the data contained in EHR system are typically accessible only in formats that are not conducive to rapid synthesis and interpretation of therapeutic outcomes. In the time-pressured clinical setting, clinicians faced with large amounts of patient data in formats that are not readily interpretable often feel 'information overload'. Decision support tools that enable rapid access at the point of care to aggregate data on the most effective therapeutic outcomes derived from CER would greatly aid the clinical decision-making process and individualize patient care. In this manuscript, we highlight the role that visual analytics can play in CER-based clinical decision support. We developed a 'VisualDecisionLinc' (VDL) tool prototype that uses visual analytics to provide summarized CER-derived data views to facilitate rapid interpretation of large amounts of data. We highlight the flexibility that visual analytics offers to gain an overview of therapeutic options and outcomes and if needed, to instantly customize the evidence to the needs of the patient or clinician. The VDL tool uses visual analytics to help the clinician evaluate and understand the effectiveness and risk of different therapeutic options for different subpopulations of patients

The Curved MCA: Influence of Vessel Anatomy on Recanalization Results of Mechanical Thrombectomy after Acute Ischemic Stroke

ABSTRACT BACKGROUND AND PURPOSE: Vessel anatomy is assumed to influence results of endovascular mechanical thrombectomy using stent retrievers. The purpose of this study was to analyze the influence of vessel curvature on recanalization results in patients with acute ischemic stroke caused by large-vessel occlusion

Co-Chaperones in Targeting and Delivery of Misfolded Proteins to the 26S Proteasome

Protein homeostasis (proteostasis) is essential for the cell and is maintained by a highly conserved protein quality control (PQC) system, which triages newly synthesized, mislocalized and misfolded proteins. The ubiquitin-proteasome system (UPS), molecular chaperones, and co-chaperones are vital PQC elements that work together to facilitate degradation of misfolded and toxic protein species through the 26S proteasome. However, the underlying mechanisms are complex and remain partly unclear. Here, we provide an overview of the current knowledge on the co-chaperones that directly take part in targeting and delivery of PQC substrates for degradation. While J-domain proteins (JDPs) target substrates for the heat shock protein 70 (HSP70) chaperones, nucleotide-exchange factors (NEFs) deliver HSP70-bound substrates to the proteasome. So far, three NEFs have been established in proteasomal delivery: HSP110 and the ubiquitin-like (UBL) domain proteins BAG-1 and BAG-6, the latter acting as a chaperone itself and carrying its substrates directly to the proteasome. A better understanding of the individual delivery pathways will improve our ability to regulate the triage, and thus regulate the fate of aberrant proteins involved in cell stress and disease, examples of which are given throughout the review

Patient Electronic Health Data-Driven Approach to Clinical Decision Support

This article presents a novel visual analytics (VA)‐based clinical decision support (CDS) tool prototype that was designed as a collaborative work between Renaissance Computing Institute and Duke University. Using Major Depressive Disorder data from MindLinc electronic health record system at Duke, the CDS tool shows an approach to leverage data from comparative population (patients with similar medical profile) to enhance a clinicians’ decision making process at the point of care. The initial work is being extended in collaboration with the University of North Carolina CTSA to address the key challenges of CDS, as well as to show the use of VA to derive insight from large volumes of Electronic Health Record patient data. Clin Trans Sci 2011; Volume 4: 369–37

Differentiation of benign and malignant vertebral fractures using a convolutional neural network to extract CT-based texture features.

PURPOSE To assess the diagnostic performance of three-dimensional (3D) CT-based texture features (TFs) using a convolutional neural network (CNN)-based framework to differentiate benign (osteoporotic) and malignant vertebral fractures (VFs). METHODS A total of 409 patients who underwent routine thoracolumbar spine CT at two institutions were included. VFs were categorized as benign or malignant using either biopsy or imaging follow-up of at least three months as standard of reference. Automated detection, labelling, and segmentation of the vertebrae were performed using a CNN-based framework ( https://anduin.bonescreen.de ). Eight TFs were extracted: Varianceglobal, Skewnessglobal, energy, entropy, short-run emphasis (SRE), long-run emphasis (LRE), run-length non-uniformity (RLN), and run percentage (RP). Multivariate regression models adjusted for age and sex were used to compare TFs between benign and malignant VFs. RESULTS Skewnessglobal showed a significant difference between the two groups when analyzing fractured vertebrae from T1 to L6 (benign fracture group: 0.70 [0.64-0.76]; malignant fracture group: 0.59 [0.56-0.63]; and p = 0.017), suggesting a higher skewness in benign VFs compared to malignant VFs. CONCLUSION Three-dimensional CT-based global TF skewness assessed using a CNN-based framework showed significant difference between benign and malignant thoracolumbar VFs and may therefore contribute to the clinical diagnostic work-up of patients with VFs