319 research outputs found

    Digital voice-of-customer processing by topic modelling algorithms: insights to validate empirical results

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    Purpose: Digital voice-of-customer (digital VoC) analysis is gaining much attention in the field of quality management. Digital VoC can be a great source of knowledge about customer needs, habits and expectations. To this end, the most popular approach is based on the application of text mining algorithms named topic modelling. These algorithms can identify latent topics discussed within digital VoC and categorise each source (e.g. each review) based on its content. This paper aims to propose a structured procedure for validating the results produced by topic modelling algorithms. Design/methodology/approach: The proposed procedure compares, on random samples, the results produced by topic modelling algorithms with those generated by human evaluators. The use of specific metrics allows to make a comparison between the two approaches and to provide a preliminary empirical validation. Findings: The proposed procedure can address users of topic modelling algorithms in validating the obtained results. An application case study related to some car-sharing services supports the description. Originality/value: Despite the vast success of topic modelling-based approaches, metrics and procedures to validate the obtained results are still lacking. This paper provides a first practical and structured validation procedure specifically employed for quality-related applications

    The Mobile Spatial coordinate Measuring System II (MScMS-II):system description and preliminary assessmentof the measurement uncertainty

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    According to the increasing interest in metrological systems for the dimensional measurements of large-size objects in a wide range of industrial sectors, several solutions based on different technologies, working principles, architectures, and functionalities have recently been developed. Among all, the most flexible and easily transportable solutions are those that have aroused most interest and have found greater success. In order to address the needs of Large-Scale Metrology (LSM) applications, a distributed flexible system based on a network of low-cost InfraRed (IR) sensors – the Mobile Spatial coordinate Measuring System II (MScMS-II) – has been developed at the Industrial Quality and Metrology Laboratory of Politecnico di Torino. This paper presents a preliminary uncertainty assessment of the system referring to the measured point coordinates in the 3D space, focusing on the sources of measurement uncertainty and the related propagation laws. A preliminary metrological characterization of MScMS-II architecture, experimentally evaluated through a system prototype, is also presented and discussed

    Cooperative diagnostics for distributed LSDM systems based on triangulation

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    In the field of large-scale dimensional metrology (LSDM), new distributed systems based on different technologies have blossomed over the last decade. They generally include (i) some targets to be localized and (ii) a network of portable devices, distributed around the object to be measured, which is often bulky and difficult to handle. The objective of this paper is to present some diagnostic tests for those distributed LSDM systems that perform the target localization by triangulation. Three are the tests presented: two global tests to detect the presence of potential anomalies in the system during measurements, and one local test aimed at isolating any faulty network device(s). This kind of diagnostics is based on the cooperation of different network devices that merge their local observations, not only for target localization, but also for detecting potential measurement anomalies. Tests can be implemented in real-time, without interrupting or slowing down the measurement process. After a detailed description of the tests, we present some practical applications on MSCMS-II, a distributed LSDM system based on infrared photogrammetric technology, recently developed at DIGEP-Politecnico di Torino

    Flexible aggregation operators to support hierarchization of Engineering Characteristics in QFD

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    Quality Function Deployment (QFD) is a management tool for organizing and conducting design activities of new products and/or services together with their relevant production and/or supply processes, starting from the requirements directly expressed by the end-users. It is organized in a series of operative steps which drive from the collection of the customer needs to the definition of the technical characteristics of the production/supply processes. The first step entails the construction of the House of Quality (HoQ), a planning matrix translating the Customer Requirements (CRs) into measurable product/service technical characteristics (Engineering Characteristics – ECs). One of the main goals of this step is to transform CR importances into an EC prioritization. A robust evaluation method should consider the relationships between CRs and ECs while determining the importance levels of ECs in the HoQ. In traditional approaches, such as for example Independent Scoring Method, ordinal information is arbitrarily converted in cardinal information introducing a series of controversial assumptions. Actually, the current scientific literature presents a number of possible solutions to this problem, but the question of attributing scalar properties to information collected on ordinal scales is far from being settled. This paper proposes a method based on ME-MCDM techniques (Multi Expert / Multiple Criteria Decision Making), which is able to compute EC prioritization without operating an artificial numerical codification of the information contained in the HoQ. After a general description of the theoretical principles of the method, a series of application examples are presented and discussed

    New developments in high performance cylinder heads: application of LHIP and SPLIT cylinder head concept

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    Since specific power output of new engines is increasing, many engine components are facing new challenges. Among these, cylinder heads have to withstand tougher operating conditions in terms of temperatures and loads, which are approaching the limits of present aluminum alloys and of the manufacturing processes currently applied. The paper discusses two approaches to possibly extend the application of Aluminum alloy heads beyond their present limits: the first is the application of the Liquid Hot Isostatic Pressing (LHIP®) process aimed to improve the quality of the castings; the second is a novel design concept, split cylinder head, based on the application of different materials in different parts of the head, in order to achieve locally the required material properties

    Pharmacokinetics of single domain antibodies and conjugated nanoparticles using a hybrid near infrared method

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    Iron oxide nanoparticles and single domain antibodies from camelids (VHHs) have been increasingly recognized for their potential uses for medical diagnosis and treatment. However, there have been relatively few detailed characterizations of their pharmacokinetics (PK). The aim of this study was to develop imaging methods and pharmacokinetic models to aid the future development of a novel family of brain MRI molecular contrast agents. An efficient near-infrared (NIR) imaging method was established to monitor VHH and VHH conjugated nanoparticle kinetics in mice using a hybrid approach: kinetics in blood were assessed by direct sampling, and kinetics in kidney, liver, and brain were assessed by serial in vivo NIR imaging. These studies were performed under basal circumstances in which the VHH constructs and VHH-conjugated nanoparticles do not substantially interact with targets nor cross the blood brain barrier. Using this approach, we constructed a five-compartment PK model that fits the data well for single VHHs, engineered VHH trimers, and iron oxide nanoparticles conjugated to VHH trimers. The establishment of the feasibility of these methods lays a foundation for future PK studies of candidate brain MRI molecular contrast agents

    The success-index: an alternative approach to the h-index for evaluating an individual's research output

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    Among the most recent bibliometric indicators for normalizing the differences among fields of science in terms of citation behaviour, Kosmulski (J Informetr 5(3):481-485, 2011) proposed the NSP (number of successful paper) index. According to the authors, NSP deserves much attention for its great simplicity and immediate meaning— equivalent to those of the h-index—while it has the disadvantage of being prone to manipulation and not very efficient in terms of statistical significance. In the first part of the paper, we introduce the success-index, aimed at reducing the NSP-index's limitations, although requiring more computing effort. Next, we present a detailed analysis of the success-index from the point of view of its operational properties and a comparison with the h-index's ones. Particularly interesting is the examination of the success-index scale of measurement, which is much richer than the h-index's. This makes success-index much more versatile for different types of analysis—e.g., (cross-field) comparisons of the scientific output of (1) individual researchers, (2) researchers with different seniority, (3) research institutions of different size, (4) scientific journals, etc

    The epistatic interaction between the dopamine D3 receptor and dysbindin-1 modulates higher-order cognitive functions in mice and humans

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    The dopamine D2 and D3 receptors are implicated in schizophrenia and its pharmacological treatments. These receptors undergo intracellular trafficking processes that are modulated by dysbindin-1 (Dys). Indeed, Dys variants alter cognitive responses to antipsychotic drugs through D2-mediated mechanisms. However, the mechanism by which Dys might selectively interfere with the D3 receptor subtype is unknown. Here, we revealed an interaction between functional genetic variants altering Dys and D3. Specifically, both in patients with schizophrenia and in genetically modified mice, concomitant reduction in D3 and Dys functionality was associated with improved executive and working memory abilities. This D3/Dys interaction produced a D2/D3 imbalance favoring increased D2 signaling in the prefrontal cortex (PFC) but not in the striatum. No epistatic effects on the clinical positive and negative syndrome scale (PANSS) scores were evident, while only marginal effects on sensorimotor gating, locomotor functions, and social behavior were observed in mice. This genetic interaction between D3 and Dys suggests the D2/D3 imbalance in the PFC as a target for patient stratification and procognitive treatments in schizophrenia

    Order versus Disorder: in vivo bone formation within osteoconductive scaffolds

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    In modern biomaterial design the generation of an environment mimicking some of the extracellular matrix features is envisaged to support molecular cross-talk between cells and scaffolds during tissue formation/remodeling. In bone substitutes chemical biomimesis has been particularly exploited; conversely, the relevance of pre-determined scaffold architecture for regenerated bone outputs is still unclear. Thus we aimed to demonstrate that a different organization of collagen fibers within newly formed bone under unloading conditions can be generated by differently architectured scaffolds. An ordered and confined geometry of hydroxyapatite foams concentrated collagen fibers within the pores, and triggered their self-assembly in a cholesteric-banded pattern, resulting in compact lamellar bone. Conversely, when progenitor cells were loaded onto nanofibrous collagen-based sponges, new collagen fibers were distributed in a nematic phase, resulting mostly in woven isotropic bone. Thus specific biomaterial design relevantly contributes to properly drive collagen fibers assembly to target bone regeneration
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