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Assessing the impact of mystery client traits on service evaluation
Get PDFPurpose - This study aims to investigate the reliability of a mystery client (MC) as a service evaluation technique taking into consideration personal differences of the MC agents. Design/methodology/approach - The ratings from 144 MCs from 355 evaluations of computer and electronic stores were cross analyzed with eight psychographic and demographic profile variables. Findings - MCs who were highly involved in the product category were more critical of service responsiveness with respect to product demonstrations and listening to customer requirements. On the other hand, MCs with stronger faith in intuition were more inclined to rate services higher on empathy with respect to employees making a conscientious effort to understand customers' needs. Practical implications - Depending on the service marketing goals, managers learn to define which aspects of MC profile they should consider or avoid during the recruitment as well as becoming more critical when they analyze the evaluation reports to avoid an interpretation bias. Originality/value - The usefulness of the MC tool relies on its reliability and credibility as a marketing research technique. It was identified that the MC personality traits are more likely associated with marketing service evaluation variability
Content-Based Image Retrieval by Metric Learning From Radiology Reports: Application to Interstitial Lung Diseases
No full textContent-based image retrieval (CBIR) is a search technology that could aid medical diagnosis by retrieving and presenting earlier reported cases that are related to the one being diagnosed. To retrieve relevant cases, CBIR systems depend on supervised learning to map low-level image contents to high-level diagnostic concepts. However, the annotation by medical doctors for training and evaluation purposes is a difficult and time-consuming task, which restricts the supervised learning phase to specific CBIR problems of well-defined clinical applications. This paper proposes a new technique that automatically learns the similarity between the several exams from textual distances extracted from radiology reports, thereby successfully reducing the number of annotations needed. Our method first infers the relation between patients by using information retrieval techniques to determine the textual distances between patient radiology reports. These distances are subsequently used to supervise a metric learning algorithm, that transforms the image space accordingly to textual distances. CBIR systems with different image descriptions and different levels of medical annotations were evaluated, with and without supervision from textual distances, using a database of computer tomography scans of patients with interstitial lung diseases. The proposed method consistently improves CBIR mean average precision, with improvements that can reach 38%, and more marked gains for small annotation sets. Given the overall availability of radiology reports in picture archiving and communication systems, the proposed approach can be broadly applied to CBIR systems in different medical problems, and may facilitate the introduction of CBIR in clinical practice
Incremental scenario representations for autonomous driving using geometric polygonal primitives
No full textWhen an autonomous vehicle is traveling through some scenario it receives a continuous stream of sensor data. This sensor data arrives in an asynchronous fashion and often contains overlapping or redundant information. Thus, it is not trivial how a representation of the environment observed by the vehicle can be created and updated over time. This paper presents a novel methodology to compute an incremental 3D representation of a scenario from 3D range measurements. We propose to use macro scale polygonal primitives to model the scenario. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Furthermore, we propose mechanisms designed to update the geometric polygonal primitives over time whenever fresh sensor data is collected. Results show that the approach is capable of producing accurate descriptions of the scene, and that it is computationally very efficient when compared to other reconstruction techniques
Supplier selection in the processed food industry under uncertainty
No full textThis paper addresses an integrated framework for deciding about the supplier selection in the processed food industry under uncertainty. The relevance of including tactical production and distribution planning in this procurement decision is assessed. The contribution of this paper is three-fold. Firstly, we propose a new two-stage stochastic mixed-integer programming model for the supplier selection in the process food industry that maximizes profit and minimizes risk of low customer service. Secondly, we reiterate the importance of considering main complexities of food supply chain management such as: perishability of both raw materials and final products; uncertainty at both downstream and upstream parameters; and age dependent demand. Thirdly, we develop a solution method based on a multi-cut Benders decomposition and generalized disjunctive programming. Results indicate that sourcing and branding actions vary significantly between using an integrated and a decoupled approach. The proposed multi-cut Benders decomposition algorithm improved the solutions of the larger instances of this problem when compared with a classical Benders decomposition algorithm and with the solution of the monolithic model
NeuroKinect: A Novel Low-Cost 3Dvideo-EEG System for Epileptic Seizure Motion Quantification
Get PDFEpilepsy is a common neurological disorder which affects 0.5-1% of the world population. Its diagnosis relies both on Electroencephalogram (EEG) findings and characteristic seizure -induced body movements - called seizure semiology. Thus, synchronous EEG and (2D) video recording systems (known as Video-EEG) are the most accurate tools for epilepsy diagnosis. Despite the establishment of several quantitative methods for EEG analysis, seizure semiology is still analyzed by visual inspection, based on epileptologists' subjective interpretation of the movements of interest (MOIs) that occur during recorded seizures. In this contribution, we present NeuroKinect, a low-cost, easy to setup and operate solution for a novel 3Dvideo-EEG system. It is based on a RGB-D sensor (Microsoft Kinect camera) and performs 24/7 monitoring of an Epilepsy Monitoring Unit (EMU) bed. It does not require the attachment of any reflectors or sensors to the patient's body and has a very low maintenance load. To evaluate its performance and usability, we mounted a state-of-the-art 6-camera motion-capture system and our low-cost solution over the same EMU bed. A comparative study of seizure-simulated MOIs showed an average correlation of the resulting 3D motion trajectories of 84.2%. Then, we used our system on the routine of an EMU and collected 9 different seizures where we could perform 3D kinematic analysis of 42 MOIs arising from the temporal (TLE) (n = 19) and extratemporal (ETE) brain regions (n = 23). The obtained results showed that movement displacement and movement extent discriminated both seizure MOI groups with statistically significant levels (mean = 0.15 m vs. 0.44 m, p<0.001; mean = 0.068 m(3) vs. 0.14 m(3), p< 0.05, respectively). Furthermore, TLE MOIs were significantly shorter than ETE (mean = 23 seconds vs 35 seconds, p< 0.01) and presented higher jerking levels (mean = 345 ms(-3) vs 172 ms(-3), p< 0.05). Our newly implemented 3D approach is faster by 87.5% in extracting body motion trajectories when compared to a 2D frame by frame tracking procedure. We conclude that this new approach provides a more comfortable (both for patients and clinical professionals), simpler, faster and lower-cost procedure than previous approaches, therefore providing a reliable tool to quantitatively analyze MOI patterns of epileptic seizures in the routine of EMUs around the world. We hope this study encourages other EMUs to adopt similar approaches so that more quantitative information is used to improve epilepsy diagnosis
THE IMPACT OF INTERNATIONALIZATION AND DIVERSIFICATION ON CONSTRUCTION INDUSTRY PERFORMANCE
Get PDFThis paper investigates the impact of internationalization and diversification strategies on the financial performance of construction industry companies. The results obtained can guide the design of strategies to pursue company growth and achieve competitive advantage. The evaluation of companies' performance is based on the use of the Data Envelopment Analysis technique to aggregate financial indicators using optimized weights. The impact of internationalization and diversification on company performance is explored using truncated regression, controlling for the effect of contextual factors such as company age, size and time. Data Envelopment Analysis and truncated regression were complemented with bootstrapping to ensure the robustness of the results obtained. The activity of Portuguese and Spanish contractors in the period 2002 to 2011 is used as case study. The empirical results show that internationalization has a positive impact on financial performance, although this effect is only statistically significant for Spanish contractors. Diversification has a nonlinear relationship with performance, benefiting companies with either a small number of core activities or companies with a broad scope of activities
A bottom-up approach to leverage the participation of residential aggregators in reserve services markets
No full textThe increase of demand side participation in reserve service (RS) requires the extension of the markets' activity to the millions of consumers present in the residential sector. This paper proposes a method that performs a bottom-up aggregation of residential demand-side flexibility associated with domestic appliances, namely Thermostatically Controlled Loads (TCL). The flexibility profiles provided by each residential consumer are transformed into aggregated reserve bids to be offered in the day ahead tertiary reserve markets. A case study involving 1500 end-users associated with an aggregator bidding in the Portuguese tertiary reserve market will be used to illustrate the method. (C) 2016 Published by Elsevier B.V
Indoor localization with audible sound - Towards practical implementation
Get PDFThis paper presents an innovative evaluation and comparison of several methods and techniques necessary to implement an indoor localization system based on audible sound. Experiments were conducted in a room with conditions very close to possible practical application demonstrating that time delay estimation using generalized cross-correlation phase transform provides the best estimate to the distance to fixed anchors, and highlight the benefits of a new localization method entitled circle shrinking based on an optimization methodology. Of the three optimization methods tested, Gauss-Newton proves to be the most adequate, and among the three medium access methods evaluated, code division multiple access acoustic transmission provided the best results. A localization system combining these components and using only off-the-shelf hardware reached an average accuracy of 1.3 cm in the central area of the test room with an excitation signal-to-noise ratio as low as 7.2 dB, an almost unperceivable noise like audio signal. These results represent an advance of the state-of-the-art in indoor localization systems, pointing towards the possibility of widespread practical implementation with everyday use components
Biosensor for label-free DNA quantification based on functionalized LPGs
Get PDFA label-free fiber optic biosensor based on a long period grating (LPG) and a basic optical interrogation scheme using off the shelf components is used for the detection of in-situ DNA hybridization. A new methodology is proposed for the determination of the spectral position of the LPG mode resonance. The experimental limit of detection obtained for the DNA was 62 +/- 2 nM and the limit of quantification was 209 +/- 7 nM. The sample specificity was experimentally demonstrated using DNA targets with different base mismatches relatively to the probe and was found that the system has a single base mismatch selectivity
