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| 2. |
- Aagerup, Ulf, 1969-, et al.
(författare)
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The persuasive effects of emotional green packaging claims
- 2019
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Ingår i: British Food Journal. - Bingley : Emerald Group Publishing Limited. - 0007-070X .- 1758-4108. ; 121:12, s. 3233-3246
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Tidskriftsartikel (refereegranskat)abstract
- Purpose - The purpose of this paper is to investigate the effects of rational green packaging claims vs emotional green packaging claims on consumers' purchase propensity for organic coffee.Design/methodology/approach - Three within-subjects experiment were carried out (N=87, N=245, N=60). The experimental design encompasses packaging with rational green claims, emotional green claims, as well as a neutral (control) claim. Measured variables are introduced to assess participants' environmental commitment and information processing ability. A manipulated between-subjects variable is introduced to test how distraction interacts with preference for the claims.Findings - Overall, consumers prefer products with green claims over those with neutral (control) claims, and products with emotional green claims to those with rational green claims. The studies also reveal that this effect is moderated by participants' environmental commitment, information processing ability and by distraction. The findings were statistically significant (p<0.05).Research limitations/implications - As a lab experiment, the study provides limited generalizability and external validity. Practical implications - For most organic FMCG products, it is advisable to employ emotional packaging claims.Social implications - The presented findings provide marketers with tools to influence consumer behavior toward sustainable choices.Originality/value - The paper validates previous contributions on the effects of product claim types, and extends them by introducing comprehensive empirical data on all the Elaboration Likelihood Model's criteria for rational decision-making; motivation, opportunity and ability.
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| 3. |
- Ashfaq, Awais, 1990-, et al.
(författare)
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Machine learning in healthcare - a system’s perspective
- 2019
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Ingår i: Proceedings of the ACM SIGKDD Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK). - Arlington. ; , s. 14-17
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Konferensbidrag (refereegranskat)abstract
- A consequence of the fragmented and siloed healthcare landscape is that patient care (and data) is split along multitude of different facilities and computer systems and enabling interoperability between these systems is hard. The lack interoperability not only hinders continuity of care and burdens providers, but also hinders effective application of Machine Learning (ML) algorithms. Thus, most current ML algorithms, designed to understand patient care and facilitate clinical decision-support, are trained on limited datasets. This approach is analogous to the Newtonian paradigm of Reductionism in which a system is broken down into elementary components and a description of the whole is formed by understanding those components individually. A key limitation of the reductionist approach is that it ignores the component-component interactions and dynamics within the system which are often of prime significance in understanding the overall behaviour of complex adaptive systems (CAS). Healthcare is a CAS.Though the application of ML on health data have shown incremental improvements for clinical decision support, ML has a much a broader potential to restructure care delivery as a whole and maximize care value. However, this ML potential remains largely untapped: primarily due to functional limitations of Electronic Health Records (EHR) and the inability to see the healthcare system as a whole. This viewpoint (i) articulates the healthcare as a complex system which has a biological and an organizational perspective, (ii) motivates with examples, the need of a system's approach when addressing healthcare challenges via ML and, (iii) emphasizes to unleash EHR functionality - while duly respecting all ethical and legal concerns - to reap full benefits of ML.
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| 4. |
- Carlsson, Magnus, et al.
(författare)
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The effect of ball temperature on ball speed and carry distance in golf drives
- 2018
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Ingår i: Proceedings of the Institution of Mechanical Engineers, Part P. - London, UK : Sage Publications. - 1754-3371. ; 233:2, s. 186-192
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Tidskriftsartikel (refereegranskat)abstract
- The purpose of this study was to investigate the effect of ball temperature on impact ball speed and carry distance during golf drives in a blind randomized test design. The balls were exposed to a temperature-controlled environment (4 °C, 18 °C, 32 °C, and 46 °C) for 24 h prior to the test and each temperature group consisted of 30 balls. The 120 drives were performed by an elite male golfer (handicap: 0.0) in an indoor driving range. All drives were measured by a Doppler-radar system to determine the club-head speed, launch angle, spin rate, ball speed, and carry distance. Differences between the groups were investigated using a one-way analysis of variance. The results indicated that ball-speed and carry-distance differences occurred within the four groups (p < 0.001 and p < 0.01, respectively). The post hoc analyses showed that the ball temperatures of 18 °C and 32 °C had greater ball speeds and carry distances than balls at 4 °C and 46 °C (all p < 0.05). The intervals for the between-group differences were 0.6–0.7 m s –1 and 2.9–3.9 m for ball speed and carry distance, respectively. Hence, the results showed that ball temperature influences both the ball speed and the carry distance. Based on the findings in this study, standardization of ball temperature should be factored into governing body regulation tests for golf equipment. © IMechE 2018.
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| 5. |
- Galozy, Alexander, 1991-, et al.
(författare)
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Pitfalls of medication adherence approximation through EHR and pharmacy records: Definitions, data and computation
- 2020
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Ingår i: International Journal of Medical Informatics. - Shannon : Elsevier BV. - 1386-5056 .- 1872-8243. ; 136
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Tidskriftsartikel (refereegranskat)abstract
- Background and purpose: Patients' adherence to medication is a complex, multidimensional phenomenon. Dispensation data and electronic health records are used to approximate medication-taking through refill adherence. In-depth discussions on the adverse effects of data quality and computational differences are rare. The purpose of this article is to evaluate the impact of common pitfalls when computing medication adherence using electronic health records. Procedures: We point out common pitfalls associated with the data and operationalization of adherence measures. We provide operational definitions of refill adherence and conduct experiments to determine the effect of the pitfalls on adherence estimations. We performed statistical significance testing on the impact of common pitfalls using a baseline scenario as reference. Findings: Slight changes in definition can significantly skew refill adherence estimates. Pickup patterns cause significant disagreement between measures and the commonly used proportion of days covered. Common data related issues had a small but statistically significant (p < 0.05) impact on population-level and significant effect on individual cases. Conclusion: Data-related issues encountered in real-world administrative databases, which affect various operational definitions of refill adherence differently, can significantly skew refill adherence values, leading to false conclusions about adherence, particularly when estimating adherence for individuals.
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| 6. |
- Khandelwal, Siddhartha, 1987-
(författare)
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Gait Event Detection in the Real World
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Healthy gait requires a balance between various neuro-physiological systems and is considered an important indicator of a subject's physical and cognitive health status. As such, health-related applications would immensely benefit by performing long-term or continuous monitoring of subjects' gait in their natural environment and everyday lives. In contrast to stationary sensors such as motion capture systems and force plates, inertial sensors provide a good alternative for such gait analysis applications as they are miniature, cheap, mobile and can be easily integrated into wearable systems.This thesis focuses on improving overall gait analysis using inertial sensors by providing a methodology for detecting gait events in real-world settings. Although the experimental protocols for such analysis have been restricted to only highly-controlled lab-like indoor settings; this thesis presents a new gait database that consists of data from gait activities carried out in both, indoor and outdoor environments. The thesis shows how domain knowledge about gait could be formulated and utilized to develop methods that are robust and can tackle real-world challenges. It also shows how the proposed approach can be generalized to estimate gait events from multiple body locations. Another aspect of this thesis is to demonstrate that the traditionally used temporal error metrics are not enough for presenting the overall performance of gait event detection methods. The thesis introduces how non-parametric tests can be used to complement them and provide a better overview.The results of comparing the proposed methodology to state-of-the-art methods showed that the approach of incorporating domain knowledge into the time-frequency analysis of the signal was robust across different real-world scenarios and outperformed other methods, especially for the scenario involving variable gait speeds in outdoor settings. The methodology was also benchmarked on publicly available gait databases yielding good performance for estimating events from different body locations. To conclude, this thesis presents a road map for the development of gait analysis systems in real-world settings.
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| 7. |
- Khandelwal, Siddhartha, 1987-, et al.
(författare)
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Identification of Gait Events using Expert Knowledge and Continuous Wavelet Transform Analysis
- 2014
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Ingår i: BIOSIGNALS 2014. - [S.l.] : SciTePress. - 9789897580116 ; , s. 197-204
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Konferensbidrag (refereegranskat)abstract
- Many gait analysis applications involve long-term or continuous monitoring which require gait measurements to be taken outdoors. Wearable inertial sensors like accelerometers have become popular for such applications as they are miniature, low-powered and inexpensive but with the drawback that they are prone to noise and require robust algorithms for precise identification of gait events. However, most gait event detection algorithms have been developed by simulating physical world environments inside controlled laboratories. In this paper, we propose a novel algorithm that robustly and efficiently identifies gait events from accelerometer signals collected during both, indoor and outdoor walking of healthy subjects. The proposed method makes adept use of prior knowledge of walking gait characteristics, referred to as expert knowledge, in conjunction with continuous wavelet transform analysis to detect gait events of heel strike and toe off. It was observed that in comparison to indoor, the outdoor walking acceleration signals were of poorer quality and highly corrupted with noise. The proposed algorithm presents an automated way to effectively analyze such noisy signals in order to identify gait events.
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| 8. |
- Kleyko, Denis, et al.
(författare)
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Vehicle Classification using Road Side Sensors and Feature-free Data Smashing Approach
- 2016
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Ingår i: 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC). - Piscataway : IEEE. - 9781509018895 - 9781509018888 - 9781509018901 ; , s. 1988-1993
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Konferensbidrag (refereegranskat)abstract
- The main contribution of this paper is a study of the applicability of data smashing - a recently proposed data mining method - for vehicle classification according to the "Nordic system for intelligent classification of vehicles" standard, using measurements of road surface vibrations and magnetic field disturbances caused by passing vehicles. The main advantage of the studied classification approach is that it, in contrast to the most of traditional machine learning algorithms, does not require the extraction of features from raw signals. The proposed classification approach was evaluated on a large dataset consisting of signals from 3074 vehicles. Hence, a good estimate of the actual classification rate was obtained. The performance was compared to the previously reported results on the same problem for logistic regression. Our results show the potential trade-off between classification accuracy and classification method's development efforts could be achieved.
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| 9. |
- Monaghan, Thomas, et al.
(författare)
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In-situ time resolved spectrographic measurement using an additively manufactured metallic micro-fluidic analysis platform
- 2019
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Ingår i: PLOS ONE. - San Francisco, CA : Public Library of Science. - 1932-6203. ; 14:11
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Tidskriftsartikel (refereegranskat)abstract
- IntroductionMicrofluidic reactionware allows small volumes of reagents to be utilized for highly controlled flow chemistry applications. By integrating these microreactors with onboard analytical systems, the devices change from passive ones to active ones, increasing their functionality and usefulness. A pressing application for these active microreactors is the monitoring of reaction progress and intermediaries with respect to time, shedding light on important information about these real-time synthetic processes.ObjectiveIn this multi-disciplinary study the objective was to utilise advanced digital fabrication to research metallic, active microreactors with integrated fibre optics for reaction progress monitoring of solvent based liquids, incompatible with previously researched polymer devices, in combination with on-board Ultraviolet-visible spectroscopy for real-time reaction monitoring.MethodA solid-state, metal-based additive manufactured system (Ultrasonic Additive Manufacturing) combined with focussed ion beam milling, that permitted the accurate embedment of delicate sensory elements directly at the point of need within aluminium layers, was researched as a method to create active, metallic, flow reactors with on-board sensing. This outcome was then used to characterise and correctly identify concentrations of UV-active water-soluble B-vitamin nicotinamide and fluorescein. A dilution series was formed from 0.01–1.75 mM; which was pumped through the research device and monitored using UV-vis spectroscopy.ResultsThe results uniquely showed the in-situ ion milling of ultrasonically embedded optical fibres resulted in a metallic microfluidic reaction and monitoring device capable of measuring solvent solutions from 18 μM to 18 mM of nicotinamide and fluorescein, in real time. This level of accuracy highlights that the researched device and methods are capable of real-time spectrographic analysis of a range of chemical reactions outside of those possible with polymer devices.
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| 10. |
- Sant'Anna, Anita, 1983-, et al.
(författare)
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A wearable gait analysis system using inertial sensors Part I : Evaluation of measures of gait symmetry and normality against 3D kinematic data
- 2012
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Ingår i: BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing. - [S. l.] : SciTePress. - 9789898425898 ; , s. 180-188
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Konferensbidrag (refereegranskat)abstract
- Gait analysis (GA) is an important tool in the assessment of several physical and cognitive conditions. The lack of simple and economically viable quantitative GA systems has hindered the routine clinical use of GA in many areas. As a result, patients may be receiving sub-optimal treatment. The present study introduces and evaluates measures of gait symmetry and gait normality calculated from inertial sensor data. These indices support the creation of mobile, cheap and easy to use quantitative GA systems. The proposed method was compared to measures of symmetry and normality derived from 3D kinematic data. Results show that the proposed method is well correlated to the kinematic analysis in both symmetry (r=0.84, p<0.0001) and normality (r=0.81, p<0.0001). In addition, the proposed indices can be used to classify normal from abnormal gait.
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