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Technologies, Volume 5, Issue 4 (December 2017)

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Research

Open AccessArticle Assessing Operator Wellbeing through Physiological Measurements in Real-Time—Towards Industrial Application
Technologies 2017, 5(4), 61; doi:10.3390/technologies5040061
Received: 2 July 2017 / Revised: 13 September 2017 / Accepted: 20 September 2017 / Published: 22 September 2017
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Abstract
This article focuses on how operator wellbeing can be assessed to ensure social sustainability and operator performance at assembly stations. Rapid technological advances provide possibilities for assessing wellbeing in real-time, and from an assembly system perspective, this could enable the assessment of physiological
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This article focuses on how operator wellbeing can be assessed to ensure social sustainability and operator performance at assembly stations. Rapid technological advances provide possibilities for assessing wellbeing in real-time, and from an assembly system perspective, this could enable the assessment of physiological data in real-time. While technology is available, it has not been implemented or tested in industry. The aim of this paper was to investigate empirically how concurrent physiological measurement technologies can be integrated into an industrial application, in order to increase operator wellbeing and operator performance. A mixed method approach was used, which included a literature study, two laboratory tests, two case studies and a workshop. The results indicated that operator wellbeing could be assessed through electro-dermal activity, but that the data is perceived as difficult to interpret. For an industrial application, operator perception and data presentation are important and risks connected to personal integrity and IT-support need to be addressed. Future work includes testing how a combination of physiological measures and self-assessments can be used to assess operator wellbeing in an industrial context. Full article
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Open AccessArticle Estimating Potential Methane Emission from Municipal Solid Waste and a Site Suitability Analysis of Existing Landfills in Delhi, India
Technologies 2017, 5(4), 62; doi:10.3390/technologies5040062
Received: 16 August 2017 / Revised: 8 September 2017 / Accepted: 20 September 2017 / Published: 25 September 2017
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Abstract
The management of rapidly growing municipal solid waste (MSW) is one of the major challenges in developing countries. The current study also estimates the suitability of a site through a geographical information system using multi-criteria decision analysis (MCDA) for landfill sites in National
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The management of rapidly growing municipal solid waste (MSW) is one of the major challenges in developing countries. The current study also estimates the suitability of a site through a geographical information system using multi-criteria decision analysis (MCDA) for landfill sites in National Capital Territory (NCT). The results of the suitability index indicate that only 58.7 km2 of the land is suitable for the construction of landfill sites, while 194.27 km2 of the total area is moderately suitable. The existing three landfill sites that are currently functional and used by government organizations as landfills are found to be moderately suitable. A large fraction of MSW is disposed in landfills, which emit one third of the total anthropogenic methane (CH4) and are considered an important contributor of Green House Gases (GHGs) to the atmosphere. Thus, there is a need for the proper estimation of GHG emission from landfills, specifically CH4, which contributes 20% of the GHGs that contribute to global warming. The current study aims to estimate the CH4 emission from landfills in the NCT, Delhi, India using GHG inventory guidelines from the Intergovernmental Panel on Climate Change (IPCC). The CH4 emission from landfills has doubled from 31.06 Gg/yr to 65.16 Gg/yr from 1999 and 2000 to 2015. The generation of CH4 from MSW is strongly correlated (R2 = 0.58) with the Gross State Domestic Product (GSDP), which is an indicator of wellbeing. Full article
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Open AccessArticle The Non-Euclidean Hydrodynamic Klein–Gordon Equation with Perturbative Self-Interacting Field
Technologies 2017, 5(4), 63; doi:10.3390/technologies5040063
Received: 31 July 2017 / Revised: 22 August 2017 / Accepted: 26 September 2017 / Published: 4 October 2017
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Abstract
In this paper the quantum hydrodynamic approach for the Klein–Gordon equation (KGE) owning a perturbative self-interaction term is developed. The generalized model to non-Euclidean space–time allows for the determination of the quantum energy impulse tensor density of mesons, for the gravitational equation of
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In this paper the quantum hydrodynamic approach for the Klein–Gordon equation (KGE) owning a perturbative self-interaction term is developed. The generalized model to non-Euclidean space–time allows for the determination of the quantum energy impulse tensor density of mesons, for the gravitational equation of quantum mechanical systems. Full article
(This article belongs to the Section Quantum Technologies)
Open AccessArticle Combining Electromyography and Tactile Myography to Improve Hand and Wrist Activity Detection in Prostheses
Technologies 2017, 5(4), 64; doi:10.3390/technologies5040064
Received: 15 August 2017 / Revised: 29 September 2017 / Accepted: 2 October 2017 / Published: 6 October 2017
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Abstract
Despite recent advances in prosthetics and assistive robotics in general, robust simultaneous and proportional control of dexterous prosthetic devices remains an unsolved problem, mainly because of inadequate sensorization. In this paper, we study the application of regression to muscle activity, detected using a
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Despite recent advances in prosthetics and assistive robotics in general, robust simultaneous and proportional control of dexterous prosthetic devices remains an unsolved problem, mainly because of inadequate sensorization. In this paper, we study the application of regression to muscle activity, detected using a flexible tactile sensor recording muscle bulging in the forearm (tactile myography—TMG). The sensor is made of 320 highly sensitive cells organized in an array forming a bracelet. We propose the use of Gaussian process regression to improve the prediction of wrist, hand and single-finger activation, using TMG, surface electromyography (sEMG; the traditional approach in the field), and a combination of the two. We prove the effectiveness of the approach for different levels of activations in a real-time goal-reaching experiment using tactile data. Furthermore, we performed a batch comparison between the different forms of sensorization, using a Gaussian process with different kernel distances. Full article
(This article belongs to the Special Issue Assistive Robotics)
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Open AccessArticle Bushfire Disaster Monitoring System Using Low Power Wide Area Networks (LPWAN)
Technologies 2017, 5(4), 65; doi:10.3390/technologies5040065
Received: 21 September 2017 / Revised: 2 October 2017 / Accepted: 2 October 2017 / Published: 8 October 2017
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Abstract
Some applications, including disaster monitoring and recovery networks, use low-power wide-area networks (LPWAN). LPWAN sensors capture data bits and transmit them to public carrier networks (e.g., cellular networks) via dedicated gateways. One of the challenges encountered in disaster management scenarios revolves around the
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Some applications, including disaster monitoring and recovery networks, use low-power wide-area networks (LPWAN). LPWAN sensors capture data bits and transmit them to public carrier networks (e.g., cellular networks) via dedicated gateways. One of the challenges encountered in disaster management scenarios revolves around the carry/forward sensed data and geographical location information dissemination to the disaster relief operatives (disaster relief agency; DRA) to identify, characterise, and prioritise the affected areas. There are network topology options to reach its destination, including cellular, circuit switched, and peer-to-peer networks. In the context of natural disaster prediction, it is vital to access geographical location data as well as the timestamp. This paper proposes the usage of Pseudo A Number (PAN), that is, the calling party address, which is used by every network to include the location information instead of the actual calling party address of the gateway in LPWAN. This PAN information can be further analysed by the DRA to identify the affected areas and predict the complications of the disaster impacts in addition to the past history of damages. This paper aims to propose a solution that can predict disaster proceedings based on propagation and the velocity of impact using vector calculation of the location data and the timestamp, which are transmitted by sensors through the PAN of the gateway in LPWAN. Full article
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Open AccessFeature PaperArticle An Approach for the Simulation of Ground and Honed Technical Surfaces for Training Classifiers
Technologies 2017, 5(4), 66; doi:10.3390/technologies5040066
Received: 19 September 2017 / Revised: 5 October 2017 / Accepted: 11 October 2017 / Published: 14 October 2017
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Abstract
Training of neural networks requires large amounts of data. Simulated data sets can be helpful if the data required for the training is not available. However, the applicability of simulated data sets for training neuronal networks depends on the quality of the simulation
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Training of neural networks requires large amounts of data. Simulated data sets can be helpful if the data required for the training is not available. However, the applicability of simulated data sets for training neuronal networks depends on the quality of the simulation model used. A simple and fast approach for the simulation of ground and honed surfaces with predefined properties is being presented. The approach is used to generate a diverse data set. This set is then applied to train a neural convolution network for surface type recognition. The resulting classifier is validated on the basis of a series of real measurement data and a classification rate of >85% is achieved. A possible field of application of the presented procedure is the support of measurement technicians in the standard-compliant evaluation of measurement data by suggestion of specific data processing steps, depending on the recognized type of manufacturing process. Full article
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