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Technologies, Volume 6, Issue 4 (December 2018)

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Cover Story (view full-size image) Although companies are eager to join the fray of this new artificial intelligence (AI) trend and [...] Read more.
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Open AccessArticle Development of a Transmission Line Model for the Thickness Prediction of Thin Films via the Infrared Interference Method
Technologies 2018, 6(4), 122; https://doi.org/10.3390/technologies6040122
Received: 1 November 2018 / Revised: 15 December 2018 / Accepted: 18 December 2018 / Published: 19 December 2018
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Abstract
An efficient transmission line model in the micrometric order is presented in this paper, to determine the thickness of thin dielectric films deposited on highly-doped substrates. In particular, the estimation of the thickness is based on multiple reflections of an incident infrared electromagnetic
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An efficient transmission line model in the micrometric order is presented in this paper, to determine the thickness of thin dielectric films deposited on highly-doped substrates. In particular, the estimation of the thickness is based on multiple reflections of an incident infrared electromagnetic wave generating interference on the sensor. To this objective, the periodicity of the local maxima and minima, including the phase shift and wavelength dependence of the reflection at the layer-substrate interface, leads in the extraction of the required thickness. Moreover, a theoretical transmission line circuit is designed, in order to model the multiple interferences scenario, and an iterative method is developed to converge towards the correct coating thickness. The featured theoretical transmission line model is validated, via a direct comparison with Certified Reference Materials, to indicate its overall accuracy and reliability level. Finally, the proposed method is utilized to calculate the thickness of coated metallic samples. Full article
(This article belongs to the Special Issue Modern Circuits and Systems Technologies on Electronics)
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Open AccessArticle Mixed Topology of DF Relayed Terrestrial Optical Wireless Links with Generalized Pointing Errors over Turbulence Channels
Technologies 2018, 6(4), 121; https://doi.org/10.3390/technologies6040121
Received: 1 November 2018 / Revised: 10 December 2018 / Accepted: 12 December 2018 / Published: 17 December 2018
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Abstract
This study investigated the outage performance of a terrestrial FSO communication system that uses mixed series and parallel decode-and-forward (DF) relay-assisted (i.e., cooperative diversity) configurations, taking into account the influence of both atmospheric turbulence and pointing error effects. Turbulence-induced optical signal fading is
[...] Read more.
This study investigated the outage performance of a terrestrial FSO communication system that uses mixed series and parallel decode-and-forward (DF) relay-assisted (i.e., cooperative diversity) configurations, taking into account the influence of both atmospheric turbulence and pointing error effects. Turbulence-induced optical signal fading is modeled by gamma-gamma or the negative exponential distribution for weak to strong and saturated turbulence conditions, respectively. Additionally, weak to strong non-zero boresight misalignment-induced optical signal fading is modeled by the generalized Beckmann distribution. Under these conditions, an outage analysis of the examined FSO system is performed, in terms of both outage probability and mean outage duration metrics. Thus, fairly accurate closed-form mathematical expressions for both performance metrics are derived, while their corresponding analytical results demonstrate concrete performance and availability improvements for the total FSO system, especially when the number of the connected in parallel DF relays increases. Moreover, the obtained results are verified through the corresponding simulation results. Full article
(This article belongs to the Special Issue Modern Circuits and Systems Technologies on Communications)
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Open AccessArticle Development of a Change Management Instrument for the Implementation of Technologies
Technologies 2018, 6(4), 120; https://doi.org/10.3390/technologies6040120
Received: 31 October 2018 / Revised: 22 November 2018 / Accepted: 11 December 2018 / Published: 13 December 2018
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Abstract
The manufacturing industry is increasingly being dominated by information and communication technology, leading to the development of cyber-physical systems. Most existing frameworks on the assessment of such technological advancements see the technology as a solitary system. However, research has shown that other environmental
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The manufacturing industry is increasingly being dominated by information and communication technology, leading to the development of cyber-physical systems. Most existing frameworks on the assessment of such technological advancements see the technology as a solitary system. However, research has shown that other environmental factors like organizational processes or human factors are also affected. Drawing on the sociotechnical systems approach, future technologies could be evaluated using scenarios of digitized work. These scenarios can help classify new technologies and uncover their advantages and constraints in order to provide guidance for the digital development of organizations. We developed an instrument for evaluating scenarios of digitized work on the relevant dimensions ‘technology’, ‘human’ and ‘organization’ and conducted a quantitative study applying this instrument on three different scenarios (N = 24 subject matter experts). Results show that our instrument is capable of measuring technological, human and organizational aspects of technology implementations and detecting differences in the scenarios under investigation. The instrument’s practical value is significant as it enables the user to compare and quantify scenarios and helps companies to decide which technology they should implement. Full article
(This article belongs to the Special Issue The PErvasive Technologies Related to Assistive Environments (PETRA))
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Open AccessArticle A Taxonomy in Robot-Assisted Training: Current Trends, Needs and Challenges
Technologies 2018, 6(4), 119; https://doi.org/10.3390/technologies6040119
Received: 15 November 2018 / Revised: 9 December 2018 / Accepted: 10 December 2018 / Published: 13 December 2018
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Abstract
In this article, we present a taxonomy in Robot-Assisted Training; a growing body of research in Human–Robot Interaction which focuses on how robotic agents and devices can be used to enhance user’s performance during a cognitive or physical training task. Robot-Assisted Training systems
[...] Read more.
In this article, we present a taxonomy in Robot-Assisted Training; a growing body of research in Human–Robot Interaction which focuses on how robotic agents and devices can be used to enhance user’s performance during a cognitive or physical training task. Robot-Assisted Training systems have been successfully deployed to enhance the effects of a training session in various contexts, i.e., rehabilitation systems, educational environments, vocational settings, etc. The proposed taxonomy suggests a set of categories and parameters that can be used to characterize such systems, considering the current research trends and needs for the design, development and evaluation of Robot-Assisted Training systems. To this end, we review recent works and applications in Robot-Assisted Training systems, as well as related taxonomies in Human–Robot Interaction. The goal is to identify and discuss open challenges, highlighting the different aspects of a Robot-Assisted Training system, considering both robot perception and behavior control. Full article
(This article belongs to the Special Issue The PErvasive Technologies Related to Assistive Environments (PETRA))
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Open AccessPerspective Memristors for the Curious Outsiders
Technologies 2018, 6(4), 118; https://doi.org/10.3390/technologies6040118
Received: 28 September 2018 / Revised: 24 November 2018 / Accepted: 3 December 2018 / Published: 9 December 2018
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Abstract
We present both an overview and a perspective of recent experimental advances and proposed new approaches to performing computation using memristors. A memristor is a 2-terminal passive component with a dynamic resistance depending on an internal parameter. We provide an brief historical introduction,
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We present both an overview and a perspective of recent experimental advances and proposed new approaches to performing computation using memristors. A memristor is a 2-terminal passive component with a dynamic resistance depending on an internal parameter. We provide an brief historical introduction, as well as an overview over the physical mechanism that lead to memristive behavior. This review is meant to guide nonpractitioners in the field of memristive circuits and their connection to machine learning and neural computation. Full article
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Open AccessArticle On the Throughput Region of Wireless Random Access Protocols with Multi-Packet Reception Using Multi-Objective Optimization
Technologies 2018, 6(4), 117; https://doi.org/10.3390/technologies6040117
Received: 1 October 2018 / Revised: 29 November 2018 / Accepted: 30 November 2018 / Published: 8 December 2018
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Abstract
This paper presents a new approach for the analysis and characterization of the throughput region of wireless random access protocols enabled with multi-packet reception (MPR) capabilities. The derivation of a closed-form expression for the envelope of the throughput region under the assumption of
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This paper presents a new approach for the analysis and characterization of the throughput region of wireless random access protocols enabled with multi-packet reception (MPR) capabilities. The derivation of a closed-form expression for the envelope of the throughput region under the assumption of an arbitrary number of terminals is an open issue in the literature. To partially fill this gap, a new method based on multi-objective optimization tools is herein presented. This innovative perspective allows us to identify the envelope of the throughput region as the Pareto frontier solution that results from maximizing simultaneously all individual terminal throughput functions. To simplify this problem, a modified MPR model is proposed that mimics the conditions of collision model protocols, but it also inserts new physical (PHY) layer features that allow concurrent transmission or MPR. The N-reception model is herein introduced, where collisions of up to N signals are assumed to be always correctly resolved from a population of J terminals, where N can be related to the number of antennas or degrees of freedom of the PHY-layer used at the receiver to resolve a collision. It is shown that by using this model and under the assumption of N = J - 1 , the Pareto frontier expression can be obtained as a simple extension of the ALOHA solution. Unfortunately, for cases with N < J - 1 , the structure of the resulting determinant matrix does not allow for a simple explicit solution. To overcome this issue, a symmetrical system is proposed, and the solution is obtained by the analysis of the roots of the resulting polynomial expression. Based on this result, an equivalent sub-optimal solution for the asymmetrical case is herein identified for systems where N < J - 1 . An extension to more general reception models based on conditional reception probabilities is also presented using the proposed equivalence between the symmetric and asymmetric solutions. The results intend to shed light on the performance of MPR systems in general, and in particular to advance towards the solution of the conjecture of the equivalence between throughput and stability regions in random access. Full article
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Open AccessArticle Comparing Approaches for Evaluating Digital Interventions on the Shop Floor
Technologies 2018, 6(4), 116; https://doi.org/10.3390/technologies6040116
Received: 30 October 2018 / Revised: 30 November 2018 / Accepted: 3 December 2018 / Published: 5 December 2018
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Abstract
The introduction of innovative digital tools for supporting manufacturing processes has far-reaching effects at an organizational and individual level due to the development of Industry 4.0. The FACTS4WORKERS project funded by H2020, i.e., Worker-Centric Workplaces in Smart Factories, aims to develop user-centered assistance
[...] Read more.
The introduction of innovative digital tools for supporting manufacturing processes has far-reaching effects at an organizational and individual level due to the development of Industry 4.0. The FACTS4WORKERS project funded by H2020, i.e., Worker-Centric Workplaces in Smart Factories, aims to develop user-centered assistance systems in order to demonstrate their impact and applicability at the shop floor. To achieve this, understanding how to develop such tools is as important as assessing if advantages can be derived from the ICT system created. This study introduces the technology of a workplace solution linked to the industrial challenge of self-learning manufacturing workplaces. Subsequently, a two-step approach to evaluate the presented system is discussed, consisting of the one used in FACTS4WORKERS and the one used in the “Heuristics for Industry 4.0” project. Both approaches and the use case are introduced as a base for presenting the comparison of the results collected in this paper. The comparison of the results for the presented use case is extended with the results for the rest of the FACTS4WORKERS use cases and with future work in the framework. Full article
(This article belongs to the Special Issue Technologies for Industry 4.0)
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Open AccessArticle Identity Management and Protection Motivated by the General Data Protection Regulation of the European Union—A Conceptual Framework Based on State-of-the-Art Software Technologies
Technologies 2018, 6(4), 115; https://doi.org/10.3390/technologies6040115
Received: 31 October 2018 / Revised: 29 November 2018 / Accepted: 30 November 2018 / Published: 4 December 2018
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Abstract
In times of strongly (personal) data-driven economy, the inception of the European General Data Protection Regulation (GDPR) recently reinforced the call for transparency and informational self-determination—not only due to the penalties for data protection violations becoming significantly more severe. This paper recaps the
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In times of strongly (personal) data-driven economy, the inception of the European General Data Protection Regulation (GDPR) recently reinforced the call for transparency and informational self-determination—not only due to the penalties for data protection violations becoming significantly more severe. This paper recaps the GDPR articles that should be noticed by software designers and developers and explains how, from the perspective of computer scientists, the summarized requirements can be implemented based on state-of-the-art technologies, such as data provenance tracking, distributed usage control, and remote attestation protocols. For this, the challenges for data controllers, i.e., the service providers, as well as for the data subjects, i.e., the users whose personal data are being processed by the services, are worked out. As a result, this paper proposes the ideal functionality of a next-generation privacy dashboard interacting with data provenance and usage control infrastructure implemented at the service providers to operationalize the legal rights of the data subject granted by the GDPR. Finally, it briefly outlines the options for establishing trust in data provenance tracking and usage control infrastructures operated by the service providers themselves. Full article
(This article belongs to the Special Issue The PErvasive Technologies Related to Assistive Environments (PETRA))
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Open AccessFeature PaperArticle Trading off Network Density with Frequency Spectrum for Resource Optimization in 5G Ultra-Dense Networks
Technologies 2018, 6(4), 114; https://doi.org/10.3390/technologies6040114
Received: 26 October 2018 / Revised: 26 November 2018 / Accepted: 27 November 2018 / Published: 1 December 2018
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Abstract
To effectively increase the capacity in 5G wireless networks requires more spectrum and denser network deployments. However, due to the increasing network density, the coordination of network and spectrum management becomes a challenging task both within a single operator’s network and among multiple
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To effectively increase the capacity in 5G wireless networks requires more spectrum and denser network deployments. However, due to the increasing network density, the coordination of network and spectrum management becomes a challenging task both within a single operator’s network and among multiple operators’ networks. In this article, we develop new radio resource management (RRM) algorithms for adapting the frequency spectrum and the density of active access nodes in 5G ultra-dense networks (UDNs) to the traffic load and the user density in different geographical areas of the network. To this end, we formulate a network optimization problem where the allocation of spectrum bandwidth and the density of active access nodes are optimized to minimize a joint cost function, and we exploit Lagrange duality techniques to develop provably optimal network-scheduling algorithms. In particular, we develop density algorithms for two application scenarios. The first scenario solves the resource management problem for an operator of an ultra-dense network with exclusive access to a pool of frequency resources, while the second scenario applies to the management of the network density of collocated UDNs that belong to multiple operators sharing the same frequency spectrum. Simulation results demonstrate how effectively the algorithms can adapt the allocation of the spectrum allocation and the density of active access nodes over space and time. Full article
(This article belongs to the Special Issue Modern Circuits and Systems Technologies on Communications)
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Open AccessArticle Using the R Language to Manage and Show Statistical Information in the Cloud
Technologies 2018, 6(4), 113; https://doi.org/10.3390/technologies6040113
Received: 11 October 2018 / Revised: 15 November 2018 / Accepted: 20 November 2018 / Published: 30 November 2018
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We present a methodology to enable users to interact with the statistical information (survey data) of a public opinion institute which is stored in Cloud infrastructure. Mainly using R, this approach was developed following the open-data philosophy. Also, as we used R, the
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We present a methodology to enable users to interact with the statistical information (survey data) of a public opinion institute which is stored in Cloud infrastructure. Mainly using R, this approach was developed following the open-data philosophy. Also, as we used R, the implementation is mainly based on open-source software. R has several advantages from the point of view of data management and acquisition, as it is becoming a common framework that can be used to structure the processes involved in any statistical operation. It further simplifies the access to data and enables the use of all the power of R in Cloud infrastructure. This methodology was applied successfully to develop a tool to manage the data of the Centre d’Estudis d’Opinió, but it can be applied to other institutions to enable open access to their data. The infrastructure was also deployed to Cloud infrastructure to assure its scalability and 24/7 access. Full article
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Open AccessArticle Average Load Definition in Random Wireless Sensor Networks: The Traffic Load Case
Technologies 2018, 6(4), 112; https://doi.org/10.3390/technologies6040112
Received: 29 October 2018 / Revised: 17 November 2018 / Accepted: 23 November 2018 / Published: 28 November 2018
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Abstract
Load is a key magnitude for studying network performance for large-scale wireless sensor networks that are expected to support pervasive applications like personalized health-care, smart city and smart home, etc., in assistive environments (e.g., those supported by the Internet of Things). In these
[...] Read more.
Load is a key magnitude for studying network performance for large-scale wireless sensor networks that are expected to support pervasive applications like personalized health-care, smart city and smart home, etc., in assistive environments (e.g., those supported by the Internet of Things). In these environments, nodes are usually spread at random, since deliberate positioning is not a practical approach. Due to this randomness it is necessary to use average values for almost all networks’ magnitudes, load being no exception. However, a consistent definition for the average load is not obvious, since both nodal load and position are random variables. Current literature circumvents randomness by computing the average value over nodes that happen to fall within small areas. This approach is insufficient, because the area’s average is still a random variable and also it does not permit us to deal with single points. This paper proposes a definition for the area’s average load, based on the statistical expected value, whereas a point’s average load is seen as the load of an area that has been reduced (or contracted) to that point. These new definitions are applied in the case of traffic load in multi-hop networks. An interesting result shows that traffic load increases in steps. The simplest form of this result is the constant step, which results in an analytical expression for the traffic load case. A comparison with some real-world networks shows that most of them are accurately described by the constant step model. Full article
(This article belongs to the Special Issue The PErvasive Technologies Related to Assistive Environments (PETRA))
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Open AccessArticle Seasonality of Discrepancies between Admission and Discharge Diagnosis for Medicare Patients
Technologies 2018, 6(4), 111; https://doi.org/10.3390/technologies6040111
Received: 2 November 2018 / Revised: 20 November 2018 / Accepted: 22 November 2018 / Published: 27 November 2018
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Admission and discharge diagnoses of in-hospital patients are often in discord. Incorrect admission diagnoses are related to an increased cost of care and patient safety. Additionally, due to the seasonality of many conditions, this discord may vary across the year. In this paper,
[...] Read more.
Admission and discharge diagnoses of in-hospital patients are often in discord. Incorrect admission diagnoses are related to an increased cost of care and patient safety. Additionally, due to the seasonality of many conditions, this discord may vary across the year. In this paper, we used medical claims data to develop a methodological framework that examines these differences for Medicare beneficiaries. We provide examples for pneumonia, which is a condition with seasonal implications, and aneurysm, where early detection can be lifesaving. Following a Bayesian approach, our work quantifies and visualizes with time-series plots the degree that any clinical condition is correctly diagnosed upon admission. We examined differences in weekly intervals over a calendar year. Furthermore, the median length of stay and the mean hospital charges were compared between matching and non-matching {admission, discharge Dx} pairs, and 95% confidence intervals of the difference were estimated. We applied statistical process control methods, and then visualized the differences among the hospital charges and the length of stay, per week, with time-series plots. Our methodology and the visualizations underline the importance of a rigorous and non-delayed diagnostic process upon admission, since there are significant implications in terms of hospital outcomes and cost of care. Full article
(This article belongs to the Special Issue The PErvasive Technologies Related to Assistive Environments (PETRA))
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Open AccessArticle Human Activities Recognition Based on Neuro-Fuzzy Finite State Machine
Technologies 2018, 6(4), 110; https://doi.org/10.3390/technologies6040110
Received: 7 November 2018 / Revised: 19 November 2018 / Accepted: 22 November 2018 / Published: 26 November 2018
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Abstract
Human activity recognition and modelling comprise an area of research interest that has been tackled by many researchers. The application of different machine learning techniques including regression analysis, deep learning neural networks, and fuzzy rule-based models has already been investigated. In this paper,
[...] Read more.
Human activity recognition and modelling comprise an area of research interest that has been tackled by many researchers. The application of different machine learning techniques including regression analysis, deep learning neural networks, and fuzzy rule-based models has already been investigated. In this paper, a novel method based on Fuzzy Finite State Machine (FFSM) integrated with the learning capabilities of Neural Networks (NNs) is proposed to represent human activities in an intelligent environment. The proposed approach, called Neuro-Fuzzy Finite State Machine (N-FFSM), is able to learn the parameters of a rule-based fuzzy system, which processes the numerical input/output data gathered from the sensors and/or human experts’ knowledge. Generating fuzzy rules that represent the transition between states leads to assigning a degree of transition from one state to another. Experimental results are presented to demonstrate the effectiveness of the proposed method. The model is tested and evaluated using a dataset collected from a real home environment. The results show the effectiveness of using this method for modelling the activities of daily living based on ambient sensory datasets. The performance of the proposed method is compared with the standard NNs and FFSM techniques. Full article
(This article belongs to the Special Issue The PErvasive Technologies Related to Assistive Environments (PETRA))
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Open AccessArticle Signal Quality Assessment for Transdermal Optical Wireless Communications under Pointing Errors
Technologies 2018, 6(4), 109; https://doi.org/10.3390/technologies6040109
Received: 30 October 2018 / Revised: 13 November 2018 / Accepted: 15 November 2018 / Published: 19 November 2018
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In this paper, we assess the signal quality of the out-body to in-body optical communication link, which can be used as a fundamental enabler of novel biomedical appliances, such as medical implants, as well as biological and chemical components monitoring. In particular, we
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In this paper, we assess the signal quality of the out-body to in-body optical communication link, which can be used as a fundamental enabler of novel biomedical appliances, such as medical implants, as well as biological and chemical components monitoring. In particular, we present a mathematical understanding of the transdermal system, which takes into account the optical channel characteristics, the integrated area limitations of the in-body unit, the transceivers’ pointing errors and the particularities of the optical units. Moreover, to accommodate the propagation characteristics, we present a novel simplified, but accurate, transdermal path-gain model. Finally, we extract low-complexity closed-form expressions for the instantaneous and average signal to noise ratio of the transdermal optical link (TOL). Numerical and simulation results are provided for several insightful scenarios and reveal that pointing errors can significantly affect the reliability and effectiveness of the TOL; hence, it should be taken into account in the analysis and design of such systems. Full article
(This article belongs to the Special Issue Modern Circuits and Systems Technologies on Communications)
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Open AccessArticle Design of a Control Chart Using Extended EWMA Statistic
Technologies 2018, 6(4), 108; https://doi.org/10.3390/technologies6040108
Received: 30 October 2018 / Revised: 13 November 2018 / Accepted: 14 November 2018 / Published: 16 November 2018
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In the present paper, we propose a control chart based on extended exponentially weighted moving average (EEWMA) statistic to detect a quick shift in the mean. The mean and variance expression of the proposed EEWMA statistic are derived. The proposed EEWMA statistic is
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In the present paper, we propose a control chart based on extended exponentially weighted moving average (EEWMA) statistic to detect a quick shift in the mean. The mean and variance expression of the proposed EEWMA statistic are derived. The proposed EEWMA statistic is unbiased and simulation results show a smaller variance as compared to the traditional EWMA. The performance of the proposed control chart with the existing chart based on the EWMA statistic is evaluated in terms of average run length (ARL). Various tables were constructed for different values of parameters. The comparison of the EEWMA control chart with the traditional EWMA and Shewhart control charts illustrates that the proposed control chart performs better in terms of quick detection of the shift. The working procedure of the proposed control chart was also illustrated by simulated and application data. Full article
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Open AccessArticle Solving the Job-Shop Scheduling Problem in the Industry 4.0 Era
Technologies 2018, 6(4), 107; https://doi.org/10.3390/technologies6040107
Received: 30 August 2018 / Revised: 31 October 2018 / Accepted: 5 November 2018 / Published: 16 November 2018
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Technological developments along with the emergence of Industry 4.0 allow for new approaches to solve industrial problems, such as the Job-shop Scheduling Problem (JSP). In this sense, embedding Multi-Agent Systems (MAS) into Cyber-Physical Systems (CPS) is a highly promising approach to handle complex
[...] Read more.
Technological developments along with the emergence of Industry 4.0 allow for new approaches to solve industrial problems, such as the Job-shop Scheduling Problem (JSP). In this sense, embedding Multi-Agent Systems (MAS) into Cyber-Physical Systems (CPS) is a highly promising approach to handle complex and dynamic JSPs. This paper proposes a data exchange framework in order to deal with the JSP considering the state-of-the-art technology regarding MAS, CPS and industrial standards. The proposed framework has self-configuring features to deal with disturbances in the production line. This is possible through the development of an intelligent system based on the use of agents and the Internet of Things (IoT) to achieve real-time data exchange and decision making in the job-shop. The performance of the proposed framework is tested in a simulation study based on a real industrial case. The results substantiate gains in flexibility, scalability and efficiency through the data exchange between factory layers. Finally, the paper presents insights regarding industrial applications in the Industry 4.0 era in general and in particular with regard to the framework implementation in the analyzed industrial case. Full article
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Open AccessArticle Energy-Harvesting Powered Variable Storage Topology for Battery-Free Wireless Sensors
Technologies 2018, 6(4), 106; https://doi.org/10.3390/technologies6040106
Received: 29 October 2018 / Revised: 12 November 2018 / Accepted: 13 November 2018 / Published: 16 November 2018
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The energy autonomy of wireless sensors is one of the main roadblocks to their wide deployment. The purpose of this study is to propose simple adaptive storage architecture, which combined with energy harvesting, could replace a battery. The main concept is based on
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The energy autonomy of wireless sensors is one of the main roadblocks to their wide deployment. The purpose of this study is to propose simple adaptive storage architecture, which combined with energy harvesting, could replace a battery. The main concept is based on using several ultracapacitors (at least two) that are reconfigured in a series or in parallel according to its state of charge/discharge, either to speed up the startup of the powered system or to provide energy autonomy. The proposed structure is based on two ultra-capacitors, one of small capacitance value and one of big value. Powered by an energy-harvesting source, the devised control circuitry allows cold start up with empty ultra-capacitors, pre-regulated output voltage, and energy usage efficiency close to 94.7%. Full article
(This article belongs to the Special Issue Modern Circuits and Systems Technologies on Electronics)
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Open AccessArticle Effective 5G Wireless Downlink Scheduling and Resource Allocation in Cyber-Physical Systems
Technologies 2018, 6(4), 105; https://doi.org/10.3390/technologies6040105
Received: 15 October 2018 / Revised: 1 November 2018 / Accepted: 12 November 2018 / Published: 15 November 2018
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In emerging Cyber-Physical Systems (CPS), the demand for higher communication performance and enhanced wireless connectivity is increasing fast. To address the issue, in our recent work, we proposed a dynamic programming algorithm with polynomial time complexity for effective cross-layer downlink Scheduling and Resource
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In emerging Cyber-Physical Systems (CPS), the demand for higher communication performance and enhanced wireless connectivity is increasing fast. To address the issue, in our recent work, we proposed a dynamic programming algorithm with polynomial time complexity for effective cross-layer downlink Scheduling and Resource Allocation (SRA) considering the channel and queue state, while supporting fairness. In this paper, we extend the SRA algorithm to consider 5G use-cases, namely enhanced Machine Type Communication (eMTC), Ultra-Reliable Low Latency Communication (URLLC) and enhanced Mobile BroadBand (eMBB). In a simulation study, we evaluate the performance of our SRA algorithm in comparison to an advanced greedy cross-layer algorithm for eMTC, URLLC and LTE (long-term evolution). For eMTC and URLLC, our SRA method outperforms the greedy approach by up to 17.24%, 18.1%, 2.5% and 1.5% in terms of average goodput, correlation impact, goodput fairness and delay fairness, respectively. In the case of LTE, our approach outperforms the greedy method by 60%, 2.6% and 1.6% in terms of goodput, goodput fairness and delay fairness compared with tested baseline. Full article
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Open AccessArticle The Touch and Feel of the Past—Using Haptic and VR Artefacts to Enrich Reminiscence Therapy for People with Dementia
Technologies 2018, 6(4), 104; https://doi.org/10.3390/technologies6040104
Received: 1 October 2018 / Revised: 1 November 2018 / Accepted: 8 November 2018 / Published: 13 November 2018
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New technology always needs validation in terms of stakeholder acceptance and usability. This challenge also applies in the case of technology for reminiscence therapy for people with dementia. We are looking at how to overcome this situation and identifying how technology can support
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New technology always needs validation in terms of stakeholder acceptance and usability. This challenge also applies in the case of technology for reminiscence therapy for people with dementia. We are looking at how to overcome this situation and identifying how technology can support reminiscence therapy. Therefore, we are conducting user research with people with dementia and their caregivers, prototyping multimedia approaches and testing for efficacy and acceptance of these approaches. Reminiscence therapy is an important aspect in the care for people with dementia as it improves their wellbeing. So far, mostly conventional, analog media is used for this purpose. Our qualitative research suggests that technology can enrich traditional reminiscence therapy, foster conversations, and support positive interactions between caregivers and people with dementia. As outcomes, we identify that special consideration should be directed toward the choice of personally relevant and engaging content, contextual factors of the therapy situations, and high usability of potential therapy artefacts. Suggestions for future research and further prototype iterations are provided. Full article
(This article belongs to the Special Issue The PErvasive Technologies Related to Assistive Environments (PETRA))
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Open AccessArticle Traffic Similarity Observation Using a Genetic Algorithm and Clustering
Technologies 2018, 6(4), 103; https://doi.org/10.3390/technologies6040103
Received: 27 October 2018 / Revised: 8 November 2018 / Accepted: 9 November 2018 / Published: 11 November 2018
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Abstract
This article presents a technique of traffic similarity observation based on the statistical method of survival analysis by using a genetic algorithm. The basis comes from the k-means clustering algorithm. The observed traffic is collected from different network sources by using a NetFlow
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This article presents a technique of traffic similarity observation based on the statistical method of survival analysis by using a genetic algorithm. The basis comes from the k-means clustering algorithm. The observed traffic is collected from different network sources by using a NetFlow collector. The purpose of this technique is to propose a process of finding spread malicious traffic, e.g., ransomware, and considers the possibility of implementing a genetic-based algorithm. In our solution, a chromosome is created from clustering k-means centers, and the Davies–Bouldin validity index is used as the second fitness value in the solution. Full article
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Open AccessEditorial Special Issue on “Wearable Technologies”
Technologies 2018, 6(4), 102; https://doi.org/10.3390/technologies6040102
Received: 5 November 2018 / Accepted: 7 November 2018 / Published: 8 November 2018
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Abstract
Wearable technology will revolutionize our lives in the years to come. [...] Full article
(This article belongs to the Special Issue Wearable Technologies) Printed Edition available
Open AccessArticle Extraction of Structural and Semantic Data from 2D Floor Plans for Interactive and Immersive VR Real Estate Exploration
Technologies 2018, 6(4), 101; https://doi.org/10.3390/technologies6040101
Received: 26 September 2018 / Revised: 20 October 2018 / Accepted: 27 October 2018 / Published: 4 November 2018
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Abstract
Three-dimensional reconstructions of indoor environments are useful in various augmented and virtual scenarios. Creating a realistic virtual apartment in 3D manually does not only take time, but also needs skilled people for implementation. Analyzing a floor plan is a complicated task. Due to
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Three-dimensional reconstructions of indoor environments are useful in various augmented and virtual scenarios. Creating a realistic virtual apartment in 3D manually does not only take time, but also needs skilled people for implementation. Analyzing a floor plan is a complicated task. Due to the lack of engineering standards in creating these drawings, they can have multiple different appearances for the same building. This paper proposes multiple models and heuristics which enable fully automated 3D reconstructions out of only a 2D floor plan. Our study focuses on floor plan analysis and definition of special requirements for a 3D building model used in a Virtual Reality (VR) setup. The proposed method automatically analyzes floor plans with a pattern recognition approach, thereby extracting accurate metric information about important components of the building. An algorithm for mesh generation and extracting semantic information such as apartment separation and room type estimation is presented. A novel method for VR interaction with interior design completes the framework. The result of the presented system is intended to be used for presenting a large number of apartments to customers. It can also be used as a base for purposes such as furnishing apartments, realistic occlusions for AR (Augmented Reality) applications such as indoor navigation or analyzing purposes. Finally, a technical evaluation and an interactive user study prove the advantages of the presented system. Full article
(This article belongs to the Special Issue Technologies for Virtual and Augmented Reality Applications)
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Open AccessFeature PaperArticle The Rise of Artificial Intelligence under the Lens of Sustainability
Technologies 2018, 6(4), 100; https://doi.org/10.3390/technologies6040100
Received: 21 October 2018 / Revised: 29 October 2018 / Accepted: 1 November 2018 / Published: 3 November 2018
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Abstract
Since the 1950s, artificial intelligence (AI) has been a recurring topic in research. However, this field has only recently gained significant momentum because of the advances in technology and algorithms, along with new AI techniques such as machine learning methods for structured data,
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Since the 1950s, artificial intelligence (AI) has been a recurring topic in research. However, this field has only recently gained significant momentum because of the advances in technology and algorithms, along with new AI techniques such as machine learning methods for structured data, modern deep learning, and natural language processing for unstructured data. Although companies are eager to join the fray of this new AI trend and take advantage of its potential benefits, it is unclear what implications AI will have on society now and in the long term. Using the five dimensions of sustainability to structure the analysis, we explore the impacts of AI on several domains. We find that there is a significant impact on all five dimensions, with positive and negative impacts, and that value, collaboration, sharing responsibilities; ethics will play a vital role in any future sustainable development of AI in society. Our exploration provides a foundation for in-depth discussions and future research collaborations. Full article
(This article belongs to the Special Issue Advanced Green Information and Communication Technology)
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Open AccessArticle Architecting and Designing Sustainable Smart City Services in a Living Lab Environment
Technologies 2018, 6(4), 99; https://doi.org/10.3390/technologies6040099
Received: 1 September 2018 / Revised: 22 October 2018 / Accepted: 30 October 2018 / Published: 1 November 2018
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Abstract
In terms of sustainability, cities become smart when they provide smart services to the inhabitants using information and communication technologies without threatening the future of the environment, economy, or society. However, the process of developing such sustainable smart services has certain challenges, especially
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In terms of sustainability, cities become smart when they provide smart services to the inhabitants using information and communication technologies without threatening the future of the environment, economy, or society. However, the process of developing such sustainable smart services has certain challenges, especially in understanding the real needs of the people living in the city. Citizens or, in a wider perspective, the inhabitants of the city are the key stakeholders in the case of smart services in a city. Active involvement of the people throughout the development process is a way of successfully designing such services. On the other hand, integrating sustainability, for example, including environmental data, into smart city services is challenging. Therefore, this research aims to combine environmental data with regular smart city services, while engaging city inhabitants in the development process. This approach was adapted from the concept of living lab methodology. Finally, an application developed following this method is presented and evaluated. Full article
(This article belongs to the Special Issue Advanced Green Information and Communication Technology)
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Open AccessArticle Design of a Quick Switching Sampling System Based on the Coefficient of Variation
Technologies 2018, 6(4), 98; https://doi.org/10.3390/technologies6040098
Received: 27 September 2018 / Revised: 26 October 2018 / Accepted: 29 October 2018 / Published: 30 October 2018
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Abstract
In this research, a quick switching sampling (QSS) system based on the coefficient of variation (CV) is developed, which utilizes information from present and previous lots to make a decision about the submitted lot of product. The design parameters of the proposed plan
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In this research, a quick switching sampling (QSS) system based on the coefficient of variation (CV) is developed, which utilizes information from present and previous lots to make a decision about the submitted lot of product. The design parameters of the proposed plan are determined through a non-linear optimization solution. In addition, the performance of the proposed plan is compared with plans available in the literature in terms of sample size. Finally, one example is given to illustrate the proposed plan. Full article
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Open AccessArticle Filling the Joints: Completion and Recovery of Incomplete 3D Human Poses
Technologies 2018, 6(4), 97; https://doi.org/10.3390/technologies6040097
Received: 5 October 2018 / Revised: 26 October 2018 / Accepted: 27 October 2018 / Published: 30 October 2018
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Abstract
We present a comparative study of three matrix completion and recovery techniques based on matrix inversion, gradient descent, and Lagrange multipliers, applied to the problem of human pose estimation. 3D human pose estimation algorithms may exhibit noise or may completely fail to provide
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We present a comparative study of three matrix completion and recovery techniques based on matrix inversion, gradient descent, and Lagrange multipliers, applied to the problem of human pose estimation. 3D human pose estimation algorithms may exhibit noise or may completely fail to provide estimates for some joints. A post-process is often employed to recover the missing joints’ locations from the remaining ones, typically by enforcing kinematic constraints or by using a prior learned from a database of natural poses. Matrix completion and recovery techniques fall into the latter category and operate by filling-in missing entries of a matrix whose available/non-missing entries may be additionally corrupted by noise. We compare the performance of three such techniques in terms of the estimation error of their output as well as their runtime, in a series of simulated and real-world experiments. We conclude by recommending use cases for each of the compared techniques. Full article
(This article belongs to the Special Issue The PErvasive Technologies Related to Assistive Environments (PETRA))
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Open AccessArticle On Adaptive Control for Electrical Discharge Machining Using Vibroacoustic Emission
Technologies 2018, 6(4), 96; https://doi.org/10.3390/technologies6040096
Received: 16 October 2018 / Revised: 22 October 2018 / Accepted: 23 October 2018 / Published: 24 October 2018
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Abstract
The article is related to the research of the parameters of vibroacoustic emission for development of the monitoring and adaptive control system for electrical discharge machining. The classical control system based on a response of electrical parameters does not give an adequate data
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The article is related to the research of the parameters of vibroacoustic emission for development of the monitoring and adaptive control system for electrical discharge machining. The classical control system based on a response of electrical parameters does not give an adequate data in the cases of a new class of materials processing as conductive ceramics reinforced by conductive nano additives and carbon nanotubes and whiskers. The idle pulses, which are working on the destruction of the erosion products in the gap, count as working pulses. The application of the monitoring and control tools based on vibroacoustic emission gives adequate data about conditions in the working zone. The developed system is available to count only impulses involved in working on the destruction of the workpiece. The experiments were conducted on the samples of materials with a low melting point as austenitic steel and aluminum alloy, and hard alloys. The records of vibroacoustic signals were analyzed for detection of the monitoring and adaptive control criteria. Full article
(This article belongs to the Special Issue Reviews and Advances in Materials Processing)
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Open AccessEditorial Special Issue on “Assistive Robotics”
Technologies 2018, 6(4), 95; https://doi.org/10.3390/technologies6040095
Received: 18 October 2018 / Accepted: 18 October 2018 / Published: 20 October 2018
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Abstract
The technology behind robotics has rapidly advanced to a level enabling humans and robots to interact in everyday aspects of life. [...] Full article
(This article belongs to the Special Issue Assistive Robotics)
Open AccessArticle Physicochemical Properties of Gac (Momordica cochinchinensis (Lour.) Spreng) Seeds and Their Oil Extracted by Supercritical Carbon Dioxide and Soxhlet Methods
Technologies 2018, 6(4), 94; https://doi.org/10.3390/technologies6040094
Received: 25 September 2018 / Revised: 5 October 2018 / Accepted: 9 October 2018 / Published: 11 October 2018
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Abstract
Gac seeds are high in oil, but there are few studies on its extraction and characteristics. This study aimed to characterise Gac seeds and investigate the physicochemical properties of Gac seed oil extracted with supercritical carbon dioxide (SC-CO2) and hexane (Soxhlet).
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Gac seeds are high in oil, but there are few studies on its extraction and characteristics. This study aimed to characterise Gac seeds and investigate the physicochemical properties of Gac seed oil extracted with supercritical carbon dioxide (SC-CO2) and hexane (Soxhlet). The Gac seed kernel accounted for 66.4 ± 2.7% of the seed weight, and 53.02 ± 1.27% of it was oil. The SC-CO2 oil had a higher quality than the Soxhlet oil for important criteria, such as peroxide (0.12 ± 0.02 vs. 1.80 ± 0.01 meq O2/kg oil), free fatty acid (1.74 ± 0.12 vs. 2.47 ± 0.09 mg KOH/g oil) and unsaponifiable matter (33.2 ± 1.5 vs. 52.6 ± 2.4 g/kg) values, respectively. It also had a better colour (light yellow vs. dark greenish brown) and a higher antioxidant capacity measured with the DPPH (52.69 ± 0.06 vs. 42.98 ± 0.02 µmol Trolox equivalent/g oil) and ABTS (2.10 ± 0.12 vs. 1.52 ± 0.06 µmol Trolox equivalent/g oil) assays. However, a higher yield (53.02 ± 1.27 vs. 34.1 ± 0.8%) was obtained for the Soxhlet oil. Unless refined, the oils would not be edible due to their high unsaponifiable matter, but the SC-CO2 oil would need less refining. Alternatively, the high unsaponifiable matter in the oil, especially in the Soxhlet oil, may make it useful for medicinal purposes. Full article
Open AccessArticle Basic Study of Ventilation Using Semi-Transparent Organic Photovoltaic Sheets for Solar Chimney Systems
Technologies 2018, 6(4), 93; https://doi.org/10.3390/technologies6040093
Received: 19 July 2018 / Revised: 13 September 2018 / Accepted: 28 September 2018 / Published: 9 October 2018
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Abstract
An energy-efficient building ventilation system is presented that integrates semi-transparent organic photovoltaic (OPV) technology and solar chimney technology. It achieved a wind velocity of 0.25 m/s and electric power generation of about 1.03 W at an artificial light intensity of 320 W/m2
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An energy-efficient building ventilation system is presented that integrates semi-transparent organic photovoltaic (OPV) technology and solar chimney technology. It achieved a wind velocity of 0.25 m/s and electric power generation of about 1.03 W at an artificial light intensity of 320 W/m2, which corresponds to cloudy weather. These results support the basic study of systems combining ventilation and power generation. The integration of solar chimney ventilation with OPV power generation could be a promising system for energy savings in the future. The proposed integration could contribute to the generation of sustainable and renewable energy. Full article
(This article belongs to the Special Issue Smart Systems)
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